langchain

Commit Graph

Author	SHA1	Message	Date
ColabDog	6ad6bb46c4	Feature/add deepeval (#10349 ) Description: Adding `DeepEval` - which provides an opinionated framework for testing and evaluating LLMs Issue: Missing Deepeval Dependencies: Optional DeepEval dependency Tag maintainer: @baskaryan (not 100% sure) Twitter handle: https://twitter.com/ColabDog	1 year ago
eryk-dsai	675d57df50	New LLM integration: Ctranslate2 (#10400 ) ## Description: I've integrated CTranslate2 with LangChain. CTranlate2 is a recently popular library for efficient inference with Transformer models that compares favorably to alternatives such as HF Text Generation Inference and vLLM in [benchmarks](https://hamel.dev/notes/llm/inference/03_inference.html).	1 year ago
zhanghexian	62fa2bc518	Add Vearch vectorstore (#9846 ) --------- Co-authored-by: zhanghexian1 <zhanghexian1@jd.com> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Bagatur	7203c97e8f	Add redis self-query support (#10199 )	1 year ago
Hugues	3e5a143625	Enhancements and bug fixes for `LLMonitorCallbackHandler` (#10297 ) Hi @baskaryan, I've made updates to LLMonitorCallbackHandler to address a few bugs reported by users These changes don't alter the fundamental behavior of the callback handler. Thanks you! --------- Co-authored-by: vincelwt <vince@lyser.io>	1 year ago
Hamza Tahboub	8c0f391815	Implemented MMR search for Redis (#10140 ) Description: Implemented MMR search for Redis. Pretty straightforward, just using the already implemented MMR method on similarity search–fetched docs. Issue: #10059 Dependencies: None Twitter handle: @hamza_tahboub --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	9095dc69ac	Konko fix dependency	1 year ago
Michael Haddad	c6b27b3692	add konko chat_model files (#10267 ) _Thank you to the LangChain team for the great project and in advance for your review. Let me know if I can provide any other additional information or do things differently in the future to make your lives easier 🙏 _ @hwchase17 please let me know if you're not the right person to review 😄 This PR enables LangChain to access the Konko API via the chat_models API wrapper. Konko API is a fully managed API designed to help application developers: 1. Select the right LLM(s) for their application 2. Prototype with various open-source and proprietary LLMs 3. Move to production in-line with their security, privacy, throughput, latency SLAs without infrastructure set-up or administration using Konko AI's SOC 2 compliant infrastructure _Note on integration tests:_ We added 14 integration tests. They will all fail unless you export the right API keys. 13 will pass with a KONKO_API_KEY provided and the other one will pass with a OPENAI_API_KEY provided. When both are provided, all 14 integration tests pass. If you would like to test this yourself, please let me know and I can provide some temporary keys. ### Installation and Setup 1. First you'll need an API key 2. Install Konko AI's Python SDK 1. Enable a Python3.8+ environment `pip install konko` 3. Set API Keys Option 1: Set Environment Variables You can set environment variables for 1. KONKO_API_KEY (Required) 2. OPENAI_API_KEY (Optional) In your current shell session, use the export command: `export KONKO_API_KEY={your_KONKO_API_KEY_here}` `export OPENAI_API_KEY={your_OPENAI_API_KEY_here} #Optional` Alternatively, you can add the above lines directly to your shell startup script (such as .bashrc or .bash_profile for Bash shell and .zshrc for Zsh shell) to have them set automatically every time a new shell session starts. Option 2: Set API Keys Programmatically If you prefer to set your API keys directly within your Python script or Jupyter notebook, you can use the following commands: ```python konko.set_api_key('your_KONKO_API_KEY_here') konko.set_openai_api_key('your_OPENAI_API_KEY_here') # Optional ``` ### Calling a model Find a model on the [[Konko Introduction page](https://docs.konko.ai/docs#available-models)](https://docs.konko.ai/docs#available-models) For example, for this [[LLama 2 model](https://docs.konko.ai/docs/meta-llama-2-13b-chat)](https://docs.konko.ai/docs/meta-llama-2-13b-chat). The model id would be: `"meta-llama/Llama-2-13b-chat-hf"` Another way to find the list of models running on the Konko instance is through this [[endpoint](https://docs.konko.ai/reference/listmodels)](https://docs.konko.ai/reference/listmodels). From here, we can initialize our model: ```python chat_instance = ChatKonko(max_tokens=10, model = 'meta-llama/Llama-2-13b-chat-hf') ``` And run it: ```python msg = HumanMessage(content="Hi") chat_response = chat_instance([msg]) ```	1 year ago
Mateusz Wosinski	69fe0621d4	Merge branch 'master' into deepsense/text-to-speech	1 year ago
Leonid Ganeline	fdba711d28	docs `integrations/embeddings` consistency (#10302 ) Updated `integrations/embeddings`: fixed titles; added links, descriptions Updated `integrations/providers`.	1 year ago
Bagatur	8826293c88	Add multilingual data anon chain (#10346 )	1 year ago
Greg Richardson	300559695b	Supabase vector self querying retriever (#10304 ) ## Description Adds Supabase Vector as a self-querying retriever. - Designed to be backwards compatible with existing `filter` logic on `SupabaseVectorStore`. - Adds new filter `postgrest_filter` to `SupabaseVectorStore` `similarity_search()` methods - Supports entire PostgREST [filter query language](https://postgrest.org/en/stable/references/api/tables_views.html#read) (used by self-querying retriever, but also works as an escape hatch for more query control) - `SupabaseVectorTranslator` converts Langchain filter into the above PostgREST query - Adds Jupyter Notebook for the self-querying retriever - Adds tests ## Tag maintainer @hwchase17 ## Twitter handle [@ggrdson](https://twitter.com/ggrdson)	1 year ago
kcocco	b1d40b8626	Fix colab link(missing graph in url) and comment to match the code fo… (#10344 ) - Description: Fixing Colab broken link and comment correction to align with the code that uses Warren Buffet for wiki query - Issue: None open - Dependencies: none - Tag maintainer: n/a - Twitter handle: Not a PR change but: kcocco	1 year ago
Bagatur	49e0c83126	Split LCEL cookbook (#10342 )	1 year ago
Bagatur	41a2548611	Fix presidio docs Colab links	1 year ago
Bagatur	1d2b6c3c67	Reorganize presidio anonymization docs	1 year ago
maks-operlejn-ds	274c3dc3a8	Multilingual anonymization (#10327 ) ### Description Add multiple language support to Anonymizer PII detection in Microsoft Presidio relies on several components - in addition to the usual pattern matching (e.g. using regex), the analyser uses a model for Named Entity Recognition (NER) to extract entities such as: - `PERSON` - `LOCATION` - `DATE_TIME` - `NRP` - `ORGANIZATION` [[Source]](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/predefined_recognizers/spacy_recognizer.py) To handle NER in specific languages, we utilize unique models from the `spaCy` library, recognized for its extensive selection covering multiple languages and sizes. However, it's not restrictive, allowing for integration of alternative frameworks such as [Stanza](https://microsoft.github.io/presidio/analyzer/nlp_engines/spacy_stanza/) or [transformers](https://microsoft.github.io/presidio/analyzer/nlp_engines/transformers/) when necessary. ### Future works - automatic language detection - instead of passing the language as a parameter in `anonymizer.anonymize`, we could detect the language/s beforehand and then use the corresponding NER model. We have discussed this internally and @mateusz-wosinski-ds will look into a standalone language detection tool/chain for LangChain 😄 ### Twitter handle @deepsense_ai / @MaksOpp ### Tag maintainer @baskaryan @hwchase17 @hinthornw	1 year ago
mateusz.wosinski	868db99b17	Merge branch 'master' into deepsense/text-to-speech	1 year ago
Ofer Mendelevitch	a9eb7c6cfc	Adding Self-querying for Vectara (#10332 ) - Description: Adding support for self-querying to Vectara integration - Issue: per customer request - Tag maintainer: @rlancemartin @baskaryan - Twitter handle: @ofermend Also updated some documentation, added self-query testing, and a demo notebook with self-query example.	1 year ago
Bagatur	f0ccce76fe	nuclia db nit (#10334 )	1 year ago
Bagatur	205f406485	nuclia nb nit (#10331 )	1 year ago
maks-operlejn-ds	f747e76b73	Fixed link to colab notebook (#10320 ) small fix to anonymizer documentation	1 year ago
maks-operlejn-ds	4cc4534d81	Data deanonymization (#10093 ) ### Description The feature for pseudonymizing data with ability to retrieve original text (deanonymization) has been implemented. In order to protect private data, such as when querying external APIs (OpenAI), it is worth pseudonymizing sensitive data to maintain full privacy. But then, after the model response, it would be good to have the data in the original form. I implemented the `PresidioReversibleAnonymizer`, which consists of two parts: 1. anonymization - it works the same way as `PresidioAnonymizer`, plus the object itself stores a mapping of made-up values to original ones, for example: ``` { "PERSON": { "<anonymized>": "<original>", "John Doe": "Slim Shady" }, "PHONE_NUMBER": { "111-111-1111": "555-555-5555" } ... } ``` 2. deanonymization - using the mapping described above, it matches fake data with original data and then substitutes it. Between anonymization and deanonymization user can perform different operations, for example, passing the output to LLM. ### Future works - instance anonymization - at this point, each occurrence of PII is treated as a separate entity and separately anonymized. Therefore, two occurrences of the name John Doe in the text will be changed to two different names. It is therefore worth introducing support for full instance detection, so that repeated occurrences are treated as a single object. - better matching and substitution of fake values for real ones - currently the strategy is based on matching full strings and then substituting them. Due to the indeterminism of language models, it may happen that the value in the answer is slightly changed (e.g. John Doe -> John or Main St, New York -> New York) and such a substitution is then no longer possible. Therefore, it is worth adjusting the matching for your needs. - Q&A with anonymization - when I'm done writing all the functionality, I thought it would be a cool resource in documentation to write a notebook about retrieval from documents using anonymization. An iterative process, adding new recognizers to fit the data, lessons learned and what to look out for ### Twitter handle @deepsense_ai / @MaksOpp --------- Co-authored-by: MaksOpp <maks.operlejn@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	f4f9254dad	Move Myscale SQL vector retrieval nb	1 year ago
刘方瑞	890ed775a3	Resolve: VectorSearch enabled SQLChain? (#10177 ) Squashed from #7454 with updated features We have separated the `SQLDatabseChain` from `VectorSQLDatabseChain` and put everything into `experimental/`. Below is the original PR message from #7454. ------- We have been working on features to fill up the gap among SQL, vector search and LLM applications. Some inspiring works like self-query retrievers for VectorStores (for example [Weaviate](https://python.langchain.com/en/latest/modules/indexes/retrievers/examples/weaviate_self_query.html) and [others](https://python.langchain.com/en/latest/modules/indexes/retrievers/examples/self_query.html)) really turn those vector search databases into a powerful knowledge base! 🚀🚀 We are thinking if we can merge all in one, like SQL and vector search and LLMChains, making this SQL vector database memory as the only source of your data. Here are some benefits we can think of for now, maybe you have more 👀: With ALL data you have: since you store all your pasta in the database, you don't need to worry about the foreign keys or links between names from other data source. Flexible data structure: Even if you have changed your schema, for example added a table, the LLM will know how to JOIN those tables and use those as filters. SQL compatibility: We found that vector databases that supports SQL in the marketplace have similar interfaces, which means you can change your backend with no pain, just change the name of the distance function in your DB solution and you are ready to go! ### Issue resolved: - [Feature Proposal: VectorSearch enabled SQLChain?](https://github.com/hwchase17/langchain/issues/5122) ### Change made in this PR: - An improved schema handling that ignore `types.NullType` columns - A SQL output Parser interface in `SQLDatabaseChain` to enable Vector SQL capability and further more - A Retriever based on `SQLDatabaseChain` to retrieve data from the database for RetrievalQAChains and many others - Allow `SQLDatabaseChain` to retrieve data in python native format - Includes PR #6737 - Vector SQL Output Parser for `SQLDatabaseChain` and `SQLDatabaseChainRetriever` - Prompts that can implement text to VectorSQL - Corresponding unit-tests and notebook ### Twitter handle: - @MyScaleDB ### Tag Maintainer: Prompts / General: @hwchase17, @baskaryan DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev ### Dependencies: No dependency added	1 year ago
Eric BREHAULT	19b4ecdc39	Implement NucliaDB vector store (#10236 ) # Description This pull request allows to use the [NucliaDB](https://docs.nuclia.dev/docs/docs/nucliadb/intro) as a vector store in LangChain. It works with both a [local NucliaDB instance](https://docs.nuclia.dev/docs/docs/nucliadb/deploy/basics) or with [Nuclia Cloud](https://nuclia.cloud). # Dependencies It requires an up-to-date version of the `nuclia` Python package. @rlancemartin, @eyurtsev, @hinthornw, please review it when you have a moment :) Note: our Twitter handler is `@NucliaAI`	1 year ago
Bagatur	1fb7bdd595	Split sql use case docs (#10257 ) Split sql use case into directory so we can add other structured data pages	1 year ago
Bagatur	763212eafd	Add use case nb position (#10299 )	1 year ago
Ikko Eltociear Ashimine	ea5d29a702	Update amazon_comprehend_chain.ipynb (#10246 ) Huggingface, HuggingFace -> Hugging Face	1 year ago
captivus	86cb9da735	Updated Additional Resources section of documentation (#10260 ) - Description: Updated Additional Resources section of documentation and added to YouTube videos with excellent playlist of Langchain content from Sam Witteveen - Issue: None -- updating documentation - Dependencies: None - Tag maintainer: @baskaryan	1 year ago
JaéGeR	b8669b249e	Added Hugging face inference api (#10280 ) Embed documents without locally downloading the HF model --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Randy	1690013711	Doc: openai_functions_agent.mdx import (#10282 ) Fix the import in docmention --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
William FH	13c5951e26	Add LCEL cookbook examples (#10290 ) 1. For passing config to runnable lambda 2. For branching and merging	1 year ago
Pihplipe Oegr	bce38b7163	Add notebook example to use sqlite-vss as a vector store. (#10292 ) Follow-up PR for https://github.com/langchain-ai/langchain/pull/10047, simply adding a notebook quickstart example for the vector store with SQLite, using the class SQLiteVSS. Maintainer tag @baskaryan Co-authored-by: Philippe Oger <philippe.oger@adevinta.com>	1 year ago
Tomaz Bratanic	db73c9d5b5	Diffbot Graph Transformer / Neo4j Graph document ingestion (#9979 ) Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Nik	49341483da	Update Banana.dev docs to latest correct usage (#10183 ) - Description: this PR updates all Banana.dev-related docs to match the latest client usage. The code in the docs before this PR were out of date and would never run. - Issue: [#6404](https://github.com/langchain-ai/langchain/issues/6404) - Dependencies: - - Tag maintainer: - Twitter handle: [BananaDev_ ](https://twitter.com/BananaDev_ )	1 year ago
mateusz.wosinski	7b7bea5424	Fix linters, update notebook	1 year ago
Bagatur	c732d8fffd	use case docs reorder (#10074 )	1 year ago
William FH	be152b6a56	Better ls info (#10202 )	1 year ago
Manuel Soria	dde1992fdd	Adding custom tools to SQL Agent (#10198 ) Changes in: - `create_sql_agent` function so that user can easily add custom tools as complement for the toolkit. - updating sql use case notebook to showcase 2 examples of extra tools. Motivation for these changes is having the possibility of including domain expert knowledge to the agent, which improves accuracy and reduces time/tokens. --------- Co-authored-by: Manuel Soria <manuel.soria@greyscaleai.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Lance Martin	8998060d85	Update docs w/ prompt hub (#10197 ) Small updates to docs	1 year ago
Bagatur	a94dc6ee44	model garden nit (#10194 )	1 year ago
Aashish Saini	8bba69ffd0	Fixed some grammatical typos in doc files (#10191 ) Fixed some grammatical typos in doc files CC: @baskaryan, @eyurtsev, @rlancemartin. --------- Co-authored-by: Aashish Saini <141953346+AashishSainiShorthillsAI@users.noreply.github.com> Co-authored-by: AryamanJaiswalShorthillsAI <142397527+AryamanJaiswalShorthillsAI@users.noreply.github.com> Co-authored-by: Adarsh Shrivastav <142413097+AdarshKumarShorthillsAI@users.noreply.github.com> Co-authored-by: Vishal <141389263+VishalYadavShorthillsAI@users.noreply.github.com> Co-authored-by: ChetnaGuptaShorthillsAI <142381084+ChetnaGuptaShorthillsAI@users.noreply.github.com> Co-authored-by: PankajKumarShorthillsAI <142473460+PankajKumarShorthillsAI@users.noreply.github.com> Co-authored-by: AbhishekYadavShorthillsAI <142393903+AbhishekYadavShorthillsAI@users.noreply.github.com> Co-authored-by: AmitSinghShorthillsAI <142410046+AmitSinghShorthillsAI@users.noreply.github.com> Co-authored-by: Md Nazish Arman <142379599+MdNazishArmanShorthillsAI@users.noreply.github.com> Co-authored-by: KamalSharmaShorthillsAI <142474019+KamalSharmaShorthillsAI@users.noreply.github.com> Co-authored-by: Lakshya <lakshyagupta87@yahoo.com> Co-authored-by: Aayush <142384656+AayushShorthillsAI@users.noreply.github.com> Co-authored-by: AnujMauryaShorthillsAI <142393269+AnujMauryaShorthillsAI@users.noreply.github.com>	1 year ago
mateusz.wosinski	6b9529e11a	Update notebook	1 year ago
mateusz.wosinski	800fe4a73f	Integration with eleven labs	1 year ago
IlyaKIS1	de3322609e	Implemented Milvus translator for self-querying (#10162 ) - Implemented the MilvusTranslator for self-querying using Milvus vector store - Made unit tests to test its functionality - Documented the Milvus self-querying	1 year ago
Aashish Saini	7403faa063	Fixed typo in get_started.mdx (#10163 ) Fix typo: 'Whats up' -> 'What's up' Thanks CC: @baskaryan, @eyurtsev, @rlancemartin. --------- Co-authored-by: Aashish Saini <141953346+AashishSainiShorthillsAI@users.noreply.github.com> Co-authored-by: AryamanJaiswalShorthillsAI <142397527+AryamanJaiswalShorthillsAI@users.noreply.github.com> Co-authored-by: Adarsh Shrivastav <142413097+AdarshKumarShorthillsAI@users.noreply.github.com> Co-authored-by: Vishal <141389263+VishalYadavShorthillsAI@users.noreply.github.com> Co-authored-by: ChetnaGuptaShorthillsAI <142381084+ChetnaGuptaShorthillsAI@users.noreply.github.com> Co-authored-by: PankajKumarShorthillsAI <142473460+PankajKumarShorthillsAI@users.noreply.github.com> Co-authored-by: AbhishekYadavShorthillsAI <142393903+AbhishekYadavShorthillsAI@users.noreply.github.com> Co-authored-by: AmitSinghShorthillsAI <142410046+AmitSinghShorthillsAI@users.noreply.github.com> Co-authored-by: Aayush <142384656+AayushShorthillsAI@users.noreply.github.com>	1 year ago
Aashish Saini	f6f0b0f975	Fixed typo in bittensor.mdx (#10160 ) Fixed Typo in bittenaor.mdx --------- Co-authored-by: Aashish Saini <141953346+AashishSainiShorthillsAI@users.noreply.github.com> Co-authored-by: AryamanJaiswalShorthillsAI <142397527+AryamanJaiswalShorthillsAI@users.noreply.github.com> Co-authored-by: Adarsh Shrivastav <142413097+AdarshKumarShorthillsAI@users.noreply.github.com> Co-authored-by: Vishal <141389263+VishalYadavShorthillsAI@users.noreply.github.com> Co-authored-by: ChetnaGuptaShorthillsAI <142381084+ChetnaGuptaShorthillsAI@users.noreply.github.com> Co-authored-by: PankajKumarShorthillsAI <142473460+PankajKumarShorthillsAI@users.noreply.github.com> Co-authored-by: AbhishekYadavShorthillsAI <142393903+AbhishekYadavShorthillsAI@users.noreply.github.com> Co-authored-by: Aayush <142384656+AayushShorthillsAI@users.noreply.github.com>	1 year ago
Christophe Bornet	803d0d9656	Add the possibility to configure boto3 in the S3 loaders (#9304 ) - Description: this PR adds the possibility to configure boto3 in the S3 loaders. Any named argument you add will be used to create the Boto3 session. This is useful when the AWS credentials can't be passed as env variables or can't be read from the credentials file. - Issue: N/A - Dependencies: N/A - Tag maintainer: ? - Twitter handle: cbornet_ --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Leonid Ganeline	03174c91d0	docs: `MLflow API` and examples (#9547 ) Added docs and links to the API and examples provided by MLflow itself	1 year ago
Xiaoyu Xee	9bcfd58580	Add dashvector self query retriever (#9684 ) ## Description Add `Dashvector` retriever and self-query retriever ## How to use ```python from langchain.vectorstores.dashvector import DashVector vectorstore = DashVector.from_documents(docs, embeddings) retriever = SelfQueryRetriever.from_llm( llm, vectorstore, document_content_description, metadata_field_info, verbose=True ) ``` --------- Co-authored-by: smallrain.xuxy <smallrain.xuxy@alibaba-inc.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Leonid Ganeline	056e59672b	docs: `DeepLake` example (#9663 ) Updated the `Deep Lake` example. Added a link to an example provided by Activeloop.	1 year ago
seamusp	43c4c6dfcc	docs: misc modelIO fixes (#9734 ) Various improvements to the Model I/O section of the documentation - Changed "Chat Model" to "chat model" in a few spots for internal consistency - Minor spelling & grammar fixes to improve readability & comprehension	1 year ago
Nino Risteski	433c4a721e	typo in locall llms fixed (#9755 ) Hi, I noticed a typo in the local_llms.ipynb file and fixed it. The word challenge is without 'a' in the original file. @baskaryan , @eyurtsev Thanks. Co-authored-by: Fliprise <fliprise@Fliprises-MacBook-Pro.local>	1 year ago
seamusp	16945c9922	docs: misc retrievers fixes (#9791 ) Various miscellaneous fixes to most pages in the 'Retrievers' section of the documentation: - "VectorStore" and "vectorstore" changed to "vector store" for consistency - Various spelling, grammar, and formatting improvements for readability Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Terry Tan	8bc452a466	Enhance Google search tool SerpApi response (#10157 ) Enhance SerpApi response which potential to have more relevant output. <img width="345" alt="Screenshot 2023-09-01 at 8 26 13 AM" src="https://github.com/langchain-ai/langchain/assets/10222402/80ff684d-e02e-4143-b218-5c1b102cbf75"> Query: What is the weather in Pomfret? Before: > I should look up the current weather conditions. ... Final Answer: The current weather in Pomfret is 73°F with 1% chance of precipitation and winds at 10 mph. After: > I should look up the current weather conditions. ... Final Answer: The current weather in Pomfret is 62°F, 1% precipitation, 61% humidity, and 4 mph wind. --- Query: Top team in english premier league? Before: > I need to find out which team is currently at the top of the English Premier League ... Final Answer: Liverpool FC is currently at the top of the English Premier League. After: > I need to find out which team is currently at the top of the English Premier League ... Final Answer: Man City is currently at the top of the English Premier League. --- Query: Top team in english premier league? Before: > I need to find out which team is currently at the top of the English Premier League ... Final Answer: Liverpool FC is currently at the top of the English Premier League. After: > I need to find out which team is currently at the top of the English Premier League ... Final Answer: Man City is currently at the top of the English Premier League. --- Query: Any upcoming events in Paris? Before: > I should look for events in Paris Action: Search ... Final Answer: Upcoming events in Paris this month include Whit Sunday & Whit Monday (French National Holiday), Makeup in Paris, Paris Jazz Festival, Fete de la Musique, and Salon International de la Maison de. After: > I should look for events in Paris Action: Search ... Final Answer: Upcoming events in Paris include Elektric Park 2023, The Aces, and BEING AS AN OCEAN.	1 year ago
Aashish Saini	fe0e191fb3	Made some Grammatical error fixes (#10156 ) Made some Grammatical error fixes. CC: @baskaryan, @eyurtsev, @rlancemartin. --------- Co-authored-by: Aashish Saini <141953346+AashishSainiShorthillsAI@users.noreply.github.com> Co-authored-by: AryamanJaiswalShorthillsAI <142397527+AryamanJaiswalShorthillsAI@users.noreply.github.com> Co-authored-by: Adarsh Shrivastav <142413097+AdarshKumarShorthillsAI@users.noreply.github.com> Co-authored-by: Vishal <141389263+VishalYadavShorthillsAI@users.noreply.github.com> Co-authored-by: ChetnaGuptaShorthillsAI <142381084+ChetnaGuptaShorthillsAI@users.noreply.github.com> Co-authored-by: PankajKumarShorthillsAI <142473460+PankajKumarShorthillsAI@users.noreply.github.com> Co-authored-by: AbhishekYadavShorthillsAI <142393903+AbhishekYadavShorthillsAI@users.noreply.github.com>	1 year ago
Geonwoo Kim	e34dde3d15	docs: Fix `CustomLLM` and `Question_answering` docs (#9782 ) ### Description - Update `CustomLLM._call`: Corrected the _call method in CustomLLM to include **kwargs, ensuring consistency with parent class. - Update `Question_answering`: To fix `Page not found` error - https://python.langchain.com/docs/use_cases/code -> https://python.langchain.com/docs/use_cases/code_understanding ### Issue N/A ### Dependencies N/A ### Tag maintainer N/A ### Twitter handle N/A	1 year ago
Aashish Saini	94efede93c	Fixed Typos and grammatical issues in document files (#9789 ) Fixed typos and grammatical issues in document files. @baskaryan , @eyurtsev --------- Co-authored-by: Aashish Saini <141953346+AashishSainiShorthillsAI@users.noreply.github.com> Co-authored-by: AryamanJaiswalShorthillsAI <142397527+AryamanJaiswalShorthillsAI@users.noreply.github.com> Co-authored-by: Adarsh Shrivastav <142413097+AdarshKumarShorthillsAI@users.noreply.github.com> Co-authored-by: Vishal <141389263+VishalYadavShorthillsAI@users.noreply.github.com> Co-authored-by: ChetnaGuptaShorthillsAI <142381084+ChetnaGuptaShorthillsAI@users.noreply.github.com> Co-authored-by: PankajKumarShorthillsAI <142473460+PankajKumarShorthillsAI@users.noreply.github.com> Co-authored-by: AbhishekYadavShorthillsAI <142393903+AbhishekYadavShorthillsAI@users.noreply.github.com>	1 year ago
Philippe PRADOS	f59e5d48ed	Google drive integration (lite) (#9999 ) My other [pull-request](https://github.com/langchain-ai/langchain/pull/5135) is too big to be acceptable. I propose another 'lite' version. I update only notebook to propose an integration with the external project [`langchain-googledrive`](https://github.com/pprados/langchain-googledrive). --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Viktor Zhemchuzhnikov	507e46844e	Extend SQLChatMessageHistory (#9849 ) ### Description There is a really nice class for saving chat messages into a database - SQLChatMessageHistory. It leverages SqlAlchemy to be compatible with any supported database (in contrast with PostgresChatMessageHistory, which is basically the same but is limited to Postgres). However, the class is not really customizable in terms of what you can store. I can imagine a lot of use cases, when one will need to save a message date, along with some additional metadata. To solve this, I propose to extract the converting logic from BaseMessage to SQLAlchemy model (and vice versa) into a separate class - message converter. So instead of rewriting the whole SQLChatMessageHistory class, a user will only need to write a custom model and a simple mapping class, and pass its instance as a parameter. I also noticed that there is no documentation on this class, so I added that too, with an example of custom message converter. ### Issue N/A ### Dependencies N/A ### Tag maintainer Not yet ### Twitter handle N/A	1 year ago
Jon Bennion	fed137a8a9	adding new chain for logical fallacy removal from model output in chain (#9887 ) Description: new chain for logical fallacy removal from model output in chain and docs Issue: n/a see above Dependencies: none Tag maintainer: @hinthornw in past from my end but not sure who that would be for maintenance of chains Twitter handle: no twitter feel free to call out my git user if shout out j-space-b Note: created documentation in docs/extras --------- Co-authored-by: Jon Bennion <jb@Jons-MacBook-Pro.local> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Lance Martin	16a27ab244	Add prompt hub for various use-cases (#9879 ) Use prompt hub in our use-case docs and guides.	1 year ago
Leonid Ganeline	a52fe9528e	docs: fixed title in `Bittensor` example (#9893 ) Fixed title in the `Bittensor` example. The old title brakes the sorted order of items in the navbar. Added some formatting.	1 year ago
seamusp	abd8681341	docs: chains & memory fixes (#9895 ) Various improvements to the Chains & Memory sections of the documentation including formatting, spelling, and grammar fixes to improve readability.	1 year ago
Josh White	bc8cceebf7	Extend DynamoDBChatMessageHistory to support composite keys (#9896 ) - Description: Adds two optional parameters to the DynamoDBChatMessageHistory class to enable users to pass in a name for their PrimaryKey, or a Key object itself to enable the use of composite keys, a common DynamoDB paradigm. [AWS DynamoDB Key docs](https://aws.amazon.com/blogs/database/choosing-the-right-dynamodb-partition-key/) - Issue: N/A - Dependencies: N/A - Twitter handle: N/A --------- Co-authored-by: Josh White <josh@ctrlstack.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Blake (Yung Cher Ho)	f4bed8a04c	Takeoff baseurl support (#10091 ) ## Description This PR introduces a minor change to the TitanTakeoff integration. Instead of specifying a port on localhost, this PR will allow users to specify a baseURL instead. This will allow users to use the integration if they have TitanTakeoff deployed externally (not on localhost). This removes the hardcoded reference to localhost "http://localhost:{port}". ### Info about Titan Takeoff Titan Takeoff is an inference server created by [TitanML](https://www.titanml.co/) that allows you to deploy large language models locally on your hardware in a single command. Most generative model architectures are included, such as Falcon, Llama 2, GPT2, T5 and many more. Read more about Titan Takeoff here: - [Blog](https://medium.com/@TitanML/introducing-titan-takeoff-6c30e55a8e1e) - [Docs](https://docs.titanml.co/docs/titan-takeoff/getting-started) ### Dependencies No new dependencies are introduced. However, users will need to install the titan-iris package in their local environment and start the Titan Takeoff inferencing server in order to use the Titan Takeoff integration. Thanks for your help and please let me know if you have any questions. cc: @hwchase17 @baskaryan --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Pu Cao	05664a6f20	docs(text_splitter): update document of character splitter with tiktoken (#10001 ) The current document has not mentioned that splits larger than chunk size would happen. I update the related document and explain why it happens and how to solve it. related issue #1349 #3838 #2140	1 year ago
Leonid Ganeline	2221194450	`Yahoo Finance News` tool (#10014 ) Added: - the `Yahoo Finance News` tool - Ut-s - An example	1 year ago
Ismail Pelaseyed	5c3e9c9083	Add example of running Q&A over structured data using the `Airbyte` loaders and `pandas` (#10069 ) - Description: Added example of running Q&A over structured data using the `Airbyte` loaders and `pandas` - Dependencies: any dependencies required for this change, - Tag maintainer: @hwchase17 - Twitter handle: @pelaseyed	1 year ago
Lars von Wedel	6d82503eb1	Add parser and loader for Azure document intelligence service. (#10136 ) Hi, this PR contains loader / parser for Azure Document intelligence which is a ML-based service to ingest arbitrary PDFs / images, even if scanned. The loader generates Documents by pages of the original document. This is my first contribution to LangChain. Unfortunately I could not find the correct place for test cases. Happy to add one if you can point me to the location, but as this is a cloud-based service, a test would require network access and credentials - so might be of limited help. Dependencies: The needed dependency was already part of pyproject.toml, no change. Twitter: feel free to mention @LarsAC on the announcement	1 year ago
Harrison Chase	4abe85be57	Harrison/string inplace (#10153 ) Co-authored-by: Wrick Talukdar <wrick.talukdar@gmail.com> Co-authored-by: Anjan Biswas <anjanavb@amazon.com> Co-authored-by: Jha <nikjha@amazon.com> Co-authored-by: Lucky-Lance <77819606+Lucky-Lance@users.noreply.github.com> Co-authored-by: 陆徐东 <luxudong@MacBook-Pro.local>	1 year ago
Nino Risteski	0c0a7d19eb	Update openai_multi_functions_agent.ipynb (#10144 ) typo fix	1 year ago
Nino Risteski	f968b86652	Update apis.ipynb (#10145 ) few typo fixes	1 year ago
Guy Korland	765ef3b486	Add FalkorDB to imports (#10151 )	1 year ago
Nino Risteski	746c6ff9c3	Update index.mdx (#10142 ) fixed typos	1 year ago
Nino Risteski	fdebd3e02f	Update chat_vector_db.mdx (#10141 ) typo fix	1 year ago
Leonid Kuligin	30239b3025	added support for inference from Model Garden (#9367 ) #8850 --------- Co-authored-by: Leonid Kuligin <kuligin@google.com>	1 year ago
Leonid Ganeline	54a8df87b9	📖 docs: fixed `integration/llms` navbar (#9277 ) Fixed navbar: - renamed several files, so ToC is sorted correctly - made ToC items consistent: formatted several Titles - added several links - reformatted several docs to a consistent format - renamed several files (removed `_example` suffix) - added renamed files to the `docs/docs_skeleton/vercel.json`	1 year ago
Bagatur	b485c3048b	rm base64 images from docs (#10110 ) Causing problems indexing docs and notebook images don't render after markdown conversion anyways	1 year ago
William FH	f2fc4173c3	Update redirects meta tags (#10109 )	1 year ago
Leonid Ganeline	37e435bd00	docs: `youtube_search` tool example update (#9958 ) Added a link to source package; updated title, description.	1 year ago
Leonid Ganeline	3b8ee74e38	docs: `google-drive-tool` example fix (#10000 ) This notebook was mistakenly placed in the `toolkits` folder and appears within `Agents & Toolkits` menu. But it should be in `Tools`. Moved example into `tools/`; updated title to consistent format.	1 year ago
seamusp	afd96b2460	docs: agents & callbacks fixes (#10066 ) Various improvements to the Agents & Callbacks sections of the documentation including formatting, spelling, and grammar fixes to improve readability.	1 year ago
Benjamin Matson	58d7d86e51	feat: add bedrock chat model (#8017 ) Replace this comment with: - Description: Add Bedrock implementation of Anthropic Claude for Chat - Tag maintainer: @hwchase17, @baskaryan - Twitter handle: @bwmatson --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
KyrianC	491089754d	EdenAI LLM update. Add models name option (#8963 ) This PR follows the Eden AI (LLM + embeddings) integration. #8633 We added an optional parameter to choose different AI models for providers (like 'text-bison' for provider 'google', 'text-davinci-003' for provider 'openai', etc.). Usage: ```python llm = EdenAI( feature="text", provider="google", params={ "model": "text-bison", # new "temperature": 0.2, "max_tokens": 250, }, ) ``` You can also change the provider + model after initialization ```python llm = EdenAI( feature="text", provider="google", params={ "temperature": 0.2, "max_tokens": 250, }, ) prompt = """ hi """ llm(prompt, providers='openai', model='text-davinci-003') # change provider & model ``` The jupyter notebook as been updated with an example well. Ping: @hwchase17, @baskaryan --------- Co-authored-by: RedhaWassim <rwasssim@gmail.com> Co-authored-by: sam <melaine.samy@gmail.com>	1 year ago
Bagatur	71c418725f	index rename delete_mode -> cleanup (#10103 )	1 year ago
Bagatur	b927277809	Bagatur/eden type 2 (#10102 )	1 year ago
Bagatur	d4380339c1	eden tool nb nit (#10101 )	1 year ago
KyrianC	c7a5504789	Add EdenAI Tools (#9764 ) This PR follows the Eden AI (LLM + embeddings) integration. #8633 We added different Tools to empower agents with new capabilities : - text: explicit content detection - image: explicit content detection - image: object detection - OCR: invoice parsing - OCR: ID parsing - audio: speech to text - audio: text to speech We plan to add more in the future (like translation, language detection, + others). Usage: ```python llm=EdenAI(feature="text",provider="openai", params={"temperature" : 0.2,"max_tokens" : 250}) tools = [ EdenAiTextModerationTool(providers=["openai"],language="en"), EdenAiObjectDetectionTool(providers=["google","api4ai"]), EdenAiTextToSpeechTool(providers=["amazon"],language="en",voice="MALE"), EdenAiExplicitImageTool(providers=["amazon","google"]), EdenAiSpeechToTextTool(providers=["amazon"]), EdenAiParsingIDTool(providers=["amazon","klippa"],language="en"), EdenAiParsingInvoiceTool(providers=["amazon","google"],language="en"), ] agent_chain = initialize_agent( tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True, return_intermediate_steps=True, ) result = agent_chain(""" i have this text : 'i want to slap you' first : i want to know if this text contains explicit content or not . second : if it does contain explicit content i want to know what is the explicit content in this text, third : i want to make the text into speech . if there is URL in the observations , you will always put it in the output (final answer) . """) ``` output: > Entering new AgentExecutor chain... > I need to extract the information from the ID and then convert it to text and then to speech > Action: edenai_identity_parsing > Action Input: "https://www.citizencard.com/images/citizencard-uk-id-card-2023.jpg" > Observation: last_name : > value : ANGELA > given_names : > value : GREENE > birth_place : > birth_date : > value : 2000-11-09 > issuance_date : > expire_date : > document_id : > issuing_state : > address : > age : > country : > document_type : > value : DRIVER LICENSE FRONT > gender : > image_id : > image_signature : > mrz : > nationality : > Thought: I now need to convert the information to text and then to speech > Action: edenai_text_to_speech > Action Input: "Welcome Angela Greene!" > Observation: https://d14uq1pz7dzsdq.cloudfront.net/0c494819-0bbc-4433-bfa4-6e99bd9747ea_.mp3?Expires=1693316851&Signature=YcMoVQgPuIMEOuSpFuvhkFM8JoBMSoGMcZb7MVWdqw7JEf5~67q9dEI90o5todE5mYXB5zSYoib6rGrmfBl4Rn5~yqDwZ~Tmc24K75zpQZIEyt5~ZSnHuXy4IFWGmlIVuGYVGMGKxTGNeCRNUXDhT6TXGZlr4mwa79Ei1YT7KcNyc1dsTrYB96LphnsqOERx4X9J9XriSwxn70X8oUPFfQmLcitr-syDhiwd9Wdpg6J5yHAJjf657u7Z1lFTBMoXGBuw1VYmyno-3TAiPeUcVlQXPueJ-ymZXmwaITmGOfH7HipZngZBziofRAFdhMYbIjYhegu5jS7TxHwRuox32A__&Key-Pair-Id=K1F55BTI9AHGIK > Thought: I now know the final answer > Final Answer: https://d14uq1pz7dzsdq.cloudfront.net/0c494819-0bbc-4433-bfa4-6e99bd9747ea_.mp3?Expires=1693316851&Signature=YcMoVQgPuIMEOuSpFuvhkFM8JoBMSoGMcZb7MVWdqw7JEf5~67q9dEI90o5todE5mYXB5zSYoib6rGrmfBl4Rn5~yqDwZ~Tmc24K75zpQZIEyt5~ZSnHuXy4IFWGmlIVuGYVGMGKxTGNeCRNUXDhT6TXGZlr4mwa79Ei1YT7KcNyc1dsTrYB96LphnsqOERx4X9J9XriSwxn70X8oUPFfQmLcitr-syDhiwd9Wdpg6J5y > > Finished chain. Other examples are available in the jupyter notebook. This PR is made in parallel with EdenAI LLM update #8963 I apologize for the messy PR. While working in implementing Tools we realized there was a few problems we needed to fix on LLM as well. Ping: @hwchase17, @baskaryan --------- Co-authored-by: RedhaWassim <rwasssim@gmail.com>	1 year ago
Bagatur	5f1c67b47c	Mv LCEL docs up a level (#10073 )	1 year ago
Harrison Chase	ad9e242a7a	add snippet for max concurrency (#9892 )	1 year ago
Stefano Lottini	c710c7303f	fix wrong import line in cassandra doc page for vector store (#10041 ) This fixes the exampe import line in the general "cassandra" doc page mdx file. (it was erroneously a copy of the chat message history import statement found below).	1 year ago
Jon Bennion	cc6a20d3e6	updated prompt name in documentation for sequential chain (#10048 ) Description: updated the prompt name in a sequential chain example so that it is not overwritten by the same prompt name in the next chain (this is a sequential chain example) Issue: n/a Dependencies: none Tag maintainer: not known Twitter handle: not on twitter, feel free to use my git username for anything	1 year ago
Zizhong Zhang	641b71e2cd	refactor: rename to OpaquePrompts (#10013 ) Renamed to OpaquePrompts cc @baskaryan Thanks in advance!	1 year ago
Bagatur	8d66b00c73	Data anonymizer notebook nit (#10062 )	1 year ago
Bagatur	3efab8d3df	implement vectorstores by tencent vectordb (#9989 ) Hi there！ I'm excited to open this PR to add support for using 'Tencent Cloud VectorDB' as a vector store. Tencent Cloud VectorDB is a fully-managed, self-developed, enterprise-level distributed database service designed for storing, retrieving, and analyzing multi-dimensional vector data. The database supports multiple index types and similarity calculation methods, with a single index supporting vector scales up to 1 billion and capable of handling millions of QPS with millisecond-level query latency. Tencent Cloud VectorDB not only provides external knowledge bases for large models to improve their accuracy, but also has wide applications in AI fields such as recommendation systems, NLP services, computer vision, and intelligent customer service. The PR includes: Implementation of Vectorstore. I have read your [contributing guidelines](`72b7d76d79/.github/CONTRIBUTING.md`). And I have passed the tests below make format make lint make coverage make test	1 year ago
Bagatur	b1644bc9ad	cr	1 year ago
Cameron Vetter	e37d51cab6	fix scoring profile example (#10016 ) - Description: A change in the documentation example for Azure Cognitive Vector Search with Scoring Profile so the example works as written - Issue: #10015 - Dependencies: None - Tag maintainer: @baskaryan @ruoccofabrizio - Twitter handle: @poshporcupine	1 year ago
Hyeokjun seo	e2e05ad89e	Fix Typo : `openai_api_key` -> `serpapi_api_key` (#10020 ) Fixed typo in the comments Notebook. (which says `openai_api_key` for SerpAPI)	1 year ago
Tomaz Bratanic	f2e8399cc8	Fix link in Neo4j provider page (#10023 )	1 year ago
Bagatur	7fa82900cb	guides docs nits (#10005 )	1 year ago
Bagatur	2f03e71e67	rename local llm guide (#10004 )	1 year ago
Bagatur	781f274d19	make privacy guide section (#10003 )	1 year ago
maks-operlejn-ds	a8f804a618	Add data anonymizer (#9863 ) ### Description The feature for anonymizing data has been implemented. In order to protect private data, such as when querying external APIs (OpenAI), it is worth pseudonymizing sensitive data to maintain full privacy. Anonynization consists of two steps: 1. Identification: Identify all data fields that contain personally identifiable information (PII). 2. Replacement: Replace all PIIs with pseudo values or codes that do not reveal any personal information about the individual but can be used for reference. We're not using regular encryption, because the language model won't be able to understand the meaning or context of the encrypted data. We use Microsoft Presidio together with Faker framework for anonymization purposes because of the wide range of functionalities they provide. The full implementation is available in `PresidioAnonymizer`. ### Future works - deanonymization - add the ability to reverse anonymization. For example, the workflow could look like this: `anonymize -> LLMChain -> deanonymize`. By doing this, we will retain anonymity in requests to, for example, OpenAI, and then be able restore the original data. - instance anonymization - at this point, each occurrence of PII is treated as a separate entity and separately anonymized. Therefore, two occurrences of the name John Doe in the text will be changed to two different names. It is therefore worth introducing support for full instance detection, so that repeated occurrences are treated as a single object. ### Twitter handle @deepsense_ai / @MaksOpp --------- Co-authored-by: MaksOpp <maks.operlejn@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	98cce7dcd3	update moderation docs (#10002 )	1 year ago
Christophe Bornet	9870bfb9cd	Add bucket and object key to metadata in S3 loader (#9317 ) - Description: this PR adds `s3_object_key` and `s3_bucket` to the doc metadata when loading an S3 file. This is particularly useful when using `S3DirectoryLoader` to remove the files from the dir once they have been processed (getting the object keys from the metadata `source` field seems brittle) - Dependencies: N/A - Tag maintainer: ? - Twitter handle: _cbornet --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	1 year ago
Guy Korland	24c0b01c38	Extend the FalkorDB QA demo (#9992 ) - Description: Extend the FalkorDB QA demo - Tag maintainer: @baskaryan	1 year ago
wlleiiwang	8c4e29240c	implement vectorstores by tencent vectordb	1 year ago
Leonid Ganeline	d03d6f6fd9	Merge branch 'master' into docs-tools-menu	1 year ago
Bagatur	8fb0a9594c	Add LLMonitor Callback Handler Integration - open-source observability & analytics (#9870 ) Adds support for [llmonitor](https://llmonitor.com) callbacks. It enables: - Requests tracking / logging / analytics - Error debugging - Cost analytics - User tracking Let me know if anythings neds to be changed for merge. Thank you!	1 year ago
leo-gan	8c1678a8c7	Updated titles, descriptions.	1 year ago
Bagatur	7bba1d911b	Fix typo in code_understanding.ipynb (#9899 ) seperate -> separate	1 year ago
Bagatur	2e65434568	docs: Fix the syntax error, replace "dotenv.load_env()" with "dotenv.… (#9900 ) Description: The documents incorrectly mentions "dotenv.load_env()", but it should actually be "dotenv.load_dotenv()". You can see the screenshot below for reference: python-dotenv: 1.0.0 ![image](https://github.com/langchain-ai/langchain/assets/2959046/94dc4b51-cc2f-412d-92e9-16b8ff0d513e)	1 year ago
Bagatur	b416f5c0c8	fix a link name format to the dependents document (#9928 )	1 year ago
Bagatur	8f199239b8	docs: `llms/google vertex AI` example update (#9960 ) Updated title, description, added sections.	1 year ago
Bagatur	2a03a0087d	docs: `memory` menu (#9947 ) The [Memory](https://python.langchain.com/docs/modules/memory/) menu is clogged with unnecessary wording. I've made it more concise by simplifying titles of the example notebooks. As results, menu is shorter and better for comprehend.	1 year ago
Bagatur	f7cc125cac	docs: `memory types` menu (#9949 ) The [Memory Types](https://python.langchain.com/docs/modules/memory/types/) menu is clogged with unnecessary wording. I've made it more concise by simplifying titles of the example notebooks. As results, menu is shorter and better for comprehend.	1 year ago
Bagatur	16eb935469	Fix for similarity_search_with_score (#9903 ) - Description: the implementation for similarity_search_with_score did not actually include a score or logic to filter. Now fixed. - Tag maintainer: @rlancemartin - Twitter handle: @ofermend	1 year ago
Fredrik Gullberg	f69d236a4a	docs: Fix spelling mistakes in apis.ipynb (#9911 ) - Description: Fix spelling mistakes in apis.ipynb - Issue: [#9910](https://github.com/langchain-ai/langchain/issues/9910) Co-authored-by: Fredrik Gullberg <fredrik.gullberg@klarna.com>	1 year ago
Nate Nethercott	0024824a6e	docs: Fix spelling mistakes in retrievers/get_started.mdx (#9920 ) Description: Fix spelling mistakes in retrievers/get_started.mdx	1 year ago
leo-gan	210de0c66b	Updated title, description, added sections	1 year ago
Cameron Hutchison	bcc3463ff4	docs: Azure AD Authentication for Azure OpenAI (#9951 ) # Description This PR adds additional documentation on how to use Azure Active Directory to authenticate to an OpenAI service within Azure. This method of authentication allows organizations with more complex security requirements to use Azure OpenAI. # Issue N/A # Dependencies N/A # Twitter https://twitter.com/CamAHutchison	1 year ago
Guy Korland	7cbe872af8	Add support for Falkordb (ex-RedisGraph) (#9821 ) Replace this entire comment with: - Description: Add support for Falkordb (ex-RedisGraph) - Tag maintainer: @hwchase17 - Twitter handle: @g_korland	1 year ago
Bagatur	ede45f535e	fix intro docs (#9950 )	1 year ago
Leonid Ganeline	393816e7bd	Merge branch 'master' into docs-memory-type-menu	1 year ago
Corvus Lee	0fb95ebe66	Docs: enrich SageMaker endpoint embeddings with docstrings and examples (#9924 ) Description: added comments to address the relationship between input/output transformations and the customised inference.py script.	1 year ago
leo-gan	7c7ae34eeb	updated .mdx titles and text.	1 year ago
leo-gan	d578efba35	updated notebook titles and text.	1 year ago
Leonid Ganeline	4b6e41a939	Merge branch 'master' into docs-memory-menu	1 year ago
Tomaz Bratanic	6092422e10	Add neo4j provider page (#9941 )	1 year ago
leo-gan	c906041aa8	updated notebook titles and text.	1 year ago
Tomaz Bratanic	db13fba7ea	Add neo4j vector support (#9770 ) Neo4j has added vector index integration just recently. To allow both ingestion and integrating it as vector RAG applications, I wrapped it as a vector store as the implementation is completely different from `GraphCypherQAChain`. Here, we are not generating any Cypher statements at query time, we are simply doing the vector similarity search using the new vector index as if we were dealing with a vector database. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Tudor Golubenco	171b0b183b	Pre-release Xata version no longer required (#9915 ) Tiny PR: Since we've released version 1.0.0 of the python SDK, we no longer need to specify the pre-release version when pip installing.	1 year ago
Mike Nitsenko	c80e406e95	Cube semantic loader: allow cubes processing (#9927 ) We've started to receive feedback (after launch) that using only views is confusing. We're considering this as a good practice, as a view serves as a "facade" for your data - however, we decided to let users decide this on their own. Solves the questions from: - https://github.com/cube-js/cube/issues/7028 - https://github.com/langchain-ai/langchain/pull/9690	1 year ago
LiaoKong	8f8455b24d	fix a link name format to the dependents document	1 year ago
Ofer Mendelevitch	8b8d2a6535	fixed similarity_search_with_score to really use a score updated unit test with a test for score threshold Updated demo notebook	1 year ago
Ikko Eltociear Ashimine	766bbd6c6b	Fix typo in code_understanding.ipynb seperate -> separate	1 year ago
tongtie	82a3c2a557	docs: Fix the syntax error, replace "dotenv.load_env()" with "dotenv.load_dotenv()".	1 year ago
Mazhar (Taha) Mumbaiwala	e80834d783	docs: Fix spelling mistakes in Etherscan.ipynb (#9845 )	1 year ago
Philippe PRADOS	7fdb7439e0	Update google drive notebooks (#9851 ) Update google drive doc loader and retriever notebooks. Show how to use with langchain-googledrive package. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Xiaobing Mi	5d47833ae1	Fix typo in web_scraping.ipynb (#9835 )	1 year ago
Leonid Ganeline	b1bffea9c7	docs: fix for title of `llm_caching` nb (#9891 ) Fixed title for the `extras/integrations/llms/llm_caching.ipynb`. Existing title breaks the sorted order of items in the navbar. Updated some formatting.	1 year ago
Leonid Ganeline	e01b00aa54	docs: `ainetwork` update (#9871 ) * Added links to the AI Network * Made title consistent to other tool kits * Added `integrations/providers/` integration card page * No changes in the example code!	1 year ago
Leonid Ganeline	cf122b6269	docs: `Infino` example fix (#9888 ) - Fixed a broken link in the `integrations/providers/infino.mdx` - Fixed a title in the `integration/collbacks/infino.ipynb` example - Updated text format in this example.	1 year ago
Piyush Jain	fe1b9ee6b8	Updated notebook for comprehend moderation (#9875 ) ### Description Updated the notebook for comprehend moderation. cc @baskaryan	1 year ago
William FH	b14d74dd4d	iMessage loader (#9832 ) Add an iMessage chat loader	1 year ago
Lance Martin	8393ba9dab	Add instructions for GGUF (#9874 ) llama.cpp migrated to GGUF model format, and new releases (e.g., [here](https://huggingface.co/TheBloke)) now use GGUF.	1 year ago
hughcrt	3a4d4c940c	Change video width	1 year ago
hughcrt	97741d41c5	Add LLMonitorCallbackHandler	1 year ago
eryk-dsai	7f5713b80a	feat: grammar-based sampling in llama-cpp (#9712 ) ## Description The following PR enables the [grammar-based sampling](https://github.com/ggerganov/llama.cpp/tree/master/grammars) in llama-cpp LLM. In short, loading file with formal grammar definition will constrain model outputs. For instance, one can force the model to generate valid JSON or generate only python lists. In the follow-up PR we will add: * docs with some description why it is cool and how it works * maybe some code sample for some task such as in llama repo --------- Co-authored-by: Lance Martin <lance@langchain.dev> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Harrison Chase	c1badc1fa2	add gmail loader (#9810 )	1 year ago
Vikas Sheoran	63921e327d	docs: Fix a spelling mistake in adding_memory.ipynb (#9794 ) # Description This pull request fixes a small spelling mistake found while reading docs.	1 year ago
Rosário P. Fernandes	aab01b55db	typo: funtions --> functions (#9784 ) Minor typo in the extractions use-case	1 year ago
Sam Partee	a28eea5767	Redis metadata filtering and specification, index customization (#8612 ) ### Description The previous Redis implementation did not allow for the user to specify the index configuration (i.e. changing the underlying algorithm) or add additional metadata to use for querying (i.e. hybrid or "filtered" search). This PR introduces the ability to specify custom index attributes and metadata attributes as well as use that metadata in filtered queries. Overall, more structure was introduced to the Redis implementation that should allow for easier maintainability moving forward. # New Features The following features are now available with the Redis integration into Langchain ## Index schema generation The schema for the index will now be automatically generated if not specified by the user. For example, the data above has the multiple metadata categories. The the following example ```python from langchain.embeddings import OpenAIEmbeddings from langchain.vectorstores.redis import Redis embeddings = OpenAIEmbeddings() rds, keys = Redis.from_texts_return_keys( texts, embeddings, metadatas=metadata, redis_url="redis://localhost:6379", index_name="users" ) ``` Loading the data in through this and the other ``from_documents`` and ``from_texts`` methods will now generate index schema in Redis like the following. view index schema with the ``redisvl`` tool. [link](redisvl.com) ```bash $ rvl index info -i users ``` Index Information: \| Index Name \| Storage Type \| Prefixes \| Index Options \| Indexing \| \|--------------\|----------------\|---------------\|-----------------\|------------\| \| users \| HASH \| ['doc:users'] \| [] \| 0 \| Index Fields: \| Name \| Attribute \| Type \| Field Option \| Option Value \| \|----------------\|----------------\|---------\|----------------\|----------------\| \| user \| user \| TEXT \| WEIGHT \| 1 \| \| job \| job \| TEXT \| WEIGHT \| 1 \| \| credit_score \| credit_score \| TEXT \| WEIGHT \| 1 \| \| content \| content \| TEXT \| WEIGHT \| 1 \| \| age \| age \| NUMERIC \| \| \| \| content_vector \| content_vector \| VECTOR \| \| \| ### Custom Metadata specification The metadata schema generation has the following rules 1. All text fields are indexed as text fields. 2. All numeric fields are index as numeric fields. If you would like to have a text field as a tag field, users can specify overrides like the following for the example data ```python # this can also be a path to a yaml file index_schema = { "text": [{"name": "user"}, {"name": "job"}], "tag": [{"name": "credit_score"}], "numeric": [{"name": "age"}], } rds, keys = Redis.from_texts_return_keys( texts, embeddings, metadatas=metadata, redis_url="redis://localhost:6379", index_name="users" ) ``` This will change the index specification to Index Information: \| Index Name \| Storage Type \| Prefixes \| Index Options \| Indexing \| \|--------------\|----------------\|----------------\|-----------------\|------------\| \| users2 \| HASH \| ['doc:users2'] \| [] \| 0 \| Index Fields: \| Name \| Attribute \| Type \| Field Option \| Option Value \| \|----------------\|----------------\|---------\|----------------\|----------------\| \| user \| user \| TEXT \| WEIGHT \| 1 \| \| job \| job \| TEXT \| WEIGHT \| 1 \| \| content \| content \| TEXT \| WEIGHT \| 1 \| \| credit_score \| credit_score \| TAG \| SEPARATOR \| , \| \| age \| age \| NUMERIC \| \| \| \| content_vector \| content_vector \| VECTOR \| \| \| and throw a warning to the user (log output) that the generated schema does not match the specified schema. ```text index_schema does not match generated schema from metadata. index_schema: {'text': [{'name': 'user'}, {'name': 'job'}], 'tag': [{'name': 'credit_score'}], 'numeric': [{'name': 'age'}]} generated_schema: {'text': [{'name': 'user'}, {'name': 'job'}, {'name': 'credit_score'}], 'numeric': [{'name': 'age'}]} ``` As long as this is on purpose, this is fine. The schema can be defined as a yaml file or a dictionary ```yaml text: - name: user - name: job tag: - name: credit_score numeric: - name: age ``` and you pass in a path like ```python rds, keys = Redis.from_texts_return_keys( texts, embeddings, metadatas=metadata, redis_url="redis://localhost:6379", index_name="users3", index_schema=Path("sample1.yml").resolve() ) ``` Which will create the same schema as defined in the dictionary example Index Information: \| Index Name \| Storage Type \| Prefixes \| Index Options \| Indexing \| \|--------------\|----------------\|----------------\|-----------------\|------------\| \| users3 \| HASH \| ['doc:users3'] \| [] \| 0 \| Index Fields: \| Name \| Attribute \| Type \| Field Option \| Option Value \| \|----------------\|----------------\|---------\|----------------\|----------------\| \| user \| user \| TEXT \| WEIGHT \| 1 \| \| job \| job \| TEXT \| WEIGHT \| 1 \| \| content \| content \| TEXT \| WEIGHT \| 1 \| \| credit_score \| credit_score \| TAG \| SEPARATOR \| , \| \| age \| age \| NUMERIC \| \| \| \| content_vector \| content_vector \| VECTOR \| \| \| ### Custom Vector Indexing Schema Users with large use cases may want to change how they formulate the vector index created by Langchain To utilize all the features of Redis for vector database use cases like this, you can now do the following to pass in index attribute modifiers like changing the indexing algorithm to HNSW. ```python vector_schema = { "algorithm": "HNSW" } rds, keys = Redis.from_texts_return_keys( texts, embeddings, metadatas=metadata, redis_url="redis://localhost:6379", index_name="users3", vector_schema=vector_schema ) ``` A more complex example may look like ```python vector_schema = { "algorithm": "HNSW", "ef_construction": 200, "ef_runtime": 20 } rds, keys = Redis.from_texts_return_keys( texts, embeddings, metadatas=metadata, redis_url="redis://localhost:6379", index_name="users3", vector_schema=vector_schema ) ``` All names correspond to the arguments you would set if using Redis-py or RedisVL. (put in doc link later) ### Better Querying Both vector queries and Range (limit) queries are now available and metadata is returned by default. The outputs are shown. ```python >>> query = "foo" >>> results = rds.similarity_search(query, k=1) >>> print(results) [Document(page_content='foo', metadata={'user': 'derrick', 'job': 'doctor', 'credit_score': 'low', 'age': '14', 'id': 'doc:users:657a47d7db8b447e88598b83da879b9d', 'score': '7.15255737305e-07'})] >>> results = rds.similarity_search_with_score(query, k=1, return_metadata=False) >>> print(results) # no metadata, but with scores [(Document(page_content='foo', metadata={}), 7.15255737305e-07)] >>> results = rds.similarity_search_limit_score(query, k=6, score_threshold=0.0001) >>> print(len(results)) # range query (only above threshold even if k is higher) 4 ``` ### Custom metadata filtering A big advantage of Redis in this space is being able to do filtering on data stored alongside the vector itself. With the example above, the following is now possible in langchain. The equivalence operators are overridden to describe a new expression language that mimic that of [redisvl](redisvl.com). This allows for arbitrarily long sequences of filters that resemble SQL commands that can be used directly with vector queries and range queries. There are two interfaces by which to do so and both are shown. ```python >>> from langchain.vectorstores.redis import RedisFilter, RedisNum, RedisText >>> age_filter = RedisFilter.num("age") > 18 >>> age_filter = RedisNum("age") > 18 # equivalent >>> results = rds.similarity_search(query, filter=age_filter) >>> print(len(results)) 3 >>> job_filter = RedisFilter.text("job") == "engineer" >>> job_filter = RedisText("job") == "engineer" # equivalent >>> results = rds.similarity_search(query, filter=job_filter) >>> print(len(results)) 2 # fuzzy match text search >>> job_filter = RedisFilter.text("job") % "eng*" >>> results = rds.similarity_search(query, filter=job_filter) >>> print(len(results)) 2 # combined filters (AND) >>> combined = age_filter & job_filter >>> results = rds.similarity_search(query, filter=combined) >>> print(len(results)) 1 # combined filters (OR) >>> combined = age_filter \| job_filter >>> results = rds.similarity_search(query, filter=combined) >>> print(len(results)) 4 ``` All the above filter results can be checked against the data above. ### Other - Issue: #3967 - Dependencies: No added dependencies - Tag maintainer: @hwchase17 @baskaryan @rlancemartin - Twitter handle: @sampartee --------- Co-authored-by: Naresh Rangan <naresh.rangan0@walmart.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Anish Shah	fa0b8f3368	fix broken wandb link in debugging page (#9771 ) - Description: Fix broken hyperlink in debugging page	1 year ago
Monami Sharma	12a373810c	Fixing broken links to Moderation and Constitutional chain (#9768 ) - Description: Fixing broken links for Moderation and Constitutional chain - Issue: N/A - Twitter handle: MonamiSharma	1 year ago
nikhilkjha	d57d08fd01	Initial commit for comprehend moderator (#9665 ) This PR implements a custom chain that wraps Amazon Comprehend API calls. The custom chain is aimed to be used with LLM chains to provide moderation capability that let’s you detect and redact PII, Toxic and Intent content in the LLM prompt, or the LLM response. The implementation accepts a configuration object to control what checks will be performed on a LLM prompt and can be used in a variety of setups using the LangChain expression language to not only detect the configured info in chains, but also other constructs such as a retriever. The included sample notebook goes over the different configuration options and how to use it with other chains. ### Usage sample ```python from langchain_experimental.comprehend_moderation import BaseModerationActions, BaseModerationFilters moderation_config = { "filters":[ BaseModerationFilters.PII, BaseModerationFilters.TOXICITY, BaseModerationFilters.INTENT ], "pii":{ "action": BaseModerationActions.ALLOW, "threshold":0.5, "labels":["SSN"], "mask_character": "X" }, "toxicity":{ "action": BaseModerationActions.STOP, "threshold":0.5 }, "intent":{ "action": BaseModerationActions.STOP, "threshold":0.5 } } comp_moderation_with_config = AmazonComprehendModerationChain( moderation_config=moderation_config, #specify the configuration client=comprehend_client, #optionally pass the Boto3 Client verbose=True ) template = """Question: {question} Answer:""" prompt = PromptTemplate(template=template, input_variables=["question"]) responses = [ "Final Answer: A credit card number looks like 1289-2321-1123-2387. A fake SSN number looks like 323-22-9980. John Doe's phone number is (999)253-9876.", "Final Answer: This is a really shitty way of constructing a birdhouse. This is fucking insane to think that any birds would actually create their motherfucking nests here." ] llm = FakeListLLM(responses=responses) llm_chain = LLMChain(prompt=prompt, llm=llm) chain = ( prompt \| comp_moderation_with_config \| {llm_chain.input_keys[0]: lambda x: x['output'] } \| llm_chain \| { "input": lambda x: x['text'] } \| comp_moderation_with_config ) response = chain.invoke({"question": "A sample SSN number looks like this 123-456-7890. Can you give me some more samples?"}) print(response['output']) ``` ### Output ``` > Entering new AmazonComprehendModerationChain chain... Running AmazonComprehendModerationChain... Running pii validation... Found PII content..stopping.. The prompt contains PII entities and cannot be processed ``` --------- Co-authored-by: Piyush Jain <piyushjain@duck.com> Co-authored-by: Anjan Biswas <anjanavb@amazon.com> Co-authored-by: Jha <nikjha@amazon.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Lance Martin	4339d21cf1	Code LLaMA in code understanding use case (#9779 ) Update Code Understanding use case doc w/ Code-llama.	1 year ago
Lance Martin	2ab04a4e32	Update agent docs, move to use-case sub-directory (#9344 ) Re-structure and add new agent page	1 year ago
Lance Martin	985873c497	Update RAG use case (move to ntbk) (#9340 )	1 year ago
Harrison Chase	709a67d9bf	multivector notebook (#9740 )	1 year ago
Fabrizio Ruocco	cacaf487c3	Azure Cognitive Search - update sdk b8, mod user agent, search with scores (#9191 ) Description: Update Azure Cognitive Search SDK to version b8 (breaking change) Customizable User Agent. Implemented Similarity search with scores @baskaryan --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Margaret Qian	30151c99c7	Update Mosaic endpoint input/output api (#7391 ) As noted in prior PRs (https://github.com/hwchase17/langchain/pull/6060, https://github.com/hwchase17/langchain/pull/7348), the input/output format has changed a few times as we've stabilized our inference API. This PR updates the API to the latest stable version as indicated in our docs: https://docs.mosaicml.com/en/latest/inference.html The input format looks like this: `{"inputs": [<prompt>]} ` The output format looks like this: ` {"outputs": [<output_text>]} ` --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Harrison Chase	ade482c17e	add twitter chat loader doc (#9737 )	1 year ago
Leonid Kuligin	87da56fb1e	Added a pdf parser based on DocAI (#9579 ) #9578 --------- Co-authored-by: Leonid Kuligin <kuligin@google.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	1 year ago
Tudor Golubenco	dc30edf51c	Xata as a chat message memory store (#9719 ) This adds Xata as a memory store also to the python version of LangChain, similar to the [one for LangChain.js](https://github.com/hwchase17/langchainjs/pull/2217). I have added a Jupyter Notebook with a simple and a more complex example using an agent. To run the integration test, you need to execute something like: ``` XATA_API_KEY='xau_...' XATA_DB_URL="https://demo-uni3q8.eu-west-1.xata.sh/db/langchain" poetry run pytest tests/integration_tests/memory/test_xata.py ``` Where `langchain` is the database you create in Xata.	1 year ago
William FH	dff00ea91e	Chat Loaders (#9708 ) Still working out interface/notebooks + need discord data dump to test out things other than copy+paste Update: - Going to remove the 'user_id' arg in the loaders themselves and just standardize on putting the "sender" arg in the extra kwargs. Then can provide a utility function to map these to ai and human messages - Going to move the discord one into just a notebook since I don't have a good dump to test on and copy+paste maybe isn't the greatest thing to support in v0 - Need to do more testing on slack since it seems the dump only includes channels and NOT 1 on 1 convos - --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Bagatur	22b6549a34	sort api classes (#9710 )	1 year ago
Tomaz Bratanic	dacf96895a	Add the option to use separate LLMs for GraphCypherQA chain (#9689 ) The Graph Chains are different in the way that it uses two LLMChains instead of one like the retrievalQA chains. Therefore, sometimes you want to use different LLM to generate the database query and to generate the final answer. This feature would make it more convenient to use different LLMs in the same chain. I have also renamed the Graph DB QA Chain to Neo4j DB QA Chain in the documentation only as it is used only for Neo4j. The naming was ambigious as it was the first graphQA chain added and wasn't sure how do you want to spin it.	1 year ago
Lance Martin	c37be7f5fb	Add Code LLaMA to code QA use case (#9713 ) Use [Ollama integration](https://ollama.ai/blog/run-code-llama-locally).	1 year ago
Leonid Ganeline	cf792891f1	📖 docs: compact api reference (#8651 ) Updated design of the "API Reference" text Here is an example of the current format: ![image](https://github.com/langchain-ai/langchain/assets/2256422/8727f2ba-1b69-497f-aa07-07f939b6da3b) It changed to `langchain.retrievers.ElasticSearchBM25Retriever` format. The same format as it is in the API Reference Toc. It also resembles code: `from langchain.retrievers import ElasticSearchBM25Retriever` (namespace THEN class_name) Current format is `ElasticSearchBM25Retriever from langchain.retrievers` (class_name THEN namespace) This change is in line with other formats and improves readability. @baskaryan	1 year ago
Patrick Loeber	6bedfdf25a	Fix docs for AssemblyAIAudioTranscriptLoader (shorter import path) (#9687 ) Uses the shorter import path `from langchain.document_loaders import` instead of the full path `from langchain.document_loaders.assemblyai` Applies those changes to the docs and the unit test. See #9667 that adds this new loader.	1 year ago
了空	7cf5c582d2	Added a link to the dependencies document (#9703 )	1 year ago
Harrison Chase	9963b32e59	Harrison/multi vector (#9700 )	1 year ago
Leonid Ganeline	b048236c1a	📖 docs: `integrations/agent_toolkits` (#9333 ) Note: There are no changes in the file names! - The group name on the main navbar changed: `Agent toolkits` -> `Agents & Toolkits`. Examples here are the mix of the Agent and Toolkit examples because Agents and Toolkits in examples are always used together. - Titles changed: removed "Agent" and "Toolkit" suffixes. The reason is the same. - Formatting: mostly cleaning the header structure, so it could be better on the right-side navbar. Main navbar is looking much cleaner now.	1 year ago
Patrick Loeber	5990651070	Add new document_loader: AssemblyAIAudioTranscriptLoader (#9667 ) This PR adds a new document loader `AssemblyAIAudioTranscriptLoader` that allows to transcribe audio files with the [AssemblyAI API](https://www.assemblyai.com) and loads the transcribed text into documents. - Add new document_loader with class `AssemblyAIAudioTranscriptLoader` - Add optional dependency `assemblyai` - Add unit tests (using a Mock client) - Add docs notebook This is the equivalent to the JS integration already available in LangChain.js. See the [LangChain JS docs AssemblyAI page](https://js.langchain.com/docs/modules/data_connection/document_loaders/integrations/web_loaders/assemblyai_audio_transcription). At its simplest, you can use the loader to get a transcript back from an audio file like this: ```python from langchain.document_loaders.assemblyai import AssemblyAIAudioTranscriptLoader loader = AssemblyAIAudioTranscriptLoader(file_path="./testfile.mp3") docs = loader.load() ``` To use it, it needs the `assemblyai` python package installed, and the environment variable `ASSEMBLYAI_API_KEY` set with your API key. Alternatively, the API key can also be passed as an argument. Twitter handles to shout out if so kindly 🙇 [@AssemblyAI](https://twitter.com/AssemblyAI) and [@patloeber](https://twitter.com/patloeber) --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	1 year ago
seamusp	25f2c82ae8	docs:misc fixes (#9671 ) Improve internal consistency in LangChain documentation - Change occurrences of eg and eg. to e.g. - Fix headers containing unnecessary capital letters. - Change instances of "few shot" to "few-shot". - Add periods to end of sentences where missing. - Minor spelling and grammar fixes.	1 year ago
Eugene Yurtsev	b88dfcb42a	Add indexing support (#9614 ) This PR introduces a persistence layer to help with indexing workflows into vectostores. The indexing code helps users to: 1. Avoid writing duplicated content into the vectostore 2. Avoid over-writing content if it's unchanged Importantly, this keeps on working even if the content being written is derived via a set of transformations from some source content (e.g., indexing children documents that were derived from parent documents by chunking.) The two main components are: 1. Persistence layer that keeps track of which keys were updated and when. Keeping track of the timestamp of updates, allows to clean up old content safely, and with minimal complexity. 2. HashedDocument which is used to hash the contents (including metadata) of the documents. We rely on the hashes for identifying duplicates. The indexing code works with ANY document loader. To add transformations to the documents, users for now can add a custom document loader that composes an existing loader together with document transformers. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Lakshay Kansal	a8c916955f	Updates to Nomic Atlas and GPT4All documentation (#9414 ) Description: Updates for Nomic AI Atlas and GPT4All integrations documentation. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Keras Conv3d	cbaea8d63b	tair fix distance_type error, and add hybrid search (#9531 ) - fix: distance_type error, - feature: Tair add hybrid search --------- Co-authored-by: thw <hanwen.thw@alibaba-inc.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Jacob Lee	278ef0bdcf	Adds ChatOllama (#9628 ) @rlancemartin --------- Co-authored-by: Adilkhan Sarsen <54854336+adolkhan@users.noreply.github.com> Co-authored-by: Kim Minjong <make.dirty.code@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Lance Martin <lance@langchain.dev> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	80dd162e0d	mv embedding cache docs (#9664 )	1 year ago
Bagatur	a40c12bb88	Update the nlpcloud connector after some changes on the NLP Cloud API (#9586 ) - Description: remove some text generation deprecated parameters and update the embeddings doc, - Tag maintainer: @rlancemartin	1 year ago
Bagatur	d8e2dd4c89	mv	1 year ago
Bagatur	e2e582f1f6	Fixed source key name for docugami loader (#8598 ) The Docugami loader was not returning the source metadata key. This was triggering this exception when used with retrievers, per https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/schema/prompt_template.py#L193C1-L195C41 The fix is simple and just updates the metadata key name for the document each chunk is sourced from, from "name" to "source" as expected. I tested by running the python notebook that has an end to end scenario in it. Tagging DataLoader maintainers @rlancemartin @eyurtsev	1 year ago
Zizhong Zhang	8a03836160	docs: fix PromptGuard docs (#9659 ) Fix PromptGuard docs. Noticed several trivial issues on the docs when integrating the new class. cc @baskaryan	1 year ago
Yong woo Song	f0ae10a20e	Fix typo in tigris (#9637 ) The link has a typo in [tigirs docs](https://python.langchain.com/docs/integrations/providers/tigris), so I couldn't access it. So, I have corrected it. Thanks! ☺️	1 year ago
Junlin Zhou	5b9bdcac1b	docs: fix link url (#9643 ) This pull request corrects the URL links in the Async API documentation to align with the updated project layout. The links had not been updated despite the changes in layout.	1 year ago
Aashish Saini	eb92da84a1	Fixings grammatical errors in Doc Files (#9647 ) Fixing some typos and grammatical error is doc file. @eyurtsev , @baskaryan Thanks --------- Co-authored-by: Aayush <142384656+AayushShorthillsAI@users.noreply.github.com> Co-authored-by: Ishita Chauhan <136303787+IshitaChauhanShortHillsAI@users.noreply.github.com>	1 year ago
Joseph McElroy	2a06e7b216	ElasticsearchStore: improve error logging for adding documents (#9648 ) Not obvious what the error is when you cannot index. This pr adds the ability to log the first errors reason, to help the user diagnose the issue. Also added some more documentation for when you want to use the vectorstore with an embedding model deployed in elasticsearch. Credit: @elastic and @phoey1	1 year ago
Julien Salinas	f1072cc31f	Merge branch 'master' into master	1 year ago
Leonid Ganeline	e1f4f9ac3e	docs: `integrations/providers` (#9631 ) Added missed pages for `integrations/providers` from `vectorstores`. Updated several `vectorstores` notebooks.	1 year ago
anifort	900c1f3e8d	Add support for structured data sources with google enterprise search (#9037 ) <!-- Thank you for contributing to LangChain! Replace this comment with: - Description: Added the capability to handles structured data from google enterprise search, - Issue: Retriever failed when underline search engine was integrated with structured data, - Dependencies: google-api-core - Tag maintainer: @jarokaz - Twitter handle: anifort 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: Christos Aniftos <aniftos@google.com> Co-authored-by: Holt Skinner <13262395+holtskinner@users.noreply.github.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	1 year ago
Jacob Lee	632a83c48e	Update ChatOpenAI docs with fine-tuning example (#9632 )	1 year ago
Adilkhan Sarsen	f29312eb84	Fixing deeplake.mdx file as it uses outdates links (#9602 ) deeplake.mdx was using old links and was not working properly, in the PR we fix the issue.	1 year ago
klae01	b868ef23bc	Add AINetwork blockchain toolkit integration (#9527 ) # Description This PR introduces a new toolkit for interacting with the AINetwork blockchain. The toolkit provides a set of tools for performing various operations on the AINetwork blockchain, such as transferring AIN, reading and writing values to the blockchain database, managing apps, setting rules and owners. # Dependencies [ain-py](https://github.com/ainblockchain/ain-py) >= 1.0.2 # Misc The example notebook (langchain/docs/extras/integrations/toolkits/ainetwork.ipynb) is in the PR --------- Co-authored-by: kriii <kriii@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Vanessa Arndorfer	1ea2f9adf4	Document AzureML Deployment Example (#9571 ) Description: Link an example of deploying a Langchain app to an AzureML online endpoint to the deployments documentation page. Co-authored-by: Vanessa Arndorfer <vaarndor@microsoft.com>	1 year ago
toddkim95	fba29f203a	Add to support polars (#9610 ) ### Description Polars is a DataFrame interface on top of an OLAP Query Engine implemented in Rust. Polars is faster to read than pandas, so I'm looking forward to seeing it added to the document loader. ### Dependencies polars (https://pola-rs.github.io/polars-book/user-guide/) --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Julien Salinas	4d0b7bb8e1	Remove Dolphin and GPT-J from the embeddings docs. These models are not proposed anymore.	1 year ago

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2132 Commits (bdf865d8e8dce4ac7a73df649fa8bb2fbd26bdee)