text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
from typing import Any, Dict, List, Type, Union
from langchain_community.graphs import NetworkxEntityGraph
from langchain_community.graphs.networkx_graph import (
KnowledgeTriple,
get_entities,
parse_triples,
)
from langchain_core.language_models import BaseLanguageModel
from langchain_core.messages import... | langchain/libs/langchain/langchain/memory/kg.py/0 | {
"file_path": "langchain/libs/langchain/langchain/memory/kg.py",
"repo_id": "langchain",
"token_count": 2080
} | 549 |
# coding=utf-8
# Copyright 2022 Facebook AI Research (FAIR) 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/l... | transformers/src/transformers/models/deit/modeling_tf_deit.py/0 | {
"file_path": "transformers/src/transformers/models/deit/modeling_tf_deit.py",
"repo_id": "transformers",
"token_count": 21239
} | 644 |
python_sources()
| llama_index/llama-index-integrations/tools/llama-index-tools-playgrounds/llama_index/tools/playgrounds/subgraph_inspector/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-playgrounds/llama_index/tools/playgrounds/subgraph_inspector/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,451 |
# Glossary
This is a community-created glossary. Contributions are welcome!
- **Deep Q-Learning:** A value-based deep reinforcement learning algorithm that uses a deep neural network to approximate Q-values for actions in a given state. The goal of Deep Q-learning is to find the optimal policy that maximizes the exp... | deep-rl-class/units/en/unit4/glossary.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit4/glossary.mdx",
"repo_id": "deep-rl-class",
"token_count": 421
} | 162 |
ann_accuracy:
collections:
-
server:
cache_config.cpu_cache_capacity: 16GB
engine_config.use_blas_threshold: 1100
engine_config.gpu_search_threshold: 1
gpu_resource_config.enable: true
gpu_resource_config.cache_capacity: 4GB
gpu_resource_config.search_resource... | milvus/tests/benchmark/milvus_benchmark/suites/gpu_accuracy_ann.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/suites/gpu_accuracy_ann.yaml",
"repo_id": "milvus",
"token_count": 2785
} | 2,008 |
[tool.poetry]
name = "text-generation-server"
version = "1.4.0"
description = "Text Generation Inference Python gRPC Server"
authors = ["Olivier Dehaene <olivier@huggingface.co>"]
[tool.poetry.scripts]
text-generation-server = 'text_generation_server.cli:app'
[tool.poetry.dependencies]
python = ">=3.9,<3.13"
protobuf... | text-generation-inference/server/pyproject.toml/0 | {
"file_path": "text-generation-inference/server/pyproject.toml",
"repo_id": "text-generation-inference",
"token_count": 761
} | 380 |
import * as url from "node:url";
import * as path from "node:path";
import { test, expect } from "@jest/globals";
import { Document } from "@langchain/core/documents";
import { CSVLoader } from "../fs/csv.js";
test("Test CSV loader from file with column arg", async () => {
const filePath = path.resolve(
path.dir... | langchainjs/langchain/src/document_loaders/tests/csv.test.ts/0 | {
"file_path": "langchainjs/langchain/src/document_loaders/tests/csv.test.ts",
"repo_id": "langchainjs",
"token_count": 751
} | 919 |
"""AINetwork Blockchain tool utils."""
from __future__ import annotations
import os
from typing import TYPE_CHECKING, Literal, Optional
if TYPE_CHECKING:
from ain.ain import Ain
def authenticate(network: Optional[Literal["mainnet", "testnet"]] = "testnet") -> Ain:
"""Authenticate using the AIN Blockchain"""... | langchain/libs/community/langchain_community/tools/ainetwork/utils.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/ainetwork/utils.py",
"repo_id": "langchain",
"token_count": 1083
} | 281 |
import * as fs from "fs";
import { RecursiveCharacterTextSplitter } from "langchain/text_splitter";
import { HNSWLib } from "@langchain/community/vectorstores/hnswlib";
import { OpenAIEmbeddings } from "@langchain/openai";
import { ContextualCompressionRetriever } from "langchain/retrievers/contextual_compression";
im... | langchainjs/examples/src/retrievers/embeddings_filter.ts/0 | {
"file_path": "langchainjs/examples/src/retrievers/embeddings_filter.ts",
"repo_id": "langchainjs",
"token_count": 1146
} | 847 |
import os
from typing import List, Tuple
from google.cloud import dlp_v2
from langchain_community.chat_models import ChatVertexAI
from langchain_core.messages import AIMessage, HumanMessage
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate, MessagesPlacehol... | langchain/templates/rag-google-cloud-sensitive-data-protection/rag_google_cloud_sensitive_data_protection/chain.py/0 | {
"file_path": "langchain/templates/rag-google-cloud-sensitive-data-protection/rag_google_cloud_sensitive_data_protection/chain.py",
"repo_id": "langchain",
"token_count": 1430
} | 691 |
---
sidebar_position: 2
title: Retrieval augmented generation (RAG)
hide_table_of_contents: true
---
# RAG
Let's now look at adding in a retrieval step to a prompt and an LLM, which adds up to a "retrieval-augmented generation" chain:
<details>
<summary>Interactive tutorial</summary>
The screencast below interac... | langchainjs/docs/core_docs/docs/expression_language/cookbook/retrieval.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/expression_language/cookbook/retrieval.mdx",
"repo_id": "langchainjs",
"token_count": 603
} | 694 |
from openai_functions_agent.agent import agent_executor
__all__ = ["agent_executor"]
| langchain/templates/openai-functions-agent-gmail/openai_functions_agent/__init__.py/0 | {
"file_path": "langchain/templates/openai-functions-agent-gmail/openai_functions_agent/__init__.py",
"repo_id": "langchain",
"token_count": 28
} | 703 |
from typing import Any, Dict, Optional
import httpx
from openai import AsyncAzureOpenAI, AzureOpenAI
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr, root_validator
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.constants import DEFAULT_EMBED_BATCH_SIZE
from ll... | llama_index/llama-index-legacy/llama_index/legacy/embeddings/azure_openai.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/embeddings/azure_openai.py",
"repo_id": "llama_index",
"token_count": 1903
} | 1,557 |
# (Optional) What is Curiosity in Deep Reinforcement Learning?
This is an (optional) introduction to Curiosity. If you want to learn more, you can read two additional articles where we dive into the mathematical details:
- [Curiosity-Driven Learning through Next State Prediction](https://medium.com/data-from-the-tren... | deep-rl-class/units/en/unit5/curiosity.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit5/curiosity.mdx",
"repo_id": "deep-rl-class",
"token_count": 1153
} | 168 |
<jupyter_start><jupyter_text>Running IF with 🧨 diffusers on a Free Tier Google Colab_**TL;DR**: We show how to run one of the most powerful open-source text to image models **IF** on a free-tier Google Colab with 🧨 diffusers._*by DeepFloyd &* 🤗 *HuggingFace* *Image taken from official IF GitHub repo [here](https://... | notebooks/diffusers/deepfloyd_if_free_tier_google_colab.ipynb/0 | {
"file_path": "notebooks/diffusers/deepfloyd_if_free_tier_google_colab.ipynb",
"repo_id": "notebooks",
"token_count": 9958
} | 305 |
<jupyter_start><jupyter_text>Elasticsearch>[Elasticsearch](http://www.github.com/elastic/elasticsearch) is a search database, that supports full text and vector searches. Basic ExampleIn this basic example, we take the a Paul Graham essay, split it into chunks, embed it using an open-source embedding model, load it ... | llama_index/docs/examples/vector_stores/Elasticsearch_demo.ipynb/0 | {
"file_path": "llama_index/docs/examples/vector_stores/Elasticsearch_demo.ipynb",
"repo_id": "llama_index",
"token_count": 682
} | 1,082 |
// A dependency graph that contains any wasm must all be imported
// asynchronously. This `bootstrap.js` file does the single async import, so
// that no one else needs to worry about it again.
import("./index.js")
.catch(e => console.error("Error importing `index.js`:", e));
| tokenizers/tokenizers/examples/unstable_wasm/www/bootstrap.js/0 | {
"file_path": "tokenizers/tokenizers/examples/unstable_wasm/www/bootstrap.js",
"repo_id": "tokenizers",
"token_count": 79
} | 462 |
python_sources()
| llama_index/llama-index-legacy/tests/langchain_helpers/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/tests/langchain_helpers/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,534 |
# Launching LangServe from a Package
You can also launch LangServe directly from a package, without having to pull it into a project.
This can be useful when you are developing a package and want to test it quickly.
The downside of this is that it gives you a little less control over how the LangServe APIs are configu... | langchain/templates/docs/LAUNCHING_PACKAGE.md/0 | {
"file_path": "langchain/templates/docs/LAUNCHING_PACKAGE.md",
"repo_id": "langchain",
"token_count": 403
} | 633 |
compute_environment: LOCAL_MACHINE
debug: false
deepspeed_config:
deepspeed_multinode_launcher: standard
gradient_accumulation_steps: 1
zero3_init_flag: false
zero_stage: 1
distributed_type: DEEPSPEED
downcast_bf16: 'no'
machine_rank: 0
main_training_function: main
mixed_precision: 'bf16'
num_machines: 1
num_pr... | trl/examples/accelerate_configs/deepspeed_zero1.yaml/0 | {
"file_path": "trl/examples/accelerate_configs/deepspeed_zero1.yaml",
"repo_id": "trl",
"token_count": 171
} | 856 |
<jupyter_start><jupyter_text>Jaguar Vector Database1. It is a distributed vector database2. The “ZeroMove” feature of JaguarDB enables instant horizontal scalability3. Multimodal: embeddings, text, images, videos, PDFs, audio, time series, and geospatial4. All-masters: allows both parallel reads and writes5. Anomaly de... | langchain/docs/docs/integrations/vectorstores/jaguar.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/vectorstores/jaguar.ipynb",
"repo_id": "langchain",
"token_count": 1945
} | 182 |
from typing import Any, Callable, Dict, Optional, Sequence
# from mistralai.models.chat_completion import ChatMessage
from llama_index.core.base.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
CompletionResponse,
CompletionResponseAsyncGen,
CompletionRe... | llama_index/llama-index-integrations/llms/llama-index-llms-mistralai/llama_index/llms/mistralai/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-mistralai/llama_index/llms/mistralai/base.py",
"repo_id": "llama_index",
"token_count": 4658
} | 1,314 |
# LlamaIndex Vector_Stores Integration: Supabase
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-supabase/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-supabase/README.md",
"repo_id": "llama_index",
"token_count": 13
} | 1,476 |
repos:
- repo: https://github.com/dnephin/pre-commit-golang
rev: v0.5.0
hooks:
- id: golangci-lint
args: [--config=.golangci.yml, --timeout=3m]
- repo: https://github.com/crate-ci/typos
rev: v1.16.10
hooks:
- id: typos
- repo: https://github.com/trufflesecurity/trufflehog
r... | milvus/.pre-commit-config.yaml/0 | {
"file_path": "milvus/.pre-commit-config.yaml",
"repo_id": "milvus",
"token_count": 281
} | 1,698 |
#!/usr/bin/env python3
import argparse
import json
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.models import create_model
from transformers import (
BeitImageProcessor,
Data2VecVisionConfig,
Data2VecVisionForImageClassification,
Data2VecVisionModel,
)
def... | transformers/src/transformers/models/data2vec/convert_data2vec_vision_original_pytorch_checkpoint_to_pytorch.py/0 | {
"file_path": "transformers/src/transformers/models/data2vec/convert_data2vec_vision_original_pytorch_checkpoint_to_pytorch.py",
"repo_id": "transformers",
"token_count": 7103
} | 653 |
# coding=utf-8
# Copyright 2020 Huggingface
#
# 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/examples/legacy/seq2seq/old_test_fsmt_bleu_score.py/0 | {
"file_path": "transformers/examples/legacy/seq2seq/old_test_fsmt_bleu_score.py",
"repo_id": "transformers",
"token_count": 997
} | 518 |
from llama_index.core.base.embeddings.base import BaseEmbedding
from llama_index.embeddings.anyscale import AnyscaleEmbedding
def test_anyscale_class():
emb = AnyscaleEmbedding()
assert isinstance(emb, BaseEmbedding)
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-anyscale/tests/test_anyscale_embedding.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-anyscale/tests/test_anyscale_embedding.py",
"repo_id": "llama_index",
"token_count": 81
} | 1,190 |
locust_insert_performance:
collections:
-
milvus:
db_config.primary_path: /test/milvus/db_data_011/insert_sift_1m_128_l2_2
collection_name: local_1m_128_l2
ni_per: 50000
build_index: false
index_type: ivf_sq8
index_param:
nlist: 1024
task:
load_s... | milvus/tests/benchmark/milvus_benchmark/suites/2_locust_insert_flush.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/suites/2_locust_insert_flush.yaml",
"repo_id": "milvus",
"token_count": 338
} | 1,940 |
# coding=utf-8
# Copyright 2023 IBM and 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
#
# Unle... | transformers/tests/models/patchtsmixer/test_modeling_patchtsmixer.py/0 | {
"file_path": "transformers/tests/models/patchtsmixer/test_modeling_patchtsmixer.py",
"repo_id": "transformers",
"token_count": 20454
} | 761 |
<svg xmlns="http://www.w3.org/2000/svg" width="32" height="32" fill="none">
<path
fill="#2063EC"
d="M4 15.55C4 9.72 8.72 5 14.55 5h4.11a9.34 9.34 0 1 1 0 18.68H7.58l-2.89 2.8a.41.41 0 0 1-.69-.3V15.55Z"
/>
</svg>
| chat-ui/static/chatui/logo.svg/0 | {
"file_path": "chat-ui/static/chatui/logo.svg",
"repo_id": "chat-ui",
"token_count": 125
} | 122 |
from llama_index.callbacks.uptrain.base import UpTrainCallbackHandler
from llama_index.core.callbacks.base_handler import BaseCallbackHandler
def test_handler_callable():
names_of_base_classes = [b.__name__ for b in UpTrainCallbackHandler.__mro__]
assert BaseCallbackHandler.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/callbacks/llama-index-callbacks-uptrain/tests/test_uptrain_callback.py/0 | {
"file_path": "llama_index/llama-index-integrations/callbacks/llama-index-callbacks-uptrain/tests/test_uptrain_callback.py",
"repo_id": "llama_index",
"token_count": 99
} | 1,297 |
package streamrpc
import (
"context"
"io"
"sync"
"google.golang.org/grpc"
"github.com/milvus-io/milvus/internal/proto/internalpb"
)
type QueryStreamServer interface {
Send(*internalpb.RetrieveResults) error
Context() context.Context
}
type QueryStreamClient interface {
Recv() (*internalpb.RetrieveResults, e... | milvus/internal/util/streamrpc/streamer.go/0 | {
"file_path": "milvus/internal/util/streamrpc/streamer.go",
"repo_id": "milvus",
"token_count": 1010
} | 1,945 |
package typeutil
import (
"fmt"
"math"
"path"
"github.com/apache/arrow/go/v12/arrow/array"
"github.com/golang/protobuf/proto"
"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
"github.com/milvus-io/milvus/internal/storage"
"github.com/milvus-io/milvus/pkg/common"
"github.com/milvus-io/milvus/pkg/log"
... | milvus/internal/util/typeutil/storage.go/0 | {
"file_path": "milvus/internal/util/typeutil/storage.go",
"repo_id": "milvus",
"token_count": 1942
} | 1,946 |
"""
These functions match what the spec of hnswlib is.
"""
import numpy as np
from numpy.typing import ArrayLike
def l2(x: ArrayLike, y: ArrayLike) -> float:
return np.linalg.norm(x - y) ** 2
def cosine(x: ArrayLike, y: ArrayLike) -> float:
# This epsilon is used to prevent division by zero, and the value i... | chroma/chromadb/utils/distance_functions.py/0 | {
"file_path": "chroma/chromadb/utils/distance_functions.py",
"repo_id": "chroma",
"token_count": 284
} | 29 |
# 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... | transformers/tests/pipelines/test_pipelines_image_feature_extraction.py/0 | {
"file_path": "transformers/tests/pipelines/test_pipelines_image_feature_extraction.py",
"repo_id": "transformers",
"token_count": 2574
} | 760 |
"""All integration tests for chains."""
| langchain/libs/langchain/tests/integration_tests/chains/__init__.py/0 | {
"file_path": "langchain/libs/langchain/tests/integration_tests/chains/__init__.py",
"repo_id": "langchain",
"token_count": 9
} | 636 |
import json
import os
import pickle
import subprocess
from functools import partial
from pathlib import Path
from tempfile import gettempdir
from textwrap import dedent
from types import FunctionType
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from multiprocess import... | datasets/tests/test_fingerprint.py/0 | {
"file_path": "datasets/tests/test_fingerprint.py",
"repo_id": "datasets",
"token_count": 6783
} | 154 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-google/llama_index/readers/google/keep/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-google/llama_index/readers/google/keep/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,371 |
from abc import abstractmethod
from typing import List, Sequence, Optional, Tuple
from uuid import UUID
from chromadb.api.types import (
Embeddings,
Documents,
IDs,
Metadatas,
Metadata,
Where,
WhereDocument,
)
from chromadb.config import Component
class DB(Component):
@abstractmethod
... | chroma/chromadb/db/__init__.py/0 | {
"file_path": "chroma/chromadb/db/__init__.py",
"repo_id": "chroma",
"token_count": 1349
} | 14 |
# coding=utf-8
# Copyright 2023 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... | transformers/tests/test_image_processing_utils.py/0 | {
"file_path": "transformers/tests/test_image_processing_utils.py",
"repo_id": "transformers",
"token_count": 2518
} | 766 |
# coding=utf-8
# Copyright 2018 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 a... | transformers/examples/pytorch/test_accelerate_examples.py/0 | {
"file_path": "transformers/examples/pytorch/test_accelerate_examples.py",
"repo_id": "transformers",
"token_count": 6360
} | 590 |
import os
import time
import uuid
from typing import List
import numpy as np
import pinecone # type: ignore
import pytest
from langchain_core.documents import Document
from langchain_openai import OpenAIEmbeddings
from pinecone import PodSpec
from langchain_pinecone import Pinecone
INDEX_NAME = "langchain-test-inde... | langchain/libs/partners/pinecone/tests/integration_tests/test_vectorstores.py/0 | {
"file_path": "langchain/libs/partners/pinecone/tests/integration_tests/test_vectorstores.py",
"repo_id": "langchain",
"token_count": 5062
} | 623 |
# Summary [[summary]]
That was a lot of information! Let's summarize:
- Reinforcement Learning is a computational approach of learning from actions. We build an agent that learns from the environment **by interacting with it through trial and error** and receiving rewards (negative or positive) as feedback.
- The go... | deep-rl-class/units/en/unit1/summary.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit1/summary.mdx",
"repo_id": "deep-rl-class",
"token_count": 382
} | 163 |
python_sources()
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-clickhouse/llama_index/vector_stores/clickhouse/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-clickhouse/llama_index/vector_stores/clickhouse/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,514 |
from typing import List
from langchain_core.documents import Document
from langchain_community.retrievers.breebs import BreebsRetriever
class TestBreebsRetriever:
def test_breeb_query(self) -> None:
breeb_key = "Parivoyage"
query = "What are the best churches to visit in Paris?"
breeb_re... | langchain/libs/community/tests/integration_tests/retrievers/test_breebs.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/retrievers/test_breebs.py",
"repo_id": "langchain",
"token_count": 289
} | 344 |
# Generated content DO NOT EDIT
from .. import models
Model = models.Model
BPE = models.BPE
Unigram = models.Unigram
WordLevel = models.WordLevel
WordPiece = models.WordPiece
| tokenizers/bindings/python/py_src/tokenizers/models/__init__.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/models/__init__.py",
"repo_id": "tokenizers",
"token_count": 56
} | 458 |
"""Power BI agent."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Dict, List, Optional
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.language_models import BaseLanguageModel
from langchain_community.agent_toolkits.powerbi.prompt import (
POWERBI_PREFIX... | langchain/libs/community/langchain_community/agent_toolkits/powerbi/base.py/0 | {
"file_path": "langchain/libs/community/langchain_community/agent_toolkits/powerbi/base.py",
"repo_id": "langchain",
"token_count": 1019
} | 214 |
# 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/models/t5/__init__.py/0 | {
"file_path": "transformers/src/transformers/models/t5/__init__.py",
"repo_id": "transformers",
"token_count": 1938
} | 664 |
# ResNeXt
A **ResNeXt** repeats a [building block](https://paperswithcode.com/method/resnext-block) that aggregates a set of transformations with the same topology. Compared to a [ResNet](https://paperswithcode.com/method/resnet), it exposes a new dimension, *cardinality* (the size of the set of transformations) $C$,... | pytorch-image-models/docs/models/resnext.md/0 | {
"file_path": "pytorch-image-models/docs/models/resnext.md",
"repo_id": "pytorch-image-models",
"token_count": 3053
} | 356 |
#!/usr/bin/env python3
# coding=utf-8
# Copyright 2023-present 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
#... | peft/tests/test_lora_megatron.py/0 | {
"file_path": "peft/tests/test_lora_megatron.py",
"repo_id": "peft",
"token_count": 2964
} | 330 |
from llama_index.legacy.core.base_query_engine import BaseQueryEngine
# SQL
from llama_index.legacy.indices.struct_store.sql_query import (
NLSQLTableQueryEngine,
PGVectorSQLQueryEngine,
SQLTableRetrieverQueryEngine,
)
from llama_index.legacy.query_engine.citation_query_engine import CitationQueryEngine
fr... | llama_index/llama-index-legacy/llama_index/legacy/query_engine/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/query_engine/__init__.py",
"repo_id": "llama_index",
"token_count": 962
} | 1,588 |
# Modify this Procfile to fit your needs
web: uvicorn main:app --host 0.0.0.0 --port 8080 | weblangchain/Procfile/0 | {
"file_path": "weblangchain/Procfile",
"repo_id": "weblangchain",
"token_count": 32
} | 2,148 |
# Generated content DO NOT EDIT
from .. import processors
PostProcessor = processors.PostProcessor
BertProcessing = processors.BertProcessing
ByteLevel = processors.ByteLevel
RobertaProcessing = processors.RobertaProcessing
Sequence = processors.Sequence
TemplateProcessing = processors.TemplateProcessing
| tokenizers/bindings/python/py_src/tokenizers/processors/__init__.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/processors/__init__.py",
"repo_id": "tokenizers",
"token_count": 74
} | 415 |
import { BaseTransformOutputParser } from "./transform.js";
/**
* OutputParser that parses LLMResult into the top likely string and
* encodes it into bytes.
*/
export class BytesOutputParser extends BaseTransformOutputParser<Uint8Array> {
static lc_name() {
return "BytesOutputParser";
}
lc_namespace = ["... | langchainjs/langchain-core/src/output_parsers/bytes.ts/0 | {
"file_path": "langchainjs/langchain-core/src/output_parsers/bytes.ts",
"repo_id": "langchainjs",
"token_count": 193
} | 834 |
from typing import List
from langchain import hub
from langchain.agents import AgentExecutor
from langchain.agents.format_scratchpad import format_log_to_str
from langchain.agents.output_parsers import ReActJsonSingleInputOutputParser
from langchain.callbacks.manager import CallbackManagerForRetrieverRun
from langchai... | langchain/templates/retrieval-agent-fireworks/retrieval_agent_fireworks/chain.py/0 | {
"file_path": "langchain/templates/retrieval-agent-fireworks/retrieval_agent_fireworks/chain.py",
"repo_id": "langchain",
"token_count": 1401
} | 710 |
"""Test the airbyte document loader.
Light test to ensure that the airbyte document loader can be imported.
"""
def test_airbyte_import() -> None:
"""Test that the airbyte document loader can be imported."""
from langchain_community.document_loaders import airbyte # noqa
| langchain/libs/community/tests/unit_tests/document_loaders/test_airbyte.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/document_loaders/test_airbyte.py",
"repo_id": "langchain",
"token_count": 78
} | 375 |
# Streaming
## What is Streaming?
Token streaming is the mode in which the server returns the tokens one by one as the model generates them. This enables showing progressive generations to the user rather than waiting for the whole generation. Streaming is an essential aspect of the end-user experience as it reduces ... | text-generation-inference/docs/source/conceptual/streaming.md/0 | {
"file_path": "text-generation-inference/docs/source/conceptual/streaming.md",
"repo_id": "text-generation-inference",
"token_count": 1981
} | 417 |
// 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/querycoordv2/checkers/channel_checker_test.go/0 | {
"file_path": "milvus/internal/querycoordv2/checkers/channel_checker_test.go",
"repo_id": "milvus",
"token_count": 3104
} | 1,751 |
import { LanceDB } from "@langchain/community/vectorstores/lancedb";
import { OpenAIEmbeddings } from "@langchain/openai";
import { connect } from "vectordb";
import * as fs from "node:fs/promises";
import * as path from "node:path";
import os from "node:os";
export const run = async () => {
const dir = await fs.mkd... | langchainjs/examples/src/indexes/vector_stores/lancedb/fromTexts.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/lancedb/fromTexts.ts",
"repo_id": "langchainjs",
"token_count": 300
} | 817 |
# 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/LICENSE-2.0
#
# Unless required by appl... | accelerate/examples/cv_example.py/0 | {
"file_path": "accelerate/examples/cv_example.py",
"repo_id": "accelerate",
"token_count": 3205
} | 9 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
get_... | datasets/tests/test_file_utils.py/0 | {
"file_path": "datasets/tests/test_file_utils.py",
"repo_id": "datasets",
"token_count": 2016
} | 160 |
from llama_index.core.tools.tool_spec.base import BaseToolSpec
from llama_index.tools.requests import RequestsToolSpec
def test_class():
names_of_base_classes = [b.__name__ for b in RequestsToolSpec.__mro__]
assert BaseToolSpec.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/tools/llama-index-tools-requests/tests/test_tools_requests.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-requests/tests/test_tools_requests.py",
"repo_id": "llama_index",
"token_count": 94
} | 1,435 |
package datacoord
import (
"testing"
"github.com/samber/lo"
"github.com/stretchr/testify/suite"
"go.uber.org/zap"
"github.com/milvus-io/milvus-proto/go-api/v2/commonpb"
"github.com/milvus-io/milvus-proto/go-api/v2/msgpb"
"github.com/milvus-io/milvus/internal/proto/datapb"
"github.com/milvus-io/milvus/pkg/log... | milvus/internal/datacoord/compaction_l0_view_test.go/0 | {
"file_path": "milvus/internal/datacoord/compaction_l0_view_test.go",
"repo_id": "milvus",
"token_count": 1677
} | 1,772 |
#ifndef _qdq_8_cuh
#define _qdq_8_cuh
#include "qdq_util.cuh"
#include "../../config.h"
#if QMODE_8BIT == 1
// Not implemented
#else
__forceinline__ __device__ void shuffle_8bit_4
(
uint32_t* q,
int stride
)
{
}
__forceinline__ __device__ void dequant_8bit_8
(
const uint32_t q_0,
const uint32_t ... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_8.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_8.cuh",
"repo_id": "text-generation-inference",
"token_count": 336
} | 440 |
import inspect
def is_caller_internal(depth: int = 2) -> bool:
"""Return whether the caller at `depth` of this function is internal."""
try:
frame = inspect.currentframe()
except AttributeError:
return False
if frame is None:
return False
try:
for _ in range(depth):... | langchain/libs/core/langchain_core/_api/internal.py/0 | {
"file_path": "langchain/libs/core/langchain_core/_api/internal.py",
"repo_id": "langchain",
"token_count": 283
} | 386 |
import json
import urllib.request
from typing import Any, List
from langchain_core.documents import Document
from langchain_core.utils import stringify_dict
from langchain_community.document_loaders.base import BaseLoader
class FigmaFileLoader(BaseLoader):
"""Load `Figma` file."""
def __init__(self, access... | langchain/libs/community/langchain_community/document_loaders/figma.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/figma.py",
"repo_id": "langchain",
"token_count": 668
} | 247 |
<!--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... | accelerate/docs/source/usage_guides/quantization.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/quantization.md",
"repo_id": "accelerate",
"token_count": 1962
} | 4 |
# Tavily Search API
[Tavily's Search API](https://tavily.com) is a search engine built specifically for AI agents (LLMs), delivering real-time, accurate, and factual results at speed.
## Usage
import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
<IntegrationInstallTooltip></Integ... | langchainjs/docs/core_docs/docs/integrations/retrievers/tavily.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/retrievers/tavily.mdx",
"repo_id": "langchainjs",
"token_count": 248
} | 710 |
from llama_index.readers.airbyte_shopify.base import AirbyteShopifyReader
__all__ = ["AirbyteShopifyReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-shopify/llama_index/readers/airbyte_shopify/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-shopify/llama_index/readers/airbyte_shopify/__init__.py",
"repo_id": "llama_index",
"token_count": 36
} | 1,260 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/retrievers/llama-index-retrievers-you/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/retrievers/llama-index-retrievers-you/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,586 |
<jupyter_start><jupyter_text>Timescale Vector (Postgres) self-querying [Timescale Vector](https://www.timescale.com/ai) is PostgreSQL++ for AI applications. It enables you to efficiently store and query billions of vector embeddings in `PostgreSQL`.This notebook shows how to use the Postgres vector database (`Timescale... | langchain/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb",
"repo_id": "langchain",
"token_count": 2909
} | 157 |
<jupyter_start><jupyter_text>ClickUp>[ClickUp](https://clickup.com/) is an all-in-one productivity platform that provides small and large teams across industries with flexible and customizable work management solutions, tools, and functions. >It is a cloud-based project management solution for businesses of all sizes f... | langchain/docs/docs/integrations/toolkits/clickup.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/toolkits/clickup.ipynb",
"repo_id": "langchain",
"token_count": 3668
} | 177 |
from typing import Any, List, Optional
from langchain_core.callbacks.manager import CallbackManagerForLLMRun
from langchain_core.language_models.chat_models import BaseChatModel
from langchain_core.messages import AIMessage, BaseMessage
from langchain_core.outputs import ChatGeneration, ChatResult
class FakeChatLLMT... | langchain/libs/partners/robocorp/tests/unit_tests/_fixtures.py/0 | {
"file_path": "langchain/libs/partners/robocorp/tests/unit_tests/_fixtures.py",
"repo_id": "langchain",
"token_count": 1251
} | 639 |
<jupyter_start><jupyter_text>Lantern Vector StoreIn this notebook we are going to show how to use [Postgresql](https://www.postgresql.org) and [Lantern](https://github.com/lanterndata/lantern) to perform vector searches in LlamaIndex If you're opening this Notebook on colab, you will probably need to install LlamaInde... | llama_index/docs/examples/vector_stores/LanternIndexDemo.ipynb/0 | {
"file_path": "llama_index/docs/examples/vector_stores/LanternIndexDemo.ipynb",
"repo_id": "llama_index",
"token_count": 1843
} | 1,132 |
// 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/core/src/index/SkipIndex.h/0 | {
"file_path": "milvus/internal/core/src/index/SkipIndex.h",
"repo_id": "milvus",
"token_count": 4255
} | 1,739 |
python_sources()
| llama_index/llama-index-legacy/llama_index/legacy/readers/schema/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/readers/schema/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,596 |
import os
import tempfile
from pathlib import Path
from unittest import TestCase
import pyarrow as pa
import pytest
from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from... | datasets/tests/test_arrow_reader.py/0 | {
"file_path": "datasets/tests/test_arrow_reader.py",
"repo_id": "datasets",
"token_count": 5688
} | 142 |
python_tests(
name="tests",
)
| llama_index/llama-index-core/tests/query_pipeline/BUILD/0 | {
"file_path": "llama_index/llama-index-core/tests/query_pipeline/BUILD",
"repo_id": "llama_index",
"token_count": 15
} | 1,156 |
from langchain_community.utils.math import (
Matrix,
cosine_similarity,
cosine_similarity_top_k,
)
__all__ = ["Matrix", "cosine_similarity", "cosine_similarity_top_k"]
| langchain/libs/langchain/langchain/utils/math.py/0 | {
"file_path": "langchain/libs/langchain/langchain/utils/math.py",
"repo_id": "langchain",
"token_count": 71
} | 610 |
<jupyter_start><jupyter_text>Tracking token usageThis notebook goes over how to track your token usage for specific calls. It is currently only implemented for the OpenAI API.Let's first look at an extremely simple example of tracking token usage for a single LLM call.<jupyter_code>from langchain.callbacks import get_o... | langchain/docs/docs/modules/model_io/llms/token_usage_tracking.ipynb/0 | {
"file_path": "langchain/docs/docs/modules/model_io/llms/token_usage_tracking.ipynb",
"repo_id": "langchain",
"token_count": 860
} | 197 |
<!--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/bart.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/bart.md",
"repo_id": "transformers",
"token_count": 3297
} | 497 |
python_sources()
| llama_index/llama-index-integrations/llms/llama-index-llms-vllm/llama_index/llms/vllm/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-vllm/llama_index/llms/vllm/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,283 |
from llama_index.readers.pandas_ai.base import PandasAIReader
__all__ = ["PandasAIReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-pandas-ai/llama_index/readers/pandas_ai/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-pandas-ai/llama_index/readers/pandas_ai/__init__.py",
"repo_id": "llama_index",
"token_count": 36
} | 1,361 |
# MEP(Milvus Enhancement Proposals) Templates
Current state: [One of "Under Discussion", "Accepted", "Rejected"]
ISSUE: link to the GitHub issue
Keywords: list keywords about this MEP
Released: <Milvus Release Version>
## Summary(required)
What are we going to do?
## Motivation(required)
Why are we doing this?
... | milvus/docs/design_docs/00000000-MEP-Template.md/0 | {
"file_path": "milvus/docs/design_docs/00000000-MEP-Template.md",
"repo_id": "milvus",
"token_count": 382
} | 1,641 |
from langchain_core.documents import Document
__all__ = ["Document"]
| langchain/libs/langchain/langchain/docstore/document.py/0 | {
"file_path": "langchain/libs/langchain/langchain/docstore/document.py",
"repo_id": "langchain",
"token_count": 20
} | 507 |
"""Test Azue CosmosDB MongoDB vCore Vector Search functionality."""
from __future__ import annotations
import os
from time import sleep
from typing import List
import pytest
try:
from pymongo import MongoClient
INDEX_NAME = "llamaindex-test-index"
NAMESPACE = "llamaindex_test_db.llamaindex_test_collect... | llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-azurecosmosmongo/tests/test_azurecosmosmongo.py/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-azurecosmosmongo/tests/test_azurecosmosmongo.py",
"repo_id": "llama_index",
"token_count": 2094
} | 1,547 |
package datanode
import (
"sync"
"testing"
"github.com/stretchr/testify/assert"
"github.com/milvus-io/milvus/pkg/util/conc"
"github.com/milvus-io/milvus/pkg/util/paramtable"
)
func Test_getOrCreateIOPool(t *testing.T) {
ioConcurrency := Params.DataNodeCfg.IOConcurrency.GetValue()
paramtable.Get().Save(Params... | milvus/internal/datanode/io_pool_test.go/0 | {
"file_path": "milvus/internal/datanode/io_pool_test.go",
"repo_id": "milvus",
"token_count": 407
} | 1,697 |
import { authCondition } from "$lib/server/auth";
import { collections } from "$lib/server/database";
import type { SharedConversation } from "$lib/types/SharedConversation";
import { getShareUrl } from "$lib/utils/getShareUrl";
import { hashConv } from "$lib/utils/hashConv";
import { error } from "@sveltejs/kit";
impo... | chat-ui/src/routes/conversation/[id]/share/+server.ts/0 | {
"file_path": "chat-ui/src/routes/conversation/[id]/share/+server.ts",
"repo_id": "chat-ui",
"token_count": 761
} | 101 |
<!--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/en/api/internal_classes_overview.md/0 | {
"file_path": "diffusers/docs/source/en/api/internal_classes_overview.md",
"repo_id": "diffusers",
"token_count": 211
} | 190 |
import { test } from "@jest/globals";
import { OpenAI } from "@langchain/openai";
import { PromptTemplate } from "@langchain/core/prompts";
import { QAEvalChain } from "../eval_chain.js";
test("Test QAEvalChain", async () => {
const model = new OpenAI({ modelName: "gpt-3.5-turbo-instruct" });
const prompt = new Pr... | langchainjs/langchain/src/evaluation/qa/tests/eval_chain.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/evaluation/qa/tests/eval_chain.int.test.ts",
"repo_id": "langchainjs",
"token_count": 418
} | 906 |
python_sources()
| llama_index/llama-index-integrations/tools/llama-index-tools-google/llama_index/tools/google/search/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-google/llama_index/tools/google/search/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,484 |
<!--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/ko/tasks/visual_question_answering.md/0 | {
"file_path": "transformers/docs/source/ko/tasks/visual_question_answering.md",
"repo_id": "transformers",
"token_count": 11287
} | 500 |
{
"name": "test-exports-bun",
"version": "0.0.0",
"private": true,
"description": "Tests for the things exported by the langchain package",
"main": "./index.mjs",
"type": "module",
"scripts": {
"build": "tsc",
"test": "bun run test:esm && bun run test:cjs && bun run test:cjs:import && bun run test... | langchainjs/environment_tests/test-exports-bun/package.json/0 | {
"file_path": "langchainjs/environment_tests/test-exports-bun/package.json",
"repo_id": "langchainjs",
"token_count": 443
} | 747 |
<jupyter_start><jupyter_text>Twitter>[Twitter](https://twitter.com/) is an online social media and social networking service.This loader fetches the text from the Tweets of a list of `Twitter` users, using the `tweepy` Python package.You must initialize the loader with your `Twitter API` token, and you need to pass in ... | langchain/docs/docs/integrations/document_loaders/twitter.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/twitter.ipynb",
"repo_id": "langchain",
"token_count": 354
} | 116 |
[tool.poetry]
name = "rag-chroma"
version = "0.1.0"
description = "RAG using Chroma"
authors = [
"Erick Friis <erick@langchain.dev>",
]
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = "^0.1"
openai = "<2"
tiktoken = ">=0.5.1"
chromadb = ">=0.4.14"
[tool.poetry.group.dev.depende... | langchain/templates/rag-chroma/pyproject.toml/0 | {
"file_path": "langchain/templates/rag-chroma/pyproject.toml",
"repo_id": "langchain",
"token_count": 287
} | 692 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/readers/llama-index-readers-chroma/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-chroma/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,475 |
<jupyter_start><jupyter_text>Token Counting HandlerThis notebook walks through how to use the TokenCountingHandler and how it can be used to track your prompt, completion, and embedding token usage over time. If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip in... | llama_index/docs/examples/callbacks/TokenCountingHandler.ipynb/0 | {
"file_path": "llama_index/docs/examples/callbacks/TokenCountingHandler.ipynb",
"repo_id": "llama_index",
"token_count": 1895
} | 1,044 |
// This example illustrates how to implement custom operations. These operations can provide their
// own forward pass (CPU and GPU versions) as well as their backward pass.
//
// In this example we add the RMS normalization operation and implement it for f32.
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[rus... | candle/candle-examples/examples/custom-ops/main.rs/0 | {
"file_path": "candle/candle-examples/examples/custom-ops/main.rs",
"repo_id": "candle",
"token_count": 1475
} | 40 |
"""Test Fireworks AI API Wrapper."""
from typing import Generator
import pytest
from langchain_core.outputs import LLMResult
from langchain_community.llms.fireworks import Fireworks
@pytest.fixture
def llm() -> Fireworks:
return Fireworks(model_kwargs={"temperature": 0, "max_tokens": 512})
@pytest.mark.schedu... | langchain/libs/community/tests/integration_tests/llms/test_fireworks.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/llms/test_fireworks.py",
"repo_id": "langchain",
"token_count": 1500
} | 337 |
<jupyter_start><jupyter_text>Example selectorsIf you have a large number of examples, you may need to select which ones to include in the prompt. The Example Selector is the class responsible for doing so.The base interface is defined as below:```pythonclass BaseExampleSelector(ABC): """Interface for selecting examp... | langchain/docs/docs/modules/model_io/prompts/example_selectors.ipynb/0 | {
"file_path": "langchain/docs/docs/modules/model_io/prompts/example_selectors.ipynb",
"repo_id": "langchain",
"token_count": 1174
} | 200 |
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