text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/en/model_doc/esm.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/esm.md",
"repo_id": "transformers",
"token_count": 1906
} | 507 |
import { test, expect } from "@jest/globals";
import { InMemoryCache } from "../caches.js";
test("InMemoryCache", async () => {
const cache = new InMemoryCache();
await cache.update("foo", "bar", [{ text: "baz" }]);
expect(await cache.lookup("foo", "bar")).toEqual([{ text: "baz" }]);
});
| langchainjs/langchain-core/src/tests/caches.test.ts/0 | {
"file_path": "langchainjs/langchain-core/src/tests/caches.test.ts",
"repo_id": "langchainjs",
"token_count": 108
} | 870 |
import { expect, test } from "@jest/globals";
import process from "process";
import { OpenAI } from "@langchain/openai";
import { SerpAPI } from "@langchain/community/tools/serpapi";
import { Calculator } from "../../../tools/calculator.js";
import { initializeAgentExecutorWithOptions } from "../../../agents/index.js";... | langchainjs/langchain/src/evaluation/agents/tests/trajectory_eval_chain.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/evaluation/agents/tests/trajectory_eval_chain.int.test.ts",
"repo_id": "langchainjs",
"token_count": 423
} | 953 |
python_tests()
| llama_index/llama-index-integrations/tools/llama-index-tools-azure-cv/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-azure-cv/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,503 |
// For format details, see https://aka.ms/devcontainer.json. For config options, see the
// README at: https://github.com/devcontainers/templates/tree/main/src/typescript-node
{
"name": "Node.js & TypeScript",
// Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
"image": ... | langchainjs/.devcontainer/devcontainer.json/0 | {
"file_path": "langchainjs/.devcontainer/devcontainer.json",
"repo_id": "langchainjs",
"token_count": 336
} | 738 |
# Vectara RAG Pack
This LlamaPack provides an end-to-end Retrieval Augmented Generation flow using Vectara.
Before you start, if you have not done so already, you would need to follow these steps:
- Create a [free Vectara account](https://vectara.com/integrations/llamaindex).
- Create a [corpus](https://docs.vectara... | llama_index/llama-index-packs/llama-index-packs-vectara-rag/README.md/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-vectara-rag/README.md",
"repo_id": "llama_index",
"token_count": 1214
} | 1,738 |
<jupyter_start><jupyter_text>ChatGPT Data>[ChatGPT](https://chat.openai.com) is an artificial intelligence (AI) chatbot developed by OpenAI.This notebook covers how to load `conversations.json` from your `ChatGPT` data export folder.You can get your data export by email by going to: https://chat.openai.com/ -> (Profile... | langchain/docs/docs/integrations/document_loaders/chatgpt_loader.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/chatgpt_loader.ipynb",
"repo_id": "langchain",
"token_count": 182
} | 109 |
"""Integration test for PubMed API Wrapper."""
from typing import List
import pytest
from langchain_core.documents import Document
from langchain_community.retrievers import PubMedRetriever
@pytest.fixture
def retriever() -> PubMedRetriever:
return PubMedRetriever()
def assert_docs(docs: List[Document]) -> No... | langchain/libs/community/tests/integration_tests/retrievers/test_pubmed.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/retrievers/test_pubmed.py",
"repo_id": "langchain",
"token_count": 404
} | 370 |
[tool.poetry]
name = "rag-timescale-hybrid-search-time"
version = "0.0.1"
description = "RAG using timescale-vector DB with the self-query retriver for metadata filtering on time"
authors = []
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = "^0.1"
openai = "<2"
fastapi = "^0.104.0"
... | langchain/templates/rag-timescale-hybrid-search-time/pyproject.toml/0 | {
"file_path": "langchain/templates/rag-timescale-hybrid-search-time/pyproject.toml",
"repo_id": "langchain",
"token_count": 338
} | 692 |
from typing import Dict, Tuple
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
Operation,
Operator,
StructuredQuery,
)
from langchain.retrievers.self_query.mongodb_atlas import MongoDBAtlasTranslator
DEFAULT_TRANSLATOR = MongoDBAtlasTranslator()
def test_visit_compari... | langchain/libs/langchain/tests/unit_tests/retrievers/self_query/test_mongodb_atlas.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/retrievers/self_query/test_mongodb_atlas.py",
"repo_id": "langchain",
"token_count": 1810
} | 611 |
import orjson as json
import logging
from typing import Optional, cast, Tuple
from typing import Sequence
from uuid import UUID
import requests
from overrides import override
import chromadb.errors as errors
from chromadb.types import Database, Tenant
import chromadb.utils.embedding_functions as ef
from chromadb.api ... | chroma/chromadb/api/fastapi.py/0 | {
"file_path": "chroma/chromadb/api/fastapi.py",
"repo_id": "chroma",
"token_count": 10269
} | 12 |
import { GooglePaLMEmbeddings } from "@langchain/community/embeddings/googlepalm";
const model = new GooglePaLMEmbeddings({
apiKey: "<YOUR API KEY>", // or set it in environment variable as `GOOGLE_PALM_API_KEY`
modelName: "models/embedding-gecko-001", // OPTIONAL
});
/* Embed queries */
const res = await model.em... | langchainjs/examples/src/models/embeddings/googlepalm.ts/0 | {
"file_path": "langchainjs/examples/src/models/embeddings/googlepalm.ts",
"repo_id": "langchainjs",
"token_count": 174
} | 805 |
import { expect, test } from "@jest/globals";
import * as url from "node:url";
import * as path from "node:path";
import { PPTXLoader } from "../fs/pptx.js";
test.skip("Test PowerPoint loader from file", async () => {
const filePath = path.resolve(
path.dirname(url.fileURLToPath(import.meta.url)),
"./example... | langchainjs/langchain/src/document_loaders/tests/pptx.test.ts/0 | {
"file_path": "langchainjs/langchain/src/document_loaders/tests/pptx.test.ts",
"repo_id": "langchainjs",
"token_count": 310
} | 868 |
<jupyter_start><jupyter_text>Etherscan>[Etherscan](https://docs.etherscan.io/) is the leading blockchain explorer, search, API and analytics platform for Ethereum, a decentralized smart contracts platform. OverviewThe `Etherscan` loader use `Etherscan API` to load transactions histories under specific account on `Ethe... | langchain/docs/docs/integrations/document_loaders/etherscan.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/etherscan.ipynb",
"repo_id": "langchain",
"token_count": 781
} | 107 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/ja/accelerate.md/0 | {
"file_path": "transformers/docs/source/ja/accelerate.md",
"repo_id": "transformers",
"token_count": 2185
} | 522 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/blipdiffusion/test_blipdiffusion.py/0 | {
"file_path": "diffusers/tests/pipelines/blipdiffusion/test_blipdiffusion.py",
"repo_id": "diffusers",
"token_count": 3065
} | 268 |
import logging
from enum import Enum
from io import BytesIO
from typing import Any, Callable, Dict, List, Optional, Union
import requests
from langchain_core.documents import Document
from tenacity import (
before_sleep_log,
retry,
stop_after_attempt,
wait_exponential,
)
from langchain_community.docum... | langchain/libs/community/langchain_community/document_loaders/confluence.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/confluence.py",
"repo_id": "langchain",
"token_count": 13226
} | 234 |
/** @type {import('next').NextConfig} */
const nextConfig = {
async redirects() {
return [
{
source: "/",
destination: "/index.html",
permanent: false,
},
];
},
};
module.exports = nextConfig;
| langchainjs/docs/api_refs/next.config.js/0 | {
"file_path": "langchainjs/docs/api_refs/next.config.js",
"repo_id": "langchainjs",
"token_count": 105
} | 688 |
from langchain_anthropic import __all__
EXPECTED_ALL = ["ChatAnthropicMessages"]
def test_all_imports() -> None:
assert sorted(EXPECTED_ALL) == sorted(__all__)
| langchain/libs/partners/anthropic/tests/unit_tests/test_imports.py/0 | {
"file_path": "langchain/libs/partners/anthropic/tests/unit_tests/test_imports.py",
"repo_id": "langchain",
"token_count": 60
} | 680 |
"""Question answering over a graph."""
from __future__ import annotations
import re
from typing import Any, Dict, List, Optional
from langchain_community.graphs.arangodb_graph import ArangoGraph
from langchain_core.callbacks import CallbackManagerForChainRun
from langchain_core.language_models import BaseLanguageMode... | langchain/libs/langchain/langchain/chains/graph_qa/arangodb.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/graph_qa/arangodb.py",
"repo_id": "langchain",
"token_count": 3838
} | 489 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/core/src/query/Plan.cpp/0 | {
"file_path": "milvus/internal/core/src/query/Plan.cpp",
"repo_id": "milvus",
"token_count": 2190
} | 1,732 |
from __future__ import annotations
import logging
from typing import Any, Dict, List, Optional
from langchain_core.embeddings import Embeddings
from langchain_core.pydantic_v1 import BaseModel, root_validator
from langchain_core.utils import get_from_dict_or_env
logger = logging.getLogger(__name__)
class VolcanoEm... | langchain/libs/community/langchain_community/embeddings/volcengine.py/0 | {
"file_path": "langchain/libs/community/langchain_community/embeddings/volcengine.py",
"repo_id": "langchain",
"token_count": 1859
} | 261 |
import pickle
from typing import Optional
import aiosqlite
from langchain_core.pydantic_v1 import Field
from langchain_core.runnables import RunnableConfig
from langchain_core.runnables.utils import ConfigurableFieldSpec
from langgraph.checkpoint.base import BaseCheckpointSaver, Checkpoint
class AsyncSqliteSaver(Ba... | langgraph/langgraph/checkpoint/aiosqlite.py/0 | {
"file_path": "langgraph/langgraph/checkpoint/aiosqlite.py",
"repo_id": "langgraph",
"token_count": 1185
} | 1,075 |
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/src/transformers/modeling_outputs.py/0 | {
"file_path": "transformers/src/transformers/modeling_outputs.py",
"repo_id": "transformers",
"token_count": 40604
} | 578 |
"""Test AzureChatOpenAI wrapper."""
import os
from typing import Any
import pytest
from langchain_core.callbacks import CallbackManager
from langchain_core.messages import BaseMessage, HumanMessage
from langchain_core.outputs import ChatGeneration, ChatResult, LLMResult
from langchain_community.chat_models import Azu... | langchain/libs/community/tests/integration_tests/chat_models/test_azure_openai.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/chat_models/test_azure_openai.py",
"repo_id": "langchain",
"token_count": 2768
} | 348 |
# Create a dataset card
Each dataset should have a dataset card to promote responsible usage and inform users of any potential biases within the dataset.
This idea was inspired by the Model Cards proposed by [Mitchell, 2018](https://arxiv.org/abs/1810.03993).
Dataset cards help users understand a dataset's contents, t... | datasets/docs/source/dataset_card.mdx/0 | {
"file_path": "datasets/docs/source/dataset_card.mdx",
"repo_id": "datasets",
"token_count": 757
} | 120 |
# Generated content DO NOT EDIT
from .. import utils
cuda_is_available = utils.cuda_is_available
get_num_threads = utils.get_num_threads
has_accelerate = utils.has_accelerate
has_mkl = utils.has_mkl
load_ggml = utils.load_ggml
load_gguf = utils.load_gguf
load_safetensors = utils.load_safetensors
save_gguf = utils.save... | candle/candle-pyo3/py_src/candle/utils/__init__.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/utils/__init__.py",
"repo_id": "candle",
"token_count": 150
} | 62 |
"""Test tree index."""
from typing import Any, Dict, List, Optional
from unittest.mock import patch
from llama_index.core.data_structs.data_structs import IndexGraph
from llama_index.core.indices.tree.base import TreeIndex
from llama_index.core.schema import BaseNode, Document
from llama_index.core.service_context im... | llama_index/llama-index-core/tests/indices/tree/test_index.py/0 | {
"file_path": "llama_index/llama-index-core/tests/indices/tree/test_index.py",
"repo_id": "llama_index",
"token_count": 3184
} | 1,234 |
python_requirements(
name="reqs",
)
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-web/llama_index/readers/web/sitemap/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-web/llama_index/readers/web/sitemap/BUILD",
"repo_id": "llama_index",
"token_count": 24
} | 1,458 |
from llama_index.core.tools.tool_spec.base import BaseToolSpec
from llama_index.tools.openai import OpenAIImageGenerationToolSpec
def test_class():
names_of_base_classes = [b.__name__ for b in OpenAIImageGenerationToolSpec.__mro__]
assert BaseToolSpec.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/tools/llama-index-tools-openai/tests/test_tools_openai_image_generation.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-openai/tests/test_tools_openai_image_generation.py",
"repo_id": "llama_index",
"token_count": 100
} | 1,493 |
# Run this command to start the database:
# docker-compose up --build
version: "3"
services:
db:
hostname: 127.0.0.1
image: ankane/pgvector
ports:
- 5432:5432
restart: always
environment:
- POSTGRES_DB=api
- POSTGRES_USER=myuser
- POSTGRES_PASSWORD=ChangeMe
volumes:
... | langchainjs/libs/langchain-community/src/vectorstores/tests/pgvector/docker-compose.yml/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/tests/pgvector/docker-compose.yml",
"repo_id": "langchainjs",
"token_count": 165
} | 1,088 |
# Custom Diffusion training example
[Custom Diffusion](https://arxiv.org/abs/2212.04488) is a method to customize text-to-image models like Stable Diffusion given just a few (4~5) images of a subject.
The `train_custom_diffusion.py` script shows how to implement the training procedure and adapt it for stable diffusio... | diffusers/examples/custom_diffusion/README.md/0 | {
"file_path": "diffusers/examples/custom_diffusion/README.md",
"repo_id": "diffusers",
"token_count": 3550
} | 206 |
import { expect, test } from "@jest/globals";
import { OpenAI, OpenAIEmbeddings, ChatOpenAI } from "@langchain/openai";
import { PromptTemplate } from "@langchain/core/prompts";
import { ConversationalRetrievalQAChain } from "../conversational_retrieval_chain.js";
import { MemoryVectorStore } from "../../vectorstores/m... | langchainjs/langchain/src/chains/tests/conversational_retrieval_chain.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/chains/tests/conversational_retrieval_chain.int.test.ts",
"repo_id": "langchainjs",
"token_count": 3931
} | 896 |
# coding=utf-8
# Copyright 2021 The HuggingFace Team Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a clone of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | transformers/tests/generation/test_flax_logits_process.py/0 | {
"file_path": "transformers/tests/generation/test_flax_logits_process.py",
"repo_id": "transformers",
"token_count": 5610
} | 726 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/de/autoclass_tutorial.md/0 | {
"file_path": "transformers/docs/source/de/autoclass_tutorial.md",
"repo_id": "transformers",
"token_count": 2616
} | 492 |
# elastic-query-generator
This template allows interacting with Elasticsearch analytics databases in natural language using LLMs.
It builds search queries via the Elasticsearch DSL API (filters and aggregations).
## Environment Setup
Set the `OPENAI_API_KEY` environment variable to access the OpenAI models.
###... | langchain/templates/elastic-query-generator/README.md/0 | {
"file_path": "langchain/templates/elastic-query-generator/README.md",
"repo_id": "langchain",
"token_count": 816
} | 688 |
var fs = require("fs");
var path = require("path");
var express = require("express");
var chroma = require("chromadb");
var app = express();
app.get("/", async (req, res) => {
const cc = new chroma.ChromaClient({ path: "http://localhost:8000" });
await cc.reset();
const google = new chroma.GoogleGenerativeAiEm... | chroma/clients/js/examples/node/app.js/0 | {
"file_path": "chroma/clients/js/examples/node/app.js",
"repo_id": "chroma",
"token_count": 427
} | 29 |
package segments
import (
"context"
"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
"github.com/milvus-io/milvus/internal/proto/internalpb"
"github.com/milvus-io/milvus/internal/proto/querypb"
"github.com/milvus-io/milvus/internal/proto/segcorepb"
)
type defaultLimitReducer struct {
req *querypb.Quer... | milvus/internal/querynodev2/segments/default_limit_reducer.go/0 | {
"file_path": "milvus/internal/querynodev2/segments/default_limit_reducer.go",
"repo_id": "milvus",
"token_count": 766
} | 2,046 |
Router Query Engine
=======================
.. automodule:: llama_index.core.query_engine.router_query_engine
:members:
:inherited-members:
:exclude-members: acombine_responses, combine_responses, default_node_to_metadata_fn
| llama_index/docs/api_reference/query/query_engines/router_query_engine.rst/0 | {
"file_path": "llama_index/docs/api_reference/query/query_engines/router_query_engine.rst",
"repo_id": "llama_index",
"token_count": 79
} | 1,083 |
"""Init file."""
| llama_index/llama-index-legacy/llama_index/legacy/indices/common/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/common/__init__.py",
"repo_id": "llama_index",
"token_count": 6
} | 1,494 |
use candle::Result;
use prost::Message;
pub mod onnx {
include!(concat!(env!("OUT_DIR"), "/onnx.rs"));
}
pub mod eval;
pub use eval::{dtype, simple_eval};
pub fn read_file<P: AsRef<std::path::Path>>(p: P) -> Result<onnx::ModelProto> {
let buf = std::fs::read(p)?;
onnx::ModelProto::decode(buf.as_slice()).... | candle/candle-onnx/src/lib.rs/0 | {
"file_path": "candle/candle-onnx/src/lib.rs",
"repo_id": "candle",
"token_count": 154
} | 63 |
from llama_index.core.llama_pack import BaseLlamaPack
from llama_index.packs.recursive_retriever import (
EmbeddedTablesUnstructuredRetrieverPack,
RecursiveRetrieverSmallToBigPack,
)
def test_class():
names_of_base_classes = [
b.__name__ for b in EmbeddedTablesUnstructuredRetrieverPack.__mro__
... | llama_index/llama-index-packs/llama-index-packs-recursive-retriever/tests/test_packs_recursive_retriever.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-recursive-retriever/tests/test_packs_recursive_retriever.py",
"repo_id": "llama_index",
"token_count": 217
} | 1,588 |
<jupyter_start><jupyter_text>Dreambooth fine-tuning for Stable Diffusion using d🧨ffusers This notebook shows how to "teach" Stable Diffusion a new concept via Dreambooth using 🤗 Hugging Face [🧨 Diffusers library](https://github.com/huggingface/diffusers). _By using just 3-5 images you can teach new concepts to Stabl... | notebooks/diffusers/sd_dreambooth_training.ipynb/0 | {
"file_path": "notebooks/diffusers/sd_dreambooth_training.ipynb",
"repo_id": "notebooks",
"token_count": 11907
} | 277 |
import threading
import time
import unittest
import unittest.mock
from typing import Any, Dict
from uuid import UUID
import pytest
from langsmith import Client
from langchain_core.outputs import LLMResult
from langchain_core.tracers.langchain import LangChainTracer
from langchain_core.tracers.schemas import Run
def... | langchain/libs/core/tests/unit_tests/tracers/test_langchain.py/0 | {
"file_path": "langchain/libs/core/tests/unit_tests/tracers/test_langchain.py",
"repo_id": "langchain",
"token_count": 2638
} | 421 |
from typing import Any
import pytest
from langchain_community.retrievers import DocArrayRetriever
from tests.integration_tests.retrievers.docarray.fixtures import ( # noqa: F401
init_elastic,
init_hnsw,
init_in_memory,
init_qdrant,
init_weaviate,
)
@pytest.mark.parametrize(
"backend",
[... | langchain/libs/community/tests/integration_tests/retrievers/docarray/test_backends.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/retrievers/docarray/test_backends.py",
"repo_id": "langchain",
"token_count": 806
} | 369 |
from stepback_qa_prompting.chain import chain
if __name__ == "__main__":
chain.invoke({"question": "was chatgpt around while trump was president?"})
| langchain/templates/stepback-qa-prompting/main.py/0 | {
"file_path": "langchain/templates/stepback-qa-prompting/main.py",
"repo_id": "langchain",
"token_count": 49
} | 758 |
python_tests()
| llama_index/llama-index-integrations/tools/llama-index-tools-notion/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-notion/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,519 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint.py",
"repo_id": "diffusers",
"token_count": 30632
} | 266 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/ko/quicktour.md/0 | {
"file_path": "diffusers/docs/source/ko/quicktour.md",
"repo_id": "diffusers",
"token_count": 11429
} | 190 |
import logging
logger = logging.getLogger("milvus_benchmark.parser")
def operations_parser(operations):
""" Get the type and params of test """
if not operations:
raise Exception("No operations in suite defined")
for run_type, run_params in operations.items():
logger.debug(run_type)
... | milvus/tests/benchmark/milvus_benchmark/parser.py/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/parser.py",
"repo_id": "milvus",
"token_count": 1292
} | 1,935 |
use crate::tokenizer::pattern::Pattern;
use crate::tokenizer::Decoder;
use crate::tokenizer::{NormalizedString, Normalizer, Result};
use crate::utils::SysRegex;
use serde::{Deserialize, Serialize};
/// Represents the different patterns that `Replace` can use
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Eq... | tokenizers/tokenizers/src/normalizers/replace.rs/0 | {
"file_path": "tokenizers/tokenizers/src/normalizers/replace.rs",
"repo_id": "tokenizers",
"token_count": 2048
} | 482 |
<jupyter_start><jupyter_text>Slack ReaderDemonstrates our Slack data connector If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-readers-slack
!pip install llama-index
import logging
import sys
logging.basicConfig(stream=sys.stdout, level=l... | llama_index/docs/examples/data_connectors/SlackDemo.ipynb/0 | {
"file_path": "llama_index/docs/examples/data_connectors/SlackDemo.ipynb",
"repo_id": "llama_index",
"token_count": 320
} | 1,054 |
python_sources()
resource(
name="py_typed",
source="py.typed",
)
| llama_index/llama-index-legacy/llama_index/legacy/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/BUILD",
"repo_id": "llama_index",
"token_count": 34
} | 1,484 |
# ESE-VoVNet
**VoVNet** is a convolutional neural network that seeks to make [DenseNet](https://paperswithcode.com/method/densenet) more efficient by concatenating all features only once in the last feature map, which makes input size constant and enables enlarging new output channel.
Read about [one-shot aggregatio... | pytorch-image-models/docs/models/ese-vovnet.md/0 | {
"file_path": "pytorch-image-models/docs/models/ese-vovnet.md",
"repo_id": "pytorch-image-models",
"token_count": 1948
} | 352 |
Empty Index Retriever
=======================
.. automodule:: llama_index.core.indices.empty.retrievers
:members:
:inherited-members:
.. :exclude-members: index_struct, query, set_llm_predictor, set_prompt_helper
| llama_index/docs/api_reference/query/retrievers/empty.rst/0 | {
"file_path": "llama_index/docs/api_reference/query/retrievers/empty.rst",
"repo_id": "llama_index",
"token_count": 81
} | 1,084 |
import type { Client } from "typesense";
import type { MultiSearchRequestSchema } from "typesense/lib/Typesense/MultiSearch.js";
import type {
SearchResponseHit,
DocumentSchema,
} from "typesense/lib/Typesense/Documents.js";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { VectorStore... | langchainjs/libs/langchain-community/src/vectorstores/typesense.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/typesense.ts",
"repo_id": "langchainjs",
"token_count": 3164
} | 1,056 |
import { Readable } from "stream";
import { GoogleAuth, GoogleAuthOptions } from "google-auth-library";
import {
GoogleAbstractedClient,
GoogleAbstractedClientOps,
} from "../types/googlevertexai-types.js";
import { GoogleVertexAIStream } from "./googlevertexai-connection.js";
class GoogleVertexAINodeStream extend... | langchainjs/libs/langchain-community/src/utils/googlevertexai-gauth.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/utils/googlevertexai-gauth.ts",
"repo_id": "langchainjs",
"token_count": 360
} | 1,020 |
from llama_index.core.llms.base import BaseLLM
from llama_index.llms.nvidia_tensorrt import LocalTensorRTLLM
def test_embedding_class():
names_of_base_classes = [b.__name__ for b in LocalTensorRTLLM.__mro__]
assert BaseLLM.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/llms/llama-index-llms-nvidia-tensorrt/tests/test_llms_nvidia_tensorrt.py/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-nvidia-tensorrt/tests/test_llms_nvidia_tensorrt.py",
"repo_id": "llama_index",
"token_count": 103
} | 1,290 |
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/src/transformers/models/cvt/configuration_cvt.py/0 | {
"file_path": "transformers/src/transformers/models/cvt/configuration_cvt.py",
"repo_id": "transformers",
"token_count": 2781
} | 586 |
mod ffi;
use candle::backend::BackendStorage;
use candle::cuda_backend::cudarc::driver::DevicePtr;
use candle::cuda_backend::WrapErr;
use candle::{CpuStorage, DType, Layout, Result, Shape, Tensor};
use half::{bf16, f16};
pub struct FlashAttn {
pub softmax_scale: f32,
pub alibi_slopes: Option<Tensor>,
pub ... | candle/candle-flash-attn/src/lib.rs/0 | {
"file_path": "candle/candle-flash-attn/src/lib.rs",
"repo_id": "candle",
"token_count": 15951
} | 51 |
python_sources()
| llama_index/llama-index-core/llama_index/core/indices/common/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/indices/common/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,189 |
"""Utility functions for working with vectors and vectorstores."""
from enum import Enum
from typing import List, Tuple, Type
import numpy as np
from langchain_core.documents import Document
from langchain_community.utils.math import cosine_similarity
class DistanceStrategy(str, Enum):
"""Enumerator of the Dis... | langchain/libs/community/langchain_community/vectorstores/utils.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/utils.py",
"repo_id": "langchain",
"token_count": 1016
} | 337 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import tqdm as hf_tqdm
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlite3
i... | datasets/src/datasets/io/sql.py/0 | {
"file_path": "datasets/src/datasets/io/sql.py",
"repo_id": "datasets",
"token_count": 2040
} | 139 |
"""Callback Handler streams to stdout on new llm token."""
import sys
from typing import Any, Dict, List, Optional
from langchain_core.callbacks import StreamingStdOutCallbackHandler
DEFAULT_ANSWER_PREFIX_TOKENS = ["Final", "Answer", ":"]
class FinalStreamingStdOutCallbackHandler(StreamingStdOutCallbackHandler):
... | langchain/libs/langchain/langchain/callbacks/streaming_stdout_final_only.py/0 | {
"file_path": "langchain/libs/langchain/langchain/callbacks/streaming_stdout_final_only.py",
"repo_id": "langchain",
"token_count": 1491
} | 451 |
# coding=utf-8
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | transformers/tests/models/bloom/test_tokenization_bloom.py/0 | {
"file_path": "transformers/tests/models/bloom/test_tokenization_bloom.py",
"repo_id": "transformers",
"token_count": 3390
} | 710 |
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | transformers/utils/sort_auto_mappings.py/0 | {
"file_path": "transformers/utils/sort_auto_mappings.py",
"repo_id": "transformers",
"token_count": 1812
} | 801 |
python_tests()
| llama_index/llama-index-integrations/retrievers/llama-index-retrievers-you/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/retrievers/llama-index-retrievers-you/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,587 |
import os
def get_boolean_env_var(var_name, default_value=False):
"""Retrieve the boolean value of an environment variable.
Args:
var_name (str): The name of the environment variable to retrieve.
default_value (bool): The default value to return if the variable
is not found.
Returns:
boo... | langchain/templates/rag-redis/rag_redis/config.py/0 | {
"file_path": "langchain/templates/rag-redis/rag_redis/config.py",
"repo_id": "langchain",
"token_count": 844
} | 685 |
import { OpenAI } from "@langchain/openai";
import { BufferWindowMemory } from "langchain/memory";
import { LLMChain } from "langchain/chains";
import { PromptTemplate } from "@langchain/core/prompts";
export const run = async () => {
const memory = new BufferWindowMemory({ memoryKey: "chat_history", k: 1 });
cons... | langchainjs/examples/src/memory/buffer_window.ts/0 | {
"file_path": "langchainjs/examples/src/memory/buffer_window.ts",
"repo_id": "langchainjs",
"token_count": 287
} | 838 |
"""Wrapper around YandexGPT chat models."""
from __future__ import annotations
import logging
from typing import Any, Callable, Dict, List, Optional, cast
from langchain_core.callbacks import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForLLMRun,
)
from langchain_core.language_models.chat_models import Ba... | langchain/libs/community/langchain_community/chat_models/yandex.py/0 | {
"file_path": "langchain/libs/community/langchain_community/chat_models/yandex.py",
"repo_id": "langchain",
"token_count": 3849
} | 223 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/tests/integration/alias/alias_test.go/0 | {
"file_path": "milvus/tests/integration/alias/alias_test.go",
"repo_id": "milvus",
"token_count": 2823
} | 2,157 |
from langchain_community.document_loaders.parsers.audio import (
OpenAIWhisperParser,
OpenAIWhisperParserLocal,
YandexSTTParser,
)
__all__ = ["OpenAIWhisperParser", "OpenAIWhisperParserLocal", "YandexSTTParser"]
| langchain/libs/langchain/langchain/document_loaders/parsers/audio.py/0 | {
"file_path": "langchain/libs/langchain/langchain/document_loaders/parsers/audio.py",
"repo_id": "langchain",
"token_count": 86
} | 512 |
import logging
import time
import pytest
from pymilvus import DataType
import numpy as np
from pathlib import Path
from base.client_base import TestcaseBase
from common import common_func as cf
from common import common_type as ct
from common.milvus_sys import MilvusSys
from common.common_type import CaseLabel, CheckTa... | milvus/tests/python_client/bulk_insert/test_bulk_insert_bench.py/0 | {
"file_path": "milvus/tests/python_client/bulk_insert/test_bulk_insert_bench.py",
"repo_id": "milvus",
"token_count": 4504
} | 1,882 |
# Hatena Blog Loader
This loader fetches article from your own [Hatena Blog](https://hatenablog.com/) blog posts using the AtomPub API.
You can get AtomPub info from the admin page after logging into Hatena Blog.
## Usage
Here's an example usage of the HatenaBlogReader.
```python
from llama_index import download_l... | llama_index/llama-index-integrations/readers/llama-index-readers-hatena-blog/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-hatena-blog/README.md",
"repo_id": "llama_index",
"token_count": 327
} | 1,333 |
import { test } from "@jest/globals";
import { OpenAI } from "@langchain/openai";
import { ConversationChain } from "../conversation.js";
test("Test ConversationChain", async () => {
const model = new OpenAI({ modelName: "gpt-3.5-turbo-instruct" });
const chain = new ConversationChain({ llm: model });
const res ... | langchainjs/langchain/src/chains/tests/conversation_chain.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/chains/tests/conversation_chain.int.test.ts",
"repo_id": "langchainjs",
"token_count": 124
} | 911 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/distributed/indexnode/service_test.go/0 | {
"file_path": "milvus/internal/distributed/indexnode/service_test.go",
"repo_id": "milvus",
"token_count": 1403
} | 1,787 |
from langchain_core.messages import AIMessage, HumanMessage
from langchain_community.chat_models.hunyuan import ChatHunyuan
def test_chat_hunyuan() -> None:
chat = ChatHunyuan()
message = HumanMessage(content="Hello")
response = chat([message])
assert isinstance(response, AIMessage)
assert isinst... | langchain/libs/community/tests/integration_tests/chat_models/test_hunyuan.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/chat_models/test_hunyuan.py",
"repo_id": "langchain",
"token_count": 266
} | 339 |
"""**Retriever** class returns Documents given a text **query**.
It is more general than a vector store. A retriever does not need to be able to
store documents, only to return (or retrieve) it. Vector stores can be used as
the backbone of a retriever, but there are other types of retrievers as well.
**Class hierarch... | langchain/libs/community/langchain_community/retrievers/__init__.py/0 | {
"file_path": "langchain/libs/community/langchain_community/retrievers/__init__.py",
"repo_id": "langchain",
"token_count": 1523
} | 276 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
MBart50TokenizerFast,
MBartForConditionalGeneration,
pipeline,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_util... | diffusers/examples/community/multilingual_stable_diffusion.py/0 | {
"file_path": "diffusers/examples/community/multilingual_stable_diffusion.py",
"repo_id": "diffusers",
"token_count": 9667
} | 212 |
#![cfg(feature = "http")]
use tokenizers::{FromPretrainedParameters, Result, Tokenizer};
#[test]
fn test_from_pretrained() -> Result<()> {
let tokenizer = Tokenizer::from_pretrained("bert-base-cased", None)?;
let encoding = tokenizer.encode("Hey there dear friend!", false)?;
assert_eq!(
encoding.ge... | tokenizers/tokenizers/tests/from_pretrained.rs/0 | {
"file_path": "tokenizers/tokenizers/tests/from_pretrained.rs",
"repo_id": "tokenizers",
"token_count": 683
} | 472 |
from llama_index.packs.auto_merging_retriever.base import AutoMergingRetrieverPack
__all__ = ["AutoMergingRetrieverPack"]
| llama_index/llama-index-packs/llama-index-packs-auto-merging-retriever/llama_index/packs/auto_merging_retriever/__init__.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-auto-merging-retriever/llama_index/packs/auto_merging_retriever/__init__.py",
"repo_id": "llama_index",
"token_count": 42
} | 1,694 |
""" MLP-Mixer, ResMLP, and gMLP in PyTorch
This impl originally based on MLP-Mixer paper.
Official JAX impl: https://github.com/google-research/vision_transformer/blob/linen/vit_jax/models_mixer.py
Paper: 'MLP-Mixer: An all-MLP Architecture for Vision' - https://arxiv.org/abs/2105.01601
@article{tolstikhin2021,
t... | pytorch-image-models/timm/models/mlp_mixer.py/0 | {
"file_path": "pytorch-image-models/timm/models/mlp_mixer.py",
"repo_id": "pytorch-image-models",
"token_count": 11661
} | 355 |
import contextlib
import copy
import fnmatch
import json
import math
import posixpath
import re
import warnings
from io import BytesIO
from pathlib import Path
from typing import Callable, Dict, List, Optional, Sequence, Tuple, Union
import fsspec
import numpy as np
from huggingface_hub import (
CommitInfo,
Co... | datasets/src/datasets/dataset_dict.py/0 | {
"file_path": "datasets/src/datasets/dataset_dict.py",
"repo_id": "datasets",
"token_count": 47125
} | 135 |
version: '3.5'
services:
etcd:
container_name: milvus-etcd
image: quay.io/coreos/etcd:v3.5.0
volumes:
- ${DOCKER_VOLUME_DIRECTORY:-.}/volumes/etcd:/etcd
command: etcd -advertise-client-urls=http://127.0.0.1:2379 -listen-client-urls http://0.0.0.0:2379 --data-dir /etcd
pulsar:
container_n... | milvus/tests/python_client/deploy/cluster/docker-compose.yml/0 | {
"file_path": "milvus/tests/python_client/deploy/cluster/docker-compose.yml",
"repo_id": "milvus",
"token_count": 2167
} | 2,179 |
//! Linear layer
//!
//! This layer applies a linear transformation to the incoming data, `y = x@w.t() + b`.
//! The bias is optional. The `forward` method can be used to apply the layer, it supports input
//! with a batch dimension (so of shape `(b_sz, in_c)`) or without (of shape `(in_c,)`), the
//! output has shape ... | candle/candle-nn/src/linear.rs/0 | {
"file_path": "candle/candle-nn/src/linear.rs",
"repo_id": "candle",
"token_count": 1120
} | 68 |
<html>
<main id="main-content">
Websites:
<a href="https://langchain.com">Langchain</a>
<a href="https://docs.langchain.com">Langchain Docs</a>
<a href="https://api.python.langchain.com/en/latest/api_reference.html"
>Langchain API Reference</a
>
</main>
</html>
| langchain/libs/community/tests/unit_tests/document_loaders/test_docs/readthedocs/index_page/test.html/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/document_loaders/test_docs/readthedocs/index_page/test.html",
"repo_id": "langchain",
"token_count": 124
} | 372 |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | datasets/metrics/f1/f1.py/0 | {
"file_path": "datasets/metrics/f1/f1.py",
"repo_id": "datasets",
"token_count": 2364
} | 130 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | transformers/examples/pytorch/speech-recognition/run_speech_recognition_ctc.py/0 | {
"file_path": "transformers/examples/pytorch/speech-recognition/run_speech_recognition_ctc.py",
"repo_id": "transformers",
"token_count": 13708
} | 577 |
from neo4j_vector_memory.chain import chain
__all__ = ["chain"]
| langchain/templates/neo4j-vector-memory/neo4j_vector_memory/__init__.py/0 | {
"file_path": "langchain/templates/neo4j-vector-memory/neo4j_vector_memory/__init__.py",
"repo_id": "langchain",
"token_count": 22
} | 645 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/core/src/common/Common.cpp/0 | {
"file_path": "milvus/internal/core/src/common/Common.cpp",
"repo_id": "milvus",
"token_count": 894
} | 1,862 |
<jupyter_start><jupyter_text>ForefrontAIThe `Forefront` platform gives you the ability to fine-tune and use [open-source large language models](https://docs.forefront.ai/forefront/master/models).This notebook goes over how to use Langchain with [ForefrontAI](https://www.forefront.ai/). Imports<jupyter_code>import os
... | langchain/docs/docs/integrations/llms/forefrontai.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/forefrontai.ipynb",
"repo_id": "langchain",
"token_count": 554
} | 114 |
from langchain.prompts.prompt import PromptTemplate
DEFAULT_INPUT_KEY = "example"
DEFAULT_PROMPT = PromptTemplate(
input_variables=[DEFAULT_INPUT_KEY], template="{example}"
)
SYNTHETIC_FEW_SHOT_PREFIX = (
"This is a test about generating synthetic data about {subject}. Examples below:"
)
SYNTHETIC_FEW_SHOT_SU... | langchain/libs/experimental/langchain_experimental/tabular_synthetic_data/prompts.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/tabular_synthetic_data/prompts.py",
"repo_id": "langchain",
"token_count": 145
} | 426 |
from langchain_core.prompts import BasePromptTemplate, format_document
__all__ = ["BasePromptTemplate", "format_document"]
| langchain/libs/langchain/langchain/schema/prompt_template.py/0 | {
"file_path": "langchain/libs/langchain/langchain/schema/prompt_template.py",
"repo_id": "langchain",
"token_count": 36
} | 590 |
from langchain_community.tools.gitlab.tool import GitLabAction
__all__ = ["GitLabAction"]
| langchain/libs/langchain/langchain/tools/gitlab/tool.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/gitlab/tool.py",
"repo_id": "langchain",
"token_count": 29
} | 555 |
# GraphQL Tool
This tool provides agents the ability to easily execute GraphQL queries against a server. The tool can be initialized with the server url and any required headers and thereafter perform queries against the server
## Usage
This tool has a more extensive example usage documented in a Jupyter notebook [h... | llama_index/llama-index-integrations/tools/llama-index-tools-graphql/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-graphql/README.md",
"repo_id": "llama_index",
"token_count": 416
} | 1,514 |
/**
* Copyright (c) Meta Platforms, Inc. and affiliates.
*
* This source code is licensed under the MIT license found in the
* LICENSE file in the root directory of this source tree.
*
* @format
*/
/**
* Creating a sidebar enables you to:
- create an ordered group of docs
- render a sidebar for each doc of t... | langchain/docs/sidebars.js/0 | {
"file_path": "langchain/docs/sidebars.js",
"repo_id": "langchain",
"token_count": 2793
} | 214 |
# DeepSparse
This page covers how to use the [DeepSparse](https://github.com/neuralmagic/deepsparse) inference runtime within LangChain.
It is broken into two parts: installation and setup, and then examples of DeepSparse usage.
## Installation and Setup
- Install the Python package with `pip install deepsparse`
- C... | langchain/docs/docs/integrations/providers/deepsparse.mdx/0 | {
"file_path": "langchain/docs/docs/integrations/providers/deepsparse.mdx",
"repo_id": "langchain",
"token_count": 406
} | 138 |
from llama_index.core.llama_pack import BaseLlamaPack
from llama_index.packs.neo4j_query_engine import Neo4jQueryEnginePack
def test_class():
names_of_base_classes = [b.__name__ for b in Neo4jQueryEnginePack.__mro__]
assert BaseLlamaPack.__name__ in names_of_base_classes
| llama_index/llama-index-packs/llama-index-packs-neo4j-query-engine/tests/test_packs_neo4j_query_engine.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-neo4j-query-engine/tests/test_packs_neo4j_query_engine.py",
"repo_id": "llama_index",
"token_count": 105
} | 1,597 |
import { OpenAI } from "@langchain/openai";
import { AWSSfnToolkit } from "@langchain/community/agents/toolkits/aws_sfn";
import { createAWSSfnAgent } from "langchain/agents/toolkits/aws_sfn";
const _EXAMPLE_STATE_MACHINE_ASL = `
{
"Comment": "A simple example of the Amazon States Language to define a state machine ... | langchainjs/examples/src/agents/aws_sfn.ts/0 | {
"file_path": "langchainjs/examples/src/agents/aws_sfn.ts",
"repo_id": "langchainjs",
"token_count": 601
} | 808 |
from langchain_community.chat_message_histories.astradb import (
AstraDBChatMessageHistory,
)
__all__ = ["AstraDBChatMessageHistory"]
| langchain/libs/langchain/langchain/memory/chat_message_histories/astradb.py/0 | {
"file_path": "langchain/libs/langchain/langchain/memory/chat_message_histories/astradb.py",
"repo_id": "langchain",
"token_count": 46
} | 523 |
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