langchain

Commit Graph

Author	SHA1	Message	Date
Harrison Chase	412fa4e1db	add guide notebook (#8258 ) <!-- Thank you for contributing to LangChain! Replace this comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - Twitter handle: we announce bigger features on Twitter. If your PR gets announced and you'd like a mention, we'll gladly shout you out! Please make sure you're PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. Maintainer responsibilities: - General / Misc / if you don't know who to tag: @baskaryan - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev - Models / Prompts: @hwchase17, @baskaryan - Memory: @hwchase17 - Agents / Tools / Toolkits: @hinthornw - Tracing / Callbacks: @agola11 - Async: @agola11 If no one reviews your PR within a few days, feel free to @-mention the same people again. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md --> --------- Co-authored-by: Nuno Campos <nuno@boringbits.io> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	1 year ago
William FH	b7c0eb9ecb	Wfh/ref links (#8454 )	1 year ago
Harrison Chase	13b4f465e2	log output parser (#8446 )	1 year ago
William FH	7d79178827	Wfh/update guide imports (#8452 )	1 year ago
William FH	d935573362	Partial formatting for chat messages (#8450 )	1 year ago
William FH	3314f54383	Update supabase docstrings (#8443 )	1 year ago
Harrison Chase	f63240649c	cr	1 year ago
Harrison Chase	17953ab61f	add notebook for sql query (#8442 )	1 year ago
Harrison Chase	2448043b84	bump and fix (#8441 )	1 year ago
Zack Proser	3892cefac6	Minor fixes to enhance notebook usability: (#8389 ) - Install langchain - Set Pinecone API key and environment as env vars - Create Pinecone index if it doesn't already exist --- - Description: Fix a couple minor issues I came across when running this notebook, - Issue: the issue # it fixes (if applicable), - Dependencies: none, - Tag maintainer: @rlancemartin @eyurtsev, - Twitter handle: @zackproser (certainly not necessary!)	1 year ago
Amélie	8ee56b9a5b	Feature: Add support for meilisearch vectorstore (#7649 ) Description: Add support for Meilisearch vector store. Resolve #7603 - No external dependencies added - A notebook has been added @rlancemartin https://twitter.com/meilisearch Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bearnardd	b7d6e1909c	fix empty ids when metadatas is provided (#8127 ) Fixes https://github.com/hwchase17/langchain/issues/7865 and https://github.com/hwchase17/langchain/issues/8061 - [x] fixes returning empty ids when metadatas argument is provided @baskaryan --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bharat Raghunathan	62b8b459c6	doc(prompts): Add redirect to fix broken link on Prompts Page (#8408 ) --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	2311d57df4	mv dropbox (#8438 )	1 year ago
Luis Valencia	7124377524	Devcontainer README -> Clarification. (#8414 ) - Description: The contribution guidlelines using devcontainer refer to the main repo and not the forked repo. We should create our changes in our own forked repo, not on langchain/main - Issue: Just documentation - Dependencies: N/A, - Tag maintainer: @baskaryan - Twitter handle: @levalencia	1 year ago
lvisdd	abe4c361f9	update get_num_tokens_from_messages model (#8431 ) (#8430) Co-authored-by: Kano Kunihiko <kkano@heroz.co.jp>	1 year ago
Jeffrey Wang	e0de62f6da	Add RoPE Scaling params from llamacpp (#8422 ) Description: Just adding parameters from `llama-python-cpp` that support RoPE scaling. @hwchase17, @baskaryan sources: papers and explanation: https://kaiokendev.github.io/context llamacpp conversation: https://github.com/ggerganov/llama.cpp/discussions/1965 Supports models like: https://huggingface.co/conceptofmind/LLongMA-2-13b	1 year ago
Bagatur	2db2987b1b	add experimental ref (#8435 )	1 year ago
Harrison Chase	fab24457bc	remove code (#8425 )	1 year ago
Harrison Chase	3a78450883	update experimental (#8402 ) some changes were made to experimental, porting them over	1 year ago
Harrison Chase	af7e70d4af	expose function for converting messages to messages (#8426 )	1 year ago
Eugene Yurtsev	06bdbe06fe	PromptTemplate update documentation and expand kwarg (#8423 ) # PromptTemplate * Update documentation to highlight the classmethod for instantiating a prompt template. * Expand kwargs in the classmethod to make parameters easier to discover This PR got reverted here: https://github.com/langchain-ai/langchain/pull/8395/files	1 year ago
Eugene Yurtsev	e62a1686e2	ChatPromptTemplate: minor fix in doc string (#8424 ) Minor fix in doc-string to use `ai` rather than `assistant`	1 year ago
Eugene Yurtsev	760c278fe0	ChatPromptTemplate: Expand support for message formats and documentation (#8244 ) * Expands support for a variety of message formats in the `from_messages` classmethod. Ideally, we could deprecate the other on-ramps to reduce the amount of classmethods users need to know about. * Expand documentation with code examples.	1 year ago
Bagatur	61dd92f821	bump 246 (#8410 )	1 year ago
Harrison Chase	394b67ab92	add kwargs to llm runnables (#8388 )	1 year ago
HeTaoPKU	d5884017a9	Add Minimax llm model to langchain (#7645 ) - Description: Minimax is a great AI startup from China, recently they released their latest model and chat API, and the API is widely-spread in China. As a result, I'd like to add the Minimax llm model to Langchain. - Tag maintainer: @hwchase17, @baskaryan --------- Co-authored-by: the <tao.he@hulu.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
James Campbell	0ad2d5f27a	[nit] Add default value for ChatOpenAI client (#7939 ) Micro convenience PR to avoid warning regarding missing `client` parameter. It is always set during initialization. @baskaryan Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Harrison Chase	82df923f37	Merge branch 'master' of github.com:hwchase17/langchain	1 year ago
Harrison Chase	1b0bfa54cf	cr	1 year ago
Jeff Vestal	c7ff5f19a8	ElasticKnnSearch rewrite - bug fix - return Document (#8180 ) Fixes: https://github.com/hwchase17/langchain/issues/7117 https://github.com/hwchase17/langchain/issues/5760 Adding back `create_index` , `add_texts`, `from_texts` to ElasticKnnSearch `from_texts` matches standard `from_texts` methods as quick start up method `knn_search` and `hybrid_result` return a list of [`Document()`, `score`,] # Test `from_texts` for quick start ``` # create new index using from_text from langchain.vectorstores.elastic_vector_search import ElasticKnnSearch from langchain.embeddings import ElasticsearchEmbeddings model_id = "sentence-transformers__all-distilroberta-v1" dims = 768 es_cloud_id = "" es_user = "" es_password = "" test_index = "knn_test_index_305" embeddings = ElasticsearchEmbeddings.from_credentials( model_id, #input_field=input_field, es_cloud_id=es_cloud_id, es_user=es_user, es_password=es_password, ) # add texts and create class instance texts = ["This is a test document", "This is another test document"] knnvectorsearch = ElasticKnnSearch.from_texts( texts=texts, embedding=embeddings, index_name= test_index, vector_query_field='vector', query_field='text', model_id=model_id, dims=dims, es_cloud_id=es_cloud_id, es_user=es_user, es_password=es_password ) # Test `add_texts` method texts2 = ["Hello, world!", "Machine learning is fun.", "I love Python."] knnvectorsearch.add_texts(texts2) query = "Hello" knn_result = knnvectorsearch.knn_search(query = query, model_id= model_id, k=2) hybrid_result = knnvectorsearch.knn_hybrid_search(query = query, model_id= model_id, k=2) ``` The mapping is as follows: ``` { "knn_test_index_012": { "mappings": { "properties": { "text": { "type": "text" }, "vector": { "type": "dense_vector", "dims": 768, "index": true, "similarity": "dot_product" } } } } } ``` # Check response type ``` >>> hybrid_result [(Document(page_content='Hello, world!', metadata={}), 0.94232327), (Document(page_content='I love Python.', metadata={}), 0.5321523)] >>> hybrid_result[0] (Document(page_content='Hello, world!', metadata={}), 0.94232327) >>> hybrid_result[0][0] Document(page_content='Hello, world!', metadata={}) >>> type(hybrid_result[0][0]) <class 'langchain.schema.document.Document'> ``` # Test with existing Index ``` from langchain.vectorstores.elastic_vector_search import ElasticKnnSearch from langchain.embeddings import ElasticsearchEmbeddings ## Initialize ElasticsearchEmbeddings model_id = "sentence-transformers__all-distilroberta-v1" dims = 768 es_cloud_id = es_user = "" es_password = "" test_index = "knn_test_index_012" embeddings = ElasticsearchEmbeddings.from_credentials( model_id, es_cloud_id=es_cloud_id, es_user=es_user, es_password=es_password, ) ## Initialize ElasticKnnSearch knn_search = ElasticKnnSearch( es_cloud_id=es_cloud_id, es_user=es_user, es_password=es_password, index_name= test_index, embedding= embeddings ) ## Test adding vectors ### Test `add_texts` method when index created texts = ["Hello, world!", "Machine learning is fun.", "I love Python."] knn_search.add_texts(texts) ``` --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Harrison Chase	a221a9ced0	Harrison/sql query (#8370 ) Co-authored-by: Nuno Campos <nuno@boringbits.io>	1 year ago
Bagatur	a1a650c743	Bagatur/from texts bug fix (#8394 ) --------- Co-authored-by: Davit Buniatyan <davit@loqsh.com> Co-authored-by: Davit Buniatyan <d@activeloop.ai> Co-authored-by: adilkhan <adilkhan.sarsen@nu.edu.kz> Co-authored-by: Ivo Stranic <istranic@gmail.com>	1 year ago
Jiayi Ni	1efb9bae5f	FEAT: Integrate Xinference LLMs and Embeddings (#8171 ) - [Xorbits Inference(Xinference)](https://github.com/xorbitsai/inference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. Xinference supports a variety of GGML-compatible models including chatglm, whisper, and vicuna, and utilizes heterogeneous hardware and a distributed architecture for seamless cross-device and cross-server model deployment. - This PR integrates Xinference models and Xinference embeddings into LangChain. - Dependencies: To install the depenedencies for this integration, run `pip install "xinference[all]"` - Example Usage: To start a local instance of Xinference, run `xinference`. To deploy Xinference in a distributed cluster, first start an Xinference supervisor using `xinference-supervisor`: `xinference-supervisor -H "${supervisor_host}"` Then, start the Xinference workers using `xinference-worker` on each server you want to run them on. `xinference-worker -e "http://${supervisor_host}:9997"` To use Xinference with LangChain, you also need to launch a model. You can use command line interface (CLI) to do so. Fo example: `xinference launch -n vicuna-v1.3 -f ggmlv3 -q q4_0`. This launches a model named vicuna-v1.3 with `model_format="ggmlv3"` and `quantization="q4_0"`. A model UID is returned for you to use. Now you can use Xinference with LangChain: ```python from langchain.llms import Xinference llm = Xinference( server_url="http://0.0.0.0:9997", # suppose the supervisor_host is "0.0.0.0" model_uid = {model_uid} # model UID returned from launching a model ) llm( prompt="Q: where can we visit in the capital of France? A:", generate_config={"max_tokens": 1024}, ) ``` You can also use RESTful client to launch a model: ```python from xinference.client import RESTfulClient client = RESTfulClient("http://0.0.0.0:9997") model_uid = client.launch_model(model_name="vicuna-v1.3", model_size_in_billions=7, quantization="q4_0") ``` The following code block demonstrates how to use Xinference embeddings with LangChain: ```python from langchain.embeddings import XinferenceEmbeddings xinference = XinferenceEmbeddings( server_url="http://0.0.0.0:9997", model_uid = model_uid ) ``` ```python query_result = xinference.embed_query("This is a test query") ``` ```python doc_result = xinference.embed_documents(["text A", "text B"]) ``` Xinference is still under rapid development. Feel free to [join our Slack community](https://xorbitsio.slack.com/join/shared_invite/zt-1z3zsm9ep-87yI9YZ_B79HLB2ccTq4WA) to get the latest updates! - Request for review: @hwchase17, @baskaryan - Twitter handle: https://twitter.com/Xorbitsio --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	877d384bc9	Revert "PromptTemplate update documentation and expand kwargs (#8234 )" (#8395 ) fyi @eyurtsev was failing a unit test	1 year ago
Gordon Clark	e66759cc9d	Github add "Create PR" tool + Docs update (#8235 ) Added a new tool to the Github toolkit called Create Pull Request. Now we can make our own langchain contributor in langchain 😁 In order to have somewhere to pull from, I also added a new env var, "GITHUB_BASE_BRANCH." This will allow the existing env var, "GITHUB_BRANCH," to be a working branch for the bot (so that it doesn't have to always commit on the main/master). For example, if you want the bot to work in a branch called `bot_dev` and your repo base is `main`, you would set up the vars like: ``` GITHUB_BASE_BRANCH = "main" GITHUB_BRANCH = "bot_dev" ``` Maintainer responsibilities: - Agents / Tools / Toolkits: @hinthornw	1 year ago
William FH	ecd4aae818	Few Shot Chat Prompt (#8038 ) Proposal for a few shot chat message example selector --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	1 year ago
Eugene Yurtsev	6dd18eee26	PromptTemplate update documentation and expand kwargs (#8234 ) # PromptTemplate * Update documentation to highlight the classmethod for instantiating a prompt template. * Expand kwargs in the classmethod to make parameters easier to discover	1 year ago
Karan V	a003a0baf6	fix(petals) allows to run models that aren't Bloom (Support for LLama and newer models) (#8356 ) In this PR: - Removed restricted model loading logic for Petals-Bloom - Removed petals imports (DistributedBloomForCausalLM, BloomTokenizerFast) - Instead imported more generalized versions of loader (AutoDistributedModelForCausalLM, AutoTokenizer) - Updated the Petals example notebook to allow for a successful installation of Petals in Apple Silicon Macs - Tag maintainer: @hwchase17, @baskaryan --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
lars.gersmann	e758e9e7f5	fix(openapi): openapi chain will work without/empty description/summa… (#8351 ) Description: This PR will enable the Open API chain to work with valid Open API specifications missing `description` and `summary` properties for path and operation nodes in open api specs. Since both `description` and `summary` property are declared optional we cannot be sure they are defined. This PR resolves this problem by providing an empty (`''`) description as fallback. The previous behavior of the Open API chain was that the underlying LLM (OpenAI) throw ed an exception since `None` is not of type string: ``` openai.error.InvalidRequestError: None is not of type 'string' - 'functions.0.description' ``` Using this PR the Open API chain will succeed also using Open API specs lacking `description` and `summary` properties for path and operation nodes. Thanks for your amazing work ! Tag maintainer: @baskaryan --------- Co-authored-by: Lars Gersmann <lars.gersmann@cm4all.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
ljeagle	caa6caeb8a	Upgrade the AwaDB from v0.3.7 to v0.3.9 and change the default embeddings (#8281 ) 1. Upgrade the AwaDB from v0.3.7 to v0.3.9 2. Change the default embedding to AwaEmbedding --------- Co-authored-by: ljeagle <awadb.vincent@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Harrison Chase	25b8cc7e3d	Harrison/update memory docs (#8384 ) Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Holt Skinner	d7e6770de8	refactor: Code refactoring & simplification for Google Cloud Enterprise Search retriever (#8369 ) Followup to https://github.com/langchain-ai/langchain/pull/7857 - Changes `_convert_search_response()` to use object attributes instead of converting to dictionary - Simplifies logic for readability	1 year ago
Taozhi Wang	594f195e54	Add embeddings for AwaEmbedding (#8353 ) - Description: Adds AwaEmbeddings class for embeddings, which provides users with a convenient way to do fine-tuning, as well as the potential need for multimodality - Tag maintainer: @baskaryan Create `Awa.ipynb`: an example notebook for AwaEmbeddings class Modify `embeddings/__init__.py`: Import the class Create `embeddings/awa.py`: The embedding class Create `embeddings/test_awa.py`: The test file. --------- Co-authored-by: taozhiwang <taozhiwa@gmail.com>	1 year ago
thehunmonkgroup	ba4e82bb47	fix missing _identifying_params() in _VertexAICommon (#8303 ) Full set of params are missing from Vertex* LLMs when `dict()` method is called. ``` >>> from langchain.chat_models.vertexai import ChatVertexAI >>> from langchain.llms.vertexai import VertexAI >>> chat_llm = ChatVertexAI() l>>> llm = VertexAI() >>> chat_llm.dict() {'_type': 'vertexai'} >>> llm.dict() {'_type': 'vertexai'} ``` This PR just uses the same mechanism used elsewhere to expose the full params. Since `_identifying_params()` is on the `_VertexAICommon` class, it should cover the chat and non-chat cases.	1 year ago
bheroder	dc3ca44e05	Add an example for azure ml managed feature store (#8324 ) We are adding an example of how one can connect to azure ml managed feature store and use such a prompt template in a llm chain. @baskaryan	1 year ago
Caitlin2694	b2e4b9dca4	Fix exception caused by restrictions in OWL (#8341 ) Description: Fix exception caused by restrictions in OWL Issue: #8331 Dependencies: none Maintainer: @baskaryan	1 year ago
Harrison Chase	cddd8ae83d	update release yml (#8364 ) only do the step that tags and adds release notes if its langchain	1 year ago
Nikita Pokidyshev	f499e6ea6a	Add FunctionMessage to _message_from_dict (#8374 ) <!-- Thank you for contributing to LangChain! Replace this comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - Twitter handle: we announce bigger features on Twitter. If your PR gets announced and you'd like a mention, we'll gladly shout you out! Please make sure you're PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. Maintainer responsibilities: - General / Misc / if you don't know who to tag: @baskaryan - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev - Models / Prompts: @hwchase17, @baskaryan - Memory: @hwchase17 - Agents / Tools / Toolkits: @hinthornw - Tracing / Callbacks: @agola11 - Async: @agola11 If no one reviews your PR within a few days, feel free to @-mention the same people again. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md -->	1 year ago
evelynmitchell	539574670c	Update tot.ipynb (#8387 ) Spelling error fix <!-- Thank you for contributing to LangChain! Replace this comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - Twitter handle: we announce bigger features on Twitter. If your PR gets announced and you'd like a mention, we'll gladly shout you out! Please make sure you're PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. Maintainer responsibilities: - General / Misc / if you don't know who to tag: @baskaryan - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev - Models / Prompts: @hwchase17, @baskaryan - Memory: @hwchase17 - Agents / Tools / Toolkits: @hinthornw - Tracing / Callbacks: @agola11 - Async: @agola11 If no one reviews your PR within a few days, feel free to @-mention the same people again. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md -->	1 year ago

... 3 4 5 6 7 ...

3638 Commits (642b57c7ff48970e392ed31dda2808ab5dcf1e9a) All Branches Search

3638 Commits (642b57c7ff48970e392ed31dda2808ab5dcf1e9a)

All Branches