id stringlengths 14 16 | source stringlengths 49 117 | text stringlengths 16 2.73k |
|---|---|---|
7ebbd3450080-3 | https://python.langchain.com/en/latest/_modules/langchain/embeddings/elasticsearch.html | # Optional, only if different from 'text_field'
input_field = "your_input_field"
# Create Elasticsearch connection
es_connection = Elasticsearch(
hosts=["localhost:9200"], http_auth=("user", "password")
)
# Instantiate E... |
7ebbd3450080-4 | https://python.langchain.com/en/latest/_modules/langchain/embeddings/elasticsearch.html | [docs] def embed_documents(self, texts: List[str]) -> List[List[float]]:
"""
Generate embeddings for a list of documents.
Args:
texts (List[str]): A list of document text strings to generate embeddings
for.
Returns:
List[List[float]]: A list of ... |
2959abaa3071-0 | https://python.langchain.com/en/latest/_modules/langchain/embeddings/modelscope_hub.html | Source code for langchain.embeddings.modelscope_hub
"""Wrapper around ModelScopeHub embedding models."""
from typing import Any, List
from pydantic import BaseModel, Extra
from langchain.embeddings.base import Embeddings
[docs]class ModelScopeEmbeddings(BaseModel, Embeddings):
"""Wrapper around modelscope_hub embed... |
2959abaa3071-1 | https://python.langchain.com/en/latest/_modules/langchain/embeddings/modelscope_hub.html | inputs = {"source_sentence": texts}
embeddings = self.embed(input=inputs)["text_embedding"]
return embeddings.tolist()
[docs] def embed_query(self, text: str) -> List[float]:
"""Compute query embeddings using a modelscope embedding model.
Args:
text: The text to embed.
... |
fe84e11fd26c-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/vectorstore.html | Source code for langchain.memory.vectorstore
"""Class for a VectorStore-backed memory object."""
from typing import Any, Dict, List, Optional, Union
from pydantic import Field
from langchain.memory.chat_memory import BaseMemory
from langchain.memory.utils import get_prompt_input_key
from langchain.schema import Documen... |
fe84e11fd26c-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/vectorstore.html | result: Union[List[Document], str]
if not self.return_docs:
result = "\n".join([doc.page_content for doc in docs])
else:
result = docs
return {self.memory_key: result}
def _form_documents(
self, inputs: Dict[str, Any], outputs: Dict[str, str]
) -> List[Doc... |
1be51795f639-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/buffer_window.html | Source code for langchain.memory.buffer_window
from typing import Any, Dict, List
from langchain.memory.chat_memory import BaseChatMemory
from langchain.schema import BaseMessage, get_buffer_string
[docs]class ConversationBufferWindowMemory(BaseChatMemory):
"""Buffer for storing conversation memory."""
human_pr... |
86c1a7aa6237-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/token_buffer.html | Source code for langchain.memory.token_buffer
from typing import Any, Dict, List
from langchain.base_language import BaseLanguageModel
from langchain.memory.chat_memory import BaseChatMemory
from langchain.schema import BaseMessage, get_buffer_string
[docs]class ConversationTokenBufferMemory(BaseChatMemory):
"""Buf... |
86c1a7aa6237-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/token_buffer.html | pruned_memory = []
while curr_buffer_length > self.max_token_limit:
pruned_memory.append(buffer.pop(0))
curr_buffer_length = self.llm.get_num_tokens_from_messages(buffer)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
a17a1ed5f4fc-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/summary_buffer.html | Source code for langchain.memory.summary_buffer
from typing import Any, Dict, List
from pydantic import root_validator
from langchain.memory.chat_memory import BaseChatMemory
from langchain.memory.summary import SummarizerMixin
from langchain.schema import BaseMessage, get_buffer_string
[docs]class ConversationSummaryB... |
a17a1ed5f4fc-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/summary_buffer.html | "Got unexpected prompt input variables. The prompt expects "
f"{prompt_variables}, but it should have {expected_keys}."
)
return values
[docs] def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None:
"""Save context from this conversation to buffer.... |
401731f983d0-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/kg.html | Source code for langchain.memory.kg
from typing import Any, Dict, List, Type, Union
from pydantic import Field
from langchain.base_language import BaseLanguageModel
from langchain.chains.llm import LLMChain
from langchain.graphs import NetworkxEntityGraph
from langchain.graphs.networkx_graph import KnowledgeTriple, get... |
401731f983d0-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/kg.html | for entity in entities:
knowledge = self.kg.get_entity_knowledge(entity)
if knowledge:
summary = f"On {entity}: {'. '.join(knowledge)}."
summary_strings.append(summary)
context: Union[str, List]
if not summary_strings:
context = [] if s... |
401731f983d0-2 | https://python.langchain.com/en/latest/_modules/langchain/memory/kg.html | output = chain.predict(
history=buffer_string,
input=input_string,
)
return get_entities(output)
def _get_current_entities(self, inputs: Dict[str, Any]) -> List[str]:
"""Get the current entities in the conversation."""
prompt_input_key = self._get_prompt_input... |
401731f983d0-3 | https://python.langchain.com/en/latest/_modules/langchain/memory/kg.html | © Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
ae02bc2bc037-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/buffer.html | Source code for langchain.memory.buffer
from typing import Any, Dict, List, Optional
from pydantic import root_validator
from langchain.memory.chat_memory import BaseChatMemory, BaseMemory
from langchain.memory.utils import get_prompt_input_key
from langchain.schema import get_buffer_string
[docs]class ConversationBuff... |
ae02bc2bc037-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/buffer.html | """Validate that return messages is not True."""
if values.get("return_messages", False):
raise ValueError(
"return_messages must be False for ConversationStringBufferMemory"
)
return values
@property
def memory_variables(self) -> List[str]:
"""Wil... |
45472d022419-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/entity.html | Source code for langchain.memory.entity
import logging
from abc import ABC, abstractmethod
from itertools import islice
from typing import Any, Dict, Iterable, List, Optional
from pydantic import BaseModel, Field
from langchain.base_language import BaseLanguageModel
from langchain.chains.llm import LLMChain
from langch... |
45472d022419-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/entity.html | [docs] def set(self, key: str, value: Optional[str]) -> None:
self.store[key] = value
[docs] def delete(self, key: str) -> None:
del self.store[key]
[docs] def exists(self, key: str) -> bool:
return key in self.store
[docs] def clear(self) -> None:
return self.store.clear()
[... |
45472d022419-2 | https://python.langchain.com/en/latest/_modules/langchain/memory/entity.html | logger.error(error)
self.session_id = session_id
self.key_prefix = key_prefix
self.ttl = ttl
self.recall_ttl = recall_ttl or ttl
@property
def full_key_prefix(self) -> str:
return f"{self.key_prefix}:{self.session_id}"
[docs] def get(self, key: str, default: Optional[s... |
45472d022419-3 | https://python.langchain.com/en/latest/_modules/langchain/memory/entity.html | self.redis_client.scan_iter(f"{self.full_key_prefix}:*"), 500
):
self.redis_client.delete(*keybatch)
[docs]class SQLiteEntityStore(BaseEntityStore):
"""SQLite-backed Entity store"""
session_id: str = "default"
table_name: str = "memory_store"
def __init__(
self,
sessi... |
45472d022419-4 | https://python.langchain.com/en/latest/_modules/langchain/memory/entity.html | if result is not None:
value = result[0]
return value
return default
[docs] def set(self, key: str, value: Optional[str]) -> None:
if not value:
return self.delete(key)
query = f"""
INSERT OR REPLACE INTO {self.full_table_name} (key, value)
... |
45472d022419-5 | https://python.langchain.com/en/latest/_modules/langchain/memory/entity.html | entity_store: BaseEntityStore = Field(default_factory=InMemoryEntityStore)
@property
def buffer(self) -> List[BaseMessage]:
return self.chat_memory.messages
@property
def memory_variables(self) -> List[str]:
"""Will always return list of memory variables.
:meta private:
"... |
45472d022419-6 | https://python.langchain.com/en/latest/_modules/langchain/memory/entity.html | """Save context from this conversation to buffer."""
super().save_context(inputs, outputs)
if self.input_key is None:
prompt_input_key = get_prompt_input_key(inputs, self.memory_variables)
else:
prompt_input_key = self.input_key
buffer_string = get_buffer_string(
... |
8ce5ec312e19-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/combined.html | Source code for langchain.memory.combined
import warnings
from typing import Any, Dict, List, Set
from pydantic import validator
from langchain.memory.chat_memory import BaseChatMemory
from langchain.schema import BaseMemory
[docs]class CombinedMemory(BaseMemory):
"""Class for combining multiple memories' data toge... |
8ce5ec312e19-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/combined.html | return memory_variables
[docs] def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, str]:
"""Load all vars from sub-memories."""
memory_data: Dict[str, Any] = {}
# Collect vars from all sub-memories
for memory in self.memories:
data = memory.load_memory_var... |
40b52c88c207-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/summary.html | Source code for langchain.memory.summary
from __future__ import annotations
from typing import Any, Dict, List, Type
from pydantic import BaseModel, root_validator
from langchain.base_language import BaseLanguageModel
from langchain.chains.llm import LLMChain
from langchain.memory.chat_memory import BaseChatMemory
from... |
40b52c88c207-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/summary.html | obj = cls(llm=llm, chat_memory=chat_memory, **kwargs)
for i in range(0, len(obj.chat_memory.messages), summarize_step):
obj.buffer = obj.predict_new_summary(
obj.chat_memory.messages[i : i + summarize_step], obj.buffer
)
return obj
@property
def memory_var... |
40b52c88c207-2 | https://python.langchain.com/en/latest/_modules/langchain/memory/summary.html | © Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
54d0d72e760c-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/simple.html | Source code for langchain.memory.simple
from typing import Any, Dict, List
from langchain.schema import BaseMemory
[docs]class SimpleMemory(BaseMemory):
"""Simple memory for storing context or other bits of information that shouldn't
ever change between prompts.
"""
memories: Dict[str, Any] = dict()
... |
544a70b4cfe8-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/readonly.html | Source code for langchain.memory.readonly
from typing import Any, Dict, List
from langchain.schema import BaseMemory
[docs]class ReadOnlySharedMemory(BaseMemory):
"""A memory wrapper that is read-only and cannot be changed."""
memory: BaseMemory
@property
def memory_variables(self) -> List[str]:
... |
7efdd614a71b-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/dynamodb.html | Source code for langchain.memory.chat_message_histories.dynamodb
import logging
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
BaseMessage,
_message_to_dict,
messages_from_dict,
messages_to_dict,
)
logger = logging.getLogger(__name__)
[docs]class DynamoDBChatMessageHi... |
7efdd614a71b-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/dynamodb.html | """Append the message to the record in DynamoDB"""
from botocore.exceptions import ClientError
messages = messages_to_dict(self.messages)
_message = _message_to_dict(message)
messages.append(_message)
try:
self.table.put_item(
Item={"SessionId": self.s... |
5418e17e8b1a-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/momento.html | Source code for langchain.memory.chat_message_histories.momento
from __future__ import annotations
import json
from datetime import timedelta
from typing import TYPE_CHECKING, Any, Optional
from langchain.schema import (
BaseChatMessageHistory,
BaseMessage,
_message_to_dict,
messages_from_dict,
)
from l... |
5418e17e8b1a-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/momento.html | you must have a Momento account at https://gomomento.com/.
Args:
session_id (str): The session ID to use for this chat session.
cache_client (CacheClient): The Momento cache client.
cache_name (str): The name of the cache to use to store the messages.
key_prefix (... |
5418e17e8b1a-2 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/momento.html | configuration: Optional[momento.config.Configuration] = None,
auth_token: Optional[str] = None,
**kwargs: Any,
) -> MomentoChatMessageHistory:
"""Construct cache from CacheClient parameters."""
try:
from momento import CacheClient, Configurations, CredentialProvider
... |
5418e17e8b1a-3 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/momento.html | [docs] def add_message(self, message: BaseMessage) -> None:
"""Store a message in the cache.
Args:
message (BaseMessage): The message object to store.
Raises:
SdkException: Momento service or network error.
Exception: Unexpected response.
"""
... |
87460b6402f8-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/redis.html | Source code for langchain.memory.chat_message_histories.redis
import json
import logging
from typing import List, Optional
from langchain.schema import (
BaseChatMessageHistory,
BaseMessage,
_message_to_dict,
messages_from_dict,
)
logger = logging.getLogger(__name__)
[docs]class RedisChatMessageHistory(... |
87460b6402f8-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/redis.html | self.redis_client.lpush(self.key, json.dumps(_message_to_dict(message)))
if self.ttl:
self.redis_client.expire(self.key, self.ttl)
[docs] def clear(self) -> None:
"""Clear session memory from Redis"""
self.redis_client.delete(self.key)
By Harrison Chase
© Copyright 2023... |
4ce61ac20698-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/postgres.html | Source code for langchain.memory.chat_message_histories.postgres
import json
import logging
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
BaseMessage,
_message_to_dict,
messages_from_dict,
)
logger = logging.getLogger(__name__)
DEFAULT_CONNECTION_STRING = "postgresql://p... |
4ce61ac20698-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/postgres.html | [docs] def add_message(self, message: BaseMessage) -> None:
"""Append the message to the record in PostgreSQL"""
from psycopg import sql
query = sql.SQL("INSERT INTO {} (session_id, message) VALUES (%s, %s);").format(
sql.Identifier(self.table_name)
)
self.cursor.e... |
78b6a6ec6554-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cassandra.html | Source code for langchain.memory.chat_message_histories.cassandra
import json
import logging
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
BaseMessage,
_message_to_dict,
messages_from_dict,
)
logger = logging.getLogger(__name__)
DEFAULT_KEYSPACE_NAME = "chat_history"
DEF... |
78b6a6ec6554-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cassandra.html | from cassandra.cluster import Cluster, PlainTextAuthProvider
except ImportError:
raise ValueError(
"Could not import cassandra-driver python package. "
"Please install it with `pip install cassandra-driver`."
)
self.cluster: Cluster = Cluster(
... |
78b6a6ec6554-2 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cassandra.html | except (OperationTimedOut, Unavailable) as error:
logger.error(
f"Unable to create cassandra \
chat message history table: {self.table_name}"
)
raise error
@property
def messages(self) -> List[BaseMessage]: # type: ignore
"""Retrieve t... |
78b6a6ec6554-3 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cassandra.html | f"DELETE FROM {self.table_name} WHERE session_id = '{self.session_id}';"
)
except (Unavailable, OperationTimedOut) as error:
logger.error("Unable to clear chat history messages from cassandra")
raise error
def __del__(self) -> None:
if self.session:
se... |
36262245d6d3-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/file.html | Source code for langchain.memory.chat_message_histories.file
import json
import logging
from pathlib import Path
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
BaseMessage,
messages_from_dict,
messages_to_dict,
)
logger = logging.getLogger(__name__)
[docs]class FileChatMe... |
2c57d593dbc1-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cosmos_db.html | Source code for langchain.memory.chat_message_histories.cosmos_db
"""Azure CosmosDB Memory History."""
from __future__ import annotations
import logging
from types import TracebackType
from typing import TYPE_CHECKING, Any, List, Optional, Type
from langchain.schema import (
BaseChatMessageHistory,
BaseMessage,... |
2c57d593dbc1-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cosmos_db.html | :param ttl: The time to live (in seconds) to use for documents in the container.
:param cosmos_client_kwargs: Additional kwargs to pass to the CosmosClient.
"""
self.cosmos_endpoint = cosmos_endpoint
self.cosmos_database = cosmos_database
self.cosmos_container = cosmos_container
... |
2c57d593dbc1-2 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cosmos_db.html | raise ImportError(
"You must install the azure-cosmos package to use the CosmosDBChatMessageHistory." # noqa: E501
) from exc
database = self._client.create_database_if_not_exists(self.cosmos_database)
self._container = database.create_container_if_not_exists(
se... |
2c57d593dbc1-3 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/cosmos_db.html | if "messages" in item and len(item["messages"]) > 0:
self.messages = messages_from_dict(item["messages"])
[docs] def add_message(self, message: BaseMessage) -> None:
"""Add a self-created message to the store"""
self.messages.append(message)
self.upsert_messages()
[docs] def up... |
a92ecc93a987-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/mongodb.html | Source code for langchain.memory.chat_message_histories.mongodb
import json
import logging
from typing import List
from langchain.schema import (
BaseChatMessageHistory,
BaseMessage,
_message_to_dict,
messages_from_dict,
)
logger = logging.getLogger(__name__)
DEFAULT_DBNAME = "chat_history"
DEFAULT_COLL... |
a92ecc93a987-1 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/mongodb.html | items = [json.loads(document["History"]) for document in cursor]
else:
items = []
messages = messages_from_dict(items)
return messages
[docs] def add_message(self, message: BaseMessage) -> None:
"""Append the message to the record in MongoDB"""
from pymongo import ... |
a2130b49991e-0 | https://python.langchain.com/en/latest/_modules/langchain/memory/chat_message_histories/in_memory.html | Source code for langchain.memory.chat_message_histories.in_memory
from typing import List
from pydantic import BaseModel
from langchain.schema import (
BaseChatMessageHistory,
BaseMessage,
)
[docs]class ChatMessageHistory(BaseChatMessageHistory, BaseModel):
messages: List[BaseMessage] = []
[docs] def add... |
a66980eb65f0-0 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/azure_openai.html | Source code for langchain.chat_models.azure_openai
"""Azure OpenAI chat wrapper."""
from __future__ import annotations
import logging
from typing import Any, Dict, Mapping
from pydantic import root_validator
from langchain.chat_models.openai import ChatOpenAI
from langchain.schema import ChatResult
from langchain.utils... |
a66980eb65f0-1 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/azure_openai.html | openai_api_version: str = ""
openai_api_key: str = ""
openai_organization: str = ""
openai_proxy: str = ""
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
openai_api_key = get_from_dict_or_en... |
a66980eb65f0-2 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/azure_openai.html | openai.proxy = {"http": openai_proxy, "https": openai_proxy} # type: ignore[assignment] # noqa: E501
except ImportError:
raise ImportError(
"Could not import openai python package. "
"Please install it with `pip install openai`."
)
try:
... |
a66980eb65f0-3 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/azure_openai.html | return super()._create_chat_result(response)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
69b77148267d-0 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/google_palm.html | Source code for langchain.chat_models.google_palm
"""Wrapper around Google's PaLM Chat API."""
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Mapping, Optional
from pydantic import BaseModel, root_validator
from tenacity import (
before_sleep_log,
... |
69b77148267d-1 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/google_palm.html | generations: List[ChatGeneration] = []
for candidate in response.candidates:
author = candidate.get("author")
if author is None:
raise ChatGooglePalmError(f"ChatResponse must have an author: {candidate}")
content = _truncate_at_stop_tokens(candidate.get("content", ""), stop)
... |
69b77148267d-2 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/google_palm.html | elif isinstance(input_message, HumanMessage) and input_message.example:
if messages:
raise ChatGooglePalmError(
"Message examples must come before other messages."
)
_, next_input_message = remaining.pop(0)
if isinstance(next_input_... |
69b77148267d-3 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/google_palm.html | """Returns a tenacity retry decorator, preconfigured to handle PaLM exceptions"""
import google.api_core.exceptions
multiplier = 2
min_seconds = 1
max_seconds = 60
max_retries = 10
return retry(
reraise=True,
stop=stop_after_attempt(max_retries),
wait=wait_exponential(mul... |
69b77148267d-4 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/google_palm.html | To use you must have the google.generativeai Python package installed and
either:
1. The ``GOOGLE_API_KEY``` environment varaible set with your API key, or
2. Pass your API key using the google_api_key kwarg to the ChatGoogle
constructor.
Example:
.. code-block:: python
... |
69b77148267d-5 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/google_palm.html | genai.configure(api_key=google_api_key)
except ImportError:
raise ChatGooglePalmError(
"Could not import google.generativeai python package. "
"Please install it with `pip install google-generativeai`"
)
values["client"] = genai
if values["... |
69b77148267d-6 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/google_palm.html | prompt = _messages_to_prompt_dict(messages)
response: genai.types.ChatResponse = await achat_with_retry(
self,
model=self.model_name,
prompt=prompt,
temperature=self.temperature,
top_p=self.top_p,
top_k=self.top_k,
candidate_cou... |
f279d0cc7c59-0 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/promptlayer_openai.html | Source code for langchain.chat_models.promptlayer_openai
"""PromptLayer wrapper."""
import datetime
from typing import Any, List, Mapping, Optional
from langchain.callbacks.manager import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForLLMRun,
)
from langchain.chat_models import ChatOpenAI
from langchain.sch... |
f279d0cc7c59-1 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/promptlayer_openai.html | """Call ChatOpenAI generate and then call PromptLayer API to log the request."""
from promptlayer.utils import get_api_key, promptlayer_api_request
request_start_time = datetime.datetime.now().timestamp()
generated_responses = super()._generate(messages, stop, run_manager)
request_end_ti... |
f279d0cc7c59-2 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/promptlayer_openai.html | message_dicts, params = super()._create_message_dicts(messages, stop)
for i, generation in enumerate(generated_responses.generations):
response_dict, params = super()._create_message_dicts(
[generation.message], stop
)
pl_request_id = await promptlayer_api_req... |
985a07b65c74-0 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/vertexai.html | Source code for langchain.chat_models.vertexai
"""Wrapper around Google VertexAI chat-based models."""
from dataclasses import dataclass, field
from typing import Dict, List, Optional
from pydantic import root_validator
from langchain.callbacks.manager import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForL... |
985a07b65c74-1 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/vertexai.html | return _ChatHistory()
first_message = history[0]
system_message = first_message if isinstance(first_message, SystemMessage) else None
chat_history = _ChatHistory(system_message=system_message)
messages_left = history[1:] if system_message else history
if len(messages_left) % 2 != 0:
raise Va... |
985a07b65c74-2 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/vertexai.html | messages: The history of the conversation as a list of messages.
stop: The list of stop words (optional).
run_manager: The Callbackmanager for LLM run, it's not used at the moment.
Returns:
The ChatResult that contains outputs generated by the model.
Raises:
... |
d78311df5ebb-0 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/anthropic.html | Source code for langchain.chat_models.anthropic
from typing import Any, Dict, List, Optional
from pydantic import Extra
from langchain.callbacks.manager import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForLLMRun,
)
from langchain.chat_models.base import BaseChatModel
from langchain.llms.anthropic import _... |
d78311df5ebb-1 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/anthropic.html | message_text = f"{self.AI_PROMPT} {message.content}"
elif isinstance(message, SystemMessage):
message_text = f"{self.HUMAN_PROMPT} <admin>{message.content}</admin>"
else:
raise ValueError(f"Got unknown type {message}")
return message_text
def _convert_messages_to_text... |
d78311df5ebb-2 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/anthropic.html | prompt = self._convert_messages_to_prompt(messages)
params: Dict[str, Any] = {"prompt": prompt, **self._default_params}
if stop:
params["stop_sequences"] = stop
if self.streaming:
completion = ""
stream_resp = self.client.completion_stream(**params)
... |
d78311df5ebb-3 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/anthropic.html | return ChatResult(generations=[ChatGeneration(message=message)])
[docs] def get_num_tokens(self, text: str) -> int:
"""Calculate number of tokens."""
if not self.count_tokens:
raise NameError("Please ensure the anthropic package is loaded")
return self.count_tokens(text)
By Harris... |
2854b704f193-0 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | Source code for langchain.chat_models.openai
"""OpenAI chat wrapper."""
from __future__ import annotations
import logging
import sys
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Mapping,
Optional,
Tuple,
Union,
)
from pydantic import Extra, Field, root_validator
fro... |
2854b704f193-1 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | reraise=True,
stop=stop_after_attempt(llm.max_retries),
wait=wait_exponential(multiplier=1, min=min_seconds, max=max_seconds),
retry=(
retry_if_exception_type(openai.error.Timeout)
| retry_if_exception_type(openai.error.APIError)
| retry_if_exception_type(open... |
2854b704f193-2 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | message_dict = {"role": "user", "content": message.content}
elif isinstance(message, AIMessage):
message_dict = {"role": "assistant", "content": message.content}
elif isinstance(message, SystemMessage):
message_dict = {"role": "system", "content": message.content}
else:
raise ValueEr... |
2854b704f193-3 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | openai_organization: Optional[str] = None
# to support explicit proxy for OpenAI
openai_proxy: Optional[str] = None
request_timeout: Optional[Union[float, Tuple[float, float]]] = None
"""Timeout for requests to OpenAI completion API. Default is 600 seconds."""
max_retries: int = 6
"""Maximum num... |
2854b704f193-4 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | f"Instead they were passed in as part of `model_kwargs` parameter."
)
values["model_kwargs"] = extra
return values
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
openai_api_k... |
2854b704f193-5 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | "due to an old version of the openai package. Try upgrading it "
"with `pip install --upgrade openai`."
)
if values["n"] < 1:
raise ValueError("n must be at least 1.")
if values["n"] > 1 and values["streaming"]:
raise ValueError("n must be 1 when strea... |
2854b704f193-6 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | [docs] def completion_with_retry(self, **kwargs: Any) -> Any:
"""Use tenacity to retry the completion call."""
retry_decorator = self._create_retry_decorator()
@retry_decorator
def _completion_with_retry(**kwargs: Any) -> Any:
return self.client.create(**kwargs)
re... |
2854b704f193-7 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | {"content": inner_completion, "role": role}
)
return ChatResult(generations=[ChatGeneration(message=message)])
response = self.completion_with_retry(messages=message_dicts, **params)
return self._create_chat_result(response)
def _create_message_dicts(
self, messages: ... |
2854b704f193-8 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | async for stream_resp in await acompletion_with_retry(
self, messages=message_dicts, **params
):
role = stream_resp["choices"][0]["delta"].get("role", role)
token = stream_resp["choices"][0]["delta"].get("content", "")
inner_completion += token... |
2854b704f193-9 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | model = "gpt-4-0314"
# Returns the number of tokens used by a list of messages.
try:
encoding = tiktoken_.encoding_for_model(model)
except KeyError:
logger.warning("Warning: model not found. Using cl100k_base encoding.")
model = "cl100k_base"
encod... |
2854b704f193-10 | https://python.langchain.com/en/latest/_modules/langchain/chat_models/openai.html | tokens_per_name = 1
else:
raise NotImplementedError(
f"get_num_tokens_from_messages() is not presently implemented "
f"for model {model}."
"See https://github.com/openai/openai-python/blob/main/chatml.md for "
"information on how messag... |
45681dc10438-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/initialize.html | Source code for langchain.agents.initialize
"""Load agent."""
from typing import Any, Optional, Sequence
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_types import AgentType
from langchain.agents.loading import AGENT_TO_CLASS, load_agent
from langchain.base_language import BaseLanguageMod... |
45681dc10438-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/initialize.html | )
if agent is not None:
if agent not in AGENT_TO_CLASS:
raise ValueError(
f"Got unknown agent type: {agent}. "
f"Valid types are: {AGENT_TO_CLASS.keys()}."
)
agent_cls = AGENT_TO_CLASS[agent]
agent_kwargs = agent_kwargs or {}
ag... |
c3f85dae222b-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | Source code for langchain.agents.agent
"""Chain that takes in an input and produces an action and action input."""
from __future__ import annotations
import asyncio
import json
import logging
import time
from abc import abstractmethod
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Sequ... |
c3f85dae222b-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Steps the LLM has taken to date,
along with observations
... |
c3f85dae222b-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | f"Got unsupported early_stopping_method `{early_stopping_method}`"
)
[docs] @classmethod
def from_llm_and_tools(
cls,
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
**kwargs: Any,
) -> BaseSingleAc... |
c3f85dae222b-3 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | elif save_path.suffix == ".yaml":
with open(file_path, "w") as f:
yaml.dump(agent_dict, f, default_flow_style=False)
else:
raise ValueError(f"{save_path} must be json or yaml")
[docs] def tool_run_logging_kwargs(self) -> Dict:
return {}
[docs]class BaseMultiAct... |
c3f85dae222b-4 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | @property
@abstractmethod
def input_keys(self) -> List[str]:
"""Return the input keys.
:meta private:
"""
[docs] def return_stopped_response(
self,
early_stopping_method: str,
intermediate_steps: List[Tuple[AgentAction, str]],
**kwargs: Any,
) -> Ag... |
c3f85dae222b-5 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | # Fetch dictionary to save
agent_dict = self.dict()
if save_path.suffix == ".json":
with open(file_path, "w") as f:
json.dump(agent_dict, f, indent=4)
elif save_path.suffix == ".yaml":
with open(file_path, "w") as f:
yaml.dump(agent_dict, f... |
c3f85dae222b-6 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | **kwargs: User inputs.
Returns:
Action specifying what tool to use.
"""
output = self.llm_chain.run(
intermediate_steps=intermediate_steps,
stop=self.stop,
callbacks=callbacks,
**kwargs,
)
return self.output_parser.parse... |
c3f85dae222b-7 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | [docs] def dict(self, **kwargs: Any) -> Dict:
"""Return dictionary representation of agent."""
_dict = super().dict()
del _dict["output_parser"]
return _dict
[docs] def get_allowed_tools(self) -> Optional[List[str]]:
return self.allowed_tools
@property
def return_va... |
c3f85dae222b-8 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | full_inputs = self.get_full_inputs(intermediate_steps, **kwargs)
full_output = self.llm_chain.predict(callbacks=callbacks, **full_inputs)
return self.output_parser.parse(full_output)
[docs] async def aplan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Ca... |
c3f85dae222b-9 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | """Validate that prompt matches format."""
prompt = values["llm_chain"].prompt
if "agent_scratchpad" not in prompt.input_variables:
logger.warning(
"`agent_scratchpad` should be a variable in prompt.input_variables."
" Did not find it, so adding it at the end.... |
c3f85dae222b-10 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | **kwargs: Any,
) -> Agent:
"""Construct an agent from an LLM and tools."""
cls._validate_tools(tools)
llm_chain = LLMChain(
llm=llm,
prompt=cls.create_prompt(tools),
callback_manager=callback_manager,
)
tool_names = [tool.name for tool in t... |
c3f85dae222b-11 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | full_inputs = {**kwargs, **new_inputs}
full_output = self.llm_chain.predict(**full_inputs)
# We try to extract a final answer
parsed_output = self.output_parser.parse(full_output)
if isinstance(parsed_output, AgentFinish):
# If we can extract, we send the ... |
c3f85dae222b-12 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | early_stopping_method: str = "force"
handle_parsing_errors: Union[
bool, str, Callable[[OutputParserException], str]
] = False
[docs] @classmethod
def from_agent_and_tools(
cls,
agent: Union[BaseSingleActionAgent, BaseMultiActionAgent],
tools: Sequence[BaseTool],
c... |
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