index int64 0 0 | repo_id stringclasses 596 values | file_path stringlengths 31 168 | content stringlengths 1 6.2M |
|---|---|---|---|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/vectorstores.ts | import * as uuid from "uuid";
import {
VectorizeIndex,
VectorizeVectorMetadata,
VectorizeVectorMetadataFilter,
} from "@cloudflare/workers-types";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { VectorStore } from "@langchain/core/vectorstores";
import { Document } from "@langchain/core/documents";
import {
AsyncCaller,
type AsyncCallerParams,
} from "@langchain/core/utils/async_caller";
import { chunkArray } from "@langchain/core/utils/chunk_array";
export interface VectorizeLibArgs extends AsyncCallerParams {
index: VectorizeIndex;
textKey?: string;
}
/**
* Type that defines the parameters for the delete operation in the
* CloudflareVectorizeStore class. It includes ids, deleteAll flag, and namespace.
*/
export type VectorizeDeleteParams = {
ids: string[];
};
/**
* Class that extends the VectorStore class and provides methods to
* interact with the Cloudflare Vectorize vector database.
*/
export class CloudflareVectorizeStore extends VectorStore {
declare FilterType: VectorizeVectorMetadataFilter;
textKey: string;
namespace?: string;
index: VectorizeIndex;
caller: AsyncCaller;
_vectorstoreType(): string {
return "cloudflare_vectorize";
}
constructor(embeddings: EmbeddingsInterface, args: VectorizeLibArgs) {
super(embeddings, args);
this.embeddings = embeddings;
const { index, textKey, ...asyncCallerArgs } = args;
if (!index) {
throw new Error(
"Must supply a Vectorize index binding, eg { index: env.VECTORIZE }"
);
}
this.index = index;
this.textKey = textKey ?? "text";
this.caller = new AsyncCaller({
maxConcurrency: 6,
maxRetries: 0,
...asyncCallerArgs,
});
}
/**
* Method that adds documents to the Vectorize database.
* @param documents Array of documents to add.
* @param options Optional ids for the documents.
* @returns Promise that resolves with the ids of the added documents.
*/
async addDocuments(
documents: Document[],
options?: { ids?: string[] } | string[]
) {
const texts = documents.map(({ pageContent }) => pageContent);
return this.addVectors(
await this.embeddings.embedDocuments(texts),
documents,
options
);
}
/**
* Method that adds vectors to the Vectorize database.
* @param vectors Array of vectors to add.
* @param documents Array of documents associated with the vectors.
* @param options Optional ids for the vectors.
* @returns Promise that resolves with the ids of the added vectors.
*/
async addVectors(
vectors: number[][],
documents: Document[],
options?: { ids?: string[] } | string[]
) {
const ids = Array.isArray(options) ? options : options?.ids;
const documentIds = ids == null ? documents.map(() => uuid.v4()) : ids;
const vectorizeVectors = vectors.map((values, idx) => {
const metadata: Record<string, VectorizeVectorMetadata> = {
...documents[idx].metadata,
[this.textKey]: documents[idx].pageContent,
};
return {
id: documentIds[idx],
metadata,
values,
};
});
// Stick to a limit of 500 vectors per upsert request
const chunkSize = 500;
const chunkedVectors = chunkArray(vectorizeVectors, chunkSize);
const batchRequests = chunkedVectors.map((chunk) =>
this.caller.call(async () => this.index.upsert(chunk))
);
await Promise.all(batchRequests);
return documentIds;
}
/**
* Method that deletes vectors from the Vectorize database.
* @param params Parameters for the delete operation.
* @returns Promise that resolves when the delete operation is complete.
*/
async delete(params: VectorizeDeleteParams): Promise<void> {
const batchSize = 1000;
const batchedIds = chunkArray(params.ids, batchSize);
const batchRequests = batchedIds.map((batchIds) =>
this.caller.call(async () => this.index.deleteByIds(batchIds))
);
await Promise.all(batchRequests);
}
/**
* Method that performs a similarity search in the Vectorize database and
* returns the results along with their scores.
* @param query Query vector for the similarity search.
* @param k Number of top results to return.
* @returns Promise that resolves with an array of documents and their scores.
*/
async similaritySearchVectorWithScore(
query: number[],
k: number,
filter?: this["FilterType"]
): Promise<[Document, number][]> {
const results = await this.index.query(query, {
returnMetadata: true,
returnValues: true,
topK: k,
filter,
});
const result: [Document, number][] = [];
if (results.matches) {
for (const res of results.matches) {
const { [this.textKey]: pageContent, ...metadata } = res.metadata ?? {};
result.push([
new Document({ metadata, pageContent: pageContent as string }),
res.score,
]);
}
}
return result;
}
/**
* Static method that creates a new instance of the CloudflareVectorizeStore class
* from texts.
* @param texts Array of texts to add to the Vectorize database.
* @param metadatas Metadata associated with the texts.
* @param embeddings Embeddings to use for the texts.
* @param dbConfig Configuration for the Vectorize database.
* @param options Optional ids for the vectors.
* @returns Promise that resolves with a new instance of the CloudflareVectorizeStore class.
*/
static async fromTexts(
texts: string[],
metadatas:
| Record<string, VectorizeVectorMetadata>[]
| Record<string, VectorizeVectorMetadata>,
embeddings: EmbeddingsInterface,
dbConfig: VectorizeLibArgs
): Promise<CloudflareVectorizeStore> {
const docs: Document[] = [];
for (let i = 0; i < texts.length; i += 1) {
const metadata = Array.isArray(metadatas) ? metadatas[i] : metadatas;
const newDoc = new Document({
pageContent: texts[i],
metadata,
});
docs.push(newDoc);
}
return CloudflareVectorizeStore.fromDocuments(docs, embeddings, dbConfig);
}
/**
* Static method that creates a new instance of the CloudflareVectorizeStore class
* from documents.
* @param docs Array of documents to add to the Vectorize database.
* @param embeddings Embeddings to use for the documents.
* @param dbConfig Configuration for the Vectorize database.
* @param options Optional ids for the vectors.
* @returns Promise that resolves with a new instance of the CloudflareVectorizeStore class.
*/
static async fromDocuments(
docs: Document[],
embeddings: EmbeddingsInterface,
dbConfig: VectorizeLibArgs
): Promise<CloudflareVectorizeStore> {
const instance = new this(embeddings, dbConfig);
await instance.addDocuments(docs);
return instance;
}
/**
* Static method that creates a new instance of the CloudflareVectorizeStore class
* from an existing index.
* @param embeddings Embeddings to use for the documents.
* @param dbConfig Configuration for the Vectorize database.
* @returns Promise that resolves with a new instance of the CloudflareVectorizeStore class.
*/
static async fromExistingIndex(
embeddings: EmbeddingsInterface,
dbConfig: VectorizeLibArgs
): Promise<CloudflareVectorizeStore> {
const instance = new this(embeddings, dbConfig);
return instance;
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/caches.ts | import type { KVNamespace } from "@cloudflare/workers-types";
import {
BaseCache,
getCacheKey,
serializeGeneration,
deserializeStoredGeneration,
} from "@langchain/core/caches";
import { Generation } from "@langchain/core/outputs";
/**
* Represents a specific implementation of a caching mechanism using Cloudflare KV
* as the underlying storage system. It extends the `BaseCache` class and
* overrides its methods to provide the Cloudflare KV-specific logic.
* @example
* ```typescript
* // Example of using OpenAI with Cloudflare KV as cache in a Cloudflare Worker
* const cache = new CloudflareKVCache(env.KV_NAMESPACE);
* const model = new ChatAnthropic({
* cache,
* });
* const response = await model.invoke("How are you today?");
* return new Response(JSON.stringify(response), {
* headers: { "content-type": "application/json" },
* });
*
* ```
*/
export class CloudflareKVCache extends BaseCache {
private binding: KVNamespace;
constructor(binding: KVNamespace) {
super();
this.binding = binding;
}
/**
* Retrieves data from the cache. It constructs a cache key from the given
* `prompt` and `llmKey`, and retrieves the corresponding value from the
* Cloudflare KV namespace.
* @param prompt The prompt used to construct the cache key.
* @param llmKey The LLM key used to construct the cache key.
* @returns An array of Generations if found, null otherwise.
*/
public async lookup(prompt: string, llmKey: string) {
let idx = 0;
let key = getCacheKey(prompt, llmKey, String(idx));
let value = await this.binding.get(key);
const generations: Generation[] = [];
while (value) {
generations.push(deserializeStoredGeneration(JSON.parse(value)));
idx += 1;
key = getCacheKey(prompt, llmKey, String(idx));
value = await this.binding.get(key);
}
return generations.length > 0 ? generations : null;
}
/**
* Updates the cache with new data. It constructs a cache key from the
* given `prompt` and `llmKey`, and stores the `value` in the Cloudflare KV
* namespace.
* @param prompt The prompt used to construct the cache key.
* @param llmKey The LLM key used to construct the cache key.
* @param value The value to be stored in the cache.
*/
public async update(prompt: string, llmKey: string, value: Generation[]) {
for (let i = 0; i < value.length; i += 1) {
const key = getCacheKey(prompt, llmKey, String(i));
await this.binding.put(
key,
JSON.stringify(serializeGeneration(value[i]))
);
}
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/message_histories.ts | import { v4 } from "uuid";
import type { D1Database } from "@cloudflare/workers-types";
import { BaseListChatMessageHistory } from "@langchain/core/chat_history";
import {
BaseMessage,
StoredMessage,
StoredMessageData,
mapChatMessagesToStoredMessages,
mapStoredMessagesToChatMessages,
} from "@langchain/core/messages";
/**
* Type definition for the input parameters required when instantiating a
* CloudflareD1MessageHistory object.
*/
export type CloudflareD1MessageHistoryInput = {
tableName?: string;
sessionId: string;
database?: D1Database;
};
/**
* Interface for the data transfer object used when selecting stored
* messages from the Cloudflare D1 database.
*/
interface selectStoredMessagesDTO {
id: string;
session_id: string;
type: string;
content: string;
role: string | null;
name: string | null;
additional_kwargs: string;
}
/**
* Class for storing and retrieving chat message history from a
* Cloudflare D1 database. Extends the BaseListChatMessageHistory class.
* @example
* ```typescript
* const memory = new BufferMemory({
* returnMessages: true,
* chatHistory: new CloudflareD1MessageHistory({
* tableName: "stored_message",
* sessionId: "example",
* database: env.DB,
* }),
* });
*
* const chainInput = { input };
*
* const res = await memory.chatHistory.invoke(chainInput);
* await memory.saveContext(chainInput, {
* output: res,
* });
* ```
*/
export class CloudflareD1MessageHistory extends BaseListChatMessageHistory {
lc_namespace = ["langchain", "stores", "message", "cloudflare_d1"];
public database: D1Database;
private tableName: string;
private sessionId: string;
private tableInitialized: boolean;
constructor(fields: CloudflareD1MessageHistoryInput) {
super(fields);
const { sessionId, database, tableName } = fields;
if (database) {
this.database = database;
} else {
throw new Error(
"Either a client or config must be provided to CloudflareD1MessageHistory"
);
}
this.tableName = tableName || "langchain_chat_histories";
this.tableInitialized = false;
this.sessionId = sessionId;
}
/**
* Private method to ensure that the necessary table exists in the
* Cloudflare D1 database before performing any operations. If the table
* does not exist, it is created.
* @returns Promise that resolves to void.
*/
private async ensureTable(): Promise<void> {
if (this.tableInitialized) {
return;
}
const query = `CREATE TABLE IF NOT EXISTS ${this.tableName} (id TEXT PRIMARY KEY, session_id TEXT, type TEXT, content TEXT, role TEXT, name TEXT, additional_kwargs TEXT);`;
await this.database.prepare(query).bind().all();
const idIndexQuery = `CREATE INDEX IF NOT EXISTS id_index ON ${this.tableName} (id);`;
await this.database.prepare(idIndexQuery).bind().all();
const sessionIdIndexQuery = `CREATE INDEX IF NOT EXISTS session_id_index ON ${this.tableName} (session_id);`;
await this.database.prepare(sessionIdIndexQuery).bind().all();
this.tableInitialized = true;
}
/**
* Method to retrieve all messages from the Cloudflare D1 database for the
* current session.
* @returns Promise that resolves to an array of BaseMessage objects.
*/
async getMessages(): Promise<BaseMessage[]> {
await this.ensureTable();
const query = `SELECT * FROM ${this.tableName} WHERE session_id = ?`;
const rawStoredMessages = await this.database
.prepare(query)
.bind(this.sessionId)
.all();
const storedMessagesObject =
rawStoredMessages.results as unknown as selectStoredMessagesDTO[];
const orderedMessages: StoredMessage[] = storedMessagesObject.map(
(message) => {
const data = {
content: message.content,
additional_kwargs: JSON.parse(message.additional_kwargs),
} as StoredMessageData;
if (message.role) {
data.role = message.role;
}
if (message.name) {
data.name = message.name;
}
return {
type: message.type,
data,
};
}
);
return mapStoredMessagesToChatMessages(orderedMessages);
}
/**
* Method to add a new message to the Cloudflare D1 database for the current
* session.
* @param message The BaseMessage object to be added to the database.
* @returns Promise that resolves to void.
*/
async addMessage(message: BaseMessage): Promise<void> {
await this.ensureTable();
const messageToAdd = mapChatMessagesToStoredMessages([message]);
const query = `INSERT INTO ${this.tableName} (id, session_id, type, content, role, name, additional_kwargs) VALUES(?, ?, ?, ?, ?, ?, ?)`;
const id = v4();
await this.database
.prepare(query)
.bind(
id,
this.sessionId,
messageToAdd[0].type || null,
messageToAdd[0].data.content || null,
messageToAdd[0].data.role || null,
messageToAdd[0].data.name || null,
JSON.stringify(messageToAdd[0].data.additional_kwargs)
)
.all();
}
/**
* Method to delete all messages from the Cloudflare D1 database for the
* current session.
* @returns Promise that resolves to void.
*/
async clear(): Promise<void> {
await this.ensureTable();
const query = `DELETE FROM ? WHERE session_id = ? `;
await this.database
.prepare(query)
.bind(this.tableName, this.sessionId)
.all();
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/llms.ts | import { LLM, type BaseLLMParams } from "@langchain/core/language_models/llms";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { GenerationChunk } from "@langchain/core/outputs";
import { convertEventStreamToIterableReadableDataStream } from "./utils/event_source_parse.js";
/**
* Interface for CloudflareWorkersAI input parameters.
*/
export interface CloudflareWorkersAIInput {
cloudflareAccountId?: string;
cloudflareApiToken?: string;
model?: string;
baseUrl?: string;
streaming?: boolean;
}
/**
* Class representing the CloudflareWorkersAI language model. It extends the LLM (Large
* Language Model) class, providing a standard interface for interacting
* with the CloudflareWorkersAI language model.
*/
export class CloudflareWorkersAI
extends LLM
implements CloudflareWorkersAIInput
{
model = "@cf/meta/llama-2-7b-chat-int8";
cloudflareAccountId?: string;
cloudflareApiToken?: string;
baseUrl: string;
streaming = false;
static lc_name() {
return "CloudflareWorkersAI";
}
lc_serializable = true;
constructor(fields?: CloudflareWorkersAIInput & BaseLLMParams) {
super(fields ?? {});
this.model = fields?.model ?? this.model;
this.streaming = fields?.streaming ?? this.streaming;
this.cloudflareAccountId =
fields?.cloudflareAccountId ??
getEnvironmentVariable("CLOUDFLARE_ACCOUNT_ID");
this.cloudflareApiToken =
fields?.cloudflareApiToken ??
getEnvironmentVariable("CLOUDFLARE_API_TOKEN");
this.baseUrl =
fields?.baseUrl ??
`https://api.cloudflare.com/client/v4/accounts/${this.cloudflareAccountId}/ai/run`;
if (this.baseUrl.endsWith("/")) {
this.baseUrl = this.baseUrl.slice(0, -1);
}
}
/**
* Method to validate the environment.
*/
validateEnvironment() {
if (this.baseUrl === undefined) {
if (!this.cloudflareAccountId) {
throw new Error(
`No Cloudflare account ID found. Please provide it when instantiating the CloudflareWorkersAI class, or set it as "CLOUDFLARE_ACCOUNT_ID" in your environment variables.`
);
}
if (!this.cloudflareApiToken) {
throw new Error(
`No Cloudflare API key found. Please provide it when instantiating the CloudflareWorkersAI class, or set it as "CLOUDFLARE_API_KEY" in your environment variables.`
);
}
}
}
/** Get the identifying parameters for this LLM. */
get identifyingParams() {
return { model: this.model };
}
/**
* Get the parameters used to invoke the model
*/
invocationParams() {
return {
model: this.model,
};
}
/** Get the type of LLM. */
_llmType() {
return "cloudflare";
}
async _request(
prompt: string,
options: this["ParsedCallOptions"],
stream?: boolean
) {
this.validateEnvironment();
const url = `${this.baseUrl}/${this.model}`;
const headers = {
Authorization: `Bearer ${this.cloudflareApiToken}`,
"Content-Type": "application/json",
};
const data = { prompt, stream };
return this.caller.call(async () => {
const response = await fetch(url, {
method: "POST",
headers,
body: JSON.stringify(data),
signal: options.signal,
});
if (!response.ok) {
const error = new Error(
`Cloudflare LLM call failed with status code ${response.status}`
);
// eslint-disable-next-line @typescript-eslint/no-explicit-any
(error as any).response = response;
throw error;
}
return response;
});
}
async *_streamResponseChunks(
prompt: string,
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): AsyncGenerator<GenerationChunk> {
const response = await this._request(prompt, options, true);
if (!response.body) {
throw new Error("Empty response from Cloudflare. Please try again.");
}
const stream = convertEventStreamToIterableReadableDataStream(
response.body
);
for await (const chunk of stream) {
if (chunk !== "[DONE]") {
const parsedChunk = JSON.parse(chunk);
const generationChunk = new GenerationChunk({
text: parsedChunk.response,
});
yield generationChunk;
// eslint-disable-next-line no-void
void runManager?.handleLLMNewToken(generationChunk.text ?? "");
}
}
}
/** Call out to CloudflareWorkersAI's complete endpoint.
Args:
prompt: The prompt to pass into the model.
Returns:
The string generated by the model.
Example:
let response = CloudflareWorkersAI.call("Tell me a joke.");
*/
async _call(
prompt: string,
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): Promise<string> {
if (!this.streaming) {
const response = await this._request(prompt, options);
const responseData = await response.json();
return responseData.result.response;
} else {
const stream = this._streamResponseChunks(prompt, options, runManager);
let finalResult: GenerationChunk | undefined;
for await (const chunk of stream) {
if (finalResult === undefined) {
finalResult = chunk;
} else {
finalResult = finalResult.concat(chunk);
}
}
return finalResult?.text ?? "";
}
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/index.ts | export * from "./chat_models.js";
export * from "./llms.js";
export * from "./embeddings.js";
export * from "./vectorstores.js";
export * from "./caches.js";
export * from "./message_histories.js";
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/chat_models.ts | import {
LangSmithParams,
SimpleChatModel,
type BaseChatModelParams,
} from "@langchain/core/language_models/chat_models";
import type { BaseLanguageModelCallOptions } from "@langchain/core/language_models/base";
import {
AIMessageChunk,
BaseMessage,
ChatMessage,
} from "@langchain/core/messages";
import { ChatGenerationChunk } from "@langchain/core/outputs";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import type { CloudflareWorkersAIInput } from "./llms.js";
import { convertEventStreamToIterableReadableDataStream } from "./utils/event_source_parse.js";
/**
* An interface defining the options for a Cloudflare Workers AI call. It extends
* the BaseLanguageModelCallOptions interface.
*/
export interface ChatCloudflareWorkersAICallOptions
extends BaseLanguageModelCallOptions {}
/**
* A class that enables calls to the Cloudflare Workers AI API to access large language
* models in a chat-like fashion. It extends the SimpleChatModel class and
* implements the CloudflareWorkersAIInput interface.
* @example
* ```typescript
* const model = new ChatCloudflareWorkersAI({
* model: "@cf/meta/llama-2-7b-chat-int8",
* cloudflareAccountId: process.env.CLOUDFLARE_ACCOUNT_ID,
* cloudflareApiToken: process.env.CLOUDFLARE_API_TOKEN
* });
*
* const response = await model.invoke([
* ["system", "You are a helpful assistant that translates English to German."],
* ["human", `Translate "I love programming".`]
* ]);
*
* console.log(response);
* ```
*/
export class ChatCloudflareWorkersAI
extends SimpleChatModel
implements CloudflareWorkersAIInput
{
static lc_name() {
return "ChatCloudflareWorkersAI";
}
lc_serializable = true;
model = "@cf/meta/llama-2-7b-chat-int8";
cloudflareAccountId?: string;
cloudflareApiToken?: string;
baseUrl: string;
streaming = false;
constructor(fields?: CloudflareWorkersAIInput & BaseChatModelParams) {
super(fields ?? {});
this.model = fields?.model ?? this.model;
this.streaming = fields?.streaming ?? this.streaming;
this.cloudflareAccountId =
fields?.cloudflareAccountId ??
getEnvironmentVariable("CLOUDFLARE_ACCOUNT_ID");
this.cloudflareApiToken =
fields?.cloudflareApiToken ??
getEnvironmentVariable("CLOUDFLARE_API_TOKEN");
this.baseUrl =
fields?.baseUrl ??
`https://api.cloudflare.com/client/v4/accounts/${this.cloudflareAccountId}/ai/run`;
if (this.baseUrl.endsWith("/")) {
this.baseUrl = this.baseUrl.slice(0, -1);
}
}
getLsParams(options: this["ParsedCallOptions"]): LangSmithParams {
return {
ls_provider: "cloudflare",
ls_model_name: this.model,
ls_model_type: "chat",
ls_stop: options.stop,
};
}
get lc_secrets(): { [key: string]: string } | undefined {
return {
cloudflareApiToken: "CLOUDFLARE_API_TOKEN",
};
}
_llmType() {
return "cloudflare";
}
/** Get the identifying parameters for this LLM. */
get identifyingParams() {
return { model: this.model };
}
/**
* Get the parameters used to invoke the model
*/
invocationParams(_options?: this["ParsedCallOptions"]) {
return {
model: this.model,
};
}
_combineLLMOutput() {
return {};
}
/**
* Method to validate the environment.
*/
validateEnvironment() {
if (!this.cloudflareAccountId) {
throw new Error(
`No Cloudflare account ID found. Please provide it when instantiating the CloudflareWorkersAI class, or set it as "CLOUDFLARE_ACCOUNT_ID" in your environment variables.`
);
}
if (!this.cloudflareApiToken) {
throw new Error(
`No Cloudflare API key found. Please provide it when instantiating the CloudflareWorkersAI class, or set it as "CLOUDFLARE_API_KEY" in your environment variables.`
);
}
}
async _request(
messages: BaseMessage[],
options: this["ParsedCallOptions"],
stream?: boolean
) {
this.validateEnvironment();
const url = `${this.baseUrl}/${this.model}`;
const headers = {
Authorization: `Bearer ${this.cloudflareApiToken}`,
"Content-Type": "application/json",
};
const formattedMessages = this._formatMessages(messages);
const data = { messages: formattedMessages, stream };
return this.caller.call(async () => {
const response = await fetch(url, {
method: "POST",
headers,
body: JSON.stringify(data),
signal: options.signal,
});
if (!response.ok) {
const error = new Error(
`Cloudflare LLM call failed with status code ${response.status}`
);
// eslint-disable-next-line @typescript-eslint/no-explicit-any
(error as any).response = response;
throw error;
}
return response;
});
}
async *_streamResponseChunks(
messages: BaseMessage[],
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): AsyncGenerator<ChatGenerationChunk> {
const response = await this._request(messages, options, true);
if (!response.body) {
throw new Error("Empty response from Cloudflare. Please try again.");
}
const stream = convertEventStreamToIterableReadableDataStream(
response.body
);
for await (const chunk of stream) {
if (chunk !== "[DONE]") {
const parsedChunk = JSON.parse(chunk);
const generationChunk = new ChatGenerationChunk({
message: new AIMessageChunk({ content: parsedChunk.response }),
text: parsedChunk.response,
});
yield generationChunk;
// eslint-disable-next-line no-void
void runManager?.handleLLMNewToken(generationChunk.text ?? "");
}
}
}
protected _formatMessages(
messages: BaseMessage[]
): { role: string; content: string }[] {
const formattedMessages = messages.map((message) => {
let role;
if (message._getType() === "human") {
role = "user";
} else if (message._getType() === "ai") {
role = "assistant";
} else if (message._getType() === "system") {
role = "system";
} else if (ChatMessage.isInstance(message)) {
role = message.role;
} else {
console.warn(
`Unsupported message type passed to Cloudflare: "${message._getType()}"`
);
role = "user";
}
if (typeof message.content !== "string") {
throw new Error(
"ChatCloudflareWorkersAI currently does not support non-string message content."
);
}
return {
role,
content: message.content,
};
});
return formattedMessages;
}
/** @ignore */
async _call(
messages: BaseMessage[],
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): Promise<string> {
if (!this.streaming) {
const response = await this._request(messages, options);
const responseData = await response.json();
return responseData.result.response;
} else {
const stream = this._streamResponseChunks(messages, options, runManager);
let finalResult: ChatGenerationChunk | undefined;
for await (const chunk of stream) {
if (finalResult === undefined) {
finalResult = chunk;
} else {
finalResult = finalResult.concat(chunk);
}
}
const messageContent = finalResult?.message.content;
if (messageContent && typeof messageContent !== "string") {
throw new Error(
"Non-string output for ChatCloudflareWorkersAI is currently not supported."
);
}
return messageContent ?? "";
}
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/embeddings.ts | import { Ai } from "@cloudflare/workers-types";
import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings";
import { chunkArray } from "@langchain/core/utils/chunk_array";
type AiTextEmbeddingsInput = {
text: string | string[];
};
type AiTextEmbeddingsOutput = {
shape: number[];
data: number[][];
};
export interface CloudflareWorkersAIEmbeddingsParams extends EmbeddingsParams {
/** Binding */
binding: Ai;
/**
* Model name to use
* Alias for `model`
*/
modelName?: string;
/**
* Model name to use
*/
model?: string;
/**
* The maximum number of documents to embed in a single request.
*/
batchSize?: number;
/**
* Whether to strip new lines from the input text. This is recommended by
* OpenAI, but may not be suitable for all use cases.
*/
stripNewLines?: boolean;
}
export class CloudflareWorkersAIEmbeddings extends Embeddings {
modelName = "@cf/baai/bge-base-en-v1.5";
model = "@cf/baai/bge-base-en-v1.5";
batchSize = 50;
stripNewLines = true;
ai: Ai;
constructor(fields: CloudflareWorkersAIEmbeddingsParams) {
super(fields);
if (!fields.binding) {
throw new Error(
"Must supply a Workers AI binding, eg { binding: env.AI }"
);
}
this.ai = fields.binding;
this.modelName = fields?.model ?? fields.modelName ?? this.model;
this.model = this.modelName;
this.stripNewLines = fields.stripNewLines ?? this.stripNewLines;
}
async embedDocuments(texts: string[]): Promise<number[][]> {
const batches = chunkArray(
this.stripNewLines ? texts.map((t) => t.replace(/\n/g, " ")) : texts,
this.batchSize
);
const batchRequests = batches.map((batch) => this.runEmbedding(batch));
const batchResponses = await Promise.all(batchRequests);
const embeddings: number[][] = [];
for (let i = 0; i < batchResponses.length; i += 1) {
const batchResponse = batchResponses[i];
for (let j = 0; j < batchResponse.length; j += 1) {
embeddings.push(batchResponse[j]);
}
}
return embeddings;
}
async embedQuery(text: string): Promise<number[]> {
const data = await this.runEmbedding([
this.stripNewLines ? text.replace(/\n/g, " ") : text,
]);
return data[0];
}
private async runEmbedding(texts: string[]) {
return this.caller.call(async () => {
const response: AiTextEmbeddingsOutput = await this.ai.run(
// eslint-disable-next-line @typescript-eslint/no-explicit-any
this.model as any,
{
text: texts,
} as AiTextEmbeddingsInput
);
return response.data;
});
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare/src | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/tests/chat_models.standard.int.test.ts | /* eslint-disable no-process-env */
import { test, expect } from "@jest/globals";
import { ChatModelIntegrationTests } from "@langchain/standard-tests";
import { AIMessageChunk } from "@langchain/core/messages";
import {
ChatCloudflareWorkersAI,
ChatCloudflareWorkersAICallOptions,
} from "../chat_models.js";
class ChatCloudflareWorkersAIStandardIntegrationTests extends ChatModelIntegrationTests<
ChatCloudflareWorkersAICallOptions,
AIMessageChunk
> {
constructor() {
if (
!process.env.CLOUDFLARE_ACCOUNT_ID ||
!process.env.CLOUDFLARE_API_TOKEN
) {
throw new Error(
"Skipping Cloudflare Workers AI integration tests because CLOUDFLARE_ACCOUNT_ID or CLOUDFLARE_API_TOKEN is not set"
);
}
super({
Cls: ChatCloudflareWorkersAI,
chatModelHasToolCalling: false,
chatModelHasStructuredOutput: false,
constructorArgs: {},
});
}
async testUsageMetadataStreaming() {
this.skipTestMessage(
"testUsageMetadataStreaming",
"ChatCloudflareWorkersAI",
"Streaming tokens is not currently supported."
);
}
async testUsageMetadata() {
this.skipTestMessage(
"testUsageMetadata",
"ChatCloudflareWorkersAI",
"Usage metadata tokens is not currently supported."
);
}
}
const testClass = new ChatCloudflareWorkersAIStandardIntegrationTests();
test("ChatCloudflareWorkersAIStandardIntegrationTests", async () => {
const testResults = await testClass.runTests();
expect(testResults).toBe(true);
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare/src | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/tests/llms.int.test.ts | /* eslint-disable no-process-env */
import { test } from "@jest/globals";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { CloudflareWorkersAI } from "../llms.js";
// Save the original value of the 'LANGCHAIN_CALLBACKS_BACKGROUND' environment variable
const originalBackground = process.env.LANGCHAIN_CALLBACKS_BACKGROUND;
test("Test CloudflareWorkersAI", async () => {
const model = new CloudflareWorkersAI({});
// @eslint-disable-next-line/@typescript-eslint/ban-ts-comment
// @ts-expect-error unused var
const res = await model.invoke("1 + 1 =");
// console.log(res);
}, 50000);
test("generate with streaming true", async () => {
// Running LangChain callbacks in the background will sometimes cause the callbackManager to execute
// after the test/llm call has already finished & returned. Set that environment variable to false
// to prevent that from happening.
process.env.LANGCHAIN_CALLBACKS_BACKGROUND = "false";
try {
const model = new CloudflareWorkersAI({
streaming: true,
});
const tokens: string[] = [];
const res = await model.invoke("What is 2 + 2?", {
callbacks: [
{
handleLLMNewToken: (token) => {
// console.log(token);
tokens.push(token);
},
},
],
});
expect(tokens.length).toBeGreaterThan(1);
expect(tokens.join("")).toEqual(res);
} finally {
// Reset the environment variable
process.env.LANGCHAIN_CALLBACKS_BACKGROUND = originalBackground;
}
});
test("Test CloudflareWorkersAI streaming", async () => {
const model = new CloudflareWorkersAI({});
const stream = await model.stream("What is 2 + 2?");
const chunks = [];
for await (const chunk of stream) {
chunks.push(chunk);
// console.log(chunk);
}
expect(chunks.length).toBeGreaterThan(1);
// console.log(chunks.join(""));
}, 50000);
test.skip("Test custom base url", async () => {
const model = new CloudflareWorkersAI({
baseUrl: `https://gateway.ai.cloudflare.com/v1/${getEnvironmentVariable(
"CLOUDFLARE_ACCOUNT_ID"
)}/lang-chainjs/workers-ai/`,
});
// @eslint-disable-next-line/@typescript-eslint/ban-ts-comment
// @ts-expect-error unused var
const res = await model.invoke("1 + 1 =");
// console.log(res);
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare/src | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/tests/chat_models.standard.test.ts | /* eslint-disable no-process-env */
import { test, expect } from "@jest/globals";
import { ChatModelUnitTests } from "@langchain/standard-tests";
import { AIMessageChunk } from "@langchain/core/messages";
import { LangSmithParams } from "@langchain/core/language_models/chat_models";
import {
ChatCloudflareWorkersAI,
ChatCloudflareWorkersAICallOptions,
} from "../chat_models.js";
class ChatCloudflareWorkersAIStandardUnitTests extends ChatModelUnitTests<
ChatCloudflareWorkersAICallOptions,
AIMessageChunk
> {
constructor() {
super({
Cls: ChatCloudflareWorkersAI,
chatModelHasToolCalling: false,
chatModelHasStructuredOutput: false,
constructorArgs: {},
});
}
testChatModelInitApiKey() {
this.skipTestMessage(
"testChatModelInitApiKey",
"ChatCloudflareWorkersAI",
this.multipleApiKeysRequiredMessage
);
}
expectedLsParams(): Partial<LangSmithParams> {
console.warn(
"Overriding testStandardParams. ChatCloudflareWorkersAI does not support temperature or max tokens."
);
return {
ls_provider: "string",
ls_model_name: "string",
ls_model_type: "chat",
ls_stop: ["Array<string>"],
};
}
}
const testClass = new ChatCloudflareWorkersAIStandardUnitTests();
test("ChatCloudflareWorkersAIStandardUnitTests", () => {
const testResults = testClass.runTests();
expect(testResults).toBe(true);
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare/src | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/tests/chat_models.int.test.ts | /* eslint-disable no-process-env */
import { describe, test } from "@jest/globals";
import { ChatMessage, HumanMessage } from "@langchain/core/messages";
import {
PromptTemplate,
ChatPromptTemplate,
AIMessagePromptTemplate,
HumanMessagePromptTemplate,
SystemMessagePromptTemplate,
} from "@langchain/core/prompts";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { ChatCloudflareWorkersAI } from "../chat_models.js";
// Save the original value of the 'LANGCHAIN_CALLBACKS_BACKGROUND' environment variable
const originalBackground = process.env.LANGCHAIN_CALLBACKS_BACKGROUND;
describe("ChatCloudflareWorkersAI", () => {
test("call", async () => {
const chat = new ChatCloudflareWorkersAI();
const message = new HumanMessage("Hello!");
// @eslint-disable-next-line/@typescript-eslint/ban-ts-comment
// @ts-expect-error unused var
const res = await chat.call([message]);
// console.log({ res });
});
test("generate", async () => {
const chat = new ChatCloudflareWorkersAI();
const message = new HumanMessage("Hello!");
// @eslint-disable-next-line/@typescript-eslint/ban-ts-comment
// @ts-expect-error unused var
const res = await chat.generate([[message]]);
// console.log(JSON.stringify(res, null, 2));
});
test("generate with streaming true", async () => {
// Running LangChain callbacks in the background will sometimes cause the callbackManager to execute
// after the test/llm call has already finished & returned. Set that environment variable to false
// to prevent that from happening.
process.env.LANGCHAIN_CALLBACKS_BACKGROUND = "false";
try {
const chat = new ChatCloudflareWorkersAI({
streaming: true,
});
const message = new HumanMessage("What is 2 + 2?");
const tokens: string[] = [];
const res = await chat.generate([[message]], {
callbacks: [
{
handleLLMNewToken: (token) => {
tokens.push(token);
},
},
],
});
expect(tokens.length).toBeGreaterThan(1);
expect(tokens.join("")).toEqual(res.generations[0][0].text);
} finally {
// Reset the environment variable
process.env.LANGCHAIN_CALLBACKS_BACKGROUND = originalBackground;
}
});
test("stream", async () => {
const chat = new ChatCloudflareWorkersAI();
const message = new HumanMessage("What is 2 + 2?");
const stream = await chat.stream([message]);
const chunks = [];
for await (const chunk of stream) {
// console.log(chunk.content);
chunks.push(chunk);
}
expect(chunks.length).toBeGreaterThan(1);
// console.log(chunks.map((chunk) => chunk.content).join(""));
expect(
chunks.map((chunk) => chunk.content).join("").length
).toBeGreaterThan(1);
});
test("custom messages", async () => {
const chat = new ChatCloudflareWorkersAI();
// @eslint-disable-next-line/@typescript-eslint/ban-ts-comment
// @ts-expect-error unused var
const res = await chat.call([new ChatMessage("Hello!", "user")]);
// console.log(JSON.stringify(res, null, 2));
});
test("prompt templates", async () => {
const chat = new ChatCloudflareWorkersAI();
// PaLM doesn't support translation yet
const systemPrompt = PromptTemplate.fromTemplate(
"You are a helpful assistant who must always respond like a {job}."
);
const chatPrompt = ChatPromptTemplate.fromMessages([
new SystemMessagePromptTemplate(systemPrompt),
HumanMessagePromptTemplate.fromTemplate("{text}"),
]);
// @eslint-disable-next-line/@typescript-eslint/ban-ts-comment
// @ts-expect-error unused var
const responseA = await chat.generatePrompt([
await chatPrompt.formatPromptValue({
job: "pirate",
text: "What would be a good company name a company that makes colorful socks?",
}),
]);
// console.log(responseA.generations);
});
test("longer chain of messages", async () => {
const chat = new ChatCloudflareWorkersAI();
const chatPrompt = ChatPromptTemplate.fromMessages([
HumanMessagePromptTemplate.fromTemplate(`Hi, my name is Joe!`),
AIMessagePromptTemplate.fromTemplate(`Nice to meet you, Joe!`),
HumanMessagePromptTemplate.fromTemplate("{text}"),
]);
// @eslint-disable-next-line/@typescript-eslint/ban-ts-comment
// @ts-expect-error unused var
const responseA = await chat.generatePrompt([
await chatPrompt.formatPromptValue({
text: "What did I just say my name was?",
}),
]);
// console.log(responseA.generations);
});
test.skip("custom base url", async () => {
const chat = new ChatCloudflareWorkersAI({
baseUrl: `https://gateway.ai.cloudflare.com/v1/${getEnvironmentVariable(
"CLOUDFLARE_ACCOUNT_ID"
)}/lang-chainjs/workers-ai/`,
});
const chatPrompt = ChatPromptTemplate.fromMessages([
HumanMessagePromptTemplate.fromTemplate(`Hi, my name is Joe!`),
AIMessagePromptTemplate.fromTemplate(`Nice to meet you, Joe!`),
HumanMessagePromptTemplate.fromTemplate("{text}"),
]);
// @eslint-disable-next-line/@typescript-eslint/ban-ts-comment
// @ts-expect-error unused var
const responseA = await chat.generatePrompt([
await chatPrompt.formatPromptValue({
text: "What did I just say my name was?",
}),
]);
// console.log(responseA.generations);
});
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare/src | lc_public_repos/langchainjs/libs/langchain-cloudflare/src/utils/event_source_parse.ts | /* eslint-disable prefer-template */
/* eslint-disable default-case */
/* eslint-disable no-plusplus */
// Adapted from https://github.com/gfortaine/fetch-event-source/blob/main/src/parse.ts
// due to a packaging issue in the original.
// MIT License
import { type Readable } from "stream";
import { IterableReadableStream } from "@langchain/core/utils/stream";
export const EventStreamContentType = "text/event-stream";
/**
* Represents a message sent in an event stream
* https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format
*/
export interface EventSourceMessage {
/** The event ID to set the EventSource object's last event ID value. */
id: string;
/** A string identifying the type of event described. */
event: string;
/** The event data */
data: string;
/** The reconnection interval (in milliseconds) to wait before retrying the connection */
retry?: number;
}
function isNodeJSReadable(x: unknown): x is Readable {
return x != null && typeof x === "object" && "on" in x;
}
/**
* Converts a ReadableStream into a callback pattern.
* @param stream The input ReadableStream.
* @param onChunk A function that will be called on each new byte chunk in the stream.
* @returns {Promise<void>} A promise that will be resolved when the stream closes.
*/
export async function getBytes(
stream: ReadableStream<Uint8Array>,
onChunk: (arr: Uint8Array, flush?: boolean) => void
) {
// stream is a Node.js Readable / PassThrough stream
// this can happen if node-fetch is polyfilled
if (isNodeJSReadable(stream)) {
return new Promise<void>((resolve) => {
stream.on("readable", () => {
let chunk;
// eslint-disable-next-line no-constant-condition
while (true) {
chunk = stream.read();
if (chunk == null) {
onChunk(new Uint8Array(), true);
break;
}
onChunk(chunk);
}
resolve();
});
});
}
const reader = stream.getReader();
// CHANGED: Introduced a "flush" mechanism to process potential pending messages when the stream ends.
// This change is essential to ensure that we capture every last piece of information from streams,
// such as those from Azure OpenAI, which may not terminate with a blank line. Without this
// mechanism, we risk ignoring a possibly significant last message.
// See https://github.com/langchain-ai/langchainjs/issues/1299 for details.
// eslint-disable-next-line no-constant-condition
while (true) {
const result = await reader.read();
if (result.done) {
onChunk(new Uint8Array(), true);
break;
}
onChunk(result.value);
}
}
const enum ControlChars {
NewLine = 10,
CarriageReturn = 13,
Space = 32,
Colon = 58,
}
/**
* Parses arbitary byte chunks into EventSource line buffers.
* Each line should be of the format "field: value" and ends with \r, \n, or \r\n.
* @param onLine A function that will be called on each new EventSource line.
* @returns A function that should be called for each incoming byte chunk.
*/
export function getLines(
onLine: (line: Uint8Array, fieldLength: number, flush?: boolean) => void
) {
let buffer: Uint8Array | undefined;
let position: number; // current read position
let fieldLength: number; // length of the `field` portion of the line
let discardTrailingNewline = false;
// return a function that can process each incoming byte chunk:
return function onChunk(arr: Uint8Array, flush?: boolean) {
if (flush) {
onLine(arr, 0, true);
return;
}
if (buffer === undefined) {
buffer = arr;
position = 0;
fieldLength = -1;
} else {
// we're still parsing the old line. Append the new bytes into buffer:
buffer = concat(buffer, arr);
}
const bufLength = buffer.length;
let lineStart = 0; // index where the current line starts
while (position < bufLength) {
if (discardTrailingNewline) {
if (buffer[position] === ControlChars.NewLine) {
lineStart = ++position; // skip to next char
}
discardTrailingNewline = false;
}
// start looking forward till the end of line:
let lineEnd = -1; // index of the \r or \n char
for (; position < bufLength && lineEnd === -1; ++position) {
switch (buffer[position]) {
case ControlChars.Colon:
if (fieldLength === -1) {
// first colon in line
fieldLength = position - lineStart;
}
break;
// eslint-disable-next-line @typescript-eslint/ban-ts-comment
// @ts-ignore:7029 \r case below should fallthrough to \n:
case ControlChars.CarriageReturn:
discardTrailingNewline = true;
// eslint-disable-next-line no-fallthrough
case ControlChars.NewLine:
lineEnd = position;
break;
}
}
if (lineEnd === -1) {
// We reached the end of the buffer but the line hasn't ended.
// Wait for the next arr and then continue parsing:
break;
}
// we've reached the line end, send it out:
onLine(buffer.subarray(lineStart, lineEnd), fieldLength);
lineStart = position; // we're now on the next line
fieldLength = -1;
}
if (lineStart === bufLength) {
buffer = undefined; // we've finished reading it
} else if (lineStart !== 0) {
// Create a new view into buffer beginning at lineStart so we don't
// need to copy over the previous lines when we get the new arr:
buffer = buffer.subarray(lineStart);
position -= lineStart;
}
};
}
/**
* Parses line buffers into EventSourceMessages.
* @param onId A function that will be called on each `id` field.
* @param onRetry A function that will be called on each `retry` field.
* @param onMessage A function that will be called on each message.
* @returns A function that should be called for each incoming line buffer.
*/
export function getMessages(
onMessage?: (msg: EventSourceMessage) => void,
onId?: (id: string) => void,
onRetry?: (retry: number) => void
) {
let message = newMessage();
const decoder = new TextDecoder();
// return a function that can process each incoming line buffer:
return function onLine(
line: Uint8Array,
fieldLength: number,
flush?: boolean
) {
if (flush) {
if (!isEmpty(message)) {
onMessage?.(message);
message = newMessage();
}
return;
}
if (line.length === 0) {
// empty line denotes end of message. Trigger the callback and start a new message:
onMessage?.(message);
message = newMessage();
} else if (fieldLength > 0) {
// exclude comments and lines with no values
// line is of format "<field>:<value>" or "<field>: <value>"
// https://html.spec.whatwg.org/multipage/server-sent-events.html#event-stream-interpretation
const field = decoder.decode(line.subarray(0, fieldLength));
const valueOffset =
fieldLength + (line[fieldLength + 1] === ControlChars.Space ? 2 : 1);
const value = decoder.decode(line.subarray(valueOffset));
switch (field) {
case "data":
// if this message already has data, append the new value to the old.
// otherwise, just set to the new value:
message.data = message.data ? message.data + "\n" + value : value; // otherwise,
break;
case "event":
message.event = value;
break;
case "id":
onId?.((message.id = value));
break;
case "retry": {
const retry = parseInt(value, 10);
if (!Number.isNaN(retry)) {
// per spec, ignore non-integers
onRetry?.((message.retry = retry));
}
break;
}
}
}
};
}
function concat(a: Uint8Array, b: Uint8Array) {
const res = new Uint8Array(a.length + b.length);
res.set(a);
res.set(b, a.length);
return res;
}
function newMessage(): EventSourceMessage {
// data, event, and id must be initialized to empty strings:
// https://html.spec.whatwg.org/multipage/server-sent-events.html#event-stream-interpretation
// retry should be initialized to undefined so we return a consistent shape
// to the js engine all the time: https://mathiasbynens.be/notes/shapes-ics#takeaways
return {
data: "",
event: "",
id: "",
retry: undefined,
};
}
export function convertEventStreamToIterableReadableDataStream(
stream: ReadableStream
) {
const dataStream = new ReadableStream({
async start(controller) {
const enqueueLine = getMessages((msg) => {
if (msg.data) controller.enqueue(msg.data);
});
const onLine = (
line: Uint8Array,
fieldLength: number,
flush?: boolean
) => {
enqueueLine(line, fieldLength, flush);
if (flush) controller.close();
};
await getBytes(stream, getLines(onLine));
},
});
return IterableReadableStream.fromReadableStream(dataStream);
}
function isEmpty(message: EventSourceMessage): boolean {
return (
message.data === "" &&
message.event === "" &&
message.id === "" &&
message.retry === undefined
);
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cloudflare | lc_public_repos/langchainjs/libs/langchain-cloudflare/scripts/jest-setup-after-env.js | import { awaitAllCallbacks } from "@langchain/core/callbacks/promises";
import { afterAll, jest } from "@jest/globals";
afterAll(awaitAllCallbacks);
// Allow console.log to be disabled in tests
if (process.env.DISABLE_CONSOLE_LOGS === "true") {
console.log = jest.fn();
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/tsconfig.json | {
"extends": "@tsconfig/recommended",
"compilerOptions": {
"outDir": "../dist",
"rootDir": "./src",
"target": "ES2021",
"lib": ["ES2021", "ES2022.Object", "DOM"],
"module": "ES2020",
"moduleResolution": "nodenext",
"esModuleInterop": true,
"declaration": true,
"noImplicitReturns": true,
"noFallthroughCasesInSwitch": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"useDefineForClassFields": true,
"strictPropertyInitialization": false,
"allowJs": true,
"strict": true
},
"include": ["src/**/*"],
"exclude": ["node_modules", "dist", "docs"]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/LICENSE | The MIT License
Copyright (c) 2023 LangChain
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE. |
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/jest.config.cjs | /** @type {import('ts-jest').JestConfigWithTsJest} */
module.exports = {
preset: "ts-jest/presets/default-esm",
testEnvironment: "./jest.env.cjs",
modulePathIgnorePatterns: ["dist/", "docs/"],
moduleNameMapper: {
"^(\\.{1,2}/.*)\\.js$": "$1",
},
transform: {
"^.+\\.tsx?$": ["@swc/jest"],
},
transformIgnorePatterns: [
"/node_modules/",
"\\.pnp\\.[^\\/]+$",
"./scripts/jest-setup-after-env.js",
],
setupFiles: ["dotenv/config"],
testTimeout: 20_000,
passWithNoTests: true,
collectCoverageFrom: ["src/**/*.ts"],
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/jest.env.cjs | const { TestEnvironment } = require("jest-environment-node");
class AdjustedTestEnvironmentToSupportFloat32Array extends TestEnvironment {
constructor(config, context) {
// Make `instanceof Float32Array` return true in tests
// to avoid https://github.com/xenova/transformers.js/issues/57 and https://github.com/jestjs/jest/issues/2549
super(config, context);
this.global.Float32Array = Float32Array;
}
}
module.exports = AdjustedTestEnvironmentToSupportFloat32Array;
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/README.md | # @langchain/mixedbread-ai
This package contains the LangChain.js integrations for the [Mixedbread AI API](https://mixedbread.ai/).
## Installation
```bash
npm install @langchain/mixedbread-ai
```
This package, along with the main LangChain package, depends on [`@langchain/core`](https://npmjs.com/package/@langchain/core/). If you are using this package with other LangChain packages, you should make sure that all of the packages depend on the same instance of `@langchain/core`.
## Authentication
To use this package, you need a Mixedbread AI API key. You can obtain your API key by signing up at [Mixedbread AI](https://mixedbread.ai).
Either set the `MXBAI_API_KEY` environment variable to your Mixedbread AI API key, or pass it as the `apiKey` option to the constructor of the class you are using.
## Embeddings
This package provides access to the different embedding models provided by the Mixedbread AI API, such as the "mixedbread-ai/mxbai-embed-large-v1" model.
Learn more: [Embeddings API](https://mixedbread.ai/docs/embeddings)
```typescript
const embeddings = new MixedbreadAIEmbeddings({ apiKey: 'your-api-key' });
const texts = ["Baking bread is fun", "I love baking"];
const result = await embeddings.embedDocuments(texts);
console.log(result);
```
## Reranking
This package provides access to the reranking API provided by Mixedbread AI. It allows you to rerank a list of documents based on a query. Available models include "mixedbread-ai/mxbai-rerank-large-v1".
Learn more: [Reranking API](https://mixedbread.ai/docs/reranking)
```typescript
const reranker = new MixedbreadAIReranker({ apiKey: 'your-api-key' });
const documents = [{ pageContent: "To bake bread you need flour" }, { pageContent: "To bake bread you need yeast" }];
const query = "What do you need to bake bread?";
const result = await reranker.compressDocuments(documents, query);
console.log(result);
```
## Development
To develop the `@langchain/mixedbread-ai` package, follow these instructions:
### Install dependencies
```bash
yarn install
```
### Build the package
```bash
yarn build
```
Or from the repo root:
```bash
yarn build --filter=@langchain/mixedbread-ai
```
### Run tests
Test files should live within a `tests/` folder in the `src/` directory. Unit tests should end in `.test.ts` and integration tests should end in `.int.test.ts`:
```bash
yarn test
yarn test:int
```
### Lint & Format
Run the linter & formatter to ensure your code is up to standard:
```bash
yarn lint && yarn format
```
### Adding new entry points
If you add a new file to be exported, either import & re-export from `src/index.ts`, or add it to the `entrypoints` field in the `config` variable located inside `langchain.config.js` and run `yarn build` to generate the new entry point. |
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/.release-it.json | {
"github": {
"release": true,
"autoGenerate": true,
"tokenRef": "GITHUB_TOKEN_RELEASE"
},
"npm": {
"versionArgs": [
"--workspaces-update=false"
]
}
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/.eslintrc.cjs | module.exports = {
extends: [
"airbnb-base",
"eslint:recommended",
"prettier",
"plugin:@typescript-eslint/recommended",
],
parserOptions: {
ecmaVersion: 12,
parser: "@typescript-eslint/parser",
project: "./tsconfig.json",
sourceType: "module",
},
plugins: ["@typescript-eslint", "no-instanceof", "eslint-plugin-jest"],
ignorePatterns: [
".eslintrc.cjs",
"scripts",
"node_modules",
"dist",
"dist-cjs",
"*.js",
"*.cjs",
"*.d.ts",
],
rules: {
"no-process-env": 2,
"no-instanceof/no-instanceof": 2,
"@typescript-eslint/explicit-module-boundary-types": 0,
"@typescript-eslint/no-empty-function": 0,
"@typescript-eslint/no-shadow": 0,
"@typescript-eslint/no-empty-interface": 0,
"@typescript-eslint/no-use-before-define": ["error", "nofunc"],
"@typescript-eslint/no-unused-vars": ["warn", { args: "none" }],
"@typescript-eslint/no-floating-promises": "error",
"@typescript-eslint/no-misused-promises": "error",
camelcase: 0,
"class-methods-use-this": 0,
"import/extensions": [2, "ignorePackages"],
"import/no-extraneous-dependencies": [
"error",
{ devDependencies: ["**/*.test.ts"] },
],
"import/no-unresolved": 0,
"import/prefer-default-export": 0,
"keyword-spacing": "error",
"max-classes-per-file": 0,
"max-len": 0,
"no-await-in-loop": 0,
"no-bitwise": 0,
"no-console": 0,
"no-restricted-syntax": 0,
"no-shadow": 0,
"no-continue": 0,
"no-void": 0,
"no-underscore-dangle": 0,
"no-use-before-define": 0,
"no-useless-constructor": 0,
"no-return-await": 0,
"consistent-return": 0,
"no-else-return": 0,
"func-names": 0,
"no-lonely-if": 0,
"prefer-rest-params": 0,
'jest/no-focused-tests': 'error',
"new-cap": ["error", { properties: false, capIsNew: false }],
},
overrides: [
{
files: ['**/*.test.ts'],
rules: {
'@typescript-eslint/no-unused-vars': 'off'
}
}
]
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/langchain.config.js | import { resolve, dirname } from "node:path";
import { fileURLToPath } from "node:url";
/**
* @param {string} relativePath
* @returns {string}
*/
function abs(relativePath) {
return resolve(dirname(fileURLToPath(import.meta.url)), relativePath);
}
export const config = {
internals: [/node\:/, /@langchain\/core\//],
entrypoints: {
index: "index",
},
tsConfigPath: resolve("./tsconfig.json"),
cjsSource: "./dist-cjs",
cjsDestination: "./dist",
abs,
} |
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/package.json | {
"name": "@langchain/mixedbread-ai",
"version": "0.2.0",
"description": "Mixedbread AI integration for LangChain.js",
"type": "module",
"engines": {
"node": ">=18"
},
"main": "./index.js",
"types": "./index.d.ts",
"repository": {
"type": "git",
"url": "git@github.com:langchain-ai/langchainjs.git"
},
"homepage": "https://github.com/langchain-ai/langchainjs/tree/main/libs/langchain-mixedbread-ai/",
"scripts": {
"build": "yarn turbo:command build:internal --filter=@langchain/mixedbread-ai",
"build:internal": "yarn lc_build --create-entrypoints --pre --tree-shaking",
"lint:eslint": "NODE_OPTIONS=--max-old-space-size=4096 eslint --cache --ext .ts,.js src/",
"lint:dpdm": "dpdm --exit-code circular:1 --no-warning --no-tree src/*.ts src/**/*.ts",
"lint": "yarn lint:eslint && yarn lint:dpdm",
"lint:fix": "yarn lint:eslint --fix && yarn lint:dpdm",
"clean": "rm -rf .turbo dist/",
"prepack": "yarn build",
"test": "NODE_OPTIONS=--experimental-vm-modules jest --testPathIgnorePatterns=\\.int\\.test.ts --testTimeout 30000 --maxWorkers=50%",
"test:watch": "NODE_OPTIONS=--experimental-vm-modules jest --watch --testPathIgnorePatterns=\\.int\\.test.ts",
"test:single": "NODE_OPTIONS=--experimental-vm-modules yarn run jest --config jest.config.cjs --testTimeout 100000",
"test:int": "NODE_OPTIONS=--experimental-vm-modules jest --testPathPattern=\\.int\\.test.ts --testTimeout 100000 --maxWorkers=50%",
"test:standard:unit": "NODE_OPTIONS=--experimental-vm-modules jest --testPathPattern=\\.standard\\.test.ts --testTimeout 100000 --maxWorkers=50%",
"test:standard:int": "NODE_OPTIONS=--experimental-vm-modules jest --testPathPattern=\\.standard\\.int\\.test.ts --testTimeout 100000 --maxWorkers=50%",
"test:standard": "yarn test:standard:unit && yarn test:standard:int",
"format": "prettier --config .prettierrc --write \"src\"",
"format:check": "prettier --config .prettierrc --check \"src\""
},
"author": "LangChain",
"license": "MIT",
"dependencies": {
"@mixedbread-ai/sdk": "^2.2.3"
},
"peerDependencies": {
"@langchain/core": ">=0.2.5 <0.4.0"
},
"devDependencies": {
"@jest/globals": "^29.5.0",
"@langchain/core": "workspace:*",
"@langchain/scripts": ">=0.1.0 <0.2.0",
"@langchain/standard-tests": "0.0.0",
"@swc/core": "^1.3.90",
"@swc/jest": "^0.2.29",
"@tsconfig/recommended": "^1.0.3",
"@typescript-eslint/eslint-plugin": "^6.12.0",
"@typescript-eslint/parser": "^6.12.0",
"dotenv": "^16.3.1",
"dpdm": "^3.12.0",
"eslint": "^8.33.0",
"eslint-config-airbnb-base": "^15.0.0",
"eslint-config-prettier": "^8.6.0",
"eslint-plugin-import": "^2.27.5",
"eslint-plugin-jest": "^27.6.0",
"eslint-plugin-no-instanceof": "^1.0.1",
"eslint-plugin-prettier": "^4.2.1",
"jest": "^29.5.0",
"jest-environment-node": "^29.6.4",
"prettier": "^2.8.3",
"release-it": "^17.6.0",
"rollup": "^4.5.2",
"ts-jest": "^29.1.0",
"typescript": "<5.2.0"
},
"publishConfig": {
"access": "public"
},
"exports": {
".": {
"types": {
"import": "./index.d.ts",
"require": "./index.d.cts",
"default": "./index.d.ts"
},
"import": "./index.js",
"require": "./index.cjs"
},
"./package.json": "./package.json"
},
"files": [
"dist/",
"index.cjs",
"index.js",
"index.d.ts",
"index.d.cts"
]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/tsconfig.cjs.json | {
"extends": "./tsconfig.json",
"compilerOptions": {
"module": "commonjs",
"declaration": false
},
"exclude": ["node_modules", "dist", "docs", "**/tests"]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/turbo.json | {
"extends": ["//"],
"pipeline": {
"build": {
"outputs": ["**/dist/**"]
},
"build:internal": {
"dependsOn": ["^build:internal"]
}
}
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/.prettierrc | {
"$schema": "https://json.schemastore.org/prettierrc",
"printWidth": 80,
"tabWidth": 2,
"useTabs": false,
"semi": true,
"singleQuote": false,
"quoteProps": "as-needed",
"jsxSingleQuote": false,
"trailingComma": "es5",
"bracketSpacing": true,
"arrowParens": "always",
"requirePragma": false,
"insertPragma": false,
"proseWrap": "preserve",
"htmlWhitespaceSensitivity": "css",
"vueIndentScriptAndStyle": false,
"endOfLine": "lf"
}
|
0 | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/src/reranker.ts | import { DocumentInterface } from "@langchain/core/documents";
import { BaseDocumentCompressor } from "@langchain/core/retrievers/document_compressors";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { MixedbreadAIClient, MixedbreadAI } from "@mixedbread-ai/sdk";
type RerankingRequestWithoutInput = Omit<
MixedbreadAI.RerankingRequest,
"query" | "input"
>;
/**
* Interface extending RerankingRequestWithoutInput with additional
* parameters specific to the MixedbreadAIRerank class.
*/
export interface MixedbreadAIRerankParams
extends Omit<RerankingRequestWithoutInput, "model"> {
/**
* The model to use for reranking. For example "default" or "mixedbread-ai/mxbai-rerank-large-v1".
* @default {"default"}
*/
model?: string;
/**
* The API key to use.
* @default {process.env.MXBAI_API_KEY}
*/
apiKey?: string;
/**
* The base URL of the MixedbreadAI API.
*/
baseUrl?: string;
/**
* The maximum number of retries to attempt.
* @default {3}
*/
maxRetries?: number;
}
/**
* Document compressor that uses Mixedbread AI's rerank API.
*
* This class utilizes Mixedbread AI's reranking model to reorder a set of documents based on their relevance
* to a given query. The reranked documents are then used for various applications like search results refinement.
*
* @example
* const reranker = new MixedbreadAIReranker({ apiKey: 'your-api-key' });
* const documents = [{ pageContent: "To bake bread you need flour" }, { pageContent: "To bake bread you need yeast" }];
* const query = "What do you need to bake bread?";
* const result = await reranker.compressDocuments(documents, query);
* console.log(result);
*
* @example
* const reranker = new MixedbreadAIReranker({
* apiKey: 'your-api-key',
* model: 'mixedbread-ai/mxbai-rerank-large-v1',
* topK: 5,
* rankFields: ["title", "content"],
* returnInput: true,
* maxRetries: 5
* });
* const documents = [{ title: "Bread Recipe", content: "To bake bread you need flour" }, { title: "Bread Recipe", content: "To bake bread you need yeast" }];
* const query = "What do you need to bake bread?";
* const result = await reranker.rerank(documents, query);
* console.log(result);
*/
export class MixedbreadAIReranker extends BaseDocumentCompressor {
lc_secrets = {
apiKey: "MXBAI_API_KEY",
};
requestParams: RerankingRequestWithoutInput;
maxRetries: number;
private client: MixedbreadAIClient;
/**
* Constructor for MixedbreadAIReranker.
* @param {Partial<MixedbreadAIRerankParams>} params - An optional object with properties to configure the instance.
* @throws {Error} If the API key is not provided or found in the environment variables.
*
* @example
* const reranker = new MixedbreadAIReranker({
* apiKey: 'your-api-key',
* model: 'mixedbread-ai/mxbai-rerank-large-v1',
* maxRetries: 5
* });
*/
constructor(params?: Partial<MixedbreadAIRerankParams>) {
super();
const apiKey = params?.apiKey ?? getEnvironmentVariable("MXBAI_API_KEY");
if (!apiKey) {
throw new Error(
"Mixedbread AI API key not found. Either provide it in the constructor or set the 'MXBAI_API_KEY' environment variable."
);
}
this.maxRetries = params?.maxRetries ?? 3;
this.requestParams = {
model: params?.model ?? "default",
topK: params?.topK,
rankFields: params?.rankFields,
returnInput: params?.returnInput,
};
this.client = new MixedbreadAIClient({
apiKey,
environment: params?.baseUrl,
});
}
/**
* Compress documents using Mixedbread AI's reranking API.
*
* @param {DocumentInterface[]} documents - A list of documents to compress.
* @param {string} query - The query to use for compressing the documents.
* @returns {Promise<DocumentInterface[]>} A Promise that resolves to a list of compressed documents.
*
* @example
* const documents = [{ pageContent: "To bake bread you need flour" }, { pageContent: "To bake bread you need yeast" }];
* const query = "What do you need to bake bread?";
* const result = await reranker.compressDocuments(documents, query);
* console.log(result);
*/
async compressDocuments(
documents: DocumentInterface[],
query: string
): Promise<DocumentInterface[]> {
if (documents.length === 0) {
return [];
}
const input = documents.map((doc) => doc.pageContent);
const result = await this.client.reranking({
query,
input,
...this.requestParams,
});
return result.data.map((document) => {
const doc = documents[document.index];
doc.metadata.relevanceScore = document.score;
return doc;
});
}
/**
* Reranks a list of documents based on their relevance to a query using the Mixedbread AI API.
* Returns an ordered list of documents sorted by their relevance to the provided query.
* @param {Array<string> | DocumentInterface[] | Array<Record<string, unknown>>} documents - A list of documents as strings, DocumentInterfaces, or objects with a `pageContent` key.
* @param {string} query - The query to use for reranking the documents.
* @param {RerankingRequestWithoutInput} [options] - Optional parameters for reranking.
* @returns {Promise<MixedbreadAI.RankedDocument[]>} A Promise that resolves to an ordered list of documents with relevance scores.
*
* @example
* const documents = ["To bake bread you need flour", "To bake bread you need yeast"];
* const query = "What do you need to bake bread?";
* const result = await reranker.rerank(documents, query);
* console.log(result);
*/
async rerank(
documents:
| Array<string>
| DocumentInterface[]
| Array<Record<string, unknown>>,
query: string,
options?: RerankingRequestWithoutInput
): Promise<Array<MixedbreadAI.RankedDocument>> {
if (documents.length === 0) {
return [];
}
const input =
typeof documents[0] === "object" && "pageContent" in documents[0]
? (documents as DocumentInterface[]).map((doc) => doc.pageContent)
: (documents as Array<string>);
const result = await this.client.reranking(
{
query,
input,
...this.requestParams,
...options,
},
{
maxRetries: this.maxRetries,
}
);
return result.data;
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/src/index.ts | export * from "./embeddings.js";
export * from "./reranker.js";
|
0 | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/src/embeddings.ts | import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { Embeddings, type EmbeddingsParams } from "@langchain/core/embeddings";
import { chunkArray } from "@langchain/core/utils/chunk_array";
import { MixedbreadAIClient, MixedbreadAI } from "@mixedbread-ai/sdk";
type EmbeddingsRequestWithoutInput = Omit<
MixedbreadAI.EmbeddingsRequest,
"input"
>;
/**
* Interface extending EmbeddingsParams with additional
* parameters specific to the MixedbreadAIEmbeddings class.
*/
export interface MixedbreadAIEmbeddingsParams
extends EmbeddingsParams,
Omit<EmbeddingsRequestWithoutInput, "model"> {
/**
* The model to use for generating embeddings.
* @default {"mixedbread-ai/mxbai-embed-large-v1"}
*/
model?: string;
/**
* The maximum number of documents to embed in a single request.
* @default {128}
*/
batchSize?: number;
/**
* The API key to use.
* @default {process.env.MXBAI_API_KEY}
*/
apiKey?: string;
/**
* The base URL for the API.
*/
baseUrl?: string;
}
/**
* Class for generating embeddings using the Mixedbread AI API.
*
* This class leverages the model "mixedbread-ai/mxbai-embed-large-v1" to generate
* embeddings for text documents. The embeddings can be used for various NLP tasks
* such as similarity comparison, clustering, or as features in machine learning models.
*
* @example
* const embeddings = new MixedbreadAIEmbeddings({ apiKey: 'your-api-key' });
* const texts = ["Baking bread is fun", "I love baking"];
* const result = await embeddings.embedDocuments(texts);
* console.log(result);
*
* @example
* const embeddings = new MixedbreadAIEmbeddings({
* apiKey: 'your-api-key',
* model: 'mixedbread-ai/mxbai-embed-large-v1',
* encodingFormat: MixedbreadAI.EncodingFormat.Binary,
* dimensions: 512,
* normalized: true,
* });
* const texts = ["Baking bread is fun", "I love baking"];
* const result = await embeddings.embedDocuments(texts);
* console.log(result);
*/
export class MixedbreadAIEmbeddings extends Embeddings {
lc_secrets = {
apiKey: "MXBAI_API_KEY",
};
requestParams: EmbeddingsRequestWithoutInput;
batchSize: number;
private client: MixedbreadAIClient;
/**
* Constructor for MixedbreadAIEmbeddings.
* @param {Partial<MixedbreadAIEmbeddingsParams>} params - An optional object with properties to configure the instance.
* @throws {Error} If the API key is not provided or found in the environment variables.
* @throws {Error} If the batch size exceeds 256.
*
* @example
* const embeddings = new MixedbreadAIEmbeddings({
* apiKey: 'your-api-key',
* model: 'mixedbread-ai/mxbai-embed-large-v1',
* batchSize: 64
* });
*/
constructor(params?: Partial<MixedbreadAIEmbeddingsParams>) {
super({ maxConcurrency: 2, ...(params ?? {}) });
const apiKey = params?.apiKey ?? getEnvironmentVariable("MXBAI_API_KEY");
if (!apiKey) {
throw new Error(
"Mixedbread AI API key not found. Either provide it in the constructor or set the 'MXBAI_API_KEY' environment variable."
);
}
if (params?.batchSize && params?.batchSize > 256) {
throw new Error(
"The maximum batch size for Mixedbread AI embeddings API is 256."
);
}
this.batchSize = params?.batchSize ?? 128;
this.requestParams = {
model: params?.model ?? "mixedbread-ai/mxbai-embed-large-v1",
normalized: params?.normalized,
dimensions: params?.dimensions,
encodingFormat: params?.encodingFormat,
truncationStrategy: params?.truncationStrategy,
prompt: params?.prompt,
};
this.client = new MixedbreadAIClient({
apiKey,
environment: params?.baseUrl,
});
}
/**
* Generates embeddings for an array of texts.
* @param {string[]} texts - An array of strings to generate embeddings for.
* @returns {Promise<number[][]>} A Promise that resolves to an array of embeddings.
*
* @example
* const embeddings = new MixedbreadAIEmbeddings({ apiKey: 'your-api-key' });
* const texts = ["Baking bread is fun", "I love baking"];
* const result = await embeddings.embedDocuments(texts);
* console.log(result);
*/
async embedDocuments(texts: string[]): Promise<number[][]> {
if (texts.length === 0) {
return [];
}
const batches = chunkArray(texts, this.batchSize);
const batchRequests = batches.map((batch) =>
this.createEmbeddingsWithRetry(batch)
);
const batchResponses = await Promise.all(batchRequests);
return batchResponses.flat();
}
/**
* Generates an embedding for a single text.
* @param {string} text - A string to generate an embedding for.
* @returns {Promise<number[]>} A Promise that resolves to an array of numbers representing the embedding.
*
* @example
* const embeddings = new MixedbreadAIEmbeddings({ apiKey: 'your-api-key' });
* const text = "Represent this sentence for searching relevant passages: Is baking bread fun?";
* const result = await embeddings.embedQuery(text);
* console.log(result);
*/
async embedQuery(text: string): Promise<number[]> {
const [embedding] = await this.createEmbeddingsWithRetry(text);
return embedding;
}
/**
* Private method to make a request to the Mixedbread AI API to generate embeddings. Handles retry logic.
* @param {string | string[]} input - A string or an array of strings to generate embeddings for.
* @returns {Promise<number[][]>} A Promise that resolves to the API response.
*/
private async createEmbeddingsWithRetry(
input: string | string[]
): Promise<number[][]> {
return this.caller.call(async () => {
const response = await this.client.embeddings({
...this.requestParams,
input,
});
return response.data.map((d) => d.embedding as number[]);
});
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/src | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/src/tests/embeddings.int.test.ts | import { test, expect } from "@jest/globals";
import { MixedbreadAIEmbeddings } from "../embeddings.js";
test("Test MixedbreadAIEmbeddings.embedQuery", async () => {
const mxbai = new MixedbreadAIEmbeddings();
const res = await mxbai.embedQuery("mixedbread ai");
expect(typeof res[0]).toBe("number");
});
test("Test MixedbreadAIEmbeddings.embedDocuments", async () => {
const mxbai = new MixedbreadAIEmbeddings();
const res = await mxbai.embedDocuments([
"mischbrot ki gmbh",
"mixedbread ai inc.",
]);
expect(res).toHaveLength(2);
expect(typeof res[0][0]).toBe("number");
expect(typeof res[1][0]).toBe("number");
});
test("Test MixedbreadAIEmbeddings concurrency", async () => {
const mxbai = new MixedbreadAIEmbeddings({
batchSize: 1,
maxConcurrency: 2,
});
const res = await mxbai.embedDocuments([
"Bread",
"No bread",
"Bread again",
"No bread again",
"Bread one more time",
"No bread one more time",
]);
expect(res).toHaveLength(6);
expect(res.find((embedding) => typeof embedding[0] !== "number")).toBe(
undefined
);
});
|
0 | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/src | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/src/tests/reranker.int.test.ts | /* eslint-disable no-process-env */
import { Document } from "@langchain/core/documents";
import { MixedbreadAIReranker } from "../reranker.js";
const query = "What is the capital of France?";
const documents = [
new Document({
pageContent:
"Bread is a staple food prepared from a dough of flour and water",
}),
new Document({
pageContent:
"There are many types of bread, such as baguette, focaccia, and sourdough, and they are all delicious.",
}),
new Document({
pageContent:
"And it is usually baked, such as the models from mixedbread ai",
}),
];
test("MixedbreadAIReranker can indeed rerank documents with compressDocuments method", async () => {
const mxbaiReranker = new MixedbreadAIReranker();
const rerankedDocuments = await mxbaiReranker.compressDocuments(
documents,
query
);
// console.log(rerankedDocuments);
expect(rerankedDocuments).toHaveLength(3);
});
test("MixedbreadAIReranker can indeed rerank documents with rerank method", async () => {
const mxbaiReranker = new MixedbreadAIReranker();
const rerankedDocuments = await mxbaiReranker.rerank(
documents.map((doc) => doc.pageContent),
query
);
// console.log(rerankedDocuments);
expect(rerankedDocuments).toHaveLength(3);
});
|
0 | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai | lc_public_repos/langchainjs/libs/langchain-mixedbread-ai/scripts/jest-setup-after-env.js | import { awaitAllCallbacks } from "@langchain/core/callbacks/promises";
import { afterAll, jest } from "@jest/globals";
afterAll(awaitAllCallbacks);
// Allow console.log to be disabled in tests
if (process.env.DISABLE_CONSOLE_LOGS === "true") {
console.log = jest.fn();
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/tsconfig.json | {
"extends": "@tsconfig/recommended",
"compilerOptions": {
"outDir": "../dist",
"rootDir": "./src",
"target": "ES2021",
"lib": ["ES2021", "ES2022.Object", "DOM"],
"module": "nodenext",
"moduleResolution": "nodenext",
"esModuleInterop": true,
"declaration": true,
"noImplicitReturns": true,
"noFallthroughCasesInSwitch": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"useDefineForClassFields": true,
"strictPropertyInitialization": false,
"allowJs": true,
"strict": true
},
"include": ["src/**/*"],
"exclude": ["node_modules", "dist", "docs"]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/LICENSE | The MIT License
Copyright (c) 2023 LangChain
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE. |
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/jest.config.cjs | /** @type {import('ts-jest').JestConfigWithTsJest} */
module.exports = {
preset: "ts-jest/presets/default-esm",
testEnvironment: "./jest.env.cjs",
modulePathIgnorePatterns: ["dist/", "docs/"],
moduleNameMapper: {
"^(\\.{1,2}/.*)\\.js$": "$1",
},
transform: {
"^.+\\.tsx?$": ["@swc/jest"],
},
transformIgnorePatterns: [
"/node_modules/",
"\\.pnp\\.[^\\/]+$",
"./scripts/jest-setup-after-env.js",
],
setupFiles: ["dotenv/config"],
testTimeout: 20_000,
passWithNoTests: true,
collectCoverageFrom: ["src/**/*.ts"],
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/jest.env.cjs | const { TestEnvironment } = require("jest-environment-node");
class AdjustedTestEnvironmentToSupportFloat32Array extends TestEnvironment {
constructor(config, context) {
// Make `instanceof Float32Array` return true in tests
// to avoid https://github.com/xenova/transformers.js/issues/57 and https://github.com/jestjs/jest/issues/2549
super(config, context);
this.global.Float32Array = Float32Array;
}
}
module.exports = AdjustedTestEnvironmentToSupportFloat32Array;
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/README.md | # LangChain.js Standard Tests
This package contains the base standard tests for LangChain.js. It includes unit, and integration test classes.
This package is not intended to be used outside of the LangChain.js project, and thus it is not published to npm.
At the moment, we only have support for standard tets for chat models.
## Usage
Each LangChain.js integration should contain both unit and integration standard tests.
The package should have `@langchain/standard-tests` as a dev workspace dependency like so:
`package.json`:
```json
{
"devDependencies": {
"@langchain/standard-tests": "workspace:*"
}
}
```
To use the standard tests, you could create two files:
- `src/tests/chat_models.standard.test.ts` - chat model unit tests
- `src/tests/chat_models.standard.int.test.ts` - chat model integration tests
Your unit test file should look like this:
`chat_models.standard.test.ts`:
```typescript
/* eslint-disable no-process-env */
import { test, expect } from "@jest/globals";
import { ChatModelUnitTests } from "@langchain/standard-tests";
import { AIMessageChunk } from "@langchain/core/messages";
import { MyChatModel, MyChatModelCallOptions } from "../chat_models.js";
class MyChatModelStandardUnitTests extends ChatModelUnitTests<
MyChatModelCallOptions,
AIMessageChunk
> {
constructor() {
super({
Cls: MyChatModel,
chatModelHasToolCalling: true, // Set to true if the model has tool calling support
chatModelHasStructuredOutput: true, // Set to true if the model has withStructuredOutput support
constructorArgs: {}, // Any additional constructor args
});
// This must be set so method like `.bindTools` or `.withStructuredOutput`
// which we call after instantiating the model will work.
// (constructor will throw if API key is not set)
process.env.CHAT_MODEL_API_KEY = "test";
}
testChatModelInitApiKey() {
// Unset the API key env var here so this test can properly check
// the API key class arg.
process.env.CHAT_MODEL_API_KEY = "";
super.testChatModelInitApiKey();
// Re-set the API key env var here so other tests can run properly.
process.env.CHAT_MODEL_API_KEY = "test";
}
}
const testClass = new MyChatModelStandardUnitTests();
test("MyChatModelStandardUnitTests", () => {
const testResults = testClass.runTests();
expect(testResults).toBe(true);
});
```
To use the standard tests, extend the `ChatModelUnitTests` class, passing in your chat model's call options and message chunk types. Super the constructor with your chat model class, any additional constructor args, and set `chatModelHasToolCalling` and `chatModelHasStructuredOutput` flags if supported.
Set the model env var in the constructor directly to `process.env` for the tests to run properly. You can optionally override test methods to replace or add code before/after the test runs.
Run all tests by calling `.runTests()`, which returns `true` if all tests pass, `false` otherwise. Tests are called in `try`/`catch` blocks, so failing tests are caught and marked as failed, but the rest still run.
For integration tests, extend `ChatModelIntegrationTests` instead. Integration tests have an optional arg for all methods (except `withStructuredOutput`) to pass in "invoke" time call options. For example, in the OpenAI integration test:
```typescript
async testUsageMetadataStreaming() {
// ChatOpenAI does not support streaming tokens by
// default, so we must pass in a call option to
// enable streaming tokens.
const callOptions: ChatOpenAI["ParsedCallOptions"] = {
stream_options: {
include_usage: true,
},
};
await super.testUsageMetadataStreaming(callOptions);
}
```
This overrides the base `testUsageMetadataStreaming` to pass a `callOptions` arg enabling streaming tokens.
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/.release-it.json | {
"github": {
"release": true,
"autoGenerate": true,
"tokenRef": "GITHUB_TOKEN_RELEASE"
},
"npm": {
"versionArgs": ["--workspaces-update=false"]
}
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/.eslintrc.cjs | module.exports = {
extends: [
"airbnb-base",
"eslint:recommended",
"prettier",
"plugin:@typescript-eslint/recommended",
],
parserOptions: {
ecmaVersion: 12,
parser: "@typescript-eslint/parser",
project: "./tsconfig.json",
sourceType: "module",
},
plugins: ["@typescript-eslint", "no-instanceof"],
ignorePatterns: [
".eslintrc.cjs",
"scripts",
"node_modules",
"dist",
"dist-cjs",
"*.js",
"*.cjs",
"*.d.ts",
],
rules: {
"no-process-env": 2,
"no-instanceof/no-instanceof": 2,
"@typescript-eslint/explicit-module-boundary-types": 0,
"@typescript-eslint/no-empty-function": 0,
"@typescript-eslint/no-shadow": 0,
"@typescript-eslint/no-empty-interface": 0,
"@typescript-eslint/no-explicit-any": "warn",
"@typescript-eslint/no-use-before-define": ["error", "nofunc"],
"@typescript-eslint/no-unused-vars": ["warn", { args: "none" }],
"@typescript-eslint/no-floating-promises": "error",
"@typescript-eslint/no-misused-promises": "error",
camelcase: 0,
"class-methods-use-this": 0,
"import/extensions": [2, "ignorePackages"],
"import/no-extraneous-dependencies": [
"error",
{ devDependencies: ["**/*.test.ts"] },
],
"import/no-unresolved": 0,
"import/prefer-default-export": 0,
"keyword-spacing": "error",
"max-classes-per-file": 0,
"max-len": 0,
"no-await-in-loop": 0,
"no-bitwise": 0,
"no-console": 0,
"no-restricted-syntax": 0,
"no-shadow": 0,
"no-continue": 0,
"no-void": 0,
"no-underscore-dangle": 0,
"no-use-before-define": 0,
"no-useless-constructor": 0,
"no-return-await": 0,
"consistent-return": 0,
"no-else-return": 0,
"func-names": 0,
"no-lonely-if": 0,
"prefer-rest-params": 0,
"new-cap": ["error", { properties: false, capIsNew: false }],
},
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/langchain.config.js | import { resolve, dirname } from "node:path";
import { fileURLToPath } from "node:url";
/**
* @param {string} relativePath
* @returns {string}
*/
function abs(relativePath) {
return resolve(dirname(fileURLToPath(import.meta.url)), relativePath);
}
export const config = {
internals: [/node\:/, /@langchain\/core\//],
entrypoints: {
index: "index",
},
tsConfigPath: resolve("./tsconfig.json"),
cjsSource: "./dist-cjs",
cjsDestination: "./dist",
abs,
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/package.json | {
"name": "@langchain/standard-tests",
"version": "0.0.0",
"description": "Standard tests for LangChain.js",
"type": "module",
"engines": {
"node": ">=18"
},
"main": "./index.js",
"types": "./index.d.ts",
"repository": {
"type": "git",
"url": "git@github.com:langchain-ai/langchainjs.git"
},
"homepage": "https://github.com/langchain-ai/langchainjs/tree/main/libs/langchain-standard-tests/",
"scripts": {
"build": "yarn turbo:command build:internal --filter=@langchain/standard-tests",
"build:internal": "yarn lc_build --create-entrypoints --pre --tree-shaking",
"lint:eslint": "NODE_OPTIONS=--max-old-space-size=4096 eslint --cache --ext .ts,.js src/",
"lint:dpdm": "dpdm --exit-code circular:1 --no-warning --no-tree src/*.ts src/**/*.ts",
"lint": "yarn lint:eslint && yarn lint:dpdm",
"lint:fix": "yarn lint:eslint --fix && yarn lint:dpdm",
"clean": "rm -rf .turbo dist/",
"prepack": "yarn build",
"test": "NODE_OPTIONS=--experimental-vm-modules jest --testPathIgnorePatterns=\\.int\\.test.ts --testTimeout 30000 --maxWorkers=50%",
"test:watch": "NODE_OPTIONS=--experimental-vm-modules jest --watch --testPathIgnorePatterns=\\.int\\.test.ts",
"test:single": "NODE_OPTIONS=--experimental-vm-modules yarn run jest --config jest.config.cjs --testTimeout 100000",
"test:int": "NODE_OPTIONS=--experimental-vm-modules jest --testPathPattern=\\.int\\.test.ts --testTimeout 100000 --maxWorkers=50%",
"format": "prettier --config .prettierrc --write \"src\"",
"format:check": "prettier --config .prettierrc --check \"src\""
},
"author": "LangChain",
"license": "MIT",
"dependencies": {
"@jest/globals": "^29.5.0",
"@langchain/core": "workspace:*",
"zod": "^3.22.4",
"zod-to-json-schema": "^3.23.0"
},
"devDependencies": {
"@langchain/scripts": "workspace:*",
"@swc/core": "^1.3.90",
"@swc/jest": "^0.2.29",
"@tsconfig/recommended": "^1.0.3",
"@typescript-eslint/eslint-plugin": "^6.12.0",
"@typescript-eslint/parser": "^6.12.0",
"dotenv": "^16.3.1",
"dpdm": "^3.12.0",
"eslint": "^8.33.0",
"eslint-config-airbnb-base": "^15.0.0",
"eslint-config-prettier": "^8.6.0",
"eslint-plugin-import": "^2.27.5",
"eslint-plugin-no-instanceof": "^1.0.1",
"eslint-plugin-prettier": "^4.2.1",
"jest": "^29.5.0",
"jest-environment-node": "^29.6.4",
"prettier": "^2.8.3",
"release-it": "^17.6.0",
"rollup": "^4.5.2",
"ts-jest": "^29.1.0",
"typescript": "^5.4.5"
},
"publishConfig": {
"access": "public"
},
"exports": {
".": {
"types": {
"import": "./index.d.ts",
"require": "./index.d.cts",
"default": "./index.d.ts"
},
"import": "./index.js",
"require": "./index.cjs"
},
"./package.json": "./package.json"
},
"files": [
"dist/",
"index.cjs",
"index.js",
"index.d.ts",
"index.d.cts"
]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/tsconfig.cjs.json | {
"extends": "./tsconfig.json",
"compilerOptions": {
"declaration": false
},
"exclude": ["node_modules", "dist", "docs", "**/tests"]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/turbo.json | {
"extends": ["//"],
"pipeline": {
"build": {
"outputs": ["**/dist/**"]
},
"build:internal": {
"dependsOn": ["^build:internal"]
}
}
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-standard-tests/.prettierrc | {
"$schema": "https://json.schemastore.org/prettierrc",
"printWidth": 80,
"tabWidth": 2,
"useTabs": false,
"semi": true,
"singleQuote": false,
"quoteProps": "as-needed",
"jsxSingleQuote": false,
"trailingComma": "es5",
"bracketSpacing": true,
"arrowParens": "always",
"requirePragma": false,
"insertPragma": false,
"proseWrap": "preserve",
"htmlWhitespaceSensitivity": "css",
"vueIndentScriptAndStyle": false,
"endOfLine": "lf"
}
|
0 | lc_public_repos/langchainjs/libs/langchain-standard-tests | lc_public_repos/langchainjs/libs/langchain-standard-tests/src/index.ts | export * from "./unit_tests/chat_models.js";
export * from "./integration_tests/chat_models.js";
|
0 | lc_public_repos/langchainjs/libs/langchain-standard-tests | lc_public_repos/langchainjs/libs/langchain-standard-tests/src/base.ts | import {
BaseChatModel,
BaseChatModelCallOptions,
} from "@langchain/core/language_models/chat_models";
import { BaseMessageChunk } from "@langchain/core/messages";
export type RecordStringAny = Record<string, any>;
export type BaseChatModelConstructor<
CallOptions extends BaseChatModelCallOptions = BaseChatModelCallOptions,
OutputMessageType extends BaseMessageChunk = BaseMessageChunk,
ConstructorArgs extends RecordStringAny = RecordStringAny
> = new (args: ConstructorArgs) => BaseChatModel<
CallOptions,
OutputMessageType
>;
export type BaseChatModelsTestsFields<
CallOptions extends BaseChatModelCallOptions = BaseChatModelCallOptions,
OutputMessageType extends BaseMessageChunk = BaseMessageChunk,
ConstructorArgs extends RecordStringAny = RecordStringAny
> = {
Cls: BaseChatModelConstructor<
CallOptions,
OutputMessageType,
ConstructorArgs
>;
chatModelHasToolCalling: boolean;
chatModelHasStructuredOutput: boolean;
constructorArgs: ConstructorArgs;
};
export class BaseChatModelsTests<
CallOptions extends BaseChatModelCallOptions = BaseChatModelCallOptions,
OutputMessageType extends BaseMessageChunk = BaseMessageChunk,
ConstructorArgs extends RecordStringAny = RecordStringAny
> implements
BaseChatModelsTestsFields<CallOptions, OutputMessageType, ConstructorArgs>
{
Cls: BaseChatModelConstructor<
CallOptions,
OutputMessageType,
ConstructorArgs
>;
chatModelHasToolCalling: boolean;
chatModelHasStructuredOutput: boolean;
constructorArgs: ConstructorArgs;
constructor(
fields: BaseChatModelsTestsFields<
CallOptions,
OutputMessageType,
ConstructorArgs
>
) {
this.Cls = fields.Cls;
this.chatModelHasToolCalling = fields.chatModelHasToolCalling;
this.chatModelHasStructuredOutput = fields.chatModelHasStructuredOutput;
this.constructorArgs = fields.constructorArgs;
}
get multipleApiKeysRequiredMessage(): string {
return "Multiple API keys are required.";
}
/**
* Log a warning message when skipping a test.
*/
skipTestMessage(
testName: string,
chatClassName: string,
extra?: string
): void {
console.warn(
{
chatClassName,
reason: extra ?? "n/a",
},
`Skipping ${testName}.`
);
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-standard-tests/src | lc_public_repos/langchainjs/libs/langchain-standard-tests/src/integration_tests/chat_models.ts | /* eslint-disable @typescript-eslint/no-explicit-any */
import { expect } from "@jest/globals";
import { BaseChatModelCallOptions } from "@langchain/core/language_models/chat_models";
import {
AIMessage,
AIMessageChunk,
BaseMessageChunk,
HumanMessage,
ToolMessage,
UsageMetadata,
getBufferString,
} from "@langchain/core/messages";
import { z } from "zod";
import {
StructuredTool,
StructuredToolParams,
tool,
} from "@langchain/core/tools";
import { zodToJsonSchema } from "zod-to-json-schema";
import { ChatPromptTemplate } from "@langchain/core/prompts";
import { RunnableLambda } from "@langchain/core/runnables";
import { concat } from "@langchain/core/utils/stream";
import { StreamEvent } from "@langchain/core/tracers/log_stream";
import {
BaseChatModelsTests,
BaseChatModelsTestsFields,
RecordStringAny,
} from "../base.js";
const adderSchema = /* #__PURE__ */ z
.object({
a: z.number().int().describe("The first integer to add."),
b: z.number().int().describe("The second integer to add."),
})
.describe("Add two integers");
class AdderTool extends StructuredTool {
name = "AdderTool";
description = adderSchema.description ?? "description";
schema = adderSchema;
async _call(input: z.infer<typeof adderSchema>) {
const sum = input.a + input.b;
return JSON.stringify({ result: sum });
}
}
const MATH_ADDITION_PROMPT = /* #__PURE__ */ ChatPromptTemplate.fromMessages([
[
"system",
"You are bad at math and must ALWAYS call the {toolName} function.",
],
["human", "What is the sum of 1836281973 and 19973286?"],
]);
interface ChatModelIntegrationTestsFields<
CallOptions extends BaseChatModelCallOptions = BaseChatModelCallOptions,
OutputMessageType extends BaseMessageChunk = BaseMessageChunk,
ConstructorArgs extends RecordStringAny = RecordStringAny
> extends BaseChatModelsTestsFields<
CallOptions,
OutputMessageType,
ConstructorArgs
> {
/**
* Override the default AIMessage response type
* to check for.
* @default AIMessage
*/
invokeResponseType?: typeof AIMessage | typeof AIMessageChunk;
/**
* The ID to set for function calls.
* Set this field to override the default function ID.
* @default "abc123"
*/
functionId?: string;
/**
* Whether or not the model supports parallel tool calling.
* @default false
*/
supportsParallelToolCalls?: boolean;
}
export abstract class ChatModelIntegrationTests<
CallOptions extends BaseChatModelCallOptions = BaseChatModelCallOptions,
OutputMessageType extends BaseMessageChunk = BaseMessageChunk,
ConstructorArgs extends RecordStringAny = RecordStringAny
> extends BaseChatModelsTests<CallOptions, OutputMessageType, ConstructorArgs> {
functionId = "abc123";
invokeResponseType: typeof AIMessage | typeof AIMessageChunk = AIMessage;
supportsParallelToolCalls = false;
// Add these new properties
supportedUsageMetadataDetails: {
invoke: Array<
| "audio_input"
| "audio_output"
| "reasoning_output"
| "cache_read_input"
| "cache_creation_input"
>;
stream: Array<
| "audio_input"
| "audio_output"
| "reasoning_output"
| "cache_read_input"
| "cache_creation_input"
>;
} = { invoke: [], stream: [] };
constructor(
fields: ChatModelIntegrationTestsFields<
CallOptions,
OutputMessageType,
ConstructorArgs
>
) {
super(fields);
this.functionId = fields.functionId ?? this.functionId;
this.invokeResponseType =
fields.invokeResponseType ?? this.invokeResponseType;
this.supportsParallelToolCalls =
fields.supportsParallelToolCalls ?? this.supportsParallelToolCalls;
}
/**
* Tests the basic `invoke` method of the chat model.
* This test ensures that the model can process a simple input and return a valid response.
*
* It verifies that:
* 1. The result is defined and is an instance of the correct type.
* 2. The content of the response is a non-empty string.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testInvoke(callOptions?: any) {
// Create a new instance of the chat model
const chatModel = new this.Cls(this.constructorArgs);
// Invoke the model with a simple "Hello" message
const result = await chatModel.invoke("Hello", callOptions);
// Verify that the result is defined
expect(result).toBeDefined();
// Check that the result is an instance of the expected response type
expect(result).toBeInstanceOf(this.invokeResponseType);
// Ensure that the content of the response is a string
expect(typeof result.content).toBe("string");
// Verify that the response content is not empty
expect(result.content).not.toBe("");
}
/**
* Tests the streaming capability of the chat model.
* This test ensures that the model can properly stream responses
* and that each streamed token is a valid AIMessageChunk.
*
* It verifies that:
* 1. Each streamed token is defined and is an instance of AIMessageChunk.
* 2. The content of each token is a string.
* 3. The total number of characters streamed is greater than zero.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testStream(callOptions?: any) {
const chatModel = new this.Cls(this.constructorArgs);
let numChars = 0;
// Stream the response for a simple "Hello" prompt
for await (const token of await chatModel.stream("Hello", callOptions)) {
// Verify each token is defined and of the correct type
expect(token).toBeDefined();
expect(token).toBeInstanceOf(AIMessageChunk);
// Ensure the content of each token is a string
expect(typeof token.content).toBe("string");
// Keep track of the total number of characters
numChars += token.content.length;
}
// Verify that some content was actually streamed
expect(numChars).toBeGreaterThan(0);
}
/**
* Tests the batch processing capability of the chat model.
* This test ensures that the model can handle multiple inputs simultaneously
* and return appropriate responses for each.
*
* It verifies that:
* 1. The batch results are defined and in array format.
* 2. The number of results matches the number of inputs.
* 3. Each result is of the correct type and has non-empty content.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testBatch(callOptions?: any) {
const chatModel = new this.Cls(this.constructorArgs);
// Process two simple prompts in batch
const batchResults = await chatModel.batch(["Hello", "Hey"], callOptions);
// Verify that results are returned
expect(batchResults).toBeDefined();
// Check that the results are in array format
expect(Array.isArray(batchResults)).toBe(true);
// Ensure the number of results matches the number of inputs
expect(batchResults.length).toBe(2);
// Validate each result individually
for (const result of batchResults) {
// Check that the result is defined
expect(result).toBeDefined();
// Verify the result is of the expected type
expect(result).toBeInstanceOf(this.invokeResponseType);
// Ensure the content is a non-empty string
expect(typeof result.content).toBe("string");
expect(result.content).not.toBe("");
}
}
/**
* Tests the model can properly use the `.streamEvents` method.
* This test ensures the `.streamEvents` method yields at least
* three event types: `on_chat_model_start`, `on_chat_model_stream`,
* and `on_chat_model_end`.
*
* It also verifies the first chunk is an `on_chat_model_start` event,
* and the last chunk is an `on_chat_model_end` event. The middle chunk
* should be an `on_chat_model_stream` event.
*
* Finally, it verifies the final chunk's `event.data.output` field
* matches the concatenated content of all `on_chat_model_stream` events.
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testStreamEvents(callOptions?: any) {
const chatModel = new this.Cls(this.constructorArgs);
const stream = chatModel.streamEvents("Hello", {
...callOptions,
version: "v2",
} as Partial<CallOptions> & { version: "v2" | "v1" });
const events: StreamEvent[] = [];
for await (const chunk of stream) {
events.push(chunk);
}
// It must have at least 3: on_chat_model_start, on_chat_model_stream, and on_chat_model_end
expect(events.length).toBeGreaterThanOrEqual(3);
expect(events[0].event).toBe("on_chat_model_start");
expect(events[events.length - 1].event).toBe("on_chat_model_end");
const middleItem = events[Math.floor(events.length / 2)];
expect(middleItem.event).toBe("on_chat_model_stream");
// The last event should contain the final content via the `event.data.output` field
const endContent = events[events.length - 1].data.output;
let endContentText = "";
if (typeof endContent === "string") {
endContentText = endContent;
} else if (Array.isArray(endContent) && "text" in endContent[0]) {
endContentText = endContent[0].text;
} else {
throw new Error(
`Invalid final chunk received from .streamEvents:${endContent}`
);
}
// All of the `*_stream` events should contain the content via the `event.data.output` field
// When concatenated, this chunk should equal the final chunk.
const allChunks = events.flatMap((e) => {
if (e.event === "on_chat_model_stream") {
return e.data.output;
}
return [];
});
const allChunksText: string = allChunks
.flatMap((c) => {
if (typeof c === "string") {
return c;
} else if (Array.isArray(c) && "text" in c[0]) {
return c[0].text;
}
return [];
})
.join("");
expect(endContentText).toBe(allChunksText);
}
/**
* Tests the chat model's ability to handle a conversation with multiple messages.
* This test ensures that the model can process a sequence of messages from different roles
* (Human and AI) and generate an appropriate response.
*
* It verifies that:
* 1. The result is defined and is an instance of the correct response type.
* 2. The content of the response is a non-empty string.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testConversation(callOptions?: any) {
// Create a new instance of the chat model
const chatModel = new this.Cls(this.constructorArgs);
// Prepare a conversation history with alternating Human and AI messages
const messages = [
new HumanMessage("hello"),
new AIMessage("hello"),
new HumanMessage("how are you"),
];
// Invoke the model with the conversation history
const result = await chatModel.invoke(messages, callOptions);
// Verify that the result is defined
expect(result).toBeDefined();
// Check that the result is an instance of the expected response type
expect(result).toBeInstanceOf(this.invokeResponseType);
// Ensure that the content of the response is a string
expect(typeof result.content).toBe("string");
// Verify that the response content is not empty
expect(result.content).not.toBe("");
}
/**
* Tests the usage metadata functionality of the chat model.
* This test ensures that the model returns proper usage metadata
* after invoking it with a simple message.
*
* It verifies that:
* 1. The result is defined and is an instance of the correct response type.
* 2. The result contains the `usage_metadata` field.
* 3. The `usage_metadata` field contains `input_tokens`, `output_tokens`, and `total_tokens`,
* all of which are numbers.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testUsageMetadata(callOptions?: any) {
// Create a new instance of the chat model
const chatModel = new this.Cls(this.constructorArgs);
// Invoke the model with a simple "Hello" message
const result = await chatModel.invoke("Hello", callOptions);
// Verify that the result is defined
expect(result).toBeDefined();
// Check that the result is an instance of the expected response type
expect(result).toBeInstanceOf(this.invokeResponseType);
// Ensure that the result contains usage_metadata
if (!("usage_metadata" in result)) {
throw new Error("result is not an instance of AIMessage");
}
// Extract the usage metadata from the result
const usageMetadata = result.usage_metadata as UsageMetadata;
// Verify that usage metadata is defined
expect(usageMetadata).toBeDefined();
// Check that input_tokens is a number
expect(typeof usageMetadata.input_tokens).toBe("number");
// Check that output_tokens is a number
expect(typeof usageMetadata.output_tokens).toBe("number");
// Check that total_tokens is a number
expect(typeof usageMetadata.total_tokens).toBe("number");
// Test additional usage metadata details
if (this.supportedUsageMetadataDetails.invoke.includes("audio_input")) {
const msgWithAudioInput = await this.invokeWithAudioInput(false);
this.assertAudioInputMetadata(msgWithAudioInput);
}
if (this.supportedUsageMetadataDetails.invoke.includes("audio_output")) {
const msgWithAudioOutput = await this.invokeWithAudioOutput(false);
this.assertAudioOutputMetadata(msgWithAudioOutput);
}
if (
this.supportedUsageMetadataDetails.invoke.includes("reasoning_output")
) {
const msgWithReasoningOutput = await this.invokeWithReasoningOutput(
false
);
this.assertReasoningOutputMetadata(msgWithReasoningOutput);
}
if (
this.supportedUsageMetadataDetails.invoke.includes("cache_read_input")
) {
const msgWithCacheReadInput = await this.invokeWithCacheReadInput(false);
this.assertCacheReadInputMetadata(msgWithCacheReadInput);
}
if (
this.supportedUsageMetadataDetails.invoke.includes("cache_creation_input")
) {
const msgWithCacheCreationInput = await this.invokeWithCacheCreationInput(
false
);
this.assertCacheCreationInputMetadata(msgWithCacheCreationInput);
}
}
async invokeWithAudioInput(_stream: boolean): Promise<AIMessage> {
// Initialize the model so we can access the `.getName()` method
// for better error messages.
const chatModel = new this.Cls(this.constructorArgs);
throw new Error(
`invokeWithAudioInput is not implemented on ${chatModel.getName()}` +
"standard integration tests."
);
}
async invokeWithAudioOutput(_stream: boolean): Promise<AIMessage> {
// Initialize the model so we can access the `.getName()` method
// for better error messages.
const chatModel = new this.Cls(this.constructorArgs);
throw new Error(
`invokeWithAudioOutput is not implemented on ${chatModel.getName()}` +
"standard integration tests."
);
}
async invokeWithReasoningOutput(_stream: boolean): Promise<AIMessage> {
// Initialize the model so we can access the `.getName()` method
// for better error messages.
const chatModel = new this.Cls(this.constructorArgs);
throw new Error(
`invokeWithReasoningOutput is not implemented on ${chatModel.getName()}` +
"standard integration tests."
);
}
async invokeWithCacheReadInput(_stream: boolean): Promise<AIMessage> {
// Initialize the model so we can access the `.getName()` method
// for better error messages.
const chatModel = new this.Cls(this.constructorArgs);
throw new Error(
`invokeWithCacheReadInput is not implemented on ${chatModel.getName()}` +
"standard integration tests."
);
}
async invokeWithCacheCreationInput(_stream: boolean): Promise<AIMessage> {
// Initialize the model so we can access the `.getName()` method
// for better error messages.
const chatModel = new this.Cls(this.constructorArgs);
throw new Error(
`invokeWithCacheCreationInput is not implemented on ${chatModel.getName()}` +
"standard integration tests."
);
}
private assertAudioInputMetadata(msg: AIMessage) {
expect(msg.usage_metadata).toBeDefined();
expect(msg.usage_metadata?.input_token_details).toBeDefined();
expect(typeof msg.usage_metadata?.input_token_details?.audio).toBe(
"number"
);
expect(msg.usage_metadata?.input_tokens).toBeGreaterThanOrEqual(
Object.values(msg.usage_metadata?.input_token_details ?? {}).reduce(
(a, b) => (a ?? 0) + (b ?? 0),
0
)
);
}
private assertAudioOutputMetadata(msg: AIMessage) {
expect(msg.usage_metadata).toBeDefined();
expect(msg.usage_metadata?.output_token_details).toBeDefined();
expect(typeof msg.usage_metadata?.output_token_details?.audio).toBe(
"number"
);
expect(msg.usage_metadata?.output_tokens).toBeGreaterThanOrEqual(
Object.values(msg.usage_metadata?.output_token_details ?? {}).reduce(
(a, b) => (a ?? 0) + (b ?? 0),
0
)
);
}
private assertReasoningOutputMetadata(msg: AIMessage) {
expect(msg.usage_metadata).toBeDefined();
expect(msg.usage_metadata?.output_token_details).toBeDefined();
expect(typeof msg.usage_metadata?.output_token_details?.reasoning).toBe(
"number"
);
expect(msg.usage_metadata?.output_tokens).toBeGreaterThanOrEqual(
Object.values(msg.usage_metadata?.output_token_details ?? {}).reduce(
(a, b) => (a ?? 0) + (b ?? 0),
0
)
);
}
private assertCacheReadInputMetadata(msg: AIMessage) {
expect(msg.usage_metadata).toBeDefined();
expect(msg.usage_metadata?.input_token_details).toBeDefined();
expect(typeof msg.usage_metadata?.input_token_details?.cache_read).toBe(
"number"
);
expect(msg.usage_metadata?.input_tokens).toBeGreaterThanOrEqual(
Object.values(msg.usage_metadata?.input_token_details ?? {}).reduce(
(a, b) => (a ?? 0) + (b ?? 0),
0
)
);
}
private assertCacheCreationInputMetadata(msg: AIMessage) {
expect(msg.usage_metadata).toBeDefined();
expect(msg.usage_metadata?.input_token_details).toBeDefined();
expect(typeof msg.usage_metadata?.input_token_details?.cache_creation).toBe(
"number"
);
expect(msg.usage_metadata?.input_tokens).toBeGreaterThanOrEqual(
Object.values(msg.usage_metadata?.input_token_details ?? {}).reduce(
(a, b) => (a ?? 0) + (b ?? 0),
0
)
);
}
/**
* Tests the usage metadata functionality for streaming responses from the chat model.
* This test ensures that the model returns proper usage metadata
* after streaming a response for a simple message.
*
* It verifies that:
* 1. Each streamed chunk is defined and is an instance of AIMessageChunk.
* 2. The final concatenated result contains the `usage_metadata` field.
* 3. The `usage_metadata` field contains `input_tokens`, `output_tokens`, and `total_tokens`,
* all of which are numbers.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testUsageMetadataStreaming(callOptions?: any) {
const chatModel = new this.Cls(this.constructorArgs);
let finalChunks: AIMessageChunk | undefined;
// Stream the response for a simple "Hello" prompt
for await (const chunk of await chatModel.stream("Hello", callOptions)) {
// Verify each chunk is defined and of the correct type
expect(chunk).toBeDefined();
expect(chunk).toBeInstanceOf(AIMessageChunk);
// Concatenate chunks to get the final result
if (!finalChunks) {
finalChunks = chunk;
} else {
finalChunks = finalChunks.concat(chunk);
}
}
// Ensure we received at least one chunk
if (!finalChunks) {
throw new Error("finalChunks is undefined");
}
// Extract usage metadata from the final concatenated result
const usageMetadata = finalChunks.usage_metadata;
expect(usageMetadata).toBeDefined();
// Ensure usage metadata is present
if (!usageMetadata) {
throw new Error("usageMetadata is undefined");
}
// Verify that input_tokens, output_tokens, and total_tokens are numbers
expect(typeof usageMetadata.input_tokens).toBe("number");
expect(typeof usageMetadata.output_tokens).toBe("number");
expect(typeof usageMetadata.total_tokens).toBe("number");
// Test additional usage metadata details
if (this.supportedUsageMetadataDetails.invoke.includes("audio_input")) {
const msgWithAudioInput = await this.invokeWithAudioInput(true);
this.assertAudioInputMetadata(msgWithAudioInput);
}
if (this.supportedUsageMetadataDetails.invoke.includes("audio_output")) {
const msgWithAudioOutput = await this.invokeWithAudioOutput(true);
this.assertAudioOutputMetadata(msgWithAudioOutput);
}
if (
this.supportedUsageMetadataDetails.invoke.includes("reasoning_output")
) {
const msgWithReasoningOutput = await this.invokeWithReasoningOutput(true);
this.assertReasoningOutputMetadata(msgWithReasoningOutput);
}
if (
this.supportedUsageMetadataDetails.invoke.includes("cache_read_input")
) {
const msgWithCacheReadInput = await this.invokeWithCacheReadInput(true);
this.assertCacheReadInputMetadata(msgWithCacheReadInput);
}
if (
this.supportedUsageMetadataDetails.invoke.includes("cache_creation_input")
) {
const msgWithCacheCreationInput = await this.invokeWithCacheCreationInput(
true
);
this.assertCacheCreationInputMetadata(msgWithCacheCreationInput);
}
}
/**
* Tests the chat model's ability to handle message histories with string tool contents.
* This test is specifically designed for models that support tool calling with string-based content,
* such as OpenAI's GPT models.
*
* The test performs the following steps:
* 1. Creates a chat model and binds an AdderTool to it.
* 2. Constructs a message history that includes a HumanMessage, an AIMessage with string content
* (simulating a tool call), and a ToolMessage with the tool's response.
* 3. Invokes the model with this message history.
* 4. Verifies that the result is of the expected type (AIMessage or AIMessageChunk).
*
* This test ensures that the model can correctly process and respond to complex message
* histories that include tool calls with string-based content structures.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testToolMessageHistoriesStringContent(callOptions?: any) {
// Skip the test if the model doesn't support tool calling
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
const adderTool = new AdderTool();
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test tool message histories."
);
}
// Bind the AdderTool to the model
const modelWithTools = model.bindTools([adderTool]);
const functionName = adderTool.name;
const functionArgs = { a: 1, b: 2 };
const { functionId } = this;
// Invoke the tool to get the result
const functionResult = await adderTool.invoke(functionArgs);
// Construct a message history with string-based content
const messagesStringContent = [
new HumanMessage("What is 1 + 2"),
// AIMessage with string content (simulating OpenAI's format)
new AIMessage({
content: "",
tool_calls: [
{
name: functionName,
args: functionArgs,
id: functionId,
},
],
}),
// ToolMessage with the result of the tool call
new ToolMessage(functionResult, functionId, functionName),
];
// Invoke the model with the constructed message history
const result = await modelWithTools.invoke(
messagesStringContent,
callOptions
);
// Verify that the result is of the expected type
expect(result).toBeInstanceOf(this.invokeResponseType);
}
/**
* Tests the chat model's ability to handle message histories with list tool contents.
* This test is specifically designed for models that support tool calling with list-based content,
* such as Anthropic's Claude.
*
* The test performs the following steps:
* 1. Creates a chat model and binds an AdderTool to it.
* 2. Constructs a message history that includes a HumanMessage, an AIMessage with list content
* (simulating a tool call), and a ToolMessage with the tool's response.
* 3. Invokes the model with this message history.
* 4. Verifies that the result is of the expected type (AIMessage or AIMessageChunk).
*
* This test ensures that the model can correctly process and respond to complex message
* histories that include tool calls with list-based content structures.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
*/
async testToolMessageHistoriesListContent(callOptions?: any) {
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
const adderTool = new AdderTool();
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test tool message histories."
);
}
const modelWithTools = model.bindTools([adderTool]);
const functionName = adderTool.name;
const functionArgs = { a: 1, b: 2 };
const { functionId } = this;
const functionResult = await adderTool.invoke(functionArgs);
// Construct a message history with list-based content
const messagesListContent = [
new HumanMessage("What is 1 + 2"),
// AIMessage with list content (simulating Anthropic's format)
new AIMessage({
content: [
{ type: "text", text: "some text" },
{
type: "tool_use",
id: functionId,
name: functionName,
input: functionArgs,
},
],
tool_calls: [
{
name: functionName,
args: functionArgs,
id: functionId,
},
],
}),
// ToolMessage with the result of the tool call
new ToolMessage(functionResult, functionId, functionName),
];
// Invoke the model with the constructed message history
const resultListContent = await modelWithTools.invoke(
messagesListContent,
callOptions
);
// Verify that the result is of the expected type
expect(resultListContent).toBeInstanceOf(this.invokeResponseType);
}
/**
* Tests the chat model's ability to process few-shot examples with tool calls.
* This test ensures that the model can correctly handle and respond to a conversation
* that includes tool calls within the context of few-shot examples.
*
* The test performs the following steps:
* 1. Creates a chat model and binds an AdderTool to it.
* 2. Constructs a message history that simulates a few-shot example scenario:
* - A human message asking about addition
* - An AI message with a tool call to the AdderTool
* - A ToolMessage with the result of the tool call
* - An AI message with the result
* - A new human message asking about a different addition
* 3. Invokes the model with this message history.
* 4. Verifies that the result is of the expected type (AIMessage or AIMessageChunk).
*
* This test is crucial for ensuring that the model can learn from and apply
* the patterns demonstrated in few-shot examples, particularly when those
* examples involve tool usage.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testStructuredFewShotExamples(callOptions?: any) {
// Skip the test if the model doesn't support tool calling
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
const adderTool = new AdderTool();
if (!model.bindTools) {
throw new Error("bindTools undefined. Cannot test few-shot examples.");
}
const modelWithTools = model.bindTools([adderTool]);
const functionName = adderTool.name;
const functionArgs = { a: 1, b: 2 };
const { functionId } = this;
const functionResult = await adderTool.invoke(functionArgs);
// Construct a message history that simulates a few-shot example scenario
const messagesStringContent = [
new HumanMessage("What is 1 + 2"),
new AIMessage({
content: "",
tool_calls: [
{
name: functionName,
args: functionArgs,
id: functionId,
},
],
}),
new ToolMessage(functionResult, functionId, functionName),
new AIMessage(functionResult),
new HumanMessage("What is 3 + 4"), // New question to test if the model learned from the example
];
// Invoke the model with the constructed message history
const result = await modelWithTools.invoke(
messagesStringContent,
callOptions
);
// Verify that the result is of the expected type
expect(result).toBeInstanceOf(this.invokeResponseType);
}
/**
* Tests the chat model's ability to generate structured output using the `withStructuredOutput` method.
* This test ensures that the model can correctly process a prompt and return a response
* that adheres to a predefined schema (adderSchema).
*
* It verifies that:
* 1. The model supports structured output functionality.
* 2. The result contains the expected fields ('a' and 'b') from the adderSchema.
* 3. The values of these fields are of the correct type (number).
*
* This test is crucial for ensuring that the model can generate responses
* in a specific format, which is useful for tasks requiring structured data output.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testWithStructuredOutput(callOptions?: any) {
// Skip the test if the model doesn't support structured output
if (!this.chatModelHasStructuredOutput) {
console.log("Test requires withStructuredOutput. Skipping...");
return;
}
// Create a new instance of the chat model
const model = new this.Cls(this.constructorArgs);
// Ensure the model has the withStructuredOutput method
if (!model.withStructuredOutput) {
throw new Error(
"withStructuredOutput undefined. Cannot test structured output."
);
}
// Create a new model instance with structured output capability
const modelWithTools = model.withStructuredOutput(adderSchema, {
name: "math_addition",
});
// Invoke the model with a predefined prompt
const result = await MATH_ADDITION_PROMPT.pipe(modelWithTools).invoke(
{
toolName: "math_addition",
},
callOptions
);
// Verify that the 'a' field is present and is a number
expect(result.a).toBeDefined();
expect(typeof result.a).toBe("number");
// Verify that the 'b' field is present and is a number
expect(result.b).toBeDefined();
expect(typeof result.b).toBe("number");
}
/**
* Tests the chat model's ability to generate structured output with raw response included.
* This test ensures that the model can correctly process a prompt and return a response
* that adheres to a predefined schema (adderSchema) while also including the raw model output.
*
* It verifies that:
* 1. The model supports structured output functionality with raw response inclusion.
* 2. The result contains both 'raw' and 'parsed' properties.
* 3. The 'raw' property is an instance of the expected response type.
* 4. The 'parsed' property contains the expected fields ('a' and 'b') from the adderSchema.
* 5. The values of these fields in the 'parsed' property are of the correct type (number).
*
* This test is crucial for ensuring that the model can generate responses in a specific format
* while also providing access to the original, unprocessed model output.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testWithStructuredOutputIncludeRaw(callOptions?: any) {
// Skip the test if the model doesn't support structured output
if (!this.chatModelHasStructuredOutput) {
console.log("Test requires withStructuredOutput. Skipping...");
return;
}
// Create a new instance of the chat model
const model = new this.Cls(this.constructorArgs);
// Ensure the model has the withStructuredOutput method
if (!model.withStructuredOutput) {
throw new Error(
"withStructuredOutput undefined. Cannot test tool message histories."
);
}
// Create a new model instance with structured output capability, including raw output
const modelWithTools = model.withStructuredOutput(adderSchema, {
includeRaw: true,
name: "math_addition",
});
// Invoke the model with a predefined prompt
const result = await MATH_ADDITION_PROMPT.pipe(modelWithTools).invoke(
{
toolName: "math_addition",
},
callOptions
);
// Verify that the raw output is of the expected type
expect(result.raw).toBeInstanceOf(this.invokeResponseType);
// Verify that the parsed 'a' field is present and is a number
expect(result.parsed.a).toBeDefined();
expect(typeof result.parsed.a).toBe("number");
// Verify that the parsed 'b' field is present and is a number
expect(result.parsed.b).toBeDefined();
expect(typeof result.parsed.b).toBe("number");
}
/**
* Tests the chat model's ability to bind and use OpenAI-formatted tools.
* This test ensures that the model can correctly process and use tools
* formatted in the OpenAI function calling style.
*
* It verifies that:
* 1. The model supports tool calling functionality.
* 2. The model can successfully bind an OpenAI-formatted tool.
* 3. The model invokes the bound tool correctly when prompted.
* 4. The result contains a tool call with the expected name.
*
* This test is crucial for ensuring compatibility with OpenAI's function
* calling format, which is a common standard in AI tool integration.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testBindToolsWithOpenAIFormattedTools(callOptions?: any) {
// Skip the test if the model doesn't support tool calling
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test OpenAI formatted tool calls."
);
}
// Bind an OpenAI-formatted tool to the model
const modelWithTools = model.bindTools([
{
type: "function",
function: {
name: "math_addition",
description: adderSchema.description,
parameters: zodToJsonSchema(adderSchema),
},
},
]);
// Invoke the model with a prompt that should trigger the tool use
const result: AIMessage = await MATH_ADDITION_PROMPT.pipe(
modelWithTools
).invoke(
{
toolName: "math_addition",
},
callOptions
);
// Verify that a tool call was made
expect(result.tool_calls?.[0]).toBeDefined();
if (!result.tool_calls?.[0]) {
throw new Error("result.tool_calls is undefined");
}
const { tool_calls } = result;
// Check that the correct tool was called
expect(tool_calls[0].name).toBe("math_addition");
}
/**
* Tests the chat model's ability to bind and use Runnable-like tools.
* This test ensures that the model can correctly process and use tools
* that are created from Runnable objects using the `asTool` method.
*
* It verifies that:
* 1. The model supports tool calling functionality.
* 2. The model can successfully bind a Runnable-like tool.
* 3. The model invokes the bound tool correctly when prompted.
* 4. The result contains a tool call with the expected name.
*
* This test is crucial for ensuring compatibility with tools created
* from Runnable objects, which provides a flexible way to integrate
* custom logic into the model's tool-calling capabilities.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testBindToolsWithRunnableToolLike(callOptions?: any) {
// Skip the test if the model doesn't support tool calling
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test Runnable-like tool calls."
);
}
// Create a Runnable-like tool using RunnableLambda and asTool
const runnableLike = RunnableLambda.from((_) => {
// no-op implementation for testing purposes
}).asTool({
name: "math_addition",
description: adderSchema.description,
schema: adderSchema,
});
// Bind the Runnable-like tool to the model
const modelWithTools = model.bindTools([runnableLike]);
// Invoke the model with a prompt that should trigger the tool use
const result: AIMessage = await MATH_ADDITION_PROMPT.pipe(
modelWithTools
).invoke(
{
toolName: "math_addition",
},
callOptions
);
// Verify that a tool call was made
expect(result.tool_calls?.[0]).toBeDefined();
if (!result.tool_calls?.[0]) {
throw new Error("result.tool_calls is undefined");
}
const { tool_calls } = result;
// Check that the correct tool was called
expect(tool_calls[0].name).toBe("math_addition");
}
/**
* Tests the chat model's ability to cache and retrieve complex message types.
* This test ensures that the model can correctly cache and retrieve messages
* with complex content structures, such as arrays of content objects.
*
* It verifies that:
* 1. The model can be instantiated with caching enabled.
* 2. A complex HumanMessage can be created and invoked.
* 3. The result is correctly cached after the first invocation.
* 4. A subsequent invocation with the same input retrieves the cached result.
* 5. The cached result matches the original result in both content and structure.
* 6. No additional cache entries are created for repeated invocations.
*
* This test is crucial for ensuring that the caching mechanism works correctly
* with various message structures, maintaining consistency and efficiency.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testCacheComplexMessageTypes(callOptions?: any) {
// Create a new instance of the chat model with caching enabled
const model = new this.Cls({
...this.constructorArgs,
cache: true,
});
if (!model.cache) {
throw new Error("Cache not enabled");
}
// Create a complex HumanMessage with an array of content objects
const humanMessage = new HumanMessage({
content: [
{
type: "text",
text: "Hello there!",
},
],
});
const prompt = getBufferString([humanMessage]);
const llmKey = model._getSerializedCacheKeyParametersForCall({} as any);
// Invoke the model to trigger a cache update
await model.invoke([humanMessage], callOptions);
const cacheValue = await model.cache.lookup(prompt, llmKey);
// Verify that the cache contains exactly one generation
expect(cacheValue !== null).toBeTruthy();
if (!cacheValue) return;
expect(cacheValue).toHaveLength(1);
// Ensure the cached value has the expected structure
expect("message" in cacheValue[0]).toBeTruthy();
if (!("message" in cacheValue[0])) return;
const cachedMessage = cacheValue[0].message as AIMessage;
// Invoke the model again with the same prompt to trigger a cache hit
const result = await model.invoke([humanMessage], callOptions);
// Verify that the result matches the cached value
expect(result.content).toBe(cacheValue[0].text);
expect(result).toEqual(cachedMessage);
// Ensure no additional cache entries were created
const cacheValue2 = await model.cache.lookup(prompt, llmKey);
expect(cacheValue2).toEqual(cacheValue);
}
/**
* Tests the chat model's ability to stream tokens while using tool calls.
* This test ensures that the model can correctly stream responses that include tool calls,
* and that the streamed response contains the expected information.
*
* It verifies that:
* 1. The model can be bound with a tool and streamed successfully.
* 2. The streamed result contains at least one tool call.
* 3. The usage metadata is present in the streamed result.
* 4. Both input and output tokens are present and greater than zero in the usage metadata.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testStreamTokensWithToolCalls(callOptions?: any) {
const model = new this.Cls(this.constructorArgs);
if (!model.bindTools) {
throw new Error("bindTools is undefined");
}
// Create and bind the AdderTool to the model
const adderTool = new AdderTool();
const modelWithTools = model.bindTools([adderTool]);
// Stream the response using the MATH_ADDITION_PROMPT
const stream = await MATH_ADDITION_PROMPT.pipe(modelWithTools).stream(
{
toolName: "math_addition",
},
callOptions
);
// Concatenate all chunks into a single result
let result: AIMessageChunk | undefined;
for await (const chunk of stream) {
if (!result) {
result = chunk;
} else {
result = result.concat(chunk);
}
}
expect(result).toBeDefined();
if (!result) return;
// Verify a tool was actually called.
// We only check for the presence of the first tool call, not the exact number,
// as some models might call the tool multiple times.
expect(result.tool_calls?.[0]).toBeDefined();
// Verify usage metadata is present and contains expected fields
expect(result.usage_metadata).toBeDefined();
expect(result.usage_metadata?.input_tokens).toBeDefined();
expect(result.usage_metadata?.input_tokens).toBeGreaterThan(0);
expect(result.usage_metadata?.output_tokens).toBeDefined();
expect(result.usage_metadata?.output_tokens).toBeGreaterThan(0);
}
/**
* Tests the chat model's ability to use tool calls in a multi-turn conversation.
* This test verifies that the model can:
* 1. Invoke a tool in response to a user query.
* 2. Use the AIMessage containing the tool call in a followup request.
* 3. Process the tool's response and generate a final answer.
*
* This capability is crucial for building agents or other pipelines that involve tool usage.
*
* The test follows these steps:
* 1. Bind a weather tool to the model.
* 2. Send an initial query about the weather.
* 3. Verify the model makes a tool call.
* 4. Simulate the tool's response.
* 5. Send a followup request including the tool call and response.
* 6. Verify the model generates a non-empty final response.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testModelCanUseToolUseAIMessage(callOptions?: any) {
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test OpenAI formatted tool calls."
);
}
// Define a simple weather schema for the tool
const weatherSchema = z.object({
location: z.string().describe("The location to get the weather for."),
});
// Create a mock weather tool that always returns sunny weather
const weatherTool = tool(
(_) => "The weather in San Francisco is 70 degrees and sunny.",
{
name: "get_current_weather",
schema: weatherSchema,
description: "Get the current weather for a location.",
}
);
// Bind the weather tool to the model
const modelWithTools = model.bindTools([weatherTool]);
// Initialize the conversation with a weather query
const messages = [
new HumanMessage(
"What's the weather like in San Francisco right now? Use the 'get_current_weather' tool to find the answer."
),
];
// Send the initial query and expect a tool call
const result: AIMessage = await modelWithTools.invoke(
messages,
callOptions
);
expect(result.tool_calls?.[0]).toBeDefined();
if (!result.tool_calls?.[0]) {
throw new Error("result.tool_calls is undefined");
}
const { tool_calls } = result;
expect(tool_calls[0].name).toBe("get_current_weather");
// Add the model's response (including tool call) to the conversation
messages.push(result);
// Simulate the tool's response
const toolMessage = new ToolMessage({
tool_call_id: tool_calls[0].id ?? "",
name: tool_calls[0].name,
content: await weatherTool.invoke(
tool_calls[0].args as z.infer<typeof weatherSchema>
),
});
messages.push(toolMessage);
// Send a followup request including the tool call and response
const finalResult = await modelWithTools.invoke(messages, callOptions);
// Verify that the model generated a non-empty response
expect(finalResult.content).not.toBe("");
}
/**
* Tests the chat model's ability to use tool calls in a multi-turn conversation with streaming.
* This test verifies that the model can:
* 1. Stream a response that includes a tool call.
* 2. Use the AIMessage containing the tool call in a followup request.
* 3. Stream a final response that processes the tool's output.
*
* This test is crucial for ensuring that the model can handle tool usage in a streaming context,
* which is important for building responsive agents or other AI systems that require real-time interaction.
*
* The test follows these steps:
* 1. Bind a weather tool to the model.
* 2. Stream an initial query about the weather.
* 3. Verify the streamed result contains a tool call.
* 4. Simulate the tool's response.
* 5. Stream a followup request including the tool call and response.
* 6. Verify the model generates a non-empty final streamed response.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testModelCanUseToolUseAIMessageWithStreaming(callOptions?: any) {
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test OpenAI formatted tool calls."
);
}
// Define a simple weather schema for the tool
const weatherSchema = z.object({
location: z.string().describe("The location to get the weather for."),
});
// Create a mock weather tool that always returns sunny weather
const weatherTool = tool(
(_) => "The weather in San Francisco is 70 degrees and sunny.",
{
name: "get_current_weather",
schema: weatherSchema,
description: "Get the current weather for a location.",
}
);
// Bind the weather tool to the model
const modelWithTools = model.bindTools([weatherTool]);
// Initialize the conversation with a weather query
const messages = [
new HumanMessage(
"What's the weather like in San Francisco right now? Use the 'get_current_weather' tool to find the answer."
),
];
// Stream the initial query and expect a tool call
const stream = await modelWithTools.stream(messages, callOptions);
let result: AIMessageChunk | undefined;
for await (const chunk of stream) {
// Concatenate chunks to build the complete response
result = !result ? chunk : concat(result, chunk);
}
expect(result).toBeDefined();
if (!result) return;
// Verify that the streamed result contains a tool call
expect(result.tool_calls?.[0]).toBeDefined();
if (!result.tool_calls?.[0]) {
throw new Error("result.tool_calls is undefined");
}
const { tool_calls } = result;
expect(tool_calls[0].name).toBe("get_current_weather");
// Add the model's response (including tool call) to the conversation
messages.push(result);
// Simulate the tool's response
const toolMessage = new ToolMessage({
tool_call_id: tool_calls[0].id ?? "",
name: tool_calls[0].name,
content: await weatherTool.invoke(
tool_calls[0].args as z.infer<typeof weatherSchema>
),
});
messages.push(toolMessage);
// Stream a followup request including the tool call and response
const finalStream = await modelWithTools.stream(messages, callOptions);
let finalResult: AIMessageChunk | undefined;
for await (const chunk of finalStream) {
// Concatenate chunks to build the complete final response
finalResult = !finalResult ? chunk : concat(finalResult, chunk);
}
expect(finalResult).toBeDefined();
if (!finalResult) return;
// Verify that the model generated a non-empty streamed response
expect(finalResult.content).not.toBe("");
}
/**
* Tests the chat model's ability to handle a more complex tool schema.
* This test verifies that the model can correctly process and use a tool
* with a schema that includes a `z.record(z.unknown())` field, which
* represents an object with unknown/any fields.
*
* The test performs the following steps:
* 1. Defines a complex schema with nested objects and unknown fields.
* 2. Creates a chat prompt template that instructs the model to use the tool.
* 3. Invokes the model with structured output using the complex schema.
* 4. Verifies that the result contains all expected fields and types.
*
* This test is particularly important for ensuring compatibility with APIs
* that may not accept JSON schemas with unknown object fields (e.g., Google's API).
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testInvokeMoreComplexTools(callOptions?: any) {
// Skip the test if the model doesn't support tool calling
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test OpenAI formatted tool calls."
);
}
// Define a complex schema with nested objects and a record of unknown fields
const complexSchema = z.object({
decision: z.enum(["UseAPI", "UseFallback"]),
explanation: z.string(),
apiDetails: z.object({
serviceName: z.string(),
endpointName: z.string(),
parameters: z.record(z.unknown()), // This field represents an object with any structure
extractionPath: z.string(),
}),
});
const toolName = "service_tool";
// Create a chat prompt template that instructs the model to use the tool
const prompt = ChatPromptTemplate.fromMessages([
["system", "You're a helpful assistant. Always use the {toolName} tool."],
[
"human",
`I want to use the UseAPI because it's faster. For the API details use the following:
Service name: {serviceName}
Endpoint name: {endpointName}
Parameters: {parameters}
Extraction path: {extractionPath}`,
],
]);
// Bind the complex schema to the model as a structured output tool
const modelWithTools = model.withStructuredOutput(complexSchema, {
name: toolName,
});
// Invoke the model with the prompt and tool
const result = await prompt.pipe(modelWithTools).invoke(
{
toolName,
serviceName: "MyService",
endpointName: "MyEndpoint",
parameters: JSON.stringify({ param1: "value1", param2: "value2" }),
extractionPath: "Users/johndoe/data",
},
callOptions
);
// Verify that all expected fields are present and of the correct type
expect(result.decision).toBeDefined();
expect(result.explanation).toBeDefined();
expect(result.apiDetails).toBeDefined();
expect(typeof result.apiDetails === "object").toBeTruthy();
}
/**
* Tests the chat model's ability to handle parallel tool calls in various scenarios.
* This comprehensive test covers three aspects of parallel tool calling:
* 1. Invoking multiple tools simultaneously
* 2. Streaming responses with parallel tool calls
* 3. Processing message histories containing parallel tool calls
*
* The test uses a weather tool and a current time tool to simulate complex, multi-tool scenarios.
* It ensures that the model can correctly process and respond to prompts requiring multiple tool calls,
* both in streaming and non-streaming contexts, and can handle message histories with parallel tool calls.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* @param {boolean} onlyVerifyHistory If true, only verifies the message history test.
*/
async testParallelToolCalling(callOptions?: any, onlyVerifyHistory = false) {
// Skip the test if the model doesn't support tool calling
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
// Skip the test if the model doesn't support parallel tool calls
if (!this.supportsParallelToolCalls) {
console.log("Test requires parallel tool calls. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test OpenAI formatted tool calls."
);
}
const weatherTool = tool((_) => "no-op", {
name: "get_current_weather",
description: "Get the current weather in a given location",
schema: z.object({
location: z.string().describe("The city name, e.g. San Francisco"),
}),
});
const currentTimeTool = tool((_) => "no-op", {
name: "get_current_time",
description: "Get the current time in a given location",
schema: z.object({
location: z.string().describe("The city name, e.g. San Francisco"),
}),
});
const modelWithTools = model.bindTools([weatherTool, currentTimeTool]);
const callParallelToolsPrompt =
"What's the weather and current time in San Francisco?\n" +
"Ensure you ALWAYS call the 'get_current_weather' tool for weather and 'get_current_time' tool for time.";
// Save the result of the parallel tool calls for the history test.
let parallelToolCallsMessage: AIMessage | undefined;
/**
* Tests the basic functionality of invoking multiple tools in parallel.
* Verifies that the model can call both the weather and current time tools simultaneously.
*/
const invokeParallelTools = async () => {
const result: AIMessage = await modelWithTools.invoke(
callParallelToolsPrompt,
callOptions
);
// Model should call at least two tools. Using greater than or equal since it might call the current time tool multiple times.
expect(result.tool_calls?.length).toBeGreaterThanOrEqual(2);
if (!result.tool_calls?.length) return;
const weatherToolCalls = result.tool_calls.find(
(tc) => tc.name === weatherTool.name
);
const currentTimeToolCalls = result.tool_calls.find(
(tc) => tc.name === currentTimeTool.name
);
expect(weatherToolCalls).toBeDefined();
expect(currentTimeToolCalls).toBeDefined();
parallelToolCallsMessage = result;
};
/**
* Tests the model's ability to stream responses while making parallel tool calls.
* Ensures that the streamed result contains calls to both the weather and current time tools.
*/
const streamParallelTools = async () => {
const stream = await modelWithTools.stream(
callParallelToolsPrompt,
callOptions
);
let finalChunk: AIMessageChunk | undefined;
for await (const chunk of stream) {
finalChunk = !finalChunk ? chunk : concat(finalChunk, chunk);
}
expect(finalChunk).toBeDefined();
if (!finalChunk) return;
// Model should call at least two tools. Do not penalize for calling more than two tools, as
// long as it calls both the weather and current time tools.
expect(finalChunk.tool_calls?.length).toBeGreaterThanOrEqual(2);
if (!finalChunk.tool_calls?.length) return;
const weatherToolCalls = finalChunk.tool_calls.find(
(tc) => tc.name === weatherTool.name
);
const currentTimeToolCalls = finalChunk.tool_calls.find(
(tc) => tc.name === currentTimeTool.name
);
expect(weatherToolCalls).toBeDefined();
expect(currentTimeToolCalls).toBeDefined();
};
/**
* Tests the model's ability to process a message history containing parallel tool calls.
* Verifies that the model can generate a response based on previous tool calls without making unnecessary additional tool calls.
*/
const invokeParallelToolCallResultsInHistory = async () => {
const defaultAIMessageWithParallelTools = new AIMessage({
content: "",
tool_calls: [
{
name: weatherTool.name,
id: "get_current_weather_id",
args: { location: "San Francisco" },
},
{
name: currentTimeTool.name,
id: "get_current_time_id",
args: { location: "San Francisco" },
},
],
});
if (!parallelToolCallsMessage) {
// Allow this variable to be assigned in the first test, or if only run histories
// is passed, assign it here since the first test will not run.
parallelToolCallsMessage = defaultAIMessageWithParallelTools;
}
// Find the tool calls for the weather and current time tools so we can re-use the IDs in the message history.
const parallelToolCallWeather = parallelToolCallsMessage.tool_calls?.find(
(tc) => tc.name === weatherTool.name
);
const parallelToolCallCurrentTime =
parallelToolCallsMessage.tool_calls?.find(
(tc) => tc.name === currentTimeTool.name
);
if (!parallelToolCallWeather?.id || !parallelToolCallCurrentTime?.id) {
throw new Error(
`IDs not found in one of both of parallel tool calls:\nWeather ID: ${parallelToolCallWeather?.id}\nCurrent Time ID: ${parallelToolCallCurrentTime?.id}`
);
}
const messageHistory = [
new HumanMessage(callParallelToolsPrompt),
// The saved message from earlier when we called the model to generate the parallel tool calls.
parallelToolCallsMessage,
new ToolMessage({
name: weatherTool.name,
tool_call_id: parallelToolCallWeather.id,
content: "It is currently 24 degrees with hail in San Francisco.",
}),
new ToolMessage({
name: currentTimeTool.name,
tool_call_id: parallelToolCallCurrentTime.id,
content: "The current time in San Francisco is 12:02 PM.",
}),
];
const result: AIMessage = await modelWithTools.invoke(
messageHistory,
callOptions
);
// The model should NOT call a tool given this message history.
expect(result.tool_calls ?? []).toHaveLength(0);
if (typeof result.content === "string") {
expect(result.content).not.toBe("");
} else {
expect(result.content.length).toBeGreaterThan(0);
const textOrTextDeltaContent = result.content.find(
(c) => c.type === "text" || c.type === "text_delta"
);
expect(textOrTextDeltaContent).toBeDefined();
}
};
// Now we can invoke each of our tests synchronously, as the last test requires the result of the first test.
if (!onlyVerifyHistory) {
await invokeParallelTools();
await streamParallelTools();
}
await invokeParallelToolCallResultsInHistory();
}
/**
* Tests the chat model's ability to accept and use a StructuredToolParams schema.
* This schema contains the same fields as `StructuredToolInterface`, but does not
* require a function to be passed when the tool is created.
*
* This test verifies that the model can:
* 1. Correctly bind a tool defined using StructuredToolParams
* 2. Process a prompt that should trigger the use of the bound tool
* 3. Generate a response that includes appropriate tool calls
*
* The test uses a simple weather tool to simulate a scenario where the model
* needs to make a tool call to retrieve weather information.
*
* It ensures that the model can correctly interpret the tool's schema,
* make the appropriate tool call, and include the required arguments.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testModelCanAcceptStructuredToolParamsSchema(callOptions?: any) {
// Skip the test if the model doesn't support tool calling
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test OpenAI formatted tool calls."
);
}
const tool: StructuredToolParams = {
name: "get_current_weather",
description: "Get the current weather in a given location",
schema: z.object({
location: z.string().describe("The city name, e.g. San Francisco"),
}),
};
const modelWithTools = model.bindTools([tool]);
const prompt = "What's the weather like in San Francisco today?";
const result: AIMessage = await modelWithTools.invoke(prompt, callOptions);
// Expect at least one tool call, allow multiple.
expect(result.tool_calls?.length).toBeGreaterThanOrEqual(1);
expect(result.tool_calls?.[0].name).toBe(tool.name);
expect(result.tool_calls?.[0].args).toHaveProperty("location");
}
/**
* Tests the chat model's ability to stream responses while using tools.
* This test verifies that the model can:
* 1. Correctly bind a tool defined using StructuredToolParams
* 2. Stream a response for a prompt that should trigger the use of the bound tool
* 3. Generate a streamed response that includes appropriate tool calls
*
* The test uses a simple weather tool to simulate a scenario where the model
* needs to make a tool call to retrieve weather information in a streaming context.
*
* It ensures that the model can correctly interpret the tool's schema,
* make the appropriate tool call, and include the required arguments
* while streaming the response.
*
* @param {any | undefined} callOptions Optional call options to pass to the model.
* These options will be applied to the model at runtime.
*/
async testStreamTools(callOptions?: any) {
// Skip the test if the model doesn't support tool calling
if (!this.chatModelHasToolCalling) {
console.log("Test requires tool calling. Skipping...");
return;
}
const model = new this.Cls(this.constructorArgs);
if (!model.bindTools) {
throw new Error(
"bindTools undefined. Cannot test OpenAI formatted tool calls."
);
}
const tool: StructuredToolParams = {
name: "get_current_weather",
description: "Get the current weather in a given location",
schema: z.object({
location: z.string().describe("The city name, e.g. San Francisco"),
}),
};
const modelWithTools = model.bindTools([tool]);
const prompt = "What's the weather like in San Francisco today?";
const stream = await modelWithTools.stream(prompt, callOptions);
let full: AIMessageChunk | undefined;
for await (const chunk of stream) {
full = !full ? chunk : concat(full, chunk);
}
expect(full).toBeDefined();
if (!full) return;
// Expect at least one tool call, allow multiple.
expect(full.tool_calls?.length).toBeGreaterThanOrEqual(1);
expect(full.tool_calls?.[0].name).toBe(tool.name);
expect(full.tool_calls?.[0].args).toHaveProperty("location");
}
/**
* Run all unit tests for the chat model.
* Each test is wrapped in a try/catch block to prevent the entire test suite from failing.
* If a test fails, the error is logged to the console, and the test suite continues.
* @returns {boolean}
*/
async runTests(): Promise<boolean> {
let allTestsPassed = true;
try {
await this.testInvoke();
} catch (e: any) {
allTestsPassed = false;
console.error("testInvoke failed", e.message);
}
try {
await this.testStream();
} catch (e: any) {
allTestsPassed = false;
console.error("testStream failed", e.message);
}
try {
await this.testBatch();
} catch (e: any) {
allTestsPassed = false;
console.error("testBatch failed", e.message);
}
try {
await this.testConversation();
} catch (e: any) {
allTestsPassed = false;
console.error("testConversation failed", e.message);
}
try {
await this.testUsageMetadata();
} catch (e: any) {
allTestsPassed = false;
console.error("testUsageMetadata failed", e.message);
}
try {
await this.testUsageMetadataStreaming();
} catch (e: any) {
allTestsPassed = false;
console.error("testUsageMetadataStreaming failed", e.message);
}
try {
await this.testToolMessageHistoriesStringContent();
} catch (e: any) {
allTestsPassed = false;
console.error("testToolMessageHistoriesStringContent failed", e.message);
}
try {
await this.testToolMessageHistoriesListContent();
} catch (e: any) {
allTestsPassed = false;
console.error("testToolMessageHistoriesListContent failed", e.message);
}
try {
await this.testStructuredFewShotExamples();
} catch (e: any) {
allTestsPassed = false;
console.error("testStructuredFewShotExamples failed", e.message);
}
try {
await this.testWithStructuredOutput();
} catch (e: any) {
allTestsPassed = false;
console.error("testWithStructuredOutput failed", e.message);
}
try {
await this.testWithStructuredOutputIncludeRaw();
} catch (e: any) {
allTestsPassed = false;
console.error("testWithStructuredOutputIncludeRaw failed", e.message);
}
try {
await this.testBindToolsWithOpenAIFormattedTools();
} catch (e: any) {
allTestsPassed = false;
console.error("testBindToolsWithOpenAIFormattedTools failed", e.message);
}
try {
await this.testBindToolsWithRunnableToolLike();
} catch (e: any) {
allTestsPassed = false;
console.error("testBindToolsWithRunnableToolLike failed", e.message);
}
try {
await this.testCacheComplexMessageTypes();
} catch (e: any) {
allTestsPassed = false;
console.error("testCacheComplexMessageTypes failed", e.message);
}
try {
await this.testStreamTokensWithToolCalls();
} catch (e: any) {
allTestsPassed = false;
console.error("testStreamTokensWithToolCalls failed", e.message);
}
try {
await this.testModelCanUseToolUseAIMessage();
} catch (e: any) {
allTestsPassed = false;
console.error("testModelCanUseToolUseAIMessage failed", e.message);
}
try {
await this.testModelCanUseToolUseAIMessageWithStreaming();
} catch (e: any) {
allTestsPassed = false;
console.error(
"testModelCanUseToolUseAIMessageWithStreaming failed",
e.message
);
}
try {
await this.testInvokeMoreComplexTools();
} catch (e: any) {
allTestsPassed = false;
console.error("testInvokeMoreComplexTools failed", e.message);
}
try {
await this.testParallelToolCalling();
} catch (e: any) {
allTestsPassed = false;
console.error("testParallelToolCalling failed", e.message);
}
try {
await this.testModelCanAcceptStructuredToolParamsSchema();
} catch (e: any) {
allTestsPassed = false;
console.error(
"testModelCanAcceptStructuredToolParamsSchema failed",
e.message
);
}
try {
await this.testStreamTools();
} catch (e: any) {
allTestsPassed = false;
console.error("testStreamTools failed", e.message);
}
return allTestsPassed;
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-standard-tests/src | lc_public_repos/langchainjs/libs/langchain-standard-tests/src/unit_tests/chat_models.ts | import { expect } from "@jest/globals";
import {
BaseChatModelCallOptions,
LangSmithParams,
} from "@langchain/core/language_models/chat_models";
import { BaseMessageChunk } from "@langchain/core/messages";
import { z } from "zod";
import { StructuredTool } from "@langchain/core/tools";
import {
BaseChatModelsTests,
BaseChatModelsTestsFields,
RecordStringAny,
} from "../base.js";
const person = /* #__PURE__ */ z
.object({
name: z.string().describe("Name of the person"),
age: z.number().int().positive().describe("Age of the person"),
})
.describe("A person");
class PersonTool extends StructuredTool {
name = "PersonTool";
description = person.description ?? "description";
schema = person;
async _call(input: z.infer<typeof person>) {
return JSON.stringify(input);
}
}
export abstract class ChatModelUnitTests<
CallOptions extends BaseChatModelCallOptions = BaseChatModelCallOptions,
OutputMessageType extends BaseMessageChunk = BaseMessageChunk,
ConstructorArgs extends RecordStringAny = RecordStringAny
> extends BaseChatModelsTests<CallOptions, OutputMessageType, ConstructorArgs> {
constructor(
fields: BaseChatModelsTestsFields<
CallOptions,
OutputMessageType,
ConstructorArgs
>
) {
const standardChatModelParams: RecordStringAny = {
temperature: 0,
maxTokens: 100,
timeout: 60,
stopSequences: [],
maxRetries: 2,
};
super({
...fields,
constructorArgs: {
...standardChatModelParams,
...fields.constructorArgs,
},
});
}
/**
* Override this method if the chat model being tested does not
* support all expected LangSmith parameters.
* @returns {Partial<LangSmithParams>} The LangSmith parameters expected by the chat model.
*/
expectedLsParams(): Partial<LangSmithParams> {
return {
ls_provider: "string",
ls_model_name: "string",
ls_model_type: "chat",
ls_temperature: 0,
ls_max_tokens: 0,
ls_stop: ["Array<string>"],
};
}
testChatModelInit() {
const chatModel = new this.Cls(this.constructorArgs);
expect(chatModel).toBeDefined();
}
testChatModelInitApiKey() {
const params = { ...this.constructorArgs, apiKey: "test" };
const chatModel = new this.Cls(params);
expect(chatModel).toBeDefined();
}
testChatModelInitStreaming() {
const params = { ...this.constructorArgs, streaming: true };
const chatModel = new this.Cls(params);
expect(chatModel).toBeDefined();
}
testChatModelWithBindTools() {
if (!this.chatModelHasToolCalling) {
return;
}
const chatModel = new this.Cls(this.constructorArgs);
expect(chatModel.bindTools?.([new PersonTool()])).toBeDefined();
}
testChatModelWithStructuredOutput() {
if (!this.chatModelHasStructuredOutput) {
return;
}
const chatModel = new this.Cls(this.constructorArgs);
expect((chatModel as any).withStructuredOutput?.(person)).toBeDefined();
}
testStandardParams() {
const expectedParams = this.expectedLsParams();
const chatModel = new this.Cls(this.constructorArgs);
const lsParams = chatModel.getLsParams({} as any);
expect(lsParams).toBeDefined();
expect(Object.keys(lsParams).sort()).toEqual(
Object.keys(expectedParams).sort()
);
}
/**
* Run all unit tests for the chat model.
* Each test is wrapped in a try/catch block to prevent the entire test suite from failing.
* If a test fails, the error is logged to the console, and the test suite continues.
* @returns {boolean}
*/
runTests(): boolean {
let allTestsPassed = true;
try {
this.testChatModelInit();
} catch (e: any) {
allTestsPassed = false;
console.error("testChatModelInit failed", e);
}
try {
this.testChatModelInitApiKey();
} catch (e: any) {
allTestsPassed = false;
console.error("testChatModelInitApiKey failed", e);
}
try {
this.testChatModelInitStreaming();
} catch (e: any) {
allTestsPassed = false;
console.error("testChatModelInitStreaming failed", e);
}
try {
this.testChatModelWithBindTools();
} catch (e: any) {
allTestsPassed = false;
console.error("testChatModelWithBindTools failed", e);
}
try {
this.testChatModelWithStructuredOutput();
} catch (e: any) {
allTestsPassed = false;
console.error("testChatModelWithStructuredOutput failed", e);
}
try {
this.testStandardParams();
} catch (e: any) {
allTestsPassed = false;
console.error("testStandardParams failed", e);
}
return allTestsPassed;
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-standard-tests | lc_public_repos/langchainjs/libs/langchain-standard-tests/scripts/jest-setup-after-env.js | import { awaitAllCallbacks } from "@langchain/core/callbacks/promises";
import { afterAll, jest } from "@jest/globals";
afterAll(awaitAllCallbacks);
// Allow console.log to be disabled in tests
if (process.env.DISABLE_CONSOLE_LOGS === "true") {
console.log = jest.fn();
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/tsconfig.json | {
"extends": "@tsconfig/recommended",
"compilerOptions": {
"outDir": "../dist",
"rootDir": "./src",
"target": "ES2021",
"lib": ["ES2021", "ES2022.Object", "DOM"],
"module": "ES2020",
"moduleResolution": "nodenext",
"esModuleInterop": true,
"declaration": true,
"noImplicitReturns": true,
"noFallthroughCasesInSwitch": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"useDefineForClassFields": true,
"strictPropertyInitialization": false,
"allowJs": true,
"strict": true
},
"include": ["src/**/*"],
"exclude": ["node_modules", "dist", "docs"]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/LICENSE | The MIT License
Copyright (c) 2023 LangChain
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE. |
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/jest.config.cjs | /** @type {import('ts-jest').JestConfigWithTsJest} */
module.exports = {
preset: "ts-jest/presets/default-esm",
testEnvironment: "./jest.env.cjs",
modulePathIgnorePatterns: ["dist/", "docs/"],
moduleNameMapper: {
"^(\\.{1,2}/.*)\\.js$": "$1",
},
transform: {
"^.+\\.tsx?$": ["@swc/jest"],
},
transformIgnorePatterns: [
"/node_modules/",
"\\.pnp\\.[^\\/]+$",
"./scripts/jest-setup-after-env.js",
],
setupFiles: ["dotenv/config"],
testTimeout: 20_000,
passWithNoTests: true,
collectCoverageFrom: ["src/**/*.ts"],
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/jest.env.cjs | const { TestEnvironment } = require("jest-environment-node");
class AdjustedTestEnvironmentToSupportFloat32Array extends TestEnvironment {
constructor(config, context) {
// Make `instanceof Float32Array` return true in tests
// to avoid https://github.com/xenova/transformers.js/issues/57 and https://github.com/jestjs/jest/issues/2549
super(config, context);
this.global.Float32Array = Float32Array;
}
}
module.exports = AdjustedTestEnvironmentToSupportFloat32Array;
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/README.md | # @langchain/cohere
This package contains the LangChain.js integrations for Cohere through their SDK.
## Installation
```bash npm2yarn
npm install @langchain/cohere @langchain/core
```
This package, along with the main LangChain package, depends on [`@langchain/core`](https://npmjs.com/package/@langchain/core/).
If you are using this package with other LangChain packages, you should make sure that all of the packages depend on the same instance of @langchain/core.
You can do so by adding appropriate field to your project's `package.json` like this:
```json
{
"name": "your-project",
"version": "0.0.0",
"dependencies": {
"@langchain/cohere": "^0.0.1",
"@langchain/core": "^0.3.0",
},
"resolutions": {
"@langchain/core": "0.3.0"
},
"overrides": {
"@langchain/core": "0.3.0"
},
"pnpm": {
"overrides": {
"@langchain/core": "0.3.0"
}
}
}
```
The field you need depends on the package manager you're using, but we recommend adding a field for the common `yarn`, `npm`, and `pnpm` to maximize compatibility.
## Chat Models
This package contains the `ChatCohere` class, which is the recommended way to interface with the Cohere series of models.
To use, install the requirements, and configure your environment.
```bash
export COHERE_API_KEY=your-api-key
```
Then initialize
```typescript
import { HumanMessage } from "@langchain/core/messages";
import { ChatCohere } from "@langchain/cohere";
const model = new ChatCohere({
apiKey: process.env.COHERE_API_KEY,
});
const response = await model.invoke([new HumanMessage("Hello world!")]);
```
### Streaming
```typescript
import { HumanMessage } from "@langchain/core/messages";
import { ChatCohere } from "@langchain/cohere";
const model = new ChatCohere({
apiKey: process.env.COHERE_API_KEY,
});
const response = await model.stream([new HumanMessage("Hello world!")]);
```
## Embeddings
This package also adds support for `CohereEmbeddings` embeddings model.
```typescript
import { ChatCohere } from "@langchain/cohere";
const embeddings = new ChatCohere({
apiKey: process.env.COHERE_API_KEY,
});
const res = await embeddings.embedQuery("Hello world");
```
## Development
To develop the `@langchain/cohere` package, you'll need to follow these instructions:
### Install dependencies
```bash
yarn install
```
### Build the package
```bash
yarn build
```
Or from the repo root:
```bash
yarn build --filter=@langchain/cohere
```
### Run tests
Test files should live within a `tests/` file in the `src/` folder. Unit tests should end in `.test.ts` and integration tests should
end in `.int.test.ts`:
```bash
$ yarn test
$ yarn test:int
```
### Lint & Format
Run the linter & formatter to ensure your code is up to standard:
```bash
yarn lint && yarn format
```
### Adding new entrypoints
If you add a new file to be exported, either import & re-export from `src/index.ts`, or add it to the `entrypoints` field in the `config` variable located inside `langchain.config.js` and run `yarn build` to generate the new entrypoint.
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/.release-it.json | {
"github": {
"release": true,
"autoGenerate": true,
"tokenRef": "GITHUB_TOKEN_RELEASE"
},
"npm": {
"versionArgs": [
"--workspaces-update=false"
]
}
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/.eslintrc.cjs | module.exports = {
extends: [
"airbnb-base",
"eslint:recommended",
"prettier",
"plugin:@typescript-eslint/recommended",
],
parserOptions: {
ecmaVersion: 12,
parser: "@typescript-eslint/parser",
project: "./tsconfig.json",
sourceType: "module",
},
plugins: ["@typescript-eslint", "no-instanceof", "eslint-plugin-jest"],
ignorePatterns: [
".eslintrc.cjs",
"scripts",
"node_modules",
"dist",
"dist-cjs",
"*.js",
"*.cjs",
"*.d.ts",
],
rules: {
"no-process-env": 2,
"no-instanceof/no-instanceof": 2,
"@typescript-eslint/explicit-module-boundary-types": 0,
"@typescript-eslint/no-empty-function": 0,
"@typescript-eslint/no-shadow": 0,
"@typescript-eslint/no-empty-interface": 0,
"@typescript-eslint/no-use-before-define": ["error", "nofunc"],
"@typescript-eslint/no-unused-vars": ["warn", { args: "none" }],
"@typescript-eslint/no-floating-promises": "error",
"@typescript-eslint/no-misused-promises": "error",
"arrow-body-style": 0,
camelcase: 0,
"class-methods-use-this": 0,
"import/extensions": [2, "ignorePackages"],
"import/no-extraneous-dependencies": [
"error",
{ devDependencies: ["**/*.test.ts"] },
],
"import/no-unresolved": 0,
"import/prefer-default-export": 0,
"keyword-spacing": "error",
"max-classes-per-file": 0,
"max-len": 0,
"no-await-in-loop": 0,
"no-bitwise": 0,
"no-console": 0,
"no-restricted-syntax": 0,
"no-shadow": 0,
"no-continue": 0,
"no-void": 0,
"no-underscore-dangle": 0,
"no-use-before-define": 0,
"no-useless-constructor": 0,
"no-return-await": 0,
"consistent-return": 0,
"no-else-return": 0,
"func-names": 0,
"no-lonely-if": 0,
"prefer-rest-params": 0,
'jest/no-focused-tests': 'error',
"new-cap": ["error", { properties: false, capIsNew: false }],
},
overrides: [
{
files: ['**/*.test.ts'],
rules: {
'@typescript-eslint/no-unused-vars': 'off'
}
}
]
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/langchain.config.js | import { resolve, dirname } from "node:path";
import { fileURLToPath } from "node:url";
/**
* @param {string} relativePath
* @returns {string}
*/
function abs(relativePath) {
return resolve(dirname(fileURLToPath(import.meta.url)), relativePath);
}
export const config = {
internals: [/node\:/, /@langchain\/core\//],
entrypoints: {
index: "index",
},
tsConfigPath: resolve("./tsconfig.json"),
cjsSource: "./dist-cjs",
cjsDestination: "./dist",
abs,
} |
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/package.json | {
"name": "@langchain/cohere",
"version": "0.3.1",
"description": "Cohere integration for LangChain.js",
"type": "module",
"engines": {
"node": ">=18"
},
"main": "./index.js",
"types": "./index.d.ts",
"repository": {
"type": "git",
"url": "git@github.com:langchain-ai/langchainjs.git"
},
"homepage": "https://github.com/langchain-ai/langchainjs/tree/main/libs/langchain-cohere/",
"scripts": {
"build": "yarn turbo:command build:internal --filter=@langchain/cohere",
"build:internal": "yarn lc_build --create-entrypoints --pre --tree-shaking",
"lint:eslint": "NODE_OPTIONS=--max-old-space-size=4096 eslint --cache --ext .ts,.js src/",
"lint:dpdm": "dpdm --exit-code circular:1 --no-warning --no-tree src/*.ts src/**/*.ts",
"lint": "yarn lint:eslint && yarn lint:dpdm",
"lint:fix": "yarn lint:eslint --fix && yarn lint:dpdm",
"clean": "rm -rf .turbo dist/",
"prepack": "yarn build",
"test": "NODE_OPTIONS=--experimental-vm-modules jest --testPathIgnorePatterns=\\.int\\.test.ts --testTimeout 30000 --maxWorkers=50%",
"test:watch": "NODE_OPTIONS=--experimental-vm-modules jest --watch --testPathIgnorePatterns=\\.int\\.test.ts",
"test:single": "NODE_OPTIONS=--experimental-vm-modules yarn run jest --config jest.config.cjs --testTimeout 100000",
"test:int": "NODE_OPTIONS=--experimental-vm-modules jest --testPathPattern=\\.int\\.test.ts --testTimeout 100000 --maxWorkers=50%",
"test:standard:unit": "NODE_OPTIONS=--experimental-vm-modules jest --testPathPattern=\\.standard\\.test.ts --testTimeout 100000 --maxWorkers=50%",
"test:standard:int": "NODE_OPTIONS=--experimental-vm-modules jest --testPathPattern=\\.standard\\.int\\.test.ts --testTimeout 100000 --maxWorkers=50%",
"test:standard": "yarn test:standard:unit && yarn test:standard:int",
"format": "prettier --config .prettierrc --write \"src\"",
"format:check": "prettier --config .prettierrc --check \"src\""
},
"author": "LangChain",
"license": "MIT",
"dependencies": {
"cohere-ai": "^7.14.0",
"uuid": "^10.0.0",
"zod": "^3.23.8",
"zod-to-json-schema": "^3.23.1"
},
"peerDependencies": {
"@langchain/core": ">=0.2.21 <0.4.0"
},
"devDependencies": {
"@jest/globals": "^29.5.0",
"@langchain/core": "workspace:*",
"@langchain/scripts": ">=0.1.0 <0.2.0",
"@langchain/standard-tests": "0.0.0",
"@swc/core": "^1.3.90",
"@swc/jest": "^0.2.29",
"@tsconfig/recommended": "^1.0.3",
"@typescript-eslint/eslint-plugin": "^6.12.0",
"@typescript-eslint/parser": "^6.12.0",
"dotenv": "^16.3.1",
"dpdm": "^3.12.0",
"eslint": "^8.33.0",
"eslint-config-airbnb-base": "^15.0.0",
"eslint-config-prettier": "^8.6.0",
"eslint-plugin-import": "^2.27.5",
"eslint-plugin-jest": "^27.6.0",
"eslint-plugin-no-instanceof": "^1.0.1",
"eslint-plugin-prettier": "^4.2.1",
"jest": "^29.5.0",
"jest-environment-node": "^29.6.4",
"prettier": "^2.8.3",
"release-it": "^17.6.0",
"rollup": "^4.5.2",
"ts-jest": "^29.1.0",
"typescript": "<5.2.0"
},
"publishConfig": {
"access": "public"
},
"exports": {
".": {
"types": {
"import": "./index.d.ts",
"require": "./index.d.cts",
"default": "./index.d.ts"
},
"import": "./index.js",
"require": "./index.cjs"
},
"./package.json": "./package.json"
},
"files": [
"dist/",
"index.cjs",
"index.js",
"index.d.ts",
"index.d.cts"
]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/tsconfig.cjs.json | {
"extends": "./tsconfig.json",
"compilerOptions": {
"module": "commonjs",
"declaration": false
},
"exclude": ["node_modules", "dist", "docs", "**/tests"]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/turbo.json | {
"extends": ["//"],
"pipeline": {
"build": {
"outputs": ["**/dist/**"]
},
"build:internal": {
"dependsOn": ["^build:internal"]
}
}
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-cohere/.prettierrc | {
"$schema": "https://json.schemastore.org/prettierrc",
"printWidth": 80,
"tabWidth": 2,
"useTabs": false,
"semi": true,
"singleQuote": false,
"quoteProps": "as-needed",
"jsxSingleQuote": false,
"trailingComma": "es5",
"bracketSpacing": true,
"arrowParens": "always",
"requirePragma": false,
"insertPragma": false,
"proseWrap": "preserve",
"htmlWhitespaceSensitivity": "css",
"vueIndentScriptAndStyle": false,
"endOfLine": "lf"
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere | lc_public_repos/langchainjs/libs/langchain-cohere/src/rerank.ts | import { DocumentInterface } from "@langchain/core/documents";
import { BaseDocumentCompressor } from "@langchain/core/retrievers/document_compressors";
import { CohereClient } from "cohere-ai";
import { CohereClientOptions, getCohereClient } from "./client.js";
export interface BaseCohereRerankArgs {
/**
* The name of the model to use.
* @default {"rerank-english-v2.0"}
*/
model?: string;
/**
* How many documents to return.
* @default {3}
*/
topN?: number;
/**
* The maximum number of chunks per document.
*/
maxChunksPerDoc?: number;
}
type CohereRerankArgs = BaseCohereRerankArgs & CohereClientOptions;
/**
* Document compressor that uses `Cohere Rerank API`.
*/
export class CohereRerank extends BaseDocumentCompressor {
model: string | undefined;
topN = 3;
client: CohereClient;
maxChunksPerDoc: number | undefined;
constructor(fields?: CohereRerankArgs) {
super();
this.client = getCohereClient(fields);
this.model = fields?.model ?? this.model;
if (!this.model) {
throw new Error(
"Model not specified for CohereRerank instance. Please provide a model name from the options here: https://docs.cohere.com/reference/rerank"
);
}
this.topN = fields?.topN ?? this.topN;
this.maxChunksPerDoc = fields?.maxChunksPerDoc;
}
/**
* Compress documents using Cohere's rerank API.
*
* @param {Array<DocumentInterface>} documents A sequence of documents to compress.
* @param {string} query The query to use for compressing the documents.
*
* @returns {Promise<Array<DocumentInterface>>} A sequence of compressed documents.
*/
async compressDocuments(
documents: Array<DocumentInterface>,
query: string
): Promise<Array<DocumentInterface>> {
const _docs = documents.map((doc) => doc.pageContent);
const { results } = await this.client.rerank({
model: this.model,
query,
documents: _docs,
topN: this.topN,
maxChunksPerDoc: this.maxChunksPerDoc,
});
const finalResults: Array<DocumentInterface> = [];
for (let i = 0; i < results.length; i += 1) {
const result = results[i];
const doc = documents[result.index];
doc.metadata.relevanceScore = result.relevanceScore;
finalResults.push(doc);
}
return finalResults;
}
/**
* Returns an ordered list of documents ordered by their relevance to the provided query.
*
* @param {Array<DocumentInterface | string | Record<string, string>>} documents A list of documents as strings, DocumentInterfaces or objects with a `pageContent` key.
* @param {string} query The query to use for reranking the documents.
* @param options
* @param {string} options.model The name of the model to use.
* @param {number} options.topN How many documents to return.
* @param {number} options.maxChunksPerDoc The maximum number of chunks per document.
*
* @returns {Promise<Array<{ index: number; relevanceScore: number }>>} An ordered list of documents with relevance scores.
*/
async rerank(
documents: Array<DocumentInterface | string | Record<string, string>>,
query: string,
options?: {
model?: string;
topN?: number;
maxChunksPerDoc?: number;
}
): Promise<Array<{ index: number; relevanceScore: number }>> {
const docs = documents.map((doc) => {
if (typeof doc === "string") {
return doc;
}
return doc.pageContent;
});
const model = options?.model ?? this.model;
const topN = options?.topN ?? this.topN;
const maxChunksPerDoc = options?.maxChunksPerDoc ?? this.maxChunksPerDoc;
const { results } = await this.client.rerank({
model,
query,
documents: docs,
topN,
maxChunksPerDoc,
});
const resultObjects = results.map((result) => ({
index: result.index,
relevanceScore: result.relevanceScore,
}));
return resultObjects;
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere | lc_public_repos/langchainjs/libs/langchain-cohere/src/llms.ts | import { CohereClient, Cohere as CohereTypes } from "cohere-ai";
import { LLM, type BaseLLMParams } from "@langchain/core/language_models/llms";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import type { BaseLanguageModelCallOptions } from "@langchain/core/language_models/base";
import { CohereClientOptions, getCohereClient } from "./client.js";
/**
* Interface for the input parameters specific to the Cohere model.
*/
export interface BaseCohereInput extends BaseLLMParams {
/** Sampling temperature to use */
temperature?: number;
/**
* Maximum number of tokens to generate in the completion.
*/
maxTokens?: number;
/** Model to use */
model?: string;
}
export type CohereInput = BaseCohereInput & CohereClientOptions;
interface CohereCallOptions
extends BaseLanguageModelCallOptions,
Partial<Omit<CohereTypes.GenerateRequest, "message">> {}
/**
* Class representing a Cohere Large Language Model (LLM). It interacts
* with the Cohere API to generate text completions.
* @example
* ```typescript
* const model = new Cohere({
* temperature: 0.7,
* maxTokens: 20,
* maxRetries: 5,
* });
*
* const res = await model.invoke(
* "Question: What would be a good company name for a company that makes colorful socks?\nAnswer:"
* );
* console.log({ res });
* ```
*/
export class Cohere extends LLM<CohereCallOptions> implements CohereInput {
static lc_name() {
return "Cohere";
}
get lc_secrets(): { [key: string]: string } | undefined {
return {
apiKey: "COHERE_API_KEY",
api_key: "COHERE_API_KEY",
};
}
get lc_aliases(): { [key: string]: string } | undefined {
return {
apiKey: "cohere_api_key",
api_key: "cohere_api_key",
};
}
lc_serializable = true;
temperature = 0;
maxTokens = 250;
model: string;
apiKey: string;
client: CohereClient;
constructor(fields?: CohereInput) {
super(fields ?? {});
this.client = getCohereClient(fields);
this.maxTokens = fields?.maxTokens ?? this.maxTokens;
this.temperature = fields?.temperature ?? this.temperature;
this.model = fields?.model ?? this.model;
}
_llmType() {
return "cohere";
}
invocationParams(options: this["ParsedCallOptions"]) {
const params = {
model: this.model,
numGenerations: options.numGenerations,
maxTokens: options.maxTokens ?? this.maxTokens,
truncate: options.truncate,
temperature: options.temperature ?? this.temperature,
preset: options.preset,
endSequences: options.endSequences,
stopSequences: options.stop ?? options.stopSequences,
k: options.k,
p: options.p,
frequencyPenalty: options.frequencyPenalty,
presencePenalty: options.presencePenalty,
returnLikelihoods: options.returnLikelihoods,
};
// Filter undefined entries
return Object.fromEntries(
Object.entries(params).filter(([, value]) => value !== undefined)
);
}
/** @ignore */
async _call(
prompt: string,
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): Promise<string> {
const generateResponse = await this.caller.callWithOptions(
{ signal: options.signal },
async () => {
let response;
try {
response = await this.client.generate({
prompt,
...this.invocationParams(options),
});
// eslint-disable-next-line @typescript-eslint/no-explicit-any
} catch (e: any) {
e.status = e.status ?? e.statusCode;
throw e;
}
return response;
}
);
try {
await runManager?.handleLLMNewToken(generateResponse.generations[0].text);
return generateResponse.generations[0].text;
} catch {
console.log(generateResponse);
throw new Error("Could not parse response.");
}
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere | lc_public_repos/langchainjs/libs/langchain-cohere/src/client.ts | import { CohereClient } from "cohere-ai";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
export type CohereClientOptions = {
/**
* The API key to use. Ignored if `client` is provided
* @default {process.env.COHERE_API_KEY}
*/
apiKey?: string;
/**
* The CohereClient instance to use. Superseeds `apiKey`
*/
client?: CohereClient;
};
export function getCohereClient(fields?: CohereClientOptions): CohereClient {
if (fields?.client) {
return fields.client;
}
const apiKey = fields?.apiKey ?? getEnvironmentVariable("COHERE_API_KEY");
if (!apiKey) {
throw new Error("COHERE_API_KEY must be set");
}
return new CohereClient({ token: apiKey });
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere | lc_public_repos/langchainjs/libs/langchain-cohere/src/index.ts | export * from "./chat_models.js";
export * from "./llms.js";
export * from "./embeddings.js";
export * from "./rerank.js";
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere | lc_public_repos/langchainjs/libs/langchain-cohere/src/chat_models.ts | /* eslint-disable @typescript-eslint/no-explicit-any */
import { Cohere, CohereClient } from "cohere-ai";
import { ToolResult } from "cohere-ai/api/index.js";
import { zodToJsonSchema } from "zod-to-json-schema";
import {
AIMessage,
type BaseMessage,
isAIMessage,
MessageContent,
MessageType,
} from "@langchain/core/messages";
import {
BaseLanguageModelInput,
isOpenAITool,
} from "@langchain/core/language_models/base";
import { isLangChainTool } from "@langchain/core/utils/function_calling";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import {
BaseChatModel,
BaseChatModelCallOptions,
type BaseChatModelParams,
BindToolsInput,
LangSmithParams,
} from "@langchain/core/language_models/chat_models";
import {
ChatGeneration,
ChatGenerationChunk,
ChatResult,
} from "@langchain/core/outputs";
import { AIMessageChunk } from "@langchain/core/messages";
import { NewTokenIndices } from "@langchain/core/callbacks/base";
import {
ToolCall,
ToolCallChunk,
ToolMessage,
} from "@langchain/core/messages/tool";
import * as uuid from "uuid";
import { Runnable } from "@langchain/core/runnables";
import { CohereClientOptions, getCohereClient } from "./client.js";
type ChatCohereToolType = BindToolsInput | Cohere.Tool;
/**
* Input interface for ChatCohere
*/
export interface BaseChatCohereInput extends BaseChatModelParams {
/**
* The API key to use.
* @default {process.env.COHERE_API_KEY}
*/
apiKey?: string;
/**
* The name of the model to use.
* @default {"command"}
*/
model?: string;
/**
* What sampling temperature to use, between 0.0 and 2.0.
* Higher values like 0.8 will make the output more random,
* while lower values like 0.2 will make it more focused
* and deterministic.
* @default {0.3}
*/
temperature?: number;
/**
* Whether or not to stream the response.
* @default {false}
*/
streaming?: boolean;
/**
* Whether or not to include token usage when streaming.
* This will include an extra chunk at the end of the stream
* with `eventType: "stream-end"` and the token usage in
* `usage_metadata`.
* @default {true}
*/
streamUsage?: boolean;
}
export type ChatCohereInput = BaseChatCohereInput & CohereClientOptions;
interface TokenUsage {
completionTokens?: number;
promptTokens?: number;
totalTokens?: number;
}
export interface ChatCohereCallOptions
extends BaseChatModelCallOptions,
Partial<Omit<Cohere.ChatRequest, "message" | "tools">>,
Partial<Omit<Cohere.ChatStreamRequest, "message" | "tools">>,
Pick<ChatCohereInput, "streamUsage"> {
tools?: ChatCohereToolType[];
}
/** @deprecated Import as ChatCohereCallOptions instead. */
export interface CohereChatCallOptions extends ChatCohereCallOptions {}
function convertToDocuments(
observations: MessageContent
): Array<Record<string, any>> {
/** Converts observations into a 'document' dict */
const documents: Array<Record<string, any>> = [];
let observationsList: Array<Record<string, any>> = [];
if (typeof observations === "string") {
// strings are turned into a key/value pair and a key of 'output' is added.
observationsList = [{ output: observations }];
} else if (
// eslint-disable-next-line no-instanceof/no-instanceof
observations instanceof Map ||
(typeof observations === "object" &&
observations !== null &&
!Array.isArray(observations))
) {
// single mappings are transformed into a list to simplify the rest of the code.
observationsList = [observations];
} else if (!Array.isArray(observations)) {
// all other types are turned into a key/value pair within a list
observationsList = [{ output: observations }];
}
for (let doc of observationsList) {
// eslint-disable-next-line no-instanceof/no-instanceof
if (!(doc instanceof Map) && (typeof doc !== "object" || doc === null)) {
// types that aren't Mapping are turned into a key/value pair.
doc = { output: doc };
}
documents.push(doc);
}
return documents;
}
function convertMessageToCohereMessage(
message: BaseMessage,
toolResults: ToolResult[]
): Cohere.Message {
const getRole = (role: MessageType) => {
switch (role) {
case "system":
return "SYSTEM";
case "human":
return "USER";
case "ai":
return "CHATBOT";
case "tool":
return "TOOL";
default:
throw new Error(
`Unknown message type: '${role}'. Accepted types: 'human', 'ai', 'system', 'tool'`
);
}
};
const getContent = (content: MessageContent): string => {
if (typeof content === "string") {
return content;
}
throw new Error(
`ChatCohere does not support non text message content. Received: ${JSON.stringify(
content,
null,
2
)}`
);
};
const getToolCall = (message: BaseMessage): Cohere.ToolCall[] => {
if (isAIMessage(message) && message.tool_calls) {
return message.tool_calls.map((toolCall) => ({
name: toolCall.name,
parameters: toolCall.args,
}));
}
return [];
};
if (message._getType().toLowerCase() === "ai") {
return {
role: getRole(message._getType()),
message: getContent(message.content),
toolCalls: getToolCall(message),
};
} else if (message._getType().toLowerCase() === "tool") {
return {
role: getRole(message._getType()),
message: getContent(message.content),
toolResults,
};
} else if (
message._getType().toLowerCase() === "human" ||
message._getType().toLowerCase() === "system"
) {
return {
role: getRole(message._getType()),
message: getContent(message.content),
};
} else {
throw new Error(
"Got unknown message type. Supported types are AIMessage, ToolMessage, HumanMessage, and SystemMessage"
);
}
}
function isCohereTool(tool: any): tool is Cohere.Tool {
return (
"name" in tool && "description" in tool && "parameterDefinitions" in tool
);
}
function isToolMessage(message: BaseMessage): message is ToolMessage {
return message._getType() === "tool";
}
function _convertJsonSchemaToCohereTool(jsonSchema: Record<string, any>) {
const parameterDefinitionsProperties =
"properties" in jsonSchema ? jsonSchema.properties : {};
let parameterDefinitionsRequired =
"required" in jsonSchema ? jsonSchema.required : [];
const parameterDefinitionsFinal: Record<string, any> = {};
// Iterate through all properties
Object.keys(parameterDefinitionsProperties).forEach((propertyName) => {
// Create the property in the new object
parameterDefinitionsFinal[propertyName] =
parameterDefinitionsProperties[propertyName];
// Set the required property based on the 'required' array
if (parameterDefinitionsRequired === undefined) {
parameterDefinitionsRequired = [];
}
parameterDefinitionsFinal[propertyName].required =
parameterDefinitionsRequired.includes(propertyName);
});
return parameterDefinitionsFinal;
}
function _formatToolsToCohere(
tools: ChatCohereCallOptions["tools"]
): Cohere.Tool[] | undefined {
if (!tools) {
return undefined;
} else if (tools.every(isCohereTool)) {
return tools;
} else if (tools.every(isOpenAITool)) {
return tools.map((tool) => {
return {
name: tool.function.name,
description: tool.function.description ?? "",
parameterDefinitions: _convertJsonSchemaToCohereTool(
tool.function.parameters
),
};
});
} else if (tools.every(isLangChainTool)) {
return tools.map((tool) => {
const parameterDefinitionsFromZod = zodToJsonSchema(tool.schema);
return {
name: tool.name,
description: tool.description ?? "",
parameterDefinitions: _convertJsonSchemaToCohereTool(
parameterDefinitionsFromZod
),
};
});
} else {
throw new Error(
`Can not pass in a mix of tool schema types to ChatCohere.`
);
}
}
/**
* Integration for Cohere chat models.
*
* Setup:
* Install `@langchain/cohere` and set a environment variable called `COHERE_API_KEY`.
*
* ```bash
* npm install @langchain/cohere
* export COHERE_API_KEY="your-api-key"
* ```
*
* ## [Constructor args](https://api.js.langchain.com/classes/langchain_cohere.ChatCohere.html#constructor)
*
* ## [Runtime args](https://api.js.langchain.com/interfaces/langchain_cohere.ChatCohereCallOptions.html)
*
* Runtime args can be passed as the second argument to any of the base runnable methods `.invoke`. `.stream`, `.batch`, etc.
* They can also be passed via `.bind`, or the second arg in `.bindTools`, like shown in the examples below:
*
* ```typescript
* // When calling `.bind`, call options should be passed via the first argument
* const llmWithArgsBound = llm.bind({
* stop: ["\n"],
* tools: [...],
* });
*
* // When calling `.bindTools`, call options should be passed via the second argument
* const llmWithTools = llm.bindTools(
* [...],
* {
* stop: ["\n"],
* }
* );
* ```
*
* ## Examples
*
* <details open>
* <summary><strong>Instantiate</strong></summary>
*
* ```typescript
* import { ChatCohere } from '@langchain/cohere';
*
* const llm = new ChatCohere({
* model: "command-r-plus",
* temperature: 0,
* // other params...
* });
* ```
* </details>
*
* <br />
*
* <details>
* <summary><strong>Invoking</strong></summary>
*
* ```typescript
* const input = `Translate "I love programming" into French.`;
*
* // Models also accept a list of chat messages or a formatted prompt
* const result = await llm.invoke(input);
* console.log(result);
* ```
*
* ```txt
* AIMessage {
* "content": "\"J'adore programmer.\"",
* "additional_kwargs": {
* ...
* },
* "response_metadata": {
* "estimatedTokenUsage": {
* "completionTokens": 6,
* "promptTokens": 75,
* "totalTokens": 81
* },
* "response_id": "54cebd43-737f-458b-bff4-01b220eaf373",
* "generationId": "48a567da-0f88-4606-bba6-becbeee464bd",
* "chatHistory": [
* {
* "role": "USER",
* "message": "Translate \"I love programming\" into French."
* },
* {
* "role": "CHATBOT",
* "message": "\"J'adore programmer.\""
* }
* ],
* "finishReason": "COMPLETE",
* "meta": {
* "apiVersion": {
* "version": "1"
* },
* "billedUnits": {
* "inputTokens": 9,
* "outputTokens": 6
* },
* "tokens": {
* "inputTokens": 75,
* "outputTokens": 6
* }
* }
* },
* "tool_calls": [],
* "invalid_tool_calls": [],
* "usage_metadata": {
* "input_tokens": 75,
* "output_tokens": 6,
* "total_tokens": 81
* }
* }
* ```
* </details>
*
* <br />
*
* <details>
* <summary><strong>Streaming Chunks</strong></summary>
*
* ```typescript
* for await (const chunk of await llm.stream(input)) {
* console.log(chunk);
* }
* ```
*
* ```txt
* AIMessageChunk {
* "content": "",
* "additional_kwargs": {
* "eventType": "stream-start",
* "is_finished": false,
* "generationId": "d62c8989-8af5-4357-af79-4ea8e6eb2baa"
* },
* "response_metadata": {
* "eventType": "stream-start",
* "is_finished": false,
* "generationId": "d62c8989-8af5-4357-af79-4ea8e6eb2baa"
* },
* "tool_calls": [],
* "tool_call_chunks": [],
* "invalid_tool_calls": []
* }
* AIMessageChunk {
* "content": "\"",
* "additional_kwargs": {},
* "response_metadata": {},
* "tool_calls": [],
* "tool_call_chunks": [],
* "invalid_tool_calls": []
* }
* AIMessageChunk {
* "content": "J",
* "additional_kwargs": {},
* "response_metadata": {},
* "tool_calls": [],
* "tool_call_chunks": [],
* "invalid_tool_calls": []
* }
* AIMessageChunk {
* "content": "'",
* "additional_kwargs": {},
* "response_metadata": {},
* "tool_calls": [],
* "tool_call_chunks": [],
* "invalid_tool_calls": []
* }
* AIMessageChunk {
* "content": "adore",
* "additional_kwargs": {},
* "response_metadata": {},
* "tool_calls": [],
* "tool_call_chunks": [],
* "invalid_tool_calls": []
* }
* AIMessageChunk {
* "content": " programmer",
* "additional_kwargs": {},
* "response_metadata": {},
* "tool_calls": [],
* "tool_call_chunks": [],
* "invalid_tool_calls": []
* }
* AIMessageChunk {
* "content": ".\"",
* "additional_kwargs": {},
* "response_metadata": {},
* "tool_calls": [],
* "tool_call_chunks": [],
* "invalid_tool_calls": []
* }
* AIMessageChunk {
* "content": "",
* "additional_kwargs": {
* "eventType": "stream-end"
* },
* "response_metadata": {
* "eventType": "stream-end",
* "response_id": "687f94a6-13b7-4c2c-98be-9ca5573c722f",
* "text": "\"J'adore programmer.\"",
* "generationId": "d62c8989-8af5-4357-af79-4ea8e6eb2baa",
* "chatHistory": [
* {
* "role": "USER",
* "message": "Translate \"I love programming\" into French."
* },
* {
* "role": "CHATBOT",
* "message": "\"J'adore programmer.\""
* }
* ],
* "finishReason": "COMPLETE",
* "meta": {
* "apiVersion": {
* "version": "1"
* },
* "billedUnits": {
* "inputTokens": 9,
* "outputTokens": 6
* },
* "tokens": {
* "inputTokens": 75,
* "outputTokens": 6
* }
* }
* },
* "tool_calls": [],
* "tool_call_chunks": [],
* "invalid_tool_calls": [],
* "usage_metadata": {
* "input_tokens": 75,
* "output_tokens": 6,
* "total_tokens": 81
* }
* }
* ```
* </details>
*
* <br />
*
* <details>
* <summary><strong>Aggregate Streamed Chunks</strong></summary>
*
* ```typescript
* import { AIMessageChunk } from '@langchain/core/messages';
* import { concat } from '@langchain/core/utils/stream';
*
* const stream = await llm.stream(input);
* let full: AIMessageChunk | undefined;
* for await (const chunk of stream) {
* full = !full ? chunk : concat(full, chunk);
* }
* console.log(full);
* ```
*
* ```txt
* AIMessageChunk {
* "content": "\"J'adore programmer.\"",
* "additional_kwargs": {
* ...
* },
* "response_metadata": {
* "is_finished": false,
* "generationId": "303e0215-96f4-4da5-8c2a-10da3840afce303e0215-96f4-4da5-8c2a-10da3840afce",
* "response_id": "6a8cb7ef-f1b9-44f6-a1df-67aa506d3f0f",
* "text": "\"J'adore programmer.\"",
* "chatHistory": [
* {
* "role": "USER",
* "message": "Translate \"I love programming\" into French."
* },
* {
* "role": "CHATBOT",
* "message": "\"J'adore programmer.\""
* }
* ],
* "finishReason": "COMPLETE",
* "meta": {
* "apiVersion": {
* "version": "1"
* },
* "billedUnits": {
* "inputTokens": 9,
* "outputTokens": 6
* },
* "tokens": {
* "inputTokens": 75,
* "outputTokens": 6
* }
* }
* },
* "tool_calls": [],
* "tool_call_chunks": [],
* "invalid_tool_calls": [],
* "usage_metadata": {
* "input_tokens": 75,
* "output_tokens": 6,
* "total_tokens": 81
* }
* }
* ```
* </details>
*
* <br />
*
* <details>
* <summary><strong>Bind tools</strong></summary>
*
* ```typescript
* import { z } from 'zod';
*
* const GetWeather = {
* name: "GetWeather",
* description: "Get the current weather in a given location",
* schema: z.object({
* location: z.string().describe("The city and state, e.g. San Francisco, CA")
* }),
* }
*
* const GetPopulation = {
* name: "GetPopulation",
* description: "Get the current population in a given location",
* schema: z.object({
* location: z.string().describe("The city and state, e.g. San Francisco, CA")
* }),
* }
*
* const llmWithTools = llm.bindTools([GetWeather, GetPopulation]);
* const aiMsg = await llmWithTools.invoke(
* "Which city is hotter today and which is bigger: LA or NY?"
* );
* console.log(aiMsg.tool_calls);
* ```
*
* ```txt
* [
* {
* name: 'GetWeather',
* args: { location: 'LA' },
* id: 'ce8076ee-2ed3-429d-938c-14f3218c',
* type: 'tool_call'
* },
* {
* name: 'GetWeather',
* args: { location: 'NY' },
* id: '23d1a96e-3a2c-46f4-9d9e-cccd02c6',
* type: 'tool_call'
* },
* {
* name: 'GetPopulation',
* args: { location: 'LA' },
* id: '2bf9d627-310f-46ff-93a9-86baeae9',
* type: 'tool_call'
* },
* {
* name: 'GetPopulation',
* args: { location: 'NY' },
* id: 'c95e6ac0-ee9b-48de-86b2-12548fd1',
* type: 'tool_call'
* }
* ]
* ```
* </details>
*
* <br />
*
* <details>
* <summary><strong>Structured Output</strong></summary>
*
* ```typescript
* import { z } from 'zod';
*
* const Joke = z.object({
* setup: z.string().describe("The setup of the joke"),
* punchline: z.string().describe("The punchline to the joke"),
* rating: z.number().optional().describe("How funny the joke is, from 1 to 10")
* }).describe('Joke to tell user.');
*
* const structuredLlm = llm.withStructuredOutput(Joke, { name: "Joke" });
* const jokeResult = await structuredLlm.invoke("Tell me a joke about cats");
* console.log(jokeResult);
* ```
*
* ```txt
* {
* punchline: 'Because she wanted to be a first-aid kit.',
* rating: 5,
* setup: 'Why did the cat join the Red Cross?'
* }
* ```
* </details>
*
* <br />
*
* <summary><strong>Usage Metadata</strong></summary>
*
* ```typescript
* const aiMsgForMetadata = await llm.invoke(input);
* console.log(aiMsgForMetadata.usage_metadata);
* ```
*
* ```txt
* { input_tokens: 75, output_tokens: 6, total_tokens: 81 }
* ```
* </details>
*
* <br />
*
* <details>
* <summary><strong>Response Metadata</strong></summary>
*
* ```typescript
* const aiMsgForResponseMetadata = await llm.invoke(input);
* console.log(aiMsgForResponseMetadata.response_metadata);
* ```
*
* ```txt
* {
* estimatedTokenUsage: { completionTokens: 6, promptTokens: 75, totalTokens: 81 },
* response_id: 'a688ad65-4db2-4a7a-b6aa-124aa2410319',
* generationId: 'ee259727-18c5-43f7-b9bd-a2a60c0c040b',
* chatHistory: [
* {
* role: 'USER',
* message: 'Translate "I love programming" into French.'
* },
* { role: 'CHATBOT', message: `"J'adore programmer."` }
* ],
* finishReason: 'COMPLETE',
* meta: {
* apiVersion: { version: '1' },
* billedUnits: { inputTokens: 9, outputTokens: 6 },
* tokens: { inputTokens: 75, outputTokens: 6 }
* }
* }
* ```
* </details>
*
* <br />
*/
export class ChatCohere<
CallOptions extends ChatCohereCallOptions = ChatCohereCallOptions
>
extends BaseChatModel<CallOptions, AIMessageChunk>
implements ChatCohereInput
{
static lc_name() {
return "ChatCohere";
}
lc_serializable = true;
client: CohereClient;
model = "command-r-plus";
temperature = 0.3;
streaming = false;
streamUsage: boolean = true;
constructor(fields?: ChatCohereInput) {
super(fields ?? {});
this.client = getCohereClient(fields);
this.model = fields?.model ?? this.model;
this.temperature = fields?.temperature ?? this.temperature;
this.streaming = fields?.streaming ?? this.streaming;
this.streamUsage = fields?.streamUsage ?? this.streamUsage;
}
getLsParams(options: this["ParsedCallOptions"]): LangSmithParams {
const params = this.invocationParams(options);
return {
ls_provider: "cohere",
ls_model_name: this.model,
ls_model_type: "chat",
ls_temperature: this.temperature ?? undefined,
ls_max_tokens:
typeof params.maxTokens === "number" ? params.maxTokens : undefined,
ls_stop: Array.isArray(params.stopSequences)
? (params.stopSequences as unknown as string[])
: undefined,
};
}
_llmType() {
return "cohere";
}
invocationParams(options: this["ParsedCallOptions"]) {
if (options.tool_choice) {
throw new Error(
"'tool_choice' call option is not supported by ChatCohere."
);
}
const params = {
model: this.model,
preamble: options.preamble,
conversationId: options.conversationId,
promptTruncation: options.promptTruncation,
connectors: options.connectors,
searchQueriesOnly: options.searchQueriesOnly,
documents: options.documents,
temperature: options.temperature ?? this.temperature,
forceSingleStep: options.forceSingleStep,
tools: options.tools,
};
// Filter undefined entries
return Object.fromEntries(
Object.entries(params).filter(([, value]) => value !== undefined)
);
}
override bindTools(
tools: ChatCohereToolType[],
kwargs?: Partial<CallOptions>
): Runnable<BaseLanguageModelInput, AIMessageChunk, CallOptions> {
return this.bind({
tools: _formatToolsToCohere(tools),
...kwargs,
} as Partial<CallOptions>);
}
/** @ignore */
private _getChatRequest(
messages: BaseMessage[],
options: this["ParsedCallOptions"]
): Cohere.ChatRequest {
const params = this.invocationParams(options);
const toolResults = this._messagesToCohereToolResultsCurrChatTurn(messages);
const chatHistory = [];
let messageStr: string = "";
let tempToolResults: {
call: Cohere.ToolCall;
outputs: any;
}[] = [];
if (!params.forceSingleStep) {
for (let i = 0; i < messages.length - 1; i += 1) {
const message = messages[i];
// If there are multiple tool messages, then we need to aggregate them into one single tool message to pass into chat history
if (message._getType().toLowerCase() === "tool") {
tempToolResults = tempToolResults.concat(
this._messageToCohereToolResults(messages, i)
);
if (
i === messages.length - 1 ||
!(messages[i + 1]._getType().toLowerCase() === "tool")
) {
const cohere_message = convertMessageToCohereMessage(
message,
tempToolResults
);
chatHistory.push(cohere_message);
tempToolResults = [];
}
} else {
chatHistory.push(convertMessageToCohereMessage(message, []));
}
}
messageStr =
toolResults.length > 0
? ""
: messages[messages.length - 1].content.toString();
} else {
messageStr = "";
// if force_single_step is set to True, then message is the last human message in the conversation
for (let i = 0; i < messages.length - 1; i += 1) {
const message = messages[i];
if (isAIMessage(message) && message.tool_calls) {
continue;
}
// If there are multiple tool messages, then we need to aggregate them into one single tool message to pass into chat history
if (message._getType().toLowerCase() === "tool") {
tempToolResults = tempToolResults.concat(
this._messageToCohereToolResults(messages, i)
);
if (
i === messages.length - 1 ||
!(messages[i + 1]._getType().toLowerCase() === "tool")
) {
const cohereMessage = convertMessageToCohereMessage(
message,
tempToolResults
);
chatHistory.push(cohereMessage);
tempToolResults = [];
}
} else {
chatHistory.push(convertMessageToCohereMessage(message, []));
}
}
// Add the last human message in the conversation to the message string
for (let i = messages.length - 1; i >= 0; i -= 1) {
const message = messages[i];
if (message._getType().toLowerCase() === "human" && message.content) {
messageStr = message.content.toString();
break;
}
}
}
const req: Cohere.ChatRequest = {
message: messageStr,
chatHistory,
toolResults: toolResults.length > 0 ? toolResults : undefined,
...params,
};
return req;
}
private _getCurrChatTurnMessages(messages: BaseMessage[]): BaseMessage[] {
// Get the messages for the current chat turn.
const currentChatTurnMessages: BaseMessage[] = [];
for (let i = messages.length - 1; i >= 0; i -= 1) {
const message = messages[i];
currentChatTurnMessages.push(message);
if (message._getType().toLowerCase() === "human") {
break;
}
}
return currentChatTurnMessages.reverse();
}
private _messagesToCohereToolResultsCurrChatTurn(
messages: BaseMessage[]
): Array<{
call: Cohere.ToolCall;
outputs: ReturnType<typeof convertToDocuments>;
}> {
/** Get tool_results from messages. */
const toolResults: Array<{
call: Cohere.ToolCall;
outputs: ReturnType<typeof convertToDocuments>;
}> = [];
const currChatTurnMessages = this._getCurrChatTurnMessages(messages);
for (const message of currChatTurnMessages) {
if (isToolMessage(message)) {
const toolMessage = message;
const previousAiMsgs = currChatTurnMessages.filter(
(msg) => isAIMessage(msg) && msg.tool_calls !== undefined
) as AIMessage[];
if (previousAiMsgs.length > 0) {
const previousAiMsg = previousAiMsgs[previousAiMsgs.length - 1];
if (previousAiMsg.tool_calls) {
toolResults.push(
...previousAiMsg.tool_calls
.filter(
(lcToolCall) => lcToolCall.id === toolMessage.tool_call_id
)
.map((lcToolCall) => ({
call: {
name: lcToolCall.name,
parameters: lcToolCall.args,
},
outputs: convertToDocuments(toolMessage.content),
}))
);
}
}
}
}
return toolResults;
}
private _messageToCohereToolResults(
messages: BaseMessage[],
toolMessageIndex: number
): Array<{ call: Cohere.ToolCall; outputs: any }> {
/** Get tool_results from messages. */
const toolResults: Array<{ call: Cohere.ToolCall; outputs: any }> = [];
const toolMessage = messages[toolMessageIndex];
if (!isToolMessage(toolMessage)) {
throw new Error(
"The message index does not correspond to an instance of ToolMessage"
);
}
const messagesUntilTool = messages.slice(0, toolMessageIndex);
const previousAiMessage = messagesUntilTool
.filter((message) => isAIMessage(message) && message.tool_calls)
.slice(-1)[0] as AIMessage;
if (previousAiMessage.tool_calls) {
toolResults.push(
...previousAiMessage.tool_calls
.filter((lcToolCall) => lcToolCall.id === toolMessage.tool_call_id)
.map((lcToolCall) => ({
call: {
name: lcToolCall.name,
parameters: lcToolCall.args,
},
outputs: convertToDocuments(toolMessage.content),
}))
);
}
return toolResults;
}
private _formatCohereToolCalls(toolCalls: Cohere.ToolCall[] | null = null): {
id: string;
function: {
name: string;
arguments: Record<string, any>;
};
type: string;
}[] {
if (!toolCalls) {
return [];
}
const formattedToolCalls = [];
for (const toolCall of toolCalls) {
formattedToolCalls.push({
id: uuid.v4().substring(0, 32),
function: {
name: toolCall.name,
arguments: toolCall.parameters, // Convert arguments to string
},
type: "function",
});
}
return formattedToolCalls;
}
private _convertCohereToolCallToLangchain(
toolCalls: Record<string, any>[]
): ToolCall[] {
return toolCalls.map((toolCall) => ({
name: toolCall.function.name,
args: toolCall.function.arguments,
id: toolCall.id,
type: "tool_call",
}));
}
/** @ignore */
async _generate(
messages: BaseMessage[],
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): Promise<ChatResult> {
const tokenUsage: TokenUsage = {};
// The last message in the array is the most recent, all other messages
// are apart of the chat history.
const request = this._getChatRequest(messages, options);
// Handle streaming
if (this.streaming) {
const stream = this._streamResponseChunks(messages, options, runManager);
const finalChunks: Record<number, ChatGenerationChunk> = {};
for await (const chunk of stream) {
const index =
(chunk.generationInfo as NewTokenIndices)?.completion ?? 0;
if (finalChunks[index] === undefined) {
finalChunks[index] = chunk;
} else {
finalChunks[index] = finalChunks[index].concat(chunk);
}
}
const generations = Object.entries(finalChunks)
.sort(([aKey], [bKey]) => parseInt(aKey, 10) - parseInt(bKey, 10))
.map(([_, value]) => value);
return { generations, llmOutput: { estimatedTokenUsage: tokenUsage } };
}
// Not streaming, so we can just call the API once.
const response: Cohere.NonStreamedChatResponse =
await this.caller.callWithOptions(
{ signal: options.signal },
async () => {
let response;
try {
response = await this.client.chat(request);
} catch (e: any) {
e.status = e.status ?? e.statusCode;
throw e;
}
return response;
}
);
if (response.meta?.tokens) {
const { inputTokens, outputTokens } = response.meta.tokens;
if (outputTokens) {
tokenUsage.completionTokens =
(tokenUsage.completionTokens ?? 0) + outputTokens;
}
if (inputTokens) {
tokenUsage.promptTokens = (tokenUsage.promptTokens ?? 0) + inputTokens;
}
tokenUsage.totalTokens =
(tokenUsage.totalTokens ?? 0) +
(tokenUsage.promptTokens ?? 0) +
(tokenUsage.completionTokens ?? 0);
}
const generationInfo: Record<string, unknown> = { ...response };
delete generationInfo.text;
if (response.toolCalls && response.toolCalls.length > 0) {
// Only populate tool_calls when 1) present on the response and
// 2) has one or more calls.
generationInfo.toolCalls = this._formatCohereToolCalls(
response.toolCalls
);
}
let toolCalls: ToolCall[] = [];
if ("toolCalls" in generationInfo) {
toolCalls = this._convertCohereToolCallToLangchain(
generationInfo.toolCalls as Record<string, any>[]
);
}
const generations: ChatGeneration[] = [
{
text: response.text,
message: new AIMessage({
content: response.text,
additional_kwargs: generationInfo,
tool_calls: toolCalls,
usage_metadata: {
input_tokens: tokenUsage.promptTokens ?? 0,
output_tokens: tokenUsage.completionTokens ?? 0,
total_tokens: tokenUsage.totalTokens ?? 0,
},
}),
generationInfo,
},
];
return {
generations,
llmOutput: { estimatedTokenUsage: tokenUsage },
};
}
async *_streamResponseChunks(
messages: BaseMessage[],
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): AsyncGenerator<ChatGenerationChunk> {
const request = this._getChatRequest(messages, options);
// All models have a built in `this.caller` property for retries
const stream = await this.caller.call(async () => {
let stream;
try {
stream = await this.client.chatStream(request);
} catch (e: any) {
e.status = e.status ?? e.statusCode;
throw e;
}
return stream;
});
for await (const chunk of stream) {
if (chunk.eventType === "text-generation") {
yield new ChatGenerationChunk({
text: chunk.text,
message: new AIMessageChunk({
content: chunk.text,
}),
});
await runManager?.handleLLMNewToken(chunk.text);
} else if (chunk.eventType !== "stream-end") {
// Used for when the user uses their RAG/Search/other API
// and the stream takes more actions then just text generation.
yield new ChatGenerationChunk({
text: "",
message: new AIMessageChunk({
content: "",
additional_kwargs: {
...chunk,
},
}),
generationInfo: {
...chunk,
},
});
} else if (
chunk.eventType === "stream-end" &&
(this.streamUsage || options.streamUsage)
) {
// stream-end events contain the final token count
const input_tokens = chunk.response.meta?.tokens?.inputTokens ?? 0;
const output_tokens = chunk.response.meta?.tokens?.outputTokens ?? 0;
const chunkGenerationInfo: Record<string, any> = {
...chunk.response,
};
if (chunk.response.toolCalls && chunk.response.toolCalls.length > 0) {
// Only populate tool_calls when 1) present on the response and
// 2) has one or more calls.
chunkGenerationInfo.toolCalls = this._formatCohereToolCalls(
chunk.response.toolCalls
);
}
let toolCallChunks: ToolCallChunk[] = [];
const toolCalls = chunkGenerationInfo.toolCalls ?? [];
if (toolCalls.length > 0) {
toolCallChunks = toolCalls.map((toolCall: any) => ({
name: toolCall.function.name,
args: toolCall.function.arguments,
id: toolCall.id,
index: toolCall.index,
type: "tool_call_chunk",
}));
}
yield new ChatGenerationChunk({
text: "",
message: new AIMessageChunk({
content: "",
additional_kwargs: {
eventType: "stream-end",
},
tool_call_chunks: toolCallChunks,
usage_metadata: {
input_tokens,
output_tokens,
total_tokens: input_tokens + output_tokens,
},
}),
generationInfo: {
eventType: "stream-end",
...chunkGenerationInfo,
},
});
}
}
}
_combineLLMOutput(...llmOutputs: CohereLLMOutput[]): CohereLLMOutput {
return llmOutputs.reduce<{
[key in keyof CohereLLMOutput]: Required<CohereLLMOutput[key]>;
}>(
(acc, llmOutput) => {
if (llmOutput && llmOutput.estimatedTokenUsage) {
let completionTokens = acc.estimatedTokenUsage?.completionTokens ?? 0;
let promptTokens = acc.estimatedTokenUsage?.promptTokens ?? 0;
let totalTokens = acc.estimatedTokenUsage?.totalTokens ?? 0;
completionTokens +=
llmOutput.estimatedTokenUsage.completionTokens ?? 0;
promptTokens += llmOutput.estimatedTokenUsage.promptTokens ?? 0;
totalTokens += llmOutput.estimatedTokenUsage.totalTokens ?? 0;
acc.estimatedTokenUsage = {
completionTokens,
promptTokens,
totalTokens,
};
}
return acc;
},
{
estimatedTokenUsage: {
completionTokens: 0,
promptTokens: 0,
totalTokens: 0,
},
}
);
}
get lc_secrets(): { [key: string]: string } | undefined {
return {
apiKey: "COHERE_API_KEY",
api_key: "COHERE_API_KEY",
};
}
get lc_aliases(): { [key: string]: string } | undefined {
return {
apiKey: "cohere_api_key",
api_key: "cohere_api_key",
};
}
}
interface CohereLLMOutput {
estimatedTokenUsage?: TokenUsage;
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere | lc_public_repos/langchainjs/libs/langchain-cohere/src/embeddings.ts | import { CohereClient } from "cohere-ai";
import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings";
import { chunkArray } from "@langchain/core/utils/chunk_array";
import { CohereClientOptions, getCohereClient } from "./client.js";
/**
* Interface that extends EmbeddingsParams and defines additional
* parameters specific to the CohereEmbeddings class.
*/
export interface CohereEmbeddingsParams extends EmbeddingsParams {
model?: string;
/**
* The maximum number of documents to embed in a single request. This is
* limited by the Cohere API to a maximum of 96.
*/
batchSize?: number;
/**
* Specifies the type of embeddings you want to generate.
*/
embeddingTypes?: Array<string>;
/**
* Specifies the type of input you're giving to the model.
* Not required for older versions of the embedding models (i.e. anything lower than v3),
* but is required for more recent versions (i.e. anything bigger than v2).
*
* * `search_document` - Use this when you encode documents for embeddings that you store in a vector database for search use-cases.
* * `search_query` - Use this when you query your vector DB to find relevant documents.
* * `classification` - Use this when you use the embeddings as an input to a text classifier.
* * `clustering` - Use this when you want to cluster the embeddings.
*/
inputType?: string;
}
/**
* A class for generating embeddings using the Cohere API.
*/
export class CohereEmbeddings
extends Embeddings
implements CohereEmbeddingsParams
{
model: string | undefined;
batchSize = 48;
embeddingTypes = ["float"];
private client: CohereClient;
/**
* Constructor for the CohereEmbeddings class.
* @param fields - An optional object with properties to configure the instance.
*/
constructor(
fields?: Partial<CohereEmbeddingsParams> & {
verbose?: boolean;
} & CohereClientOptions
) {
const fieldsWithDefaults = { maxConcurrency: 2, ...fields };
super(fieldsWithDefaults);
this.client = getCohereClient(fieldsWithDefaults);
this.model = fieldsWithDefaults?.model ?? this.model;
if (!this.model) {
throw new Error(
"Model not specified for CohereEmbeddings instance. Please provide a model name from the options here: https://docs.cohere.com/reference/embed"
);
}
this.batchSize = fieldsWithDefaults?.batchSize ?? this.batchSize;
this.embeddingTypes =
fieldsWithDefaults?.embeddingTypes ?? this.embeddingTypes;
}
/**
* Generates embeddings for an array of texts.
* @param texts - An array of strings to generate embeddings for.
* @returns A Promise that resolves to an array of embeddings.
*/
async embedDocuments(texts: string[]): Promise<number[][]> {
const batches = chunkArray(texts, this.batchSize);
const batchRequests = batches.map((batch) =>
this.embeddingWithRetry({
model: this.model,
texts: batch,
// eslint-disable-next-line @typescript-eslint/no-explicit-any
inputType: "search_document" as any,
// eslint-disable-next-line @typescript-eslint/no-explicit-any
embeddingTypes: this.embeddingTypes as any,
})
);
const batchResponses = await Promise.all(batchRequests);
const embeddings: number[][] = [];
for (let i = 0; i < batchResponses.length; i += 1) {
const batch = batches[i];
const { embeddings: batchResponse } = batchResponses[i];
for (let j = 0; j < batch.length; j += 1) {
if ("float" in batchResponse && batchResponse.float) {
embeddings.push(batchResponse.float[j]);
} else if (Array.isArray(batchResponse)) {
embeddings.push(batchResponse[j as number]);
}
}
}
return embeddings;
}
/**
* Generates an embedding for a single text.
* @param text - A string to generate an embedding for.
* @returns A Promise that resolves to an array of numbers representing the embedding.
*/
async embedQuery(text: string): Promise<number[]> {
const { embeddings } = await this.embeddingWithRetry({
model: this.model,
texts: [text],
// eslint-disable-next-line @typescript-eslint/no-explicit-any
inputType: "search_query" as any,
// eslint-disable-next-line @typescript-eslint/no-explicit-any
embeddingTypes: this.embeddingTypes as any,
});
if ("float" in embeddings && embeddings.float) {
return embeddings.float[0];
} else if (Array.isArray(embeddings)) {
return embeddings[0];
} else {
throw new Error(
`Invalid response from Cohere API. Received: ${JSON.stringify(
embeddings,
null,
2
)}`
);
}
}
async embed(
request: Parameters<typeof this.client.embed>[0]
): Promise<number[]> {
const { embeddings } = await this.embeddingWithRetry(request);
if ("float" in embeddings && embeddings.float) {
return embeddings.float[0];
} else if (Array.isArray(embeddings)) {
return embeddings[0];
} else {
throw new Error(
`Invalid response from Cohere API. Received: ${JSON.stringify(
embeddings,
null,
2
)}`
);
}
}
/**
* Generates embeddings with retry capabilities.
* @param request - An object containing the request parameters for generating embeddings.
* @returns A Promise that resolves to the API response.
*/
private async embeddingWithRetry(
request: Parameters<typeof this.client.embed>[0]
) {
return this.caller.call(async () => {
let response;
try {
response = await this.client.embed(request);
// eslint-disable-next-line @typescript-eslint/no-explicit-any
} catch (e: any) {
e.status = e.status ?? e.statusCode;
throw e;
}
return response;
});
}
get lc_secrets(): { [key: string]: string } | undefined {
return {
apiKey: "COHERE_API_KEY",
api_key: "COHERE_API_KEY",
};
}
get lc_aliases(): { [key: string]: string } | undefined {
return {
apiKey: "cohere_api_key",
api_key: "cohere_api_key",
};
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere/src | lc_public_repos/langchainjs/libs/langchain-cohere/src/tests/chat_models.standard.int.test.ts | /* eslint-disable no-process-env */
import { test, expect } from "@jest/globals";
import { ChatModelIntegrationTests } from "@langchain/standard-tests";
import { AIMessageChunk } from "@langchain/core/messages";
import {
ChatCohere,
ChatCohereCallOptions,
ChatCohereInput,
} from "../chat_models.js";
class ChatCohereStandardIntegrationTests extends ChatModelIntegrationTests<
ChatCohereCallOptions,
AIMessageChunk,
ChatCohereInput
> {
constructor() {
if (!process.env.COHERE_API_KEY) {
throw new Error(
"Can not run Cohere integration tests because COHERE_API_KEY is not set"
);
}
super({
Cls: ChatCohere,
chatModelHasToolCalling: true,
chatModelHasStructuredOutput: true,
constructorArgs: {
model: "command-r-plus",
maxRetries: 1,
temperature: 0,
},
});
}
async testToolMessageHistoriesListContent() {
this.skipTestMessage(
"testToolMessageHistoriesListContent",
"ChatCohere",
"Anthropic-style tool calling is not supported."
);
}
async testStreamTokensWithToolCalls() {
this.skipTestMessage(
"testStreamTokensWithToolCalls",
"ChatCohere",
"Prompt does not always cause Cohere to invoke a tool. TODO: re-write inside this class with better prompting for cohere."
);
}
async testModelCanUseToolUseAIMessageWithStreaming() {
this.skipTestMessage(
"testModelCanUseToolUseAIMessageWithStreaming",
"ChatCohere",
"Prompt does not always cause Cohere to invoke a tool. TODO: re-write inside this class with better prompting for cohere."
);
}
async testStreamTools(): Promise<void> {
this.skipTestMessage(
"testStreamTools",
"ChatCohere",
"Cohere only responds with the tool call in the final chunk. TODO: fix implementation to actually stream tools."
);
}
}
const testClass = new ChatCohereStandardIntegrationTests();
test("ChatCohereStandardIntegrationTests", async () => {
const testResults = await testClass.runTests();
expect(testResults).toBe(true);
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere/src | lc_public_repos/langchainjs/libs/langchain-cohere/src/tests/llms.int.test.ts | /* eslint-disable no-promise-executor-return, no-process-env */
import { test } from "@jest/globals";
import { Cohere } from "../llms.js";
// Save the original value of the 'LANGCHAIN_CALLBACKS_BACKGROUND' environment variable
const originalBackground = process.env.LANGCHAIN_CALLBACKS_BACKGROUND;
test("test invoke", async () => {
const cohere = new Cohere({});
// @eslint-disable-next-line/@typescript-eslint/ban-ts-comment
// @ts-expect-error unused var
const result = await cohere.invoke(
"What is a good name for a company that makes colorful socks?"
);
// console.log({ result });
});
test("test invoke with callback", async () => {
// Running LangChain callbacks in the background will sometimes cause the callbackManager to execute
// after the test/llm call has already finished & returned. Set that environment variable to false
// to prevent that from happening.
process.env.LANGCHAIN_CALLBACKS_BACKGROUND = "false";
try {
const cohere = new Cohere({
model: "command-light",
});
const tokens: string[] = [];
const result = await cohere.invoke(
"What is a good name for a company that makes colorful socks?",
{
callbacks: [
{
handleLLMNewToken(token) {
tokens.push(token);
},
},
],
}
);
// Not streaming, so we should only get one token
expect(tokens.length).toBe(1);
expect(result).toEqual(tokens.join(""));
} finally {
// Reset the environment variable
process.env.LANGCHAIN_CALLBACKS_BACKGROUND = originalBackground;
}
});
test("should abort the request", async () => {
const cohere = new Cohere({
model: "command-light",
});
const controller = new AbortController();
await expect(async () => {
const ret = cohere.invoke("Respond with an verbose response", {
signal: controller.signal,
});
await new Promise((resolve) => setTimeout(resolve, 100));
controller.abort();
return ret;
}).rejects.toThrow("AbortError");
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere/src | lc_public_repos/langchainjs/libs/langchain-cohere/src/tests/chat_models.standard.test.ts | /* eslint-disable no-process-env */
import { test, expect } from "@jest/globals";
import { ChatModelUnitTests } from "@langchain/standard-tests";
import { AIMessageChunk } from "@langchain/core/messages";
import { ChatCohere, ChatCohereCallOptions } from "../chat_models.js";
class ChatCohereStandardUnitTests extends ChatModelUnitTests<
ChatCohereCallOptions,
AIMessageChunk
> {
constructor() {
super({
Cls: ChatCohere,
chatModelHasToolCalling: true,
chatModelHasStructuredOutput: true,
constructorArgs: {},
});
// This must be set so method like `.bindTools` or `.withStructuredOutput`
// which we call after instantiating the model will work.
// (constructor will throw if API key is not set)
process.env.COHERE_API_KEY = "test";
}
testChatModelInitApiKey() {
// Unset the API key env var here so this test can properly check
// the API key class arg.
process.env.COHERE_API_KEY = "";
super.testChatModelInitApiKey();
// Re-set the API key env var here so other tests can run properly.
process.env.COHERE_API_KEY = "test";
}
}
const testClass = new ChatCohereStandardUnitTests();
test("ChatCohereStandardUnitTests", () => {
const testResults = testClass.runTests();
expect(testResults).toBe(true);
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere/src | lc_public_repos/langchainjs/libs/langchain-cohere/src/tests/chat_models.int.test.ts | /* eslint-disable no-promise-executor-return */
import { test, expect } from "@jest/globals";
import {
AIMessageChunk,
HumanMessage,
ToolMessage,
} from "@langchain/core/messages";
import { z } from "zod";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { ChatCohere } from "../chat_models.js";
test("ChatCohere can invoke", async () => {
const model = new ChatCohere();
const response = await model.invoke([new HumanMessage("Hello world")]);
// console.log(response.additional_kwargs);
expect(response.content).toBeTruthy();
expect(response.additional_kwargs).toBeTruthy();
});
// Adding this test because token count is not documented in their
// API docs or SDK types, but their API returns it.
test("ChatCohere can count tokens", async () => {
const model = new ChatCohere();
const response = await model.generate([[new HumanMessage("Hello world")]]);
// console.log(response);
expect(response.llmOutput?.estimatedTokenUsage).toBeTruthy();
expect(
response.llmOutput?.estimatedTokenUsage.completionTokens
).toBeGreaterThan(1);
expect(response.llmOutput?.estimatedTokenUsage.promptTokens).toBeGreaterThan(
1
);
expect(response.llmOutput?.estimatedTokenUsage.totalTokens).toBeGreaterThan(
1
);
});
test("ChatCohere can stream", async () => {
const model = new ChatCohere();
const stream = await model.stream([new HumanMessage("Hello world")]);
let tokens = "";
let streamIters = 0;
for await (const streamItem of stream) {
tokens += streamItem.content;
streamIters += 1;
// console.log(tokens);
}
expect(streamIters).toBeGreaterThan(1);
});
test("should abort the request", async () => {
const cohere = new ChatCohere({
model: "command-light",
});
const controller = new AbortController();
await expect(async () => {
const ret = cohere.invoke("Respond with an verbose response", {
signal: controller.signal,
});
await new Promise((resolve) => setTimeout(resolve, 100));
controller.abort();
return ret;
}).rejects.toThrow("AbortError");
});
test("Stream token count usage_metadata", async () => {
const model = new ChatCohere({
model: "command-light",
temperature: 0,
});
let res: AIMessageChunk | null = null;
let lastRes: AIMessageChunk | null = null;
for await (const chunk of await model.stream(
"Why is the sky blue? Be concise."
)) {
if (!res) {
res = chunk;
} else {
res = res.concat(chunk);
}
lastRes = chunk;
}
// console.log(res);
expect(res?.usage_metadata).toBeDefined();
if (!res?.usage_metadata) {
return;
}
expect(res.usage_metadata.input_tokens).toBeGreaterThan(1);
expect(res.usage_metadata.output_tokens).toBeGreaterThan(10);
expect(res.usage_metadata.total_tokens).toBe(
res.usage_metadata.input_tokens + res.usage_metadata.output_tokens
);
expect(lastRes?.additional_kwargs).toBeDefined();
if (!lastRes?.additional_kwargs) {
return;
}
expect(lastRes.additional_kwargs.eventType).toBe("stream-end");
});
test("streamUsage excludes token usage", async () => {
const model = new ChatCohere({
model: "command-light",
temperature: 0,
streamUsage: false,
});
let res: AIMessageChunk | null = null;
let lastRes: AIMessageChunk | null = null;
for await (const chunk of await model.stream(
"Why is the sky blue? Be concise."
)) {
if (!res) {
res = chunk;
} else {
res = res.concat(chunk);
}
lastRes = chunk;
}
// console.log(res);
expect(res?.usage_metadata).not.toBeDefined();
if (res?.usage_metadata) {
return;
}
expect(lastRes?.additional_kwargs).toBeDefined();
if (!lastRes?.additional_kwargs) {
return;
}
expect(lastRes.additional_kwargs.eventType).not.toBe("stream-end");
});
test("Invoke token count usage_metadata", async () => {
const model = new ChatCohere({
model: "command-light",
temperature: 0,
});
const res = await model.invoke("Why is the sky blue? Be concise.");
// console.log(res);
expect(res?.usage_metadata).toBeDefined();
if (!res?.usage_metadata) {
return;
}
expect(res.usage_metadata.input_tokens).toBeGreaterThan(1);
expect(res.usage_metadata.output_tokens).toBeGreaterThan(10);
expect(res.usage_metadata.total_tokens).toBe(
res.usage_metadata.input_tokens + res.usage_metadata.output_tokens
);
});
test("Test model tool calling", async () => {
const model = new ChatCohere({
model: "command-r-plus",
temperature: 0,
});
const webSearchTool = new DynamicStructuredTool({
name: "web_search",
description: "Search the web and return the answer",
schema: z.object({
search_query: z
.string()
.describe("The search query to surf the internet for"),
}) as any /* eslint-disable-line @typescript-eslint/no-explicit-any */,
func: async ({ search_query }) => `${search_query}`,
});
const tools = [webSearchTool];
const modelWithTools = model.bindTools(tools);
const messages = [
new HumanMessage(
"Who is the president of Singapore?? USE TOOLS TO SEARCH INTERNET!!!!"
),
];
const res = await modelWithTools.invoke(messages);
// console.log(res);
expect(res?.usage_metadata).toBeDefined();
if (!res?.usage_metadata) {
return;
}
expect(res.usage_metadata.total_tokens).toBe(
res.usage_metadata.input_tokens + res.usage_metadata.output_tokens
);
expect(res.tool_calls).toBeDefined();
expect(res.tool_calls?.length).toBe(1);
const tool_id = res.response_metadata.toolCalls[0].id;
messages.push(res);
messages.push(
new ToolMessage(
"Aidan Gomez is the president of Singapore",
tool_id,
"web_search"
)
);
const resWithToolResults = await modelWithTools.invoke(messages);
// console.log(resWithToolResults);
expect(resWithToolResults?.usage_metadata).toBeDefined();
if (!resWithToolResults?.usage_metadata) {
return;
}
expect(resWithToolResults.content).toContain("Aidan Gomez");
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere/src | lc_public_repos/langchainjs/libs/langchain-cohere/src/tests/embeddings.int.test.ts | import { test, expect } from "@jest/globals";
import { CohereEmbeddings } from "../embeddings.js";
test("Test CohereEmbeddings.embedQuery", async () => {
const embeddings = new CohereEmbeddings({ model: "small" });
const res = await embeddings.embedQuery("Hello world");
expect(typeof res[0]).toBe("number");
});
test("Test CohereEmbeddings.embedDocuments", async () => {
const embeddings = new CohereEmbeddings({ model: "small" });
const res = await embeddings.embedDocuments(["Hello world", "Bye bye"]);
expect(res).toHaveLength(2);
expect(typeof res[0][0]).toBe("number");
expect(typeof res[1][0]).toBe("number");
});
test("Test CohereEmbeddings concurrency", async () => {
const embeddings = new CohereEmbeddings({
batchSize: 1,
maxConcurrency: 2,
model: "small",
});
const res = await embeddings.embedDocuments([
"Hello world",
"Bye bye",
"Hello world",
"Bye bye",
"Hello world",
"Bye bye",
]);
expect(res).toHaveLength(6);
expect(res.find((embedding) => typeof embedding[0] !== "number")).toBe(
undefined
);
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere/src | lc_public_repos/langchainjs/libs/langchain-cohere/src/tests/rerank.int.test.ts | /* eslint-disable no-process-env */
import { Document } from "@langchain/core/documents";
import { CohereRerank } from "../rerank.js";
const query = "What is the capital of France?";
const documents = [
new Document({
pageContent: "Paris is the capital of France.",
}),
new Document({
pageContent: "Build context-aware reasoning applications",
}),
new Document({
pageContent:
"Carson City is the capital city of the American state of Nevada. At the 2010 United States Census, Carson City had a population of 55,274",
}),
];
test("CohereRerank can indeed rerank documents with compressDocuments method", async () => {
const cohereRerank = new CohereRerank({
apiKey: process.env.COHERE_API_KEY,
model: "rerank-english-v2.0",
});
const rerankedDocuments = await cohereRerank.compressDocuments(
documents,
query
);
// console.log(rerankedDocuments);
expect(rerankedDocuments).toHaveLength(3);
});
test("CohereRerank can indeed rerank documents with rerank method", async () => {
const cohereRerank = new CohereRerank({
apiKey: process.env.COHERE_API_KEY,
model: "rerank-english-v2.0",
});
const rerankedDocuments = await cohereRerank.rerank(
documents.map((doc) => doc.pageContent),
query
);
// console.log(rerankedDocuments);
expect(rerankedDocuments).toHaveLength(3);
});
|
0 | lc_public_repos/langchainjs/libs/langchain-cohere | lc_public_repos/langchainjs/libs/langchain-cohere/scripts/jest-setup-after-env.js | import { awaitAllCallbacks } from "@langchain/core/callbacks/promises";
import { afterAll, jest } from "@jest/globals";
afterAll(awaitAllCallbacks);
// Allow console.log to be disabled in tests
if (process.env.DISABLE_CONSOLE_LOGS === "true") {
console.log = jest.fn();
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/tsconfig.json | {
"extends": "@tsconfig/recommended",
"compilerOptions": {
"outDir": "../dist",
"rootDir": "./src",
"target": "ES2021",
"lib": ["ES2021", "ES2022.Object", "DOM"],
"module": "ES2020",
"moduleResolution": "nodenext",
"esModuleInterop": true,
"declaration": true,
"noImplicitReturns": true,
"noFallthroughCasesInSwitch": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"useDefineForClassFields": true,
"strictPropertyInitialization": false,
"allowJs": true,
"strict": true
},
"include": ["src/**/*"],
"exclude": ["node_modules", "dist", "docs"]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/LICENSE | The MIT License
Copyright (c) 2023 LangChain
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE. |
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/jest.config.cjs | /** @type {import('ts-jest').JestConfigWithTsJest} */
module.exports = {
preset: "ts-jest/presets/default-esm",
testEnvironment: "./jest.env.cjs",
modulePathIgnorePatterns: ["dist/", "docs/"],
moduleNameMapper: {
"^(\\.{1,2}/.*)\\.js$": "$1",
},
transform: {
"^.+\\.tsx?$": ["@swc/jest"],
},
transformIgnorePatterns: [
"/node_modules/",
"\\.pnp\\.[^\\/]+$",
"./scripts/jest-setup-after-env.js",
],
setupFiles: ["dotenv/config"],
testTimeout: 20_000,
passWithNoTests: true,
collectCoverageFrom: ["src/**/*.ts"],
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/jest.env.cjs | const { TestEnvironment } = require("jest-environment-node");
class AdjustedTestEnvironmentToSupportFloat32Array extends TestEnvironment {
constructor(config, context) {
// Make `instanceof Float32Array` return true in tests
// to avoid https://github.com/xenova/transformers.js/issues/57 and https://github.com/jestjs/jest/issues/2549
super(config, context);
this.global.Float32Array = Float32Array;
}
}
module.exports = AdjustedTestEnvironmentToSupportFloat32Array;
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/README.md | # @langchain/mongodb
This package contains the LangChain.js integrations for MongoDB through their SDK.
## Installation
```bash npm2yarn
npm install @langchain/mongodb @langchain/core
```
This package, along with the main LangChain package, depends on [`@langchain/core`](https://npmjs.com/package/@langchain/core/).
If you are using this package with other LangChain packages, you should make sure that all of the packages depend on the same instance of @langchain/core.
You can do so by adding appropriate field to your project's `package.json` like this:
```json
{
"name": "your-project",
"version": "0.0.0",
"dependencies": {
"@langchain/core": "^0.3.0",
"@langchain/mongodb": "^0.0.0"
},
"resolutions": {
"@langchain/core": "^0.3.0"
},
"overrides": {
"@langchain/core": "^0.3.0"
},
"pnpm": {
"overrides": {
"@langchain/core": "^0.3.0"
}
}
}
```
The field you need depends on the package manager you're using, but we recommend adding a field for the common `yarn`, `npm`, and `pnpm` to maximize compatibility.
## Development
To develop the MongoDB package, you'll need to follow these instructions:
### Install dependencies
```bash
yarn install
```
### Build the package
```bash
yarn build
```
Or from the repo root:
```bash
yarn build --filter=@langchain/mongodb
```
### Run tests
Test files should live within a `tests/` file in the `src/` folder. Unit tests should end in `.test.ts` and integration tests should
end in `.int.test.ts`:
```bash
$ yarn test
$ yarn test:int
```
### Lint & Format
Run the linter & formatter to ensure your code is up to standard:
```bash
yarn lint && yarn format
```
### Adding new entrypoints
If you add a new file to be exported, either import & re-export from `src/index.ts`, or add it to the `entrypoints` field in the `config` variable located inside `langchain.config.js` and run `yarn build` to generate the new entrypoint.
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/.release-it.json | {
"github": {
"release": true,
"autoGenerate": true,
"tokenRef": "GITHUB_TOKEN_RELEASE"
},
"npm": {
"versionArgs": [
"--workspaces-update=false"
]
}
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/.eslintrc.cjs | module.exports = {
extends: [
"airbnb-base",
"eslint:recommended",
"prettier",
"plugin:@typescript-eslint/recommended",
],
parserOptions: {
ecmaVersion: 12,
parser: "@typescript-eslint/parser",
project: "./tsconfig.json",
sourceType: "module",
},
plugins: ["@typescript-eslint", "no-instanceof"],
ignorePatterns: [
".eslintrc.cjs",
"scripts",
"node_modules",
"dist",
"dist-cjs",
"*.js",
"*.cjs",
"*.d.ts",
],
rules: {
"no-process-env": 2,
"no-instanceof/no-instanceof": 2,
"@typescript-eslint/explicit-module-boundary-types": 0,
"@typescript-eslint/no-empty-function": 0,
"@typescript-eslint/no-shadow": 0,
"@typescript-eslint/no-empty-interface": 0,
"@typescript-eslint/no-use-before-define": ["error", "nofunc"],
"@typescript-eslint/no-unused-vars": ["warn", { args: "none" }],
"@typescript-eslint/no-floating-promises": "error",
"@typescript-eslint/no-misused-promises": "error",
camelcase: 0,
"class-methods-use-this": 0,
"import/extensions": [2, "ignorePackages"],
"import/no-extraneous-dependencies": [
"error",
{ devDependencies: ["**/*.test.ts"] },
],
"import/no-unresolved": 0,
"import/prefer-default-export": 0,
"keyword-spacing": "error",
"max-classes-per-file": 0,
"max-len": 0,
"no-await-in-loop": 0,
"no-bitwise": 0,
"no-console": 0,
"no-restricted-syntax": 0,
"no-shadow": 0,
"no-continue": 0,
"no-void": 0,
"no-underscore-dangle": 0,
"no-use-before-define": 0,
"no-useless-constructor": 0,
"no-return-await": 0,
"consistent-return": 0,
"no-else-return": 0,
"func-names": 0,
"no-lonely-if": 0,
"prefer-rest-params": 0,
"new-cap": ["error", { properties: false, capIsNew: false }],
},
overrides: [
{
files: ['**/*.test.ts'],
rules: {
'@typescript-eslint/no-unused-vars': 'off'
}
}
]
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/langchain.config.js | import { resolve, dirname } from "node:path";
import { fileURLToPath } from "node:url";
/**
* @param {string} relativePath
* @returns {string}
*/
function abs(relativePath) {
return resolve(dirname(fileURLToPath(import.meta.url)), relativePath);
}
export const config = {
internals: [/node\:/, /@langchain\/core\//],
entrypoints: {
index: "index",
},
requiresOptionalDependency: [],
tsConfigPath: resolve("./tsconfig.json"),
cjsSource: "./dist-cjs",
cjsDestination: "./dist",
abs,
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/package.json | {
"name": "@langchain/mongodb",
"version": "0.1.0",
"description": "Sample integration for LangChain.js",
"type": "module",
"engines": {
"node": ">=18"
},
"main": "./index.js",
"types": "./index.d.ts",
"repository": {
"type": "git",
"url": "git@github.com:langchain-ai/langchainjs.git"
},
"homepage": "https://github.com/langchain-ai/langchainjs/tree/main/libs/langchain-mongodb/",
"scripts": {
"build": "yarn turbo:command build:internal --filter=@langchain/mongodb",
"build:internal": "yarn lc_build --create-entrypoints --pre --tree-shaking",
"lint:eslint": "NODE_OPTIONS=--max-old-space-size=4096 eslint --cache --ext .ts,.js src/",
"lint:dpdm": "dpdm --exit-code circular:1 --no-warning --no-tree src/*.ts src/**/*.ts",
"lint": "yarn lint:eslint && yarn lint:dpdm",
"lint:fix": "yarn lint:eslint --fix && yarn lint:dpdm",
"clean": "rm -rf .turbo dist/",
"prepack": "yarn build",
"test": "NODE_OPTIONS=--experimental-vm-modules jest --testPathIgnorePatterns=\\.int\\.test.ts --testTimeout 30000 --maxWorkers=50%",
"test:watch": "NODE_OPTIONS=--experimental-vm-modules jest --watch --testPathIgnorePatterns=\\.int\\.test.ts",
"test:single": "NODE_OPTIONS=--experimental-vm-modules yarn run jest --config jest.config.cjs --testTimeout 100000",
"test:int": "NODE_OPTIONS=--experimental-vm-modules jest --testPathPattern=\\.int\\.test.ts --testTimeout 100000 --maxWorkers=50%",
"format": "prettier --config .prettierrc --write \"src\"",
"format:check": "prettier --config .prettierrc --check \"src\""
},
"author": "LangChain",
"license": "MIT",
"dependencies": {
"mongodb": "^6.3.0"
},
"peerDependencies": {
"@langchain/core": ">=0.2.21 <0.4.0"
},
"devDependencies": {
"@jest/globals": "^29.5.0",
"@langchain/core": "workspace:*",
"@langchain/openai": "workspace:*",
"@langchain/scripts": ">=0.1.0 <0.2.0",
"@swc/core": "^1.3.90",
"@swc/jest": "^0.2.29",
"@tsconfig/recommended": "^1.0.3",
"@types/uuid": "^9",
"@typescript-eslint/eslint-plugin": "^6.12.0",
"@typescript-eslint/parser": "^6.12.0",
"dotenv": "^16.3.1",
"dpdm": "^3.12.0",
"eslint": "^8.33.0",
"eslint-config-airbnb-base": "^15.0.0",
"eslint-config-prettier": "^8.6.0",
"eslint-plugin-import": "^2.27.5",
"eslint-plugin-no-instanceof": "^1.0.1",
"eslint-plugin-prettier": "^4.2.1",
"jest": "^29.5.0",
"jest-environment-node": "^29.6.4",
"prettier": "^2.8.3",
"release-it": "^17.6.0",
"rollup": "^4.5.2",
"ts-jest": "^29.1.0",
"typescript": "<5.2.0",
"uuid": "^10.0.0"
},
"publishConfig": {
"access": "public"
},
"exports": {
".": {
"types": {
"import": "./index.d.ts",
"require": "./index.d.cts",
"default": "./index.d.ts"
},
"import": "./index.js",
"require": "./index.cjs"
},
"./package.json": "./package.json"
},
"files": [
"dist/",
"index.cjs",
"index.js",
"index.d.ts",
"index.d.cts"
]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/tsconfig.cjs.json | {
"extends": "./tsconfig.json",
"compilerOptions": {
"module": "commonjs",
"declaration": false
},
"exclude": ["node_modules", "dist", "docs", "**/tests"]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/turbo.json | {
"extends": ["//"],
"pipeline": {
"build": {
"outputs": ["**/dist/**"]
},
"build:internal": {
"dependsOn": ["^build:internal"]
}
}
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-mongodb/.prettierrc | {
"$schema": "https://json.schemastore.org/prettierrc",
"printWidth": 80,
"tabWidth": 2,
"useTabs": false,
"semi": true,
"singleQuote": false,
"quoteProps": "as-needed",
"jsxSingleQuote": false,
"trailingComma": "es5",
"bracketSpacing": true,
"arrowParens": "always",
"requirePragma": false,
"insertPragma": false,
"proseWrap": "preserve",
"htmlWhitespaceSensitivity": "css",
"vueIndentScriptAndStyle": false,
"endOfLine": "lf"
}
|
0 | lc_public_repos/langchainjs/libs/langchain-mongodb | lc_public_repos/langchainjs/libs/langchain-mongodb/src/storage.ts | import { BaseStore } from "@langchain/core/stores";
import { Collection, Document as MongoDocument } from "mongodb";
/**
* Type definition for the input parameters required to initialize an
* instance of the MongoDBStoreInput class.
*/
export interface MongoDBStoreInput {
collection: Collection<MongoDocument>;
/**
* The amount of keys to retrieve per batch when yielding keys.
* @default 1000
*/
yieldKeysScanBatchSize?: number;
/**
* The namespace to use for the keys in the database.
*/
namespace?: string;
/**
* The primary key to use for the database.
* @default "_id"
*/
primaryKey?: string;
}
/**
* Class that extends the BaseStore class to interact with a MongoDB
* database. It provides methods for getting, setting, and deleting data,
* as well as yielding keys from the database.
* @example
* ```typescript
* const client = new MongoClient(process.env.MONGODB_ATLAS_URI);
* const collection = client.db("dbName").collection("collectionName");
* const store = new MongoDBStore({
* collection,
* });
*
* const docs = [
* [uuidv4(), "Dogs are tough."],
* [uuidv4(), "Cats are tough."],
* ];
* const encoder = new TextEncoder();
* const docsAsKVPairs: Array<[string, Uint8Array]> = docs.map(
* (doc) => [doc[0], encoder.encode(doc[1])]
* );
* await store.mset(docsAsKVPairs);
* ```
*/
export class MongoDBStore extends BaseStore<string, Uint8Array> {
lc_namespace = ["langchain", "storage", "mongodb"];
collection: Collection<MongoDocument>;
protected namespace?: string;
protected yieldKeysScanBatchSize = 1000;
primaryKey = "_id";
constructor(fields: MongoDBStoreInput) {
super(fields);
this.collection = fields.collection;
this.primaryKey = fields.primaryKey ?? this.primaryKey;
this.yieldKeysScanBatchSize =
fields.yieldKeysScanBatchSize ?? this.yieldKeysScanBatchSize;
this.namespace = fields.namespace;
}
_getPrefixedKey(key: string) {
if (this.namespace) {
const delimiter = "/";
return `${this.namespace}${delimiter}${key}`;
}
return key;
}
_getDeprefixedKey(key: string) {
if (this.namespace) {
const delimiter = "/";
return key.slice(this.namespace.length + delimiter.length);
}
return key;
}
/**
* Gets multiple keys from the MongoDB database.
* @param keys Array of keys to be retrieved.
* @returns An array of retrieved values.
*/
async mget(keys: string[]) {
const prefixedKeys = keys.map(this._getPrefixedKey.bind(this));
const retrievedValues = await this.collection
.find({
[this.primaryKey]: { $in: prefixedKeys },
})
.toArray();
const encoder = new TextEncoder();
const valueMap = new Map(
retrievedValues.map((item) => [item[this.primaryKey], item])
);
return prefixedKeys.map((prefixedKey) => {
const value = valueMap.get(prefixedKey);
if (!value) {
return undefined;
}
if (!("value" in value)) {
return undefined;
} else if (typeof value.value === "object") {
return encoder.encode(JSON.stringify(value.value));
} else if (typeof value.value === "string") {
return encoder.encode(value.value);
} else {
throw new Error("Unexpected value type");
}
});
}
/**
* Sets multiple keys in the MongoDB database.
* @param keyValuePairs Array of key-value pairs to be set.
* @returns Promise that resolves when all keys have been set.
*/
async mset(keyValuePairs: [string, Uint8Array][]): Promise<void> {
const decoder = new TextDecoder();
const updates = keyValuePairs.map(([key, value]) => {
const decodedValue = decoder.decode(value);
return [
{ [this.primaryKey]: this._getPrefixedKey(key) },
{
$set: {
[this.primaryKey]: this._getPrefixedKey(key),
...{ value: decodedValue },
},
},
];
});
await this.collection.bulkWrite(
updates.map(([filter, update]) => ({
updateOne: {
filter,
update,
upsert: true,
},
}))
);
}
/**
* Deletes multiple keys from the MongoDB database.
* @param keys Array of keys to be deleted.
* @returns Promise that resolves when all keys have been deleted.
*/
async mdelete(keys: string[]): Promise<void> {
const allKeysWithPrefix = keys.map(this._getPrefixedKey.bind(this));
await this.collection.deleteMany({
[this.primaryKey]: { $in: allKeysWithPrefix },
});
}
/**
* Yields keys from the MongoDB database.
* @param prefix Optional prefix to filter the keys. A wildcard (*) is always appended to the end.
* @returns An AsyncGenerator that yields keys from the MongoDB database.
*/
async *yieldKeys(prefix?: string): AsyncGenerator<string> {
let regexPattern;
if (prefix) {
// Convert wildcard (*) to regex equivalent (.*)
// Escape special regex characters in prefix to ensure they are treated as literals
const escapedPrefix = prefix.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
const regexPrefix = escapedPrefix.endsWith("*")
? escapedPrefix.slice(0, -1)
: escapedPrefix;
regexPattern = `^${this._getPrefixedKey(regexPrefix)}.*`;
} else {
regexPattern = `^${this._getPrefixedKey(".*")}`;
}
let totalDocsYielded = 0;
let cursor = await this.collection
.find(
{
[this.primaryKey]: { $regex: regexPattern },
},
{
batchSize: this.yieldKeysScanBatchSize,
}
)
.toArray();
for (const key of cursor) {
yield this._getDeprefixedKey(key[this.primaryKey]);
}
totalDocsYielded += cursor.length;
while (cursor.length !== 0) {
cursor = await this.collection
.find(
{
[this.primaryKey]: { $regex: regexPattern },
},
{
batchSize: this.yieldKeysScanBatchSize,
skip: totalDocsYielded,
}
)
.toArray();
for (const key of cursor) {
yield this._getDeprefixedKey(key[this.primaryKey]);
}
totalDocsYielded += cursor.length;
}
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-mongodb | lc_public_repos/langchainjs/libs/langchain-mongodb/src/vectorstores.ts | import { type Collection, type Document as MongoDBDocument } from "mongodb";
import {
MaxMarginalRelevanceSearchOptions,
VectorStore,
} from "@langchain/core/vectorstores";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { chunkArray } from "@langchain/core/utils/chunk_array";
import { Document } from "@langchain/core/documents";
import { maximalMarginalRelevance } from "@langchain/core/utils/math";
import {
AsyncCaller,
AsyncCallerParams,
} from "@langchain/core/utils/async_caller";
/**
* Type that defines the arguments required to initialize the
* MongoDBAtlasVectorSearch class. It includes the MongoDB collection,
* index name, text key, embedding key, primary key, and overwrite flag.
*
* @param collection MongoDB collection to store the vectors.
* @param indexName A Collections Index Name.
* @param textKey Corresponds to the plaintext of 'pageContent'.
* @param embeddingKey Key to store the embedding under.
* @param primaryKey The Key to use for upserting documents.
*/
export interface MongoDBAtlasVectorSearchLibArgs extends AsyncCallerParams {
readonly collection: Collection<MongoDBDocument>;
readonly indexName?: string;
readonly textKey?: string;
readonly embeddingKey?: string;
readonly primaryKey?: string;
}
/**
* Type that defines the filter used in the
* similaritySearchVectorWithScore and maxMarginalRelevanceSearch methods.
* It includes pre-filter, post-filter pipeline, and a flag to include
* embeddings.
*/
type MongoDBAtlasFilter = {
preFilter?: MongoDBDocument;
postFilterPipeline?: MongoDBDocument[];
includeEmbeddings?: boolean;
} & MongoDBDocument;
/**
* Class that is a wrapper around MongoDB Atlas Vector Search. It is used
* to store embeddings in MongoDB documents, create a vector search index,
* and perform K-Nearest Neighbors (KNN) search with an approximate
* nearest neighbor algorithm.
*/
export class MongoDBAtlasVectorSearch extends VectorStore {
declare FilterType: MongoDBAtlasFilter;
private readonly collection: Collection<MongoDBDocument>;
private readonly indexName: string;
private readonly textKey: string;
private readonly embeddingKey: string;
private readonly primaryKey: string;
private caller: AsyncCaller;
_vectorstoreType(): string {
return "mongodb_atlas";
}
constructor(
embeddings: EmbeddingsInterface,
args: MongoDBAtlasVectorSearchLibArgs
) {
super(embeddings, args);
this.collection = args.collection;
this.indexName = args.indexName ?? "default";
this.textKey = args.textKey ?? "text";
this.embeddingKey = args.embeddingKey ?? "embedding";
this.primaryKey = args.primaryKey ?? "_id";
this.caller = new AsyncCaller(args);
}
/**
* Method to add vectors and their corresponding documents to the MongoDB
* collection.
* @param vectors Vectors to be added.
* @param documents Corresponding documents to be added.
* @returns Promise that resolves when the vectors and documents have been added.
*/
async addVectors(
vectors: number[][],
documents: Document[],
options?: { ids?: string[] }
) {
const docs = vectors.map((embedding, idx) => ({
[this.textKey]: documents[idx].pageContent,
[this.embeddingKey]: embedding,
...documents[idx].metadata,
}));
if (options?.ids === undefined) {
await this.collection.insertMany(docs);
} else {
if (options.ids.length !== vectors.length) {
throw new Error(
`If provided, "options.ids" must be an array with the same length as "vectors".`
);
}
const { ids } = options;
for (let i = 0; i < docs.length; i += 1) {
await this.caller.call(async () => {
await this.collection.updateOne(
{ [this.primaryKey]: ids[i] },
{ $set: { [this.primaryKey]: ids[i], ...docs[i] } },
{ upsert: true }
);
});
}
}
return options?.ids ?? docs.map((doc) => doc[this.primaryKey]);
}
/**
* Method to add documents to the MongoDB collection. It first converts
* the documents to vectors using the embeddings and then calls the
* addVectors method.
* @param documents Documents to be added.
* @returns Promise that resolves when the documents have been added.
*/
async addDocuments(documents: Document[], options?: { ids?: string[] }) {
const texts = documents.map(({ pageContent }) => pageContent);
return this.addVectors(
await this.embeddings.embedDocuments(texts),
documents,
options
);
}
/**
* Method that performs a similarity search on the vectors stored in the
* MongoDB collection. It returns a list of documents and their
* corresponding similarity scores.
* @param query Query vector for the similarity search.
* @param k Number of nearest neighbors to return.
* @param filter Optional filter to be applied.
* @returns Promise that resolves to a list of documents and their corresponding similarity scores.
*/
async similaritySearchVectorWithScore(
query: number[],
k: number,
filter?: MongoDBAtlasFilter
): Promise<[Document, number][]> {
const postFilterPipeline = filter?.postFilterPipeline ?? [];
const preFilter: MongoDBDocument | undefined =
filter?.preFilter ||
filter?.postFilterPipeline ||
filter?.includeEmbeddings
? filter.preFilter
: filter;
const removeEmbeddingsPipeline = !filter?.includeEmbeddings
? [
{
$project: {
[this.embeddingKey]: 0,
},
},
]
: [];
const pipeline: MongoDBDocument[] = [
{
$vectorSearch: {
queryVector: MongoDBAtlasVectorSearch.fixArrayPrecision(query),
index: this.indexName,
path: this.embeddingKey,
limit: k,
numCandidates: 10 * k,
...(preFilter && { filter: preFilter }),
},
},
{
$set: {
score: { $meta: "vectorSearchScore" },
},
},
...removeEmbeddingsPipeline,
...postFilterPipeline,
];
const results = this.collection
.aggregate(pipeline)
.map<[Document, number]>((result) => {
const { score, [this.textKey]: text, ...metadata } = result;
return [new Document({ pageContent: text, metadata }), score];
});
return results.toArray();
}
/**
* Return documents selected using the maximal marginal relevance.
* Maximal marginal relevance optimizes for similarity to the query AND diversity
* among selected documents.
*
* @param {string} query - Text to look up documents similar to.
* @param {number} options.k - Number of documents to return.
* @param {number} options.fetchK=20- Number of documents to fetch before passing to the MMR algorithm.
* @param {number} options.lambda=0.5 - Number between 0 and 1 that determines the degree of diversity among the results,
* where 0 corresponds to maximum diversity and 1 to minimum diversity.
* @param {MongoDBAtlasFilter} options.filter - Optional Atlas Search operator to pre-filter on document fields
* or post-filter following the knnBeta search.
*
* @returns {Promise<Document[]>} - List of documents selected by maximal marginal relevance.
*/
async maxMarginalRelevanceSearch(
query: string,
options: MaxMarginalRelevanceSearchOptions<this["FilterType"]>
): Promise<Document[]> {
const { k, fetchK = 20, lambda = 0.5, filter } = options;
const queryEmbedding = await this.embeddings.embedQuery(query);
// preserve the original value of includeEmbeddings
const includeEmbeddingsFlag = options.filter?.includeEmbeddings || false;
// update filter to include embeddings, as they will be used in MMR
const includeEmbeddingsFilter = {
...filter,
includeEmbeddings: true,
};
const resultDocs = await this.similaritySearchVectorWithScore(
MongoDBAtlasVectorSearch.fixArrayPrecision(queryEmbedding),
fetchK,
includeEmbeddingsFilter
);
const embeddingList = resultDocs.map(
(doc) => doc[0].metadata[this.embeddingKey]
);
const mmrIndexes = maximalMarginalRelevance(
queryEmbedding,
embeddingList,
lambda,
k
);
return mmrIndexes.map((idx) => {
const doc = resultDocs[idx][0];
// remove embeddings if they were not requested originally
if (!includeEmbeddingsFlag) {
delete doc.metadata[this.embeddingKey];
}
return doc;
});
}
/**
* Delete documents from the collection
* @param ids - An array of document IDs to be deleted from the collection.
*
* @returns - A promise that resolves when all documents deleted
*/
// eslint-disable-next-line @typescript-eslint/no-explicit-any
async delete(params: { ids: any[] }): Promise<void> {
const CHUNK_SIZE = 50;
const chunkIds: any[][] = chunkArray(params.ids, CHUNK_SIZE); // eslint-disable-line @typescript-eslint/no-explicit-any
for (const chunk of chunkIds)
await this.collection.deleteMany({ _id: { $in: chunk } });
}
/**
* Static method to create an instance of MongoDBAtlasVectorSearch from a
* list of texts. It first converts the texts to vectors and then adds
* them to the MongoDB collection.
* @param texts List of texts to be converted to vectors.
* @param metadatas Metadata for the texts.
* @param embeddings Embeddings to be used for conversion.
* @param dbConfig Database configuration for MongoDB Atlas.
* @returns Promise that resolves to a new instance of MongoDBAtlasVectorSearch.
*/
static async fromTexts(
texts: string[],
metadatas: object[] | object,
embeddings: EmbeddingsInterface,
dbConfig: MongoDBAtlasVectorSearchLibArgs & { ids?: string[] }
): Promise<MongoDBAtlasVectorSearch> {
const docs: Document[] = [];
for (let i = 0; i < texts.length; i += 1) {
const metadata = Array.isArray(metadatas) ? metadatas[i] : metadatas;
const newDoc = new Document({
pageContent: texts[i],
metadata,
});
docs.push(newDoc);
}
return MongoDBAtlasVectorSearch.fromDocuments(docs, embeddings, dbConfig);
}
/**
* Static method to create an instance of MongoDBAtlasVectorSearch from a
* list of documents. It first converts the documents to vectors and then
* adds them to the MongoDB collection.
* @param docs List of documents to be converted to vectors.
* @param embeddings Embeddings to be used for conversion.
* @param dbConfig Database configuration for MongoDB Atlas.
* @returns Promise that resolves to a new instance of MongoDBAtlasVectorSearch.
*/
static async fromDocuments(
docs: Document[],
embeddings: EmbeddingsInterface,
dbConfig: MongoDBAtlasVectorSearchLibArgs & { ids?: string[] }
): Promise<MongoDBAtlasVectorSearch> {
const instance = new this(embeddings, dbConfig);
await instance.addDocuments(docs, { ids: dbConfig.ids });
return instance;
}
/**
* Static method to fix the precision of the array that ensures that
* every number in this array is always float when casted to other types.
* This is needed since MongoDB Atlas Vector Search does not cast integer
* inside vector search to float automatically.
* This method shall introduce a hint of error but should be safe to use
* since introduced error is very small, only applies to integer numbers
* returned by embeddings, and most embeddings shall not have precision
* as high as 15 decimal places.
* @param array Array of number to be fixed.
* @returns
*/
static fixArrayPrecision(array: number[]) {
return array.map((value) => {
if (Number.isInteger(value)) {
return value + 0.000000000000001;
}
return value;
});
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-mongodb | lc_public_repos/langchainjs/libs/langchain-mongodb/src/chat_history.ts | import { Collection, Document as MongoDBDocument } from "mongodb";
import { BaseListChatMessageHistory } from "@langchain/core/chat_history";
import {
BaseMessage,
mapChatMessagesToStoredMessages,
mapStoredMessagesToChatMessages,
} from "@langchain/core/messages";
export interface MongoDBChatMessageHistoryInput {
collection: Collection<MongoDBDocument>;
sessionId: string;
}
/**
* @example
* ```typescript
* const chatHistory = new MongoDBChatMessageHistory({
* collection: myCollection,
* sessionId: 'unique-session-id',
* });
* const messages = await chatHistory.getMessages();
* await chatHistory.clear();
* ```
*/
export class MongoDBChatMessageHistory extends BaseListChatMessageHistory {
lc_namespace = ["langchain", "stores", "message", "mongodb"];
private collection: Collection<MongoDBDocument>;
private sessionId: string;
private idKey = "sessionId";
constructor({ collection, sessionId }: MongoDBChatMessageHistoryInput) {
super();
this.collection = collection;
this.sessionId = sessionId;
}
async getMessages(): Promise<BaseMessage[]> {
const document = await this.collection.findOne({
[this.idKey]: this.sessionId,
});
const messages = document?.messages || [];
return mapStoredMessagesToChatMessages(messages);
}
async addMessage(message: BaseMessage): Promise<void> {
const messages = mapChatMessagesToStoredMessages([message]);
await this.collection.updateOne(
{ [this.idKey]: this.sessionId },
{
$push: { messages: { $each: messages } },
},
{ upsert: true }
);
}
async clear(): Promise<void> {
await this.collection.deleteOne({ [this.idKey]: this.sessionId });
}
}
|
0 | lc_public_repos/langchainjs/libs/langchain-mongodb | lc_public_repos/langchainjs/libs/langchain-mongodb/src/index.ts | export * from "./chat_history.js";
export * from "./vectorstores.js";
export * from "./storage.js";
|
0 | lc_public_repos/langchainjs/libs/langchain-mongodb/src | lc_public_repos/langchainjs/libs/langchain-mongodb/src/tests/storage.int.test.ts | /* eslint-disable no-process-env */
import { v4 as uuidv4 } from "uuid";
import { MongoClient, ServerApiVersion } from "mongodb";
import { MongoDBStore } from "../storage.js";
test("MongoDBStore can set and retrieve", async () => {
expect(process.env.MONGODB_ATLAS_URI).toBeDefined();
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!, {
serverApi: {
version: ServerApiVersion.v1,
strict: true,
deprecationErrors: true,
},
});
try {
await client.connect();
} catch (e) {
// console.error("Failed to connect");
throw Error(e as string);
}
const namespace = "langchain.test";
const [dbName, collectionName] = namespace.split(".");
const collection = client.db(dbName).collection(collectionName);
const store = new MongoDBStore({
collection,
});
expect(store).toBeDefined();
try {
const docs = [
[uuidv4(), "Dogs are tough."],
[uuidv4(), "Cats are tough."],
];
const encoder = new TextEncoder();
const decoder = new TextDecoder();
const docsAsKVPairs: Array<[string, Uint8Array]> = docs.map((doc) => [
doc[0],
encoder.encode(doc[1]),
]);
await store.mset(docsAsKVPairs);
const keysToRetrieve = docs.map((doc) => doc[0]);
keysToRetrieve.unshift("nonexistent_key_0");
keysToRetrieve.push("nonexistent_key_3");
const retrievedDocs = await store.mget(keysToRetrieve);
expect(retrievedDocs.length).toBe(keysToRetrieve.length);
// Check that the first item is undefined (nonexistent_key_0)
expect(retrievedDocs[0]).toBeUndefined();
// Check that the second and third items match the original docs
expect(decoder.decode(retrievedDocs[1])).toBe(docs[0][1]);
expect(decoder.decode(retrievedDocs[2])).toBe(docs[1][1]);
// Check that the last item is undefined (nonexistent_key_1)
expect(retrievedDocs[retrievedDocs.length - 1]).toBeUndefined();
} finally {
const keys = store.yieldKeys();
const yieldedKeys = [];
for await (const key of keys) {
yieldedKeys.push(key);
}
await store.mdelete(yieldedKeys);
await client.close();
}
});
test("MongoDBStore can delete", async () => {
expect(process.env.MONGODB_ATLAS_URI).toBeDefined();
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!, {
serverApi: {
version: ServerApiVersion.v1,
strict: true,
deprecationErrors: true,
},
});
const namespace = "langchain.test";
const [dbName, collectionName] = namespace.split(".");
const collection = client.db(dbName).collection(collectionName);
const store = new MongoDBStore({
collection,
});
try {
const docs = [
[uuidv4(), "Dogs are tough."],
[uuidv4(), "Cats are tough."],
];
const encoder = new TextEncoder();
const docsAsKVPairs: Array<[string, Uint8Array]> = docs.map((doc) => [
doc[0],
encoder.encode(doc[1]),
]);
await store.mset(docsAsKVPairs);
const docIds = docs.map((doc) => doc[0]);
await store.mdelete(docIds);
const retrievedDocs = await store.mget(docs.map((doc) => doc[0]));
expect(retrievedDocs.length).toBe(2);
const everyValueUndefined = retrievedDocs.every((v) => v === undefined);
expect(everyValueUndefined).toBe(true);
} finally {
const keys = store.yieldKeys();
const yieldedKeys = [];
for await (const key of keys) {
yieldedKeys.push(key);
}
await store.mdelete(yieldedKeys);
await client.close();
}
});
test("MongoDBStore can yield keys", async () => {
expect(process.env.MONGODB_ATLAS_URI).toBeDefined();
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!, {
serverApi: {
version: ServerApiVersion.v1,
strict: true,
deprecationErrors: true,
},
});
const namespace = "langchain.test";
const [dbName, collectionName] = namespace.split(".");
const collection = client.db(dbName).collection(collectionName);
try {
const store = new MongoDBStore({
collection,
});
const docs = [
[uuidv4(), "Dogs are tough."],
[uuidv4(), "Cats are tough."],
];
const encoder = new TextEncoder();
const docsAsKVPairs: Array<[string, Uint8Array]> = docs.map((doc) => [
doc[0],
encoder.encode(doc[1]),
]);
await store.mset(docsAsKVPairs);
const keys = store.yieldKeys();
const yieldedKeys = [];
for await (const key of keys) {
yieldedKeys.push(key);
}
expect(yieldedKeys.sort()).toEqual(docs.map((doc) => doc[0]).sort());
// delete
await store.mdelete(yieldedKeys);
} finally {
await client.close();
}
});
test("MongoDBStore can yield keys with prefix", async () => {
expect(process.env.MONGODB_ATLAS_URI).toBeDefined();
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!, {
serverApi: {
version: ServerApiVersion.v1,
strict: true,
deprecationErrors: true,
},
});
const namespace = "langchain.test";
const [dbName, collectionName] = namespace.split(".");
const collection = client.db(dbName).collection(collectionName);
const store = new MongoDBStore({
collection,
});
try {
const docs = [
["dis_one", "Dogs are tough."],
["not_dis_one", "Cats are tough."],
];
const encoder = new TextEncoder();
const docsAsKVPairs: Array<[string, Uint8Array]> = docs.map((doc) => [
doc[0],
encoder.encode(doc[1]),
]);
await store.mset(docsAsKVPairs);
const keys = store.yieldKeys("dis_one");
const yieldedKeys = [];
for await (const key of keys) {
yieldedKeys.push(key);
}
expect(yieldedKeys).toEqual(["dis_one"]);
} finally {
const keys = store.yieldKeys();
const yieldedKeys = [];
for await (const key of keys) {
yieldedKeys.push(key);
}
await store.mdelete(yieldedKeys);
await client.close();
}
});
|
0 | lc_public_repos/langchainjs/libs/langchain-mongodb/src | lc_public_repos/langchainjs/libs/langchain-mongodb/src/tests/vectorstores.int.test.ts | /* eslint-disable no-process-env */
/* eslint-disable no-promise-executor-return */
import { test, expect } from "@jest/globals";
import { MongoClient } from "mongodb";
import { setTimeout } from "timers/promises";
import { OpenAIEmbeddings } from "@langchain/openai";
import { Document } from "@langchain/core/documents";
import { MongoDBAtlasVectorSearch } from "../vectorstores.js";
/**
* The following json can be used to create an index in atlas for Cohere embeddings.
* Use "langchain.test" for the namespace and "default" for the index name.
{
"mappings": {
"fields": {
"e": { "type": "number" },
"embedding": {
"dimensions": 1536,
"similarity": "euclidean",
"type": "knnVector"
}
}
}
}
*/
test("MongoDBAtlasVectorSearch with external ids", async () => {
expect(process.env.MONGODB_ATLAS_URI).toBeDefined();
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!);
try {
const namespace = "langchain.test";
const [dbName, collectionName] = namespace.split(".");
const collection = client.db(dbName).collection(collectionName);
const vectorStore = new MongoDBAtlasVectorSearch(new OpenAIEmbeddings(), {
collection,
});
expect(vectorStore).toBeDefined();
// check if the database is empty
await collection.deleteMany({});
await vectorStore.addDocuments([
{
pageContent: "Dogs are tough.",
metadata: { a: 1, created_at: new Date().toISOString() },
},
{
pageContent: "Cats have fluff.",
metadata: { b: 1, created_at: new Date().toISOString() },
},
{
pageContent: "What is a sandwich?",
metadata: { c: 1, created_at: new Date().toISOString() },
},
{
pageContent: "That fence is purple.",
metadata: { d: 1, e: 2, created_at: new Date().toISOString() },
},
]);
// we sleep 5 seconds to make sure the index in atlas has replicated the new documents
await setTimeout(5000);
const results: Document[] = await vectorStore.similaritySearch(
"Sandwich",
1
);
expect(results.length).toEqual(1);
expect(results).toMatchObject([
{ pageContent: "What is a sandwich?", metadata: { c: 1 } },
]);
// // we can pre filter the search
// const preFilter = {
// e: { $lte: 1 },
// };
// const filteredResults = await vectorStore.similaritySearch(
// "That fence is purple",
// 1,
// preFilter
// );
// expect(filteredResults).toEqual([]);
// const retriever = vectorStore.asRetriever({
// filter: {
// preFilter,
// },
// });
// const docs = await retriever.getRelevantDocuments("That fence is purple");
// expect(docs).toEqual([]);
} finally {
await client.close();
}
});
test("MongoDBAtlasVectorSearch with Maximal Marginal Relevance", async () => {
expect(process.env.MONGODB_ATLAS_URI).toBeDefined();
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!);
try {
const namespace = "langchain.test";
const [dbName, collectionName] = namespace.split(".");
const collection = client.db(dbName).collection(collectionName);
await collection.deleteMany({});
const texts = ["foo", "foo", "foy"];
const vectorStore = await MongoDBAtlasVectorSearch.fromTexts(
texts,
{},
new OpenAIEmbeddings(),
{ collection, indexName: "default" }
);
// we sleep 5 seconds to make sure the index in atlas has replicated the new documents
await setTimeout(5000);
const output = await vectorStore.maxMarginalRelevanceSearch("foo", {
k: 10,
fetchK: 20,
lambda: 0.1,
});
expect(output).toHaveLength(texts.length);
const actual = output.map((doc) => doc.pageContent);
const expected = ["foo", "foy", "foo"];
expect(actual).toEqual(expected);
const standardRetriever = await vectorStore.asRetriever();
const standardRetrieverOutput =
await standardRetriever.getRelevantDocuments("foo");
expect(output).toHaveLength(texts.length);
const standardRetrieverActual = standardRetrieverOutput.map(
(doc) => doc.pageContent
);
const standardRetrieverExpected = ["foo", "foo", "foy"];
expect(standardRetrieverActual).toEqual(standardRetrieverExpected);
const retriever = await vectorStore.asRetriever({
searchType: "mmr",
searchKwargs: {
fetchK: 20,
lambda: 0.1,
},
});
const retrieverOutput = await retriever.getRelevantDocuments("foo");
expect(output).toHaveLength(texts.length);
const retrieverActual = retrieverOutput.map((doc) => doc.pageContent);
const retrieverExpected = ["foo", "foy", "foo"];
expect(retrieverActual).toEqual(retrieverExpected);
const similarity = await vectorStore.similaritySearchWithScore("foo", 1);
expect(similarity.length).toBe(1);
} finally {
await client.close();
}
});
test("MongoDBAtlasVectorSearch upsert", async () => {
expect(process.env.MONGODB_ATLAS_URI).toBeDefined();
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!);
try {
const namespace = "langchain.test";
const [dbName, collectionName] = namespace.split(".");
const collection = client.db(dbName).collection(collectionName);
const vectorStore = new MongoDBAtlasVectorSearch(new OpenAIEmbeddings(), {
collection,
});
expect(vectorStore).toBeDefined();
// check if the database is empty
await collection.deleteMany({});
const ids = await vectorStore.addDocuments([
{ pageContent: "Dogs are tough.", metadata: { a: 1 } },
{ pageContent: "Cats have fluff.", metadata: { b: 1 } },
{ pageContent: "What is a sandwich?", metadata: { c: 1 } },
{ pageContent: "That fence is purple.", metadata: { d: 1, e: 2 } },
]);
// we sleep 5 seconds to make sure the index in atlas has replicated the new documents
await setTimeout(5000);
const results: Document[] = await vectorStore.similaritySearch(
"Sandwich",
1
);
expect(results.length).toEqual(1);
expect(results).toMatchObject([
{ pageContent: "What is a sandwich?", metadata: { c: 1 } },
]);
await vectorStore.addDocuments(
[{ pageContent: "upserted", metadata: {} }],
{ ids: [ids[2]] }
);
// we sleep 5 seconds to make sure the index in atlas has replicated the new documents
await setTimeout(5000);
const results2: Document[] = await vectorStore.similaritySearch(
"Sandwich",
1
);
// console.log(results2);
expect(results2.length).toEqual(1);
expect(results2[0].pageContent).not.toContain("sandwich");
} finally {
await client.close();
}
});
|
0 | lc_public_repos/langchainjs/libs/langchain-mongodb/src | lc_public_repos/langchainjs/libs/langchain-mongodb/src/tests/chat_history.int.test.ts | /* eslint-disable no-process-env */
import { MongoClient, ObjectId } from "mongodb";
import { AIMessage, HumanMessage } from "@langchain/core/messages";
import { MongoDBChatMessageHistory } from "../chat_history.js";
afterAll(async () => {
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!);
await client.connect();
await client.db("langchain").dropDatabase();
await client.close();
});
test("Test MongoDB history store", async () => {
expect(process.env.MONGODB_ATLAS_URI).toBeDefined();
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!);
await client.connect();
const collection = client.db("langchain").collection("memory");
const sessionId = new ObjectId().toString();
const chatHistory = new MongoDBChatMessageHistory({
collection,
sessionId,
});
const blankResult = await chatHistory.getMessages();
expect(blankResult).toStrictEqual([]);
await chatHistory.addUserMessage("Who is the best vocalist?");
await chatHistory.addAIChatMessage("Ozzy Osbourne");
const expectedMessages = [
new HumanMessage("Who is the best vocalist?"),
new AIMessage("Ozzy Osbourne"),
];
const resultWithHistory = await chatHistory.getMessages();
expect(resultWithHistory).toEqual(expectedMessages);
await client.close();
});
test("Test clear MongoDB history store", async () => {
expect(process.env.MONGODB_ATLAS_URI).toBeDefined();
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const client = new MongoClient(process.env.MONGODB_ATLAS_URI!);
await client.connect();
const collection = client.db("langchain").collection("memory");
const sessionId = new ObjectId().toString();
const chatHistory = new MongoDBChatMessageHistory({
collection,
sessionId,
});
await chatHistory.addUserMessage("Who is the best vocalist?");
await chatHistory.addAIChatMessage("Ozzy Osbourne");
const expectedMessages = [
new HumanMessage("Who is the best vocalist?"),
new AIMessage("Ozzy Osbourne"),
];
const resultWithHistory = await chatHistory.getMessages();
expect(resultWithHistory).toEqual(expectedMessages);
await chatHistory.clear();
const blankResult = await chatHistory.getMessages();
expect(blankResult).toStrictEqual([]);
await client.close();
});
|
0 | lc_public_repos/langchainjs/libs/langchain-mongodb | lc_public_repos/langchainjs/libs/langchain-mongodb/scripts/jest-setup-after-env.js | import { awaitAllCallbacks } from "@langchain/core/callbacks/promises";
import { afterAll, jest } from "@jest/globals";
afterAll(awaitAllCallbacks);
// Allow console.log to be disabled in tests
if (process.env.DISABLE_CONSOLE_LOGS === "true") {
console.log = jest.fn();
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-openai/tsconfig.json | {
"extends": "@tsconfig/recommended",
"compilerOptions": {
"outDir": "../dist",
"rootDir": "./src",
"target": "ES2021",
"lib": [
"ES2021",
"ES2022.Object",
"DOM"
],
"module": "ES2020",
"moduleResolution": "nodenext",
"esModuleInterop": true,
"declaration": true,
"noImplicitReturns": true,
"noFallthroughCasesInSwitch": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"useDefineForClassFields": true,
"strictPropertyInitialization": false,
"allowJs": true,
"strict": true
},
"include": [
"src/**/*"
],
"exclude": [
"node_modules",
"dist",
"docs"
]
}
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-openai/LICENSE | The MIT License
Copyright (c) Harrison Chase
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE. |
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-openai/jest.config.cjs | /** @type {import('ts-jest').JestConfigWithTsJest} */
module.exports = {
preset: "ts-jest/presets/default-esm",
testEnvironment: "./jest.env.cjs",
modulePathIgnorePatterns: ["dist/", "docs/"],
moduleNameMapper: {
"^(\\.{1,2}/.*)\\.js$": "$1",
},
transform: {
'^.+\\.tsx?$': ['@swc/jest'],
},
transformIgnorePatterns: [
"/node_modules/",
"\\.pnp\\.[^\\/]+$",
"./scripts/jest-setup-after-env.js",
],
setupFiles: ["dotenv/config"],
setupFilesAfterEnv: ["./scripts/jest-setup-after-env.js"],
testTimeout: 20_000,
passWithNoTests: true
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-openai/babel.config.cjs | // babel.config.js
module.exports = {
presets: [["@babel/preset-env", { targets: { node: true } }]],
};
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-openai/audio.json | {
"id": "audio_67118ff3274c81909cd2868f46786059",
"data": 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",
"expires_at": 1729207811,
"transcript": "I'm sorry, but I can't create an audio clip of yelling. Is there anything else I can help you with?"
} |
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-openai/jest.env.cjs | const { TestEnvironment } = require("jest-environment-node");
class AdjustedTestEnvironmentToSupportFloat32Array extends TestEnvironment {
constructor(config, context) {
// Make `instanceof Float32Array` return true in tests
// to avoid https://github.com/xenova/transformers.js/issues/57 and https://github.com/jestjs/jest/issues/2549
super(config, context);
this.global.Float32Array = Float32Array;
}
}
module.exports = AdjustedTestEnvironmentToSupportFloat32Array;
|
0 | lc_public_repos/langchainjs/libs | lc_public_repos/langchainjs/libs/langchain-openai/README.md | # @langchain/openai
This package contains the LangChain.js integrations for OpenAI through their SDK.
## Installation
```bash npm2yarn
npm install @langchain/openai @langchain/core
```
This package, along with the main LangChain package, depends on [`@langchain/core`](https://npmjs.com/package/@langchain/core/).
If you are using this package with other LangChain packages, you should make sure that all of the packages depend on the same instance of @langchain/core.
You can do so by adding appropriate fields to your project's `package.json` like this:
```json
{
"name": "your-project",
"version": "0.0.0",
"dependencies": {
"@langchain/core": "^0.3.0",
"@langchain/openai": "^0.0.0"
},
"resolutions": {
"@langchain/core": "^0.3.0"
},
"overrides": {
"@langchain/core": "^0.3.0"
},
"pnpm": {
"overrides": {
"@langchain/core": "^0.3.0"
}
}
}
```
The field you need depends on the package manager you're using, but we recommend adding a field for the common `yarn`, `npm`, and `pnpm` to maximize compatibility.
## Chat Models
This package contains the `ChatOpenAI` class, which is the recommended way to interface with the OpenAI series of models.
To use, install the requirements, and configure your environment.
```bash
export OPENAI_API_KEY=your-api-key
```
Then initialize
```typescript
import { ChatOpenAI } from "@langchain/openai";
const model = new ChatOpenAI({
apiKey: process.env.OPENAI_API_KEY,
modelName: "gpt-4-1106-preview",
});
const response = await model.invoke(new HumanMessage("Hello world!"));
```
### Streaming
```typescript
import { ChatOpenAI } from "@langchain/openai";
const model = new ChatOpenAI({
apiKey: process.env.OPENAI_API_KEY,
modelName: "gpt-4-1106-preview",
});
const response = await model.stream(new HumanMessage("Hello world!"));
```
## Embeddings
This package also adds support for OpenAI's embeddings model.
```typescript
import { OpenAIEmbeddings } from "@langchain/openai";
const embeddings = new OpenAIEmbeddings({
apiKey: process.env.OPENAI_API_KEY,
});
const res = await embeddings.embedQuery("Hello world");
```
## Development
To develop the OpenAI package, you'll need to follow these instructions:
### Install dependencies
```bash
yarn install
```
### Build the package
```bash
yarn build
```
Or from the repo root:
```bash
yarn build --filter=@langchain/openai
```
### Run tests
Test files should live within a `tests/` file in the `src/` folder. Unit tests should end in `.test.ts` and integration tests should
end in `.int.test.ts`:
```bash
$ yarn test
$ yarn test:int
```
### Lint & Format
Run the linter & formatter to ensure your code is up to standard:
```bash
yarn lint && yarn format
```
### Adding new entrypoints
If you add a new file to be exported, either import & re-export from `src/index.ts`, or add it to the `entrypoints` field in the `config` variable located inside `langchain.config.js` and run `yarn build` to generate the new entrypoint.
|
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