text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
from llama_index.core.readers.base import BasePydanticReader
from llama_index.readers.twitter import TwitterTweetReader
def test_class():
names_of_base_classes = [b.__name__ for b in TwitterTweetReader.__mro__]
assert BasePydanticReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-twitter/tests/test_readers_twitter.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-twitter/tests/test_readers_twitter.py",
"repo_id": "llama_index",
"token_count": 93
} | 1,439 |
<jupyter_start><jupyter_text>Amazon Product Extraction PackThis LlamaPack provides an example of our Amazon Product Extraction pack.<jupyter_code>import nest_asyncio
nest_asyncio.apply()
from llama_index.core.llama_pack import download_llama_pack
AmazonProductExtractionPack = download_llama_pack(
"AmazonProductEx... | llama_index/llama-index-packs/llama-index-packs-amazon-product-extraction/examples/product_extraction.ipynb/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-amazon-product-extraction/examples/product_extraction.ipynb",
"repo_id": "llama_index",
"token_count": 448
} | 1,573 |
# 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 applicabl... | diffusers/src/diffusers/models/unets/unet_1d.py/0 | {
"file_path": "diffusers/src/diffusers/models/unets/unet_1d.py",
"repo_id": "diffusers",
"token_count": 4858
} | 238 |
from langchain_pinecone import __all__
EXPECTED_ALL = [
"Pinecone",
]
def test_all_imports() -> None:
assert sorted(EXPECTED_ALL) == sorted(__all__)
| langchain/libs/partners/pinecone/tests/unit_tests/test_imports.py/0 | {
"file_path": "langchain/libs/partners/pinecone/tests/unit_tests/test_imports.py",
"repo_id": "langchain",
"token_count": 64
} | 697 |
"""Mock text splitter."""
from typing import Any, List, Optional
def patch_token_splitter_newline(
self: Any, text: str, metadata_str: Optional[str] = None
) -> List[str]:
"""Mock token splitter by newline."""
if text == "":
return []
return text.split("\n")
def mock_token_splitter_newline(... | llama_index/llama-index-core/tests/mock_utils/mock_text_splitter.py/0 | {
"file_path": "llama_index/llama-index-core/tests/mock_utils/mock_text_splitter.py",
"repo_id": "llama_index",
"token_count": 191
} | 1,225 |
"""General prompt helper that can help deal with LLM context window token limitations.
At its core, it calculates available context size by starting with the context window
size of an LLM and reserve token space for the prompt template, and the output.
It provides utility for "repacking" text chunks (retrieved from i... | llama_index/llama-index-legacy/llama_index/legacy/indices/prompt_helper.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/prompt_helper.py",
"repo_id": "llama_index",
"token_count": 4533
} | 1,720 |
# rag-chroma-multi-modal
Multi-modal LLMs enable visual assistants that can perform question-answering about images.
This template create a visual assistant for slide decks, which often contain visuals such as graphs or figures.
It uses OpenCLIP embeddings to embed all of the slide images and stores them in Chroma... | langchain/templates/rag-chroma-multi-modal/README.md/0 | {
"file_path": "langchain/templates/rag-chroma-multi-modal/README.md",
"repo_id": "langchain",
"token_count": 1261
} | 675 |
<jupyter_start><jupyter_text>Refine If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-llms-openai
!pip install llama-index<jupyter_output><empty_output><jupyter_text>Download Data<jupyter_code>!mkdir -p 'data/paul_graham/'
!wget 'https://raw... | llama_index/docs/examples/response_synthesizers/refine.ipynb/0 | {
"file_path": "llama_index/docs/examples/response_synthesizers/refine.ipynb",
"repo_id": "llama_index",
"token_count": 517
} | 1,078 |
#!/usr/bin/env python
# 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/LI... | transformers/examples/tensorflow/image-classification/run_image_classification.py/0 | {
"file_path": "transformers/examples/tensorflow/image-classification/run_image_classification.py",
"repo_id": "transformers",
"token_count": 10735
} | 541 |
<!--Copyright 2023 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/tasks/zero_shot_object_detection.md/0 | {
"file_path": "transformers/docs/source/en/tasks/zero_shot_object_detection.md",
"repo_id": "transformers",
"token_count": 3901
} | 526 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,254 |
<jupyter_start><jupyter_text>OnDemandLoaderTool TutorialOur `OnDemandLoaderTool` is a powerful agent tool that allows for "on-demand" data querying from any data source on LlamaHub.This tool takes in a `BaseReader` data loader, and when called will 1) load data, 2) index data, and 3) query the data.In this walkthrough,... | llama_index/docs/examples/tools/OnDemandLoaderTool.ipynb/0 | {
"file_path": "llama_index/docs/examples/tools/OnDemandLoaderTool.ipynb",
"repo_id": "llama_index",
"token_count": 1137
} | 1,163 |
from llama_index.core.agent.react.base import ReActAgent
from llama_index.core.agent.react.formatter import ReActChatFormatter
from llama_index.core.agent.react.step import ReActAgentWorker
__all__ = ["ReActChatFormatter", "ReActAgentWorker", "ReActAgent"]
| llama_index/llama-index-core/llama_index/core/agent/react/__init__.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/agent/react/__init__.py",
"repo_id": "llama_index",
"token_count": 84
} | 1,160 |
"""Test CallbackManager."""
from unittest.mock import patch
import pytest
from langchain_core.callbacks.manager import CallbackManager, trace_as_chain_group
from langchain_core.outputs import LLMResult
from langchain_core.tracers.langchain import LangChainTracer, wait_for_all_tracers
from langchain_community.callback... | langchain/libs/community/tests/unit_tests/callbacks/test_callback_manager.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/callbacks/test_callback_manager.py",
"repo_id": "langchain",
"token_count": 2147
} | 397 |
// 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/pkg/mq/msgstream/mq_msgstream.go/0 | {
"file_path": "milvus/pkg/mq/msgstream/mq_msgstream.go",
"repo_id": "milvus",
"token_count": 11278
} | 1,823 |
# coding=utf-8
# Copyright 2023 The Suno AI Authors and 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/... | transformers/src/transformers/models/bark/modeling_bark.py/0 | {
"file_path": "transformers/src/transformers/models/bark/modeling_bark.py",
"repo_id": "transformers",
"token_count": 37224
} | 620 |
python_tests()
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-supabase/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-supabase/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,539 |
# Metric Card for Spearman Correlation Coefficient Metric (spearmanr)
## Metric Description
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0 implying no correlation.
Positive correlation... | datasets/metrics/spearmanr/README.md/0 | {
"file_path": "datasets/metrics/spearmanr/README.md",
"repo_id": "datasets",
"token_count": 1585
} | 130 |
# flake8: noqa
STRUCTURED_FORMAT_INSTRUCTIONS = """The output should be a markdown code snippet formatted in the following schema, including the leading and trailing "```json" and "```":
```json
{{
{format}
}}
```"""
STRUCTURED_FORMAT_SIMPLE_INSTRUCTIONS = """
```json
{{
{format}
}}
```"""
PYDANTIC_FORMAT_INSTRUCT... | langchain/libs/langchain/langchain/output_parsers/format_instructions.py/0 | {
"file_path": "langchain/libs/langchain/langchain/output_parsers/format_instructions.py",
"repo_id": "langchain",
"token_count": 1165
} | 533 |
from abc import abstractmethod
from typing import Any, Optional, Protocol, Sequence, runtime_checkable
from langchain_core.callbacks import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain_core.pydantic_v1 import Field
from langchain_core.tools import BaseTool
from langchain_commu... | langchain/libs/community/langchain_community/tools/memorize/tool.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/memorize/tool.py",
"repo_id": "langchain",
"token_count": 689
} | 288 |
from __future__ import annotations
import logging
import os
from abc import ABC, abstractmethod
from typing import (
TYPE_CHECKING,
Any,
Dict,
Generic,
List,
Optional,
Tuple,
Type,
TypeVar,
Union,
)
from langchain.callbacks.manager import CallbackManagerForChainRun
from langcha... | langchain/libs/experimental/langchain_experimental/rl_chain/base.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/rl_chain/base.py",
"repo_id": "langchain",
"token_count": 9221
} | 424 |
package proxy
import (
"context"
"fmt"
"reflect"
"strings"
"sync"
"github.com/casbin/casbin/v2"
"github.com/casbin/casbin/v2/model"
"go.uber.org/zap"
"google.golang.org/grpc"
"google.golang.org/grpc/codes"
"google.golang.org/grpc/status"
"github.com/milvus-io/milvus-proto/go-api/v2/commonpb"
"github.com... | milvus/internal/proxy/privilege_interceptor.go/0 | {
"file_path": "milvus/internal/proxy/privilege_interceptor.go",
"repo_id": "milvus",
"token_count": 2333
} | 1,883 |
"""LangSmith langchain_client Integration Tests."""
import datetime
import io
import os
import random
import string
import time
from datetime import timedelta
from typing import Any, Callable, Dict, cast
from uuid import uuid4
import pytest
from freezegun import freeze_time
from langchain.schema import FunctionMessag... | langsmith-sdk/python/tests/integration_tests/test_client.py/0 | {
"file_path": "langsmith-sdk/python/tests/integration_tests/test_client.py",
"repo_id": "langsmith-sdk",
"token_count": 8215
} | 1,082 |
<jupyter_start><jupyter_text>Get References from PDFs This guide shows you how to use LlamaIndex to get in-line page number citations in the response (and the response is streamed).This is a simple combination of using the page number metadata in our PDF loader along with our indexing/query abstractions to use this inf... | llama_index/docs/examples/citation/pdf_page_reference.ipynb/0 | {
"file_path": "llama_index/docs/examples/citation/pdf_page_reference.ipynb",
"repo_id": "llama_index",
"token_count": 1103
} | 1,106 |
{
"modelname": "NewTFENCDEC",
"uppercase_modelname": "NEW_TF_ENC_DEC",
"lowercase_modelname": "new_tf_enc_dec_template",
"camelcase_modelname": "NewTFEncDec",
"authors": "The HuggingFace Team",
"checkpoint_identifier": "new-tf-enc-dec-base_template",
"tokenizer_type": "Based on BART",
"generate_tensorfl... | transformers/templates/adding_a_new_model/tests/tf-seq-2-seq-bart-tokenizer.json/0 | {
"file_path": "transformers/templates/adding_a_new_model/tests/tf-seq-2-seq-bart-tokenizer.json",
"repo_id": "transformers",
"token_count": 159
} | 777 |
# 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/lilt/test_modeling_lilt.py/0 | {
"file_path": "transformers/tests/models/lilt/test_modeling_lilt.py",
"repo_id": "transformers",
"token_count": 5376
} | 821 |
"""Base query engine."""
import logging
from abc import abstractmethod
from typing import Any, Dict, List, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.core.query_pipeline.query_component import (
Chai... | llama_index/llama-index-legacy/llama_index/legacy/core/base_query_engine.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/core/base_query_engine.py",
"repo_id": "llama_index",
"token_count": 1651
} | 1,645 |
// 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/exec/expression/Expr.h/0 | {
"file_path": "milvus/internal/core/src/exec/expression/Expr.h",
"repo_id": "milvus",
"token_count": 6416
} | 1,785 |
import os
from langchain.retrievers import GoogleVertexAISearchRetriever
from langchain_community.chat_models import ChatVertexAI
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.pydantic_v1 import BaseModel
from langchain_core.runnable... | langchain/templates/rag-google-cloud-vertexai-search/rag_google_cloud_vertexai_search/chain.py/0 | {
"file_path": "langchain/templates/rag-google-cloud-vertexai-search/rag_google_cloud_vertexai_search/chain.py",
"repo_id": "langchain",
"token_count": 481
} | 692 |
{
"name": "@cfworker/json-schema",
"type": "module",
"version": "1.12.5",
"description": "A JSON schema validator that will run on Cloudflare workers. Supports drafts 4, 7, 2019-09, and 2020-12.",
"keywords": [
"json-schema",
"jsonschema",
"json",
"schema",
"cloudflare",
"worker",
... | langchainjs/langchain-core/src/utils/@cfworker/json-schema/package.json/0 | {
"file_path": "langchainjs/langchain-core/src/utils/@cfworker/json-schema/package.json",
"repo_id": "langchainjs",
"token_count": 606
} | 884 |
<!--Copyright 2023 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/fast_tokenizers.md/0 | {
"file_path": "transformers/docs/source/ja/fast_tokenizers.md",
"repo_id": "transformers",
"token_count": 1187
} | 487 |
# Observability
LlamaIndex provides **one-click observability** 🔭 to allow you to build principled LLM applications in a production setting.
A key requirement for principled development of LLM applications over your data (RAG systems, agents) is being able to observe, debug, and evaluate
your system - both as a whol... | llama_index/docs/module_guides/observability/observability.md/0 | {
"file_path": "llama_index/docs/module_guides/observability/observability.md",
"repo_id": "llama_index",
"token_count": 3113
} | 1,147 |
from langchain_community.llms.vllm import VLLM, VLLMOpenAI
__all__ = ["VLLM", "VLLMOpenAI"]
| langchain/libs/langchain/langchain/llms/vllm.py/0 | {
"file_path": "langchain/libs/langchain/langchain/llms/vllm.py",
"repo_id": "langchain",
"token_count": 41
} | 526 |
# 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 applicabl... | diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_combined.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_combined.py",
"repo_id": "diffusers",
"token_count": 18700
} | 244 |
from llama_index.readers.airbyte_salesforce.base import AirbyteSalesforceReader
__all__ = ["AirbyteSalesforceReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-salesforce/llama_index/readers/airbyte_salesforce/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-salesforce/llama_index/readers/airbyte_salesforce/__init__.py",
"repo_id": "llama_index",
"token_count": 37
} | 1,400 |
<jupyter_start><jupyter_text>Multivariate Probabilistic Time Series Forecasting with Informer IntroductionA few months ago we introduced the [Time Series Transformer](https://huggingface.co/blog/time-series-transformers), which is the vanilla Transformer ([Vaswani et al., 2017](https://arxiv.org/abs/1706.03762)) applie... | notebooks/examples/multivariate_informer.ipynb/0 | {
"file_path": "notebooks/examples/multivariate_informer.ipynb",
"repo_id": "notebooks",
"token_count": 15125
} | 323 |
from langchain_community.embeddings.huggingface import (
HuggingFaceBgeEmbeddings,
HuggingFaceEmbeddings,
HuggingFaceInferenceAPIEmbeddings,
HuggingFaceInstructEmbeddings,
)
__all__ = [
"HuggingFaceEmbeddings",
"HuggingFaceInstructEmbeddings",
"HuggingFaceBgeEmbeddings",
"HuggingFaceInf... | langchain/libs/langchain/langchain/embeddings/huggingface.py/0 | {
"file_path": "langchain/libs/langchain/langchain/embeddings/huggingface.py",
"repo_id": "langchain",
"token_count": 134
} | 498 |
package typeutil
import (
"fmt"
"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
)
func genEmptyBoolFieldData(field *schemapb.FieldSchema) *schemapb.FieldData {
return &schemapb.FieldData{
Type: field.GetDataType(),
FieldName: field.GetName(),
Field: &schemapb.FieldData_Scalars{
Scalars: &sche... | milvus/pkg/util/typeutil/gen_empty_field_data.go/0 | {
"file_path": "milvus/pkg/util/typeutil/gen_empty_field_data.go",
"repo_id": "milvus",
"token_count": 2896
} | 1,853 |
export { RunnableAssign, RunnablePassthrough } from "@langchain/core/runnables";
| langchainjs/langchain/src/schema/runnable/passthrough.ts/0 | {
"file_path": "langchainjs/langchain/src/schema/runnable/passthrough.ts",
"repo_id": "langchainjs",
"token_count": 28
} | 965 |
---
hide_table_of_contents: true
---
import CodeBlock from "@theme/CodeBlock";
import Comparisons from "@examples/guides/evaluation/examples/comparisons.ts";
# Comparing Chain Outputs
Suppose you have two different prompts (or LLMs). How do you know which will generate "better" results?
One automated way to predict... | langchainjs/docs/core_docs/docs/guides/evaluation/examples/comparisons.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/guides/evaluation/examples/comparisons.mdx",
"repo_id": "langchainjs",
"token_count": 385
} | 750 |
# 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/tests/utils/test_offline.py/0 | {
"file_path": "transformers/tests/utils/test_offline.py",
"repo_id": "transformers",
"token_count": 2916
} | 763 |
<jupyter_start><jupyter_text>Timeouts for agentsThis notebook walks through how to cap an agent executor after a certain amount of time. This can be useful for safeguarding against long running agent runs.<jupyter_code>%pip install --upgrade --quiet wikipedia
from langchain import hub
from langchain.agents import Agen... | langchain/docs/docs/modules/agents/how_to/max_time_limit.ipynb/0 | {
"file_path": "langchain/docs/docs/modules/agents/how_to/max_time_limit.ipynb",
"repo_id": "langchain",
"token_count": 1067
} | 196 |
import {
ChatPromptTemplate,
HumanMessagePromptTemplate,
MessagesPlaceholder,
} from "@langchain/core/prompts";
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIToolsAgent, AgentExecutor } from "langchain/agents";
import { SqlToolkit } from "langchain/agents/toolkits/sql";
import { AIMessage }... | langchainjs/examples/src/use_cases/sql/agents/index.ts/0 | {
"file_path": "langchainjs/examples/src/use_cases/sql/agents/index.ts",
"repo_id": "langchainjs",
"token_count": 1326
} | 826 |
from transformers import AutoTokenizer, AutoModel
import torch
import torch.nn.functional as F
# Helper: Mean Pooling - Take attention mask into account for correct averaging
def mean_pooling(model_output, attention_mask):
token_embeddings = model_output[0] #First element of model_output contains all token embedd... | notebooks/sagemaker/17_custom_inference_script/code/inference.py/0 | {
"file_path": "notebooks/sagemaker/17_custom_inference_script/code/inference.py",
"repo_id": "notebooks",
"token_count": 487
} | 288 |
# Scripts
A train, validation, inference, and checkpoint cleaning script included in the github root folder. Scripts are not currently packaged in the pip release.
The training and validation scripts evolved from early versions of the [PyTorch Imagenet Examples](https://github.com/pytorch/examples). I have added sign... | pytorch-image-models/hfdocs/source/training_script.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/training_script.mdx",
"repo_id": "pytorch-image-models",
"token_count": 2320
} | 335 |
---
sidebar_class_name: node-only
---
# Elasticsearch
:::tip Compatibility
Only available on Node.js.
:::
[Elasticsearch](https://github.com/elastic/elasticsearch) is a distributed, RESTful search engine optimized for speed and relevance on production-scale workloads. It supports also vector search using the [k-near... | langchainjs/docs/core_docs/docs/integrations/vectorstores/elasticsearch.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/vectorstores/elasticsearch.mdx",
"repo_id": "langchainjs",
"token_count": 584
} | 743 |
import asyncio
from typing import Any, Dict, Tuple
import pytest
from llama_index.core.indices.struct_store.base import default_output_parser
from llama_index.core.indices.struct_store.sql import SQLStructStoreIndex
from llama_index.core.indices.struct_store.sql_query import (
NLSQLTableQueryEngine,
NLStructSt... | llama_index/llama-index-core/tests/indices/struct_store/test_sql_query.py/0 | {
"file_path": "llama_index/llama-index-core/tests/indices/struct_store/test_sql_query.py",
"repo_id": "llama_index",
"token_count": 2389
} | 1,315 |
// 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/querynodev2/pipeline/delete_node_test.go/0 | {
"file_path": "milvus/internal/querynodev2/pipeline/delete_node_test.go",
"repo_id": "milvus",
"token_count": 1261
} | 1,766 |
# 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/src/transformers/models/upernet/convert_swin_upernet_to_pytorch.py/0 | {
"file_path": "transformers/src/transformers/models/upernet/convert_swin_upernet_to_pytorch.py",
"repo_id": "transformers",
"token_count": 6234
} | 689 |
<jupyter_start><jupyter_text>NVIDIA NeMo embeddings Connect to NVIDIA's embedding service using the `NeMoEmbeddings` class.The NeMo Retriever Embedding Microservice (NREM) brings the power of state-of-the-art text embedding to your applications, providing unmatched natural language processing and understanding capabili... | langchain/docs/docs/integrations/text_embedding/nemo.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/text_embedding/nemo.ipynb",
"repo_id": "langchain",
"token_count": 346
} | 174 |
<jupyter_start><jupyter_text>Enum parserThis notebook shows how to use an Enum output parser.<jupyter_code>from langchain.output_parsers.enum import EnumOutputParser
from enum import Enum
class Colors(Enum):
RED = "red"
GREEN = "green"
BLUE = "blue"
parser = EnumOutputParser(enum=Colors)
from langchain_co... | langchain/docs/docs/modules/model_io/output_parsers/types/enum.ipynb/0 | {
"file_path": "langchain/docs/docs/modules/model_io/output_parsers/types/enum.ipynb",
"repo_id": "langchain",
"token_count": 231
} | 205 |
from pathlib import Path
from typing import Dict, List, Optional
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document, ImageDocument
class ImageTabularChartReader(BaseReader):
"""Image parser.
Extract tabular data from a chart or figure.
"""
def __init_... | llama_index/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image_deplot/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image_deplot/base.py",
"repo_id": "llama_index",
"token_count": 1472
} | 1,437 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-cohere/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-cohere/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,357 |
from llama_index.readers.opendal.azblob.base import OpendalAzblobReader
from llama_index.readers.opendal.base import OpendalReader
from llama_index.readers.opendal.gcs.base import OpendalGcsReader
from llama_index.readers.opendal.s3.base import OpendalS3Reader
__all__ = [
"OpendalReader",
"OpendalAzblobReader"... | llama_index/llama-index-integrations/readers/llama-index-readers-opendal/llama_index/readers/opendal/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-opendal/llama_index/readers/opendal/__init__.py",
"repo_id": "llama_index",
"token_count": 153
} | 1,497 |
/* eslint-disable no-process-env */
/* eslint-disable @typescript-eslint/no-non-null-assertion */
import { beforeAll, expect, test } from "@jest/globals";
import { Document } from "@langchain/core/documents";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { SyntheticEmbeddings } from "@la... | langchainjs/libs/langchain-community/src/vectorstores/tests/googlevertexai.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/tests/googlevertexai.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1918
} | 1,019 |
---
sidebar_position: 0
sidebar_class_name: hidden
---
# Stuff
The stuff documents chain ("stuff" as in "to stuff" or "to fill") is the most straightforward of the document chains. It takes a list of documents, inserts them all into a prompt and passes that prompt to an LLM.
This chain is well-suited for application... | langchainjs/docs/core_docs/docs/modules/chains/document/stuff.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/modules/chains/document/stuff.mdx",
"repo_id": "langchainjs",
"token_count": 244
} | 783 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/readers/llama-index-readers-bitbucket/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-bitbucket/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,472 |
# coding=utf-8
# Copyright 2023 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/check_task_guides.py/0 | {
"file_path": "transformers/utils/check_task_guides.py",
"repo_id": "transformers",
"token_count": 2721
} | 845 |
---
hide_table_of_contents: true
---
import CodeBlock from "@theme/CodeBlock";
# MongoDB Chat Memory
For longer-term persistence across chat sessions, you can swap out the default in-memory `chatHistory` that backs chat memory classes like `BufferMemory` for a MongoDB instance.
## Setup
You need to install Node Mo... | langchainjs/docs/core_docs/docs/integrations/chat_memory/mongodb.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/chat_memory/mongodb.mdx",
"repo_id": "langchainjs",
"token_count": 252
} | 724 |
from langchain_community.graphs import Neo4jGraph
graph = Neo4jGraph()
# Import sample data
graph.query(
"""
MERGE (m:Movie {name:"Top Gun"})
WITH m
UNWIND ["Tom Cruise", "Val Kilmer", "Anthony Edwards", "Meg Ryan"] AS actor
MERGE (a:Person {name:actor})
MERGE (a)-[:ACTED_IN]->(m)
"""
)
# Create full text index ... | langchain/templates/neo4j-cypher-ft/ingest.py/0 | {
"file_path": "langchain/templates/neo4j-cypher-ft/ingest.py",
"repo_id": "langchain",
"token_count": 178
} | 655 |
python_sources()
| llama_index/llama-index-legacy/llama_index/legacy/response_synthesizers/google/generativeai/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/response_synthesizers/google/generativeai/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,639 |
"""
Implementation of a custom transfer agent for the transfer type "multipart" for git-lfs.
Inspired by: github.com/cbartz/git-lfs-swift-transfer-agent/blob/master/git_lfs_swift_transfer.py
Spec is: github.com/git-lfs/git-lfs/blob/master/docs/custom-transfers.md
To launch debugger while developing:
``` [lfs "cust... | transformers/src/transformers/commands/lfs.py/0 | {
"file_path": "transformers/src/transformers/commands/lfs.py",
"repo_id": "transformers",
"token_count": 3515
} | 629 |
"""EverlyAI Endpoints chat wrapper. Relies heavily on ChatOpenAI."""
from __future__ import annotations
import logging
import sys
from typing import TYPE_CHECKING, Dict, Optional, Set
from langchain_core.messages import BaseMessage
from langchain_core.pydantic_v1 import Field, root_validator
from langchain_core.utils... | langchain/libs/community/langchain_community/chat_models/everlyai.py/0 | {
"file_path": "langchain/libs/community/langchain_community/chat_models/everlyai.py",
"repo_id": "langchain",
"token_count": 2407
} | 225 |
<!--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/model_doc/biogpt.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/biogpt.md",
"repo_id": "transformers",
"token_count": 1982
} | 514 |
---
sidebar_position: 2
---
# Prompting strategies
In this guide we'll go over prompting strategies to improve SQL query generation.
We'll largely focus on methods for getting relevant database-specific information in your prompt.
## Setup
First, install the required packages and set your environment variables. Thi... | langchainjs/docs/core_docs/docs/use_cases/sql/prompting.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/use_cases/sql/prompting.mdx",
"repo_id": "langchainjs",
"token_count": 1108
} | 825 |
poetry_requirements(
name="poetry",
)
python_requirements(
name="reqs",
)
| llama_index/llama-index-integrations/readers/llama-index-readers-telegram/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-telegram/BUILD",
"repo_id": "llama_index",
"token_count": 36
} | 1,425 |
# flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.
# Copyright 2022 The HuggingFace Team and The OpenBMB Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
... | transformers/src/transformers/models/cpmant/__init__.py/0 | {
"file_path": "transformers/src/transformers/models/cpmant/__init__.py",
"repo_id": "transformers",
"token_count": 776
} | 595 |
<!--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/decision_transformer.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/decision_transformer.md",
"repo_id": "transformers",
"token_count": 639
} | 487 |
import React from "react";
import HeaderEvaluator, { MenuItem } from "../../components/HeaderEvaluator";
import { UserCardImage } from "../../components/PersonCard";
import { Center, Group } from "@mantine/core";
const AboutPage = () => {
return (
<>
<HeaderEvaluator activeTab={MenuItem.About} />
<Ce... | auto-evaluator/nextjs/pages/about/index.tsx/0 | {
"file_path": "auto-evaluator/nextjs/pages/about/index.tsx",
"repo_id": "auto-evaluator",
"token_count": 585
} | 2 |
from langchain_community.vectorstores.docarray.hnsw import DocArrayHnswSearch
__all__ = ["DocArrayHnswSearch"]
| langchain/libs/langchain/langchain/vectorstores/docarray/hnsw.py/0 | {
"file_path": "langchain/libs/langchain/langchain/vectorstores/docarray/hnsw.py",
"repo_id": "langchain",
"token_count": 36
} | 583 |
python_tests()
| llama_index/llama-index-packs/llama-index-packs-nebulagraph-query-engine/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-nebulagraph-query-engine/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,662 |
<jupyter_start><jupyter_text>ChatGPT PluginsThis example shows how to use ChatGPT Plugins within LangChain abstractions.Note 1: This currently only works for plugins with no auth.Note 2: There are almost certainly other ways to do this, this is just a first pass. If you have better ideas, please open a PR!<jupyter_code... | langchain/docs/docs/integrations/tools/chatgpt_plugins.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/tools/chatgpt_plugins.ipynb",
"repo_id": "langchain",
"token_count": 565
} | 173 |
# 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/tests/models/whisper/test_modeling_tf_whisper.py/0 | {
"file_path": "transformers/tests/models/whisper/test_modeling_tf_whisper.py",
"repo_id": "transformers",
"token_count": 21571
} | 780 |
python_sources()
| llama_index/llama-index-legacy/llama_index/legacy/tools/tool_spec/slack/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/tools/tool_spec/slack/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,526 |
from typing import (
TYPE_CHECKING,
Any,
Dict,
Iterable,
List,
Optional,
Sequence,
Type,
cast,
)
if TYPE_CHECKING:
from marvin import ai_model
from llama_index.core.bridge.pydantic import BaseModel, Field
from llama_index.core.extractors.interface import BaseExtractor
from llam... | llama_index/llama-index-integrations/extractors/llama-index-extractors-marvin/llama_index/extractors/marvin/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/extractors/llama-index-extractors-marvin/llama_index/extractors/marvin/base.py",
"repo_id": "llama_index",
"token_count": 1257
} | 1,207 |
from typing import Tuple
from langchain_core.output_parsers import BaseOutputParser
from langchain_core.prompts import PromptTemplate
class FinishedOutputParser(BaseOutputParser[Tuple[str, bool]]):
"""Output parser that checks if the output is finished."""
finished_value: str = "FINISHED"
"""Value that ... | langchain/libs/langchain/langchain/chains/flare/prompts.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/flare/prompts.py",
"repo_id": "langchain",
"token_count": 473
} | 458 |
import unittest
from langchain_community.document_loaders.parsers.language.python import PythonSegmenter
class TestPythonSegmenter(unittest.TestCase):
def setUp(self) -> None:
self.example_code = """import os
def hello(text):
print(text)
class Simple:
def __init__(self):
self.a = 1
hel... | langchain/libs/community/tests/unit_tests/document_loaders/parsers/language/test_python.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/document_loaders/parsers/language/test_python.py",
"repo_id": "langchain",
"token_count": 463
} | 403 |
# 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/src/transformers/models/auto/image_processing_auto.py/0 | {
"file_path": "transformers/src/transformers/models/auto/image_processing_auto.py",
"repo_id": "transformers",
"token_count": 8645
} | 581 |
# flake8: noqa
NASA_SEARCH_PROMPT = """
This tool is a wrapper around NASA's search API, useful when you need to search through NASA's Image and Video Library.
The input to this tool is a query specified by the user, and will be passed into NASA's `search` function.
At least one parameter must be prov... | langchain/libs/community/langchain_community/tools/nasa/prompt.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/nasa/prompt.py",
"repo_id": "langchain",
"token_count": 1626
} | 309 |
<!--Copyright 2023 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... | peft/docs/source/package_reference/multitask_prompt_tuning.md/0 | {
"file_path": "peft/docs/source/package_reference/multitask_prompt_tuning.md",
"repo_id": "peft",
"token_count": 533
} | 324 |
import { Chroma } from "@langchain/community/vectorstores/chroma";
import { OpenAIEmbeddings } from "@langchain/openai";
import { TextLoader } from "langchain/document_loaders/fs/text";
// Create docs with a loader
const loader = new TextLoader("src/document_loaders/example_data/example.txt");
const docs = await loade... | langchainjs/examples/src/indexes/vector_stores/chroma/fromDocs.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/chroma/fromDocs.ts",
"repo_id": "langchainjs",
"token_count": 320
} | 800 |
# candle-datasets
| candle/candle-datasets/README.md/0 | {
"file_path": "candle/candle-datasets/README.md",
"repo_id": "candle",
"token_count": 7
} | 33 |
import pytest
from langchain.agents.openai_assistant import OpenAIAssistantRunnable
@pytest.mark.requires("openai")
def test_user_supplied_client() -> None:
import openai
client = openai.AzureOpenAI(
azure_endpoint="azure_endpoint",
api_key="api_key",
api_version="api_version",
)... | langchain/libs/langchain/tests/unit_tests/agents/test_openai_assistant.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/agents/test_openai_assistant.py",
"repo_id": "langchain",
"token_count": 190
} | 621 |
import CodeBlock from "@theme/CodeBlock";
import Example from "@examples/tools/connery.ts";
import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
# Connery Action Tool
Using this tool, you can integrate individual Connery Action into your LangChain agent.
:::note
If you want to use... | langchainjs/docs/core_docs/docs/integrations/tools/connery.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/tools/connery.mdx",
"repo_id": "langchainjs",
"token_count": 637
} | 745 |
# 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/tests/models/reformer/test_tokenization_reformer.py/0 | {
"file_path": "transformers/tests/models/reformer/test_tokenization_reformer.py",
"repo_id": "transformers",
"token_count": 6375
} | 765 |
import multiprocessing
import numbers
import random
import numpy
import threading
import pytest
import pandas as pd
import decimal
from decimal import Decimal, getcontext
from time import sleep
import heapq
from base.client_base import TestcaseBase
from utils.util_log import test_log as log
from common import common_f... | milvus/tests/python_client/milvus_client/test_milvus_client_delete.py/0 | {
"file_path": "milvus/tests/python_client/milvus_client/test_milvus_client_delete.py",
"repo_id": "milvus",
"token_count": 5560
} | 2,040 |
// Copyright (C) 2019-2020 Zilliz. 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 l... | milvus/internal/mq/mqimpl/rocksmq/client/producer_impl_test.go/0 | {
"file_path": "milvus/internal/mq/mqimpl/rocksmq/client/producer_impl_test.go",
"repo_id": "milvus",
"token_count": 429
} | 1,732 |
import json
import urllib.request
from typing import List, Optional
from langchain_core.documents import Document
from langchain_core.utils import get_from_env, stringify_dict
from langchain_community.document_loaders.base import BaseLoader
IUGU_ENDPOINTS = {
"invoices": "https://api.iugu.com/v1/invoices",
"... | langchain/libs/community/langchain_community/document_loaders/iugu.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/iugu.py",
"repo_id": "langchain",
"token_count": 696
} | 234 |
# Trubrics
>[Trubrics](https://trubrics.com) is an LLM user analytics platform that lets you collect, analyse and manage user
prompts & feedback on AI models.
>
>Check out [Trubrics repo](https://github.com/trubrics/trubrics-sdk) for more information on `Trubrics`.
## Installation and Setup
We need to install the ... | langchain/docs/docs/integrations/providers/trubrics.mdx/0 | {
"file_path": "langchain/docs/docs/integrations/providers/trubrics.mdx",
"repo_id": "langchain",
"token_count": 168
} | 159 |
import { PromptTemplate } from "@langchain/core/prompts";
const CYPHER_GENERATION_TEMPLATE = `Task:Generate Cypher statement to query a graph database.
Instructions:
Use only the provided relationship types and properties in the schema.
Do not use any other relationship types or properties that are not provided.
Schem... | langchainjs/langchain/src/chains/graph_qa/prompts.ts/0 | {
"file_path": "langchainjs/langchain/src/chains/graph_qa/prompts.ts",
"repo_id": "langchainjs",
"token_count": 463
} | 954 |
# for backwards compatibility
from llama_index.core.base.base_query_engine import BaseQueryEngine
__all__ = [
"BaseQueryEngine",
]
| llama_index/llama-index-core/llama_index/core/indices/query/base.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/indices/query/base.py",
"repo_id": "llama_index",
"token_count": 43
} | 1,180 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#include "column_remap.cuh"
#include "../util.cuh"
const int SHUF_BLOCKSIZE_X = 256;
const int SHUF_BLOCKSIZE_Y = 16;
__global__ void column_remap_kernel
(
const half* __restrict__ x,
half* __restrict__ x_new,
const int x_width,
... | text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/column_remap.cu/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/column_remap.cu",
"repo_id": "text-generation-inference",
"token_count": 696
} | 396 |
use std::sync::{Arc, RwLock};
use pyo3::exceptions;
use pyo3::prelude::*;
use pyo3::types::*;
use crate::error::ToPyResult;
use crate::utils::{PyNormalizedString, PyNormalizedStringRefMut, PyPattern};
use serde::ser::SerializeStruct;
use serde::{Deserialize, Deserializer, Serialize, Serializer};
use tk::normalizers::... | tokenizers/bindings/python/src/normalizers.rs/0 | {
"file_path": "tokenizers/bindings/python/src/normalizers.rs",
"repo_id": "tokenizers",
"token_count": 11191
} | 461 |
import { AgentExecutor, createOpenAIToolsAgent } from "langchain/agents";
import { pull } from "langchain/hub";
import { ChatOpenAI } from "@langchain/openai";
import type { ChatPromptTemplate } from "@langchain/core/prompts";
import { TavilySearchResults } from "@langchain/community/tools/tavily_search";
import { Calc... | langchainjs/examples/src/guides/debugging/simple_agent.ts/0 | {
"file_path": "langchainjs/examples/src/guides/debugging/simple_agent.ts",
"repo_id": "langchainjs",
"token_count": 231
} | 776 |
<jupyter_start><jupyter_text>Facebook Chat>[Messenger](https://en.wikipedia.org/wiki/Messenger_(software)) is an American proprietary instant messaging app and platform developed by `Meta Platforms`. Originally developed as `Facebook Chat` in 2008, the company revamped its messaging service in 2010.This notebook covers... | langchain/docs/docs/integrations/document_loaders/facebook_chat.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/facebook_chat.ipynb",
"repo_id": "langchain",
"token_count": 177
} | 102 |
"""GitHub Toolkit."""
| langchain/libs/langchain/langchain/agents/agent_toolkits/github/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/agents/agent_toolkits/github/__init__.py",
"repo_id": "langchain",
"token_count": 9
} | 478 |
python_tests()
| llama_index/llama-index-integrations/llms/llama-index-llms-vllm/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-vllm/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,336 |
<!--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 applicable law or agreed... | transformers/docs/source/en/model_doc/rag.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/rag.md",
"repo_id": "transformers",
"token_count": 1273
} | 462 |
python_tests()
| llama_index/llama-index-integrations/readers/llama-index-readers-awadb/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-awadb/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,336 |
#include <metal_stdlib>
using namespace metal;
template<typename TYPENAME, typename INDEX_TYPENAME>
METAL_FUNC void index(
constant size_t &dst_size,
constant size_t &left_size,
constant size_t &src_dim_size,
constant size_t &right_size,
constant size_t &ids_size,
const device TYPENAME *i... | candle/candle-metal-kernels/src/indexing.metal/0 | {
"file_path": "candle/candle-metal-kernels/src/indexing.metal",
"repo_id": "candle",
"token_count": 3203
} | 54 |
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