120 Commits (7891934173b45da6c64366c65083181f0803b8c8)

Author	SHA1	Message	Date
Erick Friis	040271f33a	community[patch]: remove llmlingua extended tests (#18344)	7 months ago
Virat Singh	cd926ac3dd	community: Add PolygonFinancials Tool (#18324) ... **Description:** In this PR, I am adding a `PolygonFinancials` tool, which can be used to get financials data for a given ticker. The financials data is the fundamental data that is found in income statements, balance sheets, and cash flow statements of public US companies. **Twitter**: [@virattt](https://twitter.com/virattt)	7 months ago
Eugene Yurtsev	cd52433ba0	community[minor]: Add `SQLDatabaseLoader` document loader (#18281) ... - **Description:** A generic document loader adapter for SQLAlchemy on top of LangChain's `SQLDatabaseLoader`. - **Needed by:** https://github.com/crate-workbench/langchain/pull/1 - **Depends on:** GH-16655 - **Addressed to:** @baskaryan, @cbornet, @eyurtsev Hi from CrateDB again, in the same spirit like GH-16243 and GH-16244, this patch breaks out another commit from https://github.com/crate-workbench/langchain/pull/1, in order to reduce the size of this patch before submitting it, and to separate concerns. To accompany the SQLAlchemy adapter implementation, the patch includes integration tests for both SQLite and PostgreSQL. Let me know if corresponding utility resources should be added at different spots. With kind regards, Andreas. ### Software Tests ```console docker compose --file libs/community/tests/integration_tests/document_loaders/docker-compose/postgresql.yml up ``` ```console cd libs/community pip install psycopg2-binary pytest -vvv tests/integration_tests -k sqldatabase ``` ``` 14 passed ```  --------- Co-authored-by: Andreas Motl <andreas.motl@crate.io>	7 months ago
David Ruan	af35e2525a	community[minor]: add hugging_face_model document loader (#17323) ... - **Description:** add hugging_face_model document loader, - **Issue:** NA, - **Dependencies:** NA, --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	7 months ago
Ayo Ayibiowu	ac1d7d9de8	community[feat]: Adds LLMLingua as a document compressor (#17711) ... **Description**: This PR adds support for using the [LLMLingua project ](https://github.com/microsoft/LLMLingua) especially the LongLLMLingua (Enhancing Large Language Model Inference via Prompt Compression) as a document compressor / transformer. The LLMLingua project is an interesting project that can greatly improve RAG system by compressing prompts and contexts while keeping their semantic relevance. **Issue**: https://github.com/microsoft/LLMLingua/issues/31 **Dependencies**: [llmlingua](https://pypi.org/project/llmlingua/) @baskaryan --------- Co-authored-by: Ayodeji Ayibiowu <ayodeji.ayibiowu@getinge.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	7 months ago
am-kinetica	9b8f6455b1	Langchain vectorstore integration with Kinetica (#18102) ... - **Description:** New vectorstore integration with the Kinetica database - **Issue:** - **Dependencies:** the Kinetica Python API `pip install gpudb==7.2.0.1`, - **Tag maintainer:** @baskaryan, @hwchase17 - **Twitter handle:** --------- Co-authored-by: Chad Juliano <cjuliano@kinetica.com>	7 months ago
Dan Stambler	69344a0661	community: Add Laser Embedding Integration (#18111) ... - **Description:** Added Integration with Meta AI's LASER Language-Agnostic SEntence Representations embedding library, which supports multilingual embedding for any of the languages listed here: https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200, including several low resource languages - **Dependencies:** laser_encoders	7 months ago
Barun Amalkumar Halder	cc69976860	community[minor] : adds callback handler for Fiddler AI (#17708) ... **Description:** Callback handler to integrate fiddler with langchain. This PR adds the following - 1. `FiddlerCallbackHandler` implementation into langchain/community 2. Example notebook `fiddler.ipynb` for usage documentation [Internal Tracker : FDL-14305] **Issue:** NA **Dependencies:** - Installation of langchain-community is unaffected. - Usage of FiddlerCallbackHandler requires installation of latest fiddler-client (2.5+) **Twitter handle:** @fiddlerlabs @behalder Co-authored-by: Barun Halder <barun@fiddler.ai>	7 months ago
Chad Juliano	50ba3c68bb	community[minor]: add Kinetica LLM wrapper (#17879) ... **Description:** Initial pull request for Kinetica LLM wrapper **Issue:** N/A **Dependencies:** No new dependencies for unit tests. Integration tests require gpudb, typeguard, and faker **Twitter handle:** @chad_juliano Note: There is another pull request for Kinetica vectorstore. Ultimately we would like to make a partner package but we are starting with a community contribution.	7 months ago
Brad Erickson	ecd72d26cf	community: Bugfix - correct Ollama API path to avoid HTTP 307 (#17895) ... Sets the correct /api/generate path, without ending /, to reduce HTTP requests. Reference: https://github.com/ollama/ollama/blob/efe040f8/docs/api.md#generate-request-streaming Before: DEBUG: Starting new HTTP connection (1): localhost:11434 DEBUG: http://localhost:11434 "POST /api/generate/ HTTP/1.1" 307 0 DEBUG: http://localhost:11434 "POST /api/generate HTTP/1.1" 200 None After: DEBUG: Starting new HTTP connection (1): localhost:11434 DEBUG: http://localhost:11434 "POST /api/generate HTTP/1.1" 200 None	7 months ago
Ian	3019a594b7	community[minor]: Add tidb loader support (#17788) ... This pull request support loading data from TiDB database with Langchain. A simple usage: ``` from langchain_community.document_loaders import TiDBLoader CONNECTION_STRING = "mysql+pymysql://root@127.0.0.1:4000/test" QUERY = "select id, name, description from items;" loader = TiDBLoader( connection_string=CONNECTION_STRING, query=QUERY, page_content_columns=["name", "description"], metadata_columns=["id"], ) documents = loader.load() print(documents) ```	7 months ago
Michael Feil	242981b8f0	community[minor]: infinity embedding local option (#17671) ... **drop-in-replacement for sentence-transformers inference.** https://github.com/langchain-ai/langchain/discussions/17670 tldr from the discussion above -> around a 4x-22x speedup over using SentenceTransformers / huggingface embeddings. For more info: https://github.com/michaelfeil/infinity (pure-python dependency) --------- Co-authored-by: Erick Friis <erick@langchain.dev>	7 months ago
Zachary Toliver	29ee0496b6	community[patch]: Allow override of 'fetch_schema_from_transport' in the GraphQL tool (#17649) ... - **Description:** In order to override the bool value of "fetch_schema_from_transport" in the GraphQLAPIWrapper, a "fetch_schema_from_transport" value needed to be added to the "_EXTRA_OPTIONAL_TOOLS" dictionary in load_tools in the "graphql" key. The parameter "fetch_schema_from_transport" must also be passed in to the GraphQLAPIWrapper to allow reading of the value when creating the client. Passing as an optional parameter is probably best to avoid breaking changes. This change is necessary to support GraphQL instances that do not support fetching schema, such as TigerGraph. More info here: [TigerGraph GraphQL Schema Docs](https://docs.tigergraph.com/graphql/current/schema) - **Threads handle:** @zacharytoliver --------- Co-authored-by: Zachary Toliver <zt10191991@hotmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Guangdong Liu	47b1b7092d	community[minor]: Add SparkLLM to community (#17702)	7 months ago
Guangdong Liu	3ba1cb8650	community[minor]: Add SparkLLM Text Embedding Model and SparkLLM introduction (#17573)	7 months ago
Virat Singh	92e52e89ca	community: Add PolygonTickerNews Tool (#17808) ... Description: In this PR, I am adding a PolygonTickerNews Tool, which can be used to get the latest news for a given ticker / stock. Twitter handle: [@virattt](https://twitter.com/virattt)	7 months ago
CogniJT	919ebcc596	community[minor]: CogniSwitch Agent Toolkit for LangChain (#17312) ... **Description**: CogniSwitch focusses on making GenAI usage more reliable. It abstracts out the complexity & decision making required for tuning processing, storage & retrieval. Using simple APIs documents / URLs can be processed into a Knowledge Graph that can then be used to answer questions. **Dependencies**: No dependencies. Just network calls & API key required **Tag maintainer**: @hwchase17 **Twitter handle**: https://github.com/CogniSwitch **Documentation**: Please check `docs/docs/integrations/toolkits/cogniswitch.ipynb` **Tests**: The usual tool & toolkits tests using `test_imports.py` PR has passed linting and testing before this submission. --------- Co-authored-by: Saicharan Sridhara <145636106+saiCogniswitch@users.noreply.github.com>	7 months ago
Guangdong Liu	73edf17b4e	community[minor]: Add Apache Doris as vector store (#17527) ... --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Nejc Habjan	b4fa847a90	community[minor]: add exclude parameter to DirectoryLoader (#17316) ... - **Description:** adds an `exclude` parameter to the DirectoryLoader class, based on similar behavior in GenericLoader - **Issue:** discussed in https://github.com/langchain-ai/langchain/discussions/9059 and I think in some other issues that I cannot find at the moment 🙇 - **Dependencies:** None - **Twitter handle:** don't have one sorry! Just https://github/nejch --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	7 months ago
Bagatur	8f14234afb	infra: ignore flakey lua test (#17618)	7 months ago
Moshe Berchansky	20a56fe0a2	community[minor]: Add QuantizedEmbedders (#17391) ... **Description:** * adding Quantized embedders using optimum-intel and intel-extension-for-pytorch. * added mdx documentation and example notebooks * added embedding import testing. **Dependencies:** optimum = {extras = ["neural-compressor"], version = "^1.14.0", optional = true} intel_extension_for_pytorch = {version = "^2.2.0", optional = true} Dependencies have been added to pyproject.toml for the community lib. **Twitter handle:** @peter_izsak --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
nvpranak	91bcc9c5c9	community[minor]: Nemo embeddings(#16206) ... This PR is adding support for NVIDIA NeMo embeddings issue #16095. --------- Co-authored-by: Praveen Nakshatrala <pnakshatrala@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
wulixuan	c776cfc599	community[minor]: integrate with model Yuan2.0 (#15411) ... 1. integrate with [`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md) 2. update `langchain.llms` 3. add a new doc for [Yuan2.0 integration](docs/docs/integrations/llms/yuan2.ipynb) --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Kate Silverstein	0bc4a9b3fc	community[minor]: Adds Llamafile as an LLM (#17431) ... * **Description:** Adds a simple LLM implementation for interacting with [llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models. * **Dependencies:** N/A * **Issue:** N/A **Detail** [llamafile](https://github.com/Mozilla-Ocho/llamafile) lets you run LLMs locally from a single file on most computers without installing any dependencies. To use the llamafile LLM implementation, the user needs to: 1. Download a llamafile e.g. https://huggingface.co/jartine/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/TinyLlama-1.1B-Chat-v1.0.Q5_K_M.llamafile?download=true 2. Make the file executable. 3. Run the llamafile in 'server mode'. (All llamafiles come packaged with a lightweight server; by default, the server listens at `http://localhost:8080`.) ```bash wget https://url/of/model.llamafile chmod +x model.llamafile ./model.llamafile --server --nobrowser ``` Now, the user can invoke the LLM via the LangChain client: ```python from langchain_community.llms.llamafile import Llamafile llm = Llamafile() llm.invoke("Tell me a joke.") ```	7 months ago
Qihui Xie	5738143d4b	add mongodb_store (#13801) ... # Add MongoDB storage - **Description:** Add MongoDB Storage as an option for large doc store. Example usage: ```Python # Instantiate the MongodbStore with a MongoDB connection from langchain.storage import MongodbStore mongo_conn_str = "mongodb://localhost:27017/" mongodb_store = MongodbStore(mongo_conn_str, db_name="test-db", collection_name="test-collection") # Set values for keys doc1 = Document(page_content='test1') doc2 = Document(page_content='test2') mongodb_store.mset([("key1", doc1), ("key2", doc2)]) # Get values for keys values = mongodb_store.mget(["key1", "key2"]) # [doc1, doc2] # Iterate over keys for key in mongodb_store.yield_keys(): print(key) # Delete keys mongodb_store.mdelete(["key1", "key2"]) ``` - **Dependencies:** Use `mongomock` for integration test. --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	7 months ago
wulixuan	5d06797905	community[minor]: integrate chat models with Yuan2.0 (#16575) ... 1. integrate chat models with [`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md) 2. add a new doc for [Yuan2.0 integration](docs/docs/integrations/llms/yuan2.ipynb) Yuan2.0 is a new generation Fundamental Large Language Model developed by IEIT System. We have published all three models, Yuan 2.0-102B, Yuan 2.0-51B, and Yuan 2.0-2B. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Ian Gregory	e5472b5eb8	Framework for supporting more languages in LanguageParser (#13318) ... ## Description I am submitting this for a school project as part of a team of 5. Other team members are @LeilaChr, @maazh10, @Megabear137, @jelalalamy. This PR also has contributions from community members @Harrolee and @Mario928. Initial context is in the issue we opened (#11229). This pull request adds: - Generic framework for expanding the languages that `LanguageParser` can handle, using the [tree-sitter](https://github.com/tree-sitter/py-tree-sitter#py-tree-sitter) parsing library and existing language-specific parsers written for it - Support for the following additional languages in `LanguageParser`: - C - C++ - C# - Go - Java (contributed by @Mario928 https://github.com/ThatsJustCheesy/langchain/pull/2) - Kotlin - Lua - Perl - Ruby - Rust - Scala - TypeScript (contributed by @Harrolee https://github.com/ThatsJustCheesy/langchain/pull/1) Here is the [design document](https://docs.google.com/document/d/17dB14cKCWAaiTeSeBtxHpoVPGKrsPye8W0o_WClz2kk) if curious, but no need to read it. ## Issues - Closes #11229 - Closes #10996 - Closes #8405 ## Dependencies `tree_sitter` and `tree_sitter_languages` on PyPI. We have tried to add these as optional dependencies. ## Documentation We have updated the list of supported languages, and also added a section to `source_code.ipynb` detailing how to add support for additional languages using our framework. ## Maintainer - @hwchase17 (previously reviewed https://github.com/langchain-ai/langchain/pull/6486) Thanks!! ## Git commits We will gladly squash any/all of our commits (esp merge commits) if necessary. Let us know if this is desirable, or if you will be squash-merging anyway. <!-- Thank you for contributing to LangChain! Replace this entire 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 your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md 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. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Maaz Hashmi <mhashmi373@gmail.com> Co-authored-by: LeilaChr <87657694+LeilaChr@users.noreply.github.com> Co-authored-by: Jeremy La <jeremylai511@gmail.com> Co-authored-by: Megabear137 <zubair.alnoor27@gmail.com> Co-authored-by: Lee Harrold <lhharrold@sep.com> Co-authored-by: Mario928 <88029051+Mario928@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	7 months ago
Sridhar Ramaswamy	9f1cbbc6ed	community[minor]: Add pebblo safe document loader (#16862) ... - **Description:** Pebblo opensource project enables developers to safely load data to their Gen AI apps. It identifies semantic topics and entities found in the loaded data and summarizes them in a developer-friendly report. - **Dependencies:** none - **Twitter handle:** srics @hwchase17	7 months ago
mhavey	1bbb64d956	community[minor], langchian[minor]: Add Neptune Rdf graph and chain (#16650) ... **Description**: This PR adds a chain for Amazon Neptune graph database RDF format. It complements the existing Neptune Cypher chain. The PR also includes a Neptune RDF graph class to connect to, introspect, and query a Neptune RDF graph database from the chain. A sample notebook is provided under docs that demonstrates the overall effect: invoking the chain to make natural language queries against Neptune using an LLM. **Issue**: This is a new feature **Dependencies**: The RDF graph class depends on the AWS boto3 library if using IAM authentication to connect to the Neptune database. --------- Co-authored-by: Piyush Jain <piyushjain@duck.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Andreas Motl	1fdd9bd980	community/SQLDatabase: Generalize and trim software tests (#16659) ... - **Description:** Improve test cases for `SQLDatabase` adapter component, see [suggestion](https://github.com/langchain-ai/langchain/pull/16655#pullrequestreview-1846749474). - **Depends on:** GH-16655 - **Addressed to:** @baskaryan, @cbornet, @eyurtsev _Remark: This PR is stacked upon GH-16655, so that one will need to go in first._ Edit: Thank you for bringing in GH-17191, @eyurtsev. This is a little aftermath, improving/streamlining the corresponding test cases.	7 months ago
morgana	722aae4fd1	community: add delete method to rocksetdb vectorstore to support recordmanager (#17030) ... - **Description:** This adds a delete method so that rocksetdb can be used with `RecordManager`. - **Issue:** N/A - **Dependencies:** N/A - **Twitter handle:** `@_morgan_adams_` --------- Co-authored-by: Rockset API Bot <admin@rockset.io>	7 months ago
Spencer Kelly	54fa78c887	community[patch]: fixed vector similarity filtering (#16967) ... **Description:** changed filtering so that failed filter doesn't add document to results. Currently filtering is entirely broken and all documents are returned whether or not they pass the filter. fixes issue introduced in https://github.com/langchain-ai/langchain/pull/16190	7 months ago
Abhijeeth Padarthi	584b647b96	community[minor]: AWS Athena Document Loader (#15625) ... - **Description:** Adds the document loader for [AWS Athena](https://aws.amazon.com/athena/), a serverless and interactive analytics service. - **Dependencies:** Added boto3 as a dependency	7 months ago
david-tempelmann	93da18b667	community[minor]: Add mmr and similarity_score_threshold retrieval to DatabricksVectorSearch (#16829) ... - **Description:** This PR adds support for `search_types="mmr"` and `search_type="similarity_score_threshold"` to retrievers using `DatabricksVectorSearch`, - **Issue:** - **Dependencies:** - **Twitter handle:** --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Erick Friis	3a2eb6e12b	infra: add print rule to ruff (#16221) ... Added noqa for existing prints. Can slowly remove / will prevent more being intro'd	7 months ago
kYLe	c9999557bf	community[patch]: Modify LLMs/Anyscale work with OpenAI API v1 (#14206) ... <!-- Thank you for contributing to LangChain! Replace this entire 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 your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md 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. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> - **Description:** 1. Modify LLMs/Anyscale to work with OAI v1 2. Get rid of openai_ prefixed variables in Chat_model/ChatAnyscale 3. Modify `anyscale_api_base` to `anyscale_base_url` to follow OAI name convention (reverted) --------- Co-authored-by: Erick Friis <erick@langchain.dev>	7 months ago
Bagatur	65e97c9b53	infra: mv SQLDatabase tests to community (#17276)	7 months ago
Scott Nath	a32798abd7	community: Add you.com utility, update you retriever integration docs (#17014) ... <!-- Thank you for contributing to LangChain! Please title your PR "<package>: <description>", where <package> is whichever of langchain, community, core, experimental, etc. is being modified. Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes if applicable, - **Dependencies:** any dependencies required for this change, - **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 your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` from the root of the package you've modified to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ 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. It lives in `docs/docs/integrations` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> - **Description: changes to you.com files** - general cleanup - adds community/utilities/you.py, moving bulk of code from retriever -> utility - removes `snippet` as endpoint - adds `news` as endpoint - adds more tests <s>**Description: update community MAKE file** - adds `integration_tests` - adds `coverage`</s> - **Issue:** the issue # it fixes if applicable, - [For New Contributors: Update Integration Documentation](https://github.com/langchain-ai/langchain/issues/15664#issuecomment-1920099868) - **Dependencies:** n/a - **Twitter handle:** @scottnath - **Mastodon handle:** scottnath@mastodon.social --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Liang Zhang	7306600e2f	community[patch]: Support SerDe transform functions in Databricks LLM (#16752) ... **Description:** Databricks LLM does not support SerDe the transform_input_fn and transform_output_fn. After saving and loading, the LLM will be broken. This PR serialize these functions into a hex string using pickle, and saving the hex string in the yaml file. Using pickle to serialize a function can be flaky, but this is a simple workaround that unblocks many use cases. If more sophisticated SerDe is needed, we can improve it later. Test: Added a simple unit test. I did manual test on Databricks and it works well. The saved yaml looks like: ``` llm: _type: databricks cluster_driver_port: null cluster_id: null databricks_uri: databricks endpoint_name: databricks-mixtral-8x7b-instruct extra_params: {} host: e2-dogfood.staging.cloud.databricks.com max_tokens: null model_kwargs: null n: 1 stop: null task: null temperature: 0.0 transform_input_fn: 80049520000000000000008c085f5f6d61696e5f5f948c0f7472616e73666f726d5f696e7075749493942e transform_output_fn: null ``` @baskaryan ```python from langchain_community.embeddings import DatabricksEmbeddings from langchain_community.llms import Databricks from langchain.chains import RetrievalQA from langchain.document_loaders import TextLoader from langchain.text_splitter import CharacterTextSplitter from langchain.vectorstores import FAISS import mlflow embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en") def transform_input(**request): request["messages"] = [ { "role": "user", "content": request["prompt"] } ] del request["prompt"] return request llm = Databricks(endpoint_name="databricks-mixtral-8x7b-instruct", transform_input_fn=transform_input) persist_dir = "faiss_databricks_embedding" # Create the vector db, persist the db to a local fs folder loader = TextLoader("state_of_the_union.txt") documents = loader.load() text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) docs = text_splitter.split_documents(documents) db = FAISS.from_documents(docs, embeddings) db.save_local(persist_dir) def load_retriever(persist_directory): embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en") vectorstore = FAISS.load_local(persist_directory, embeddings) return vectorstore.as_retriever() retriever = load_retriever(persist_dir) retrievalQA = RetrievalQA.from_llm(llm=llm, retriever=retriever) with mlflow.start_run() as run: logged_model = mlflow.langchain.log_model( retrievalQA, artifact_path="retrieval_qa", loader_fn=load_retriever, persist_dir=persist_dir, ) # Load the retrievalQA chain loaded_model = mlflow.pyfunc.load_model(logged_model.model_uri) print(loaded_model.predict([{"query": "What did the president say about Ketanji Brown Jackson"}])) ```	7 months ago
ByeongUk Choi	b88329e9a5	community[patch]: Implement Unique ID Enforcement in FAISS (#17244) ... **Description:** Implemented unique ID validation in the FAISS component to ensure all document IDs are distinct. This update resolves issues related to non-unique IDs, such as inconsistent behavior during deletion processes.	7 months ago
Luiz Ferreira	34d2daffb3	community[patch]: Fix chat openai unit test (#17124) ... - **Description:** Actually the test named `test_openai_apredict` isn't testing the apredict method from ChatOpenAI. - **Twitter handle:** https://twitter.com/OAlmofadas	8 months ago
Frank	ef082c77b1	community[minor]: add github file loader to load any github file content b… (#15305) ... ### Description support load any github file content based on file extension. Why not use [git loader](https://python.langchain.com/docs/integrations/document_loaders/git#load-existing-repository-from-disk) ? git loader clones the whole repo even only interested part of files, that's too heavy. This GithubFileLoader only downloads that you are interested files. ### Twitter handle my twitter: @shufanhaotop --------- Co-authored-by: Hao Fan <h_fan@apple.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	8 months ago
Ryan Kraus	f027696b5f	community: Added new Utility runnables for NVIDIA Riva. (#15966) ... **Please tag this issue with `nvidia_genai`** - **Description:** Added new Runnables for integration NVIDIA Riva into LCEL chains for Automatic Speech Recognition (ASR) and Text To Speech (TTS). - **Issue:** N/A - **Dependencies:** To use these runnables, the NVIDIA Riva client libraries are required. It they are not installed, an error will be raised instructing how to install them. The Runnables can be safely imported without the riva client libraries. - **Twitter handle:** N/A All of the Riva Runnables are inside a single folder in the Utilities module. In this folder are four files: - common.py - Contains all code that is common to both TTS and ASR - stream.py - Contains a class representing an audio stream that allows the end user to put data into the stream like a queue. - asr.py - Contains the RivaASR runnable - tts.py - Contains the RivaTTS runnable The following Python function is an example of creating a chain that makes use of both of these Runnables: ```python def create( config: Configuration, audio_encoding: RivaAudioEncoding, sample_rate: int, audio_channels: int = 1, ) -> Runnable[ASRInputType, TTSOutputType]: """Create a new instance of the chain.""" _LOGGER.info("Instantiating the chain.") # create the riva asr client riva_asr = RivaASR( url=str(config.riva_asr.service.url), ssl_cert=config.riva_asr.service.ssl_cert, encoding=audio_encoding, audio_channel_count=audio_channels, sample_rate_hertz=sample_rate, profanity_filter=config.riva_asr.profanity_filter, enable_automatic_punctuation=config.riva_asr.enable_automatic_punctuation, language_code=config.riva_asr.language_code, ) # create the prompt template prompt = PromptTemplate.from_template("{user_input}") # model = ChatOpenAI() model = ChatNVIDIA(model="mixtral_8x7b") # type: ignore # create the riva tts client riva_tts = RivaTTS( url=str(config.riva_asr.service.url), ssl_cert=config.riva_asr.service.ssl_cert, output_directory=config.riva_tts.output_directory, language_code=config.riva_tts.language_code, voice_name=config.riva_tts.voice_name, ) # construct and return the chain return {"user_input": riva_asr} | prompt | model | riva_tts # type: ignore ``` The following code is an example of creating a new audio stream for Riva: ```python input_stream = AudioStream(maxsize=1000) # Send bytes into the stream for chunk in audio_chunks: await input_stream.aput(chunk) input_stream.close() ``` The following code is an example of how to execute the chain with RivaASR and RivaTTS ```python output_stream = asyncio.Queue() while not input_stream.complete: async for chunk in chain.astream(input_stream): output_stream.put(chunk) ``` Everything should be async safe and thread safe. Audio data can be put into the input stream while the chain is running without interruptions. --------- Co-authored-by: Hayden Wolff <hwolff@nvidia.com> Co-authored-by: Hayden Wolff <hwolff@Haydens-Laptop.local> Co-authored-by: Hayden Wolff <haydenwolff99@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev>	8 months ago
Alex Boury	334b6ebdf3	community[minor]: Breebs docs retriever (#16578) ... - **Description:** Implementation of breeb retriever with integration tests -> libs/community/tests/integration_tests/retrievers/test_breebs.py and documentation (notebook) -> docs/docs/integrations/retrievers/breebs.ipynb. - **Dependencies:** None	8 months ago
Harrison Chase	4eda647fdd	infra: add -p to mkdir in lint steps (#17013) ... Previously, if this did not find a mypy cache then it wouldnt run this makes it always run adding mypy ignore comments with existing uncaught issues to unblock other prs --------- Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	8 months ago
Erick Friis	b1a847366c	community: revert SQL Stores (#16912) ... This reverts commit cfc225ecb3. https://github.com/langchain-ai/langchain/pull/15909#issuecomment-1922418097 These will have existed in langchain-community 0.0.16 and 0.0.17.	8 months ago
Christophe Bornet	af8c5c185b	langchain[minor],community[minor]: Add async methods in BaseLoader (#16634) ... Adds: * methods `aload()` and `alazy_load()` to interface `BaseLoader` * implementation for class `MergedDataLoader ` * support for class `BaseLoader` in async function `aindex()` with unit tests Note: this is compatible with existing `aload()` methods that some loaders already had. **Twitter handle:** @cbornet_ --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>	8 months ago
thiswillbeyourgithub	1d082359ee	community: add support for callable filters in FAISS (#16190) ... - **Description:** Filtering in a FAISS vectorstores is very inflexible and doesn't allow that many use case. I think supporting callable like this enables a lot: regular expressions, condition on multiple keys etc. **Note** I had to manually alter a test. I don't understand if it was falty to begin with or if there is something funky going on. - **Issue:** None - **Dependencies:** None - **Twitter handle:** None Signed-off-by: thiswillbeyourgithub <26625900+thiswillbeyourgithub@users.noreply.github.com>	8 months ago
Volodymyr Machula	32c5be8b73	community[minor]: Connery Tool and Toolkit (#14506) ... ## Summary This PR implements the "Connery Action Tool" and "Connery Toolkit". Using them, you can integrate Connery actions into your LangChain agents and chains. Connery is an open-source plugin infrastructure for AI. With Connery, you can easily create a custom plugin with a set of actions and seamlessly integrate them into your LangChain agents and chains. Connery will handle the rest: runtime, authorization, secret management, access management, audit logs, and other vital features. Additionally, Connery and our community offer a wide range of ready-to-use open-source plugins for your convenience. Learn more about Connery: - GitHub: https://github.com/connery-io/connery-platform - Documentation: https://docs.connery.io - Twitter: https://twitter.com/connery_io ## TODOs - [x] API wrapper - [x] Integration tests - [x] Connery Action Tool - [x] Docs - [x] Example - [x] Integration tests - [x] Connery Toolkit - [x] Docs - [x] Example - [x] Formatting (`make format`) - [x] Linting (`make lint`) - [x] Testing (`make test`)	8 months ago
Neli Hateva	c95facc293	langchain[minor], community[minor]: Implement Ontotext GraphDB QA Chain (#16019) ... - **Description:** Implement Ontotext GraphDB QA Chain - **Issue:** N/A - **Dependencies:** N/A - **Twitter handle:** @OntotextGraphDB	8 months ago