390 Commits (95c3e5f85f8ed8026a11e351b57bfae488d654c4)

Author	SHA1	Message	Date
Philippe PRADOS	6dd621d636	community[minor]: Add CloudBlobLoader that supports loading data from cloud buckets (#21957) ... Thank you for contributing to LangChain! - [ ] **PR title**: "Add CloudBlobLoader" - community: Add CloudBlobLoader - [ ] **PR message**: Add cloud blob loader - **Description:** Langchain provides several approaches to read different file formats: Specific loaders (`CVSLoader`) or blob-compatible loaders (`FileSystemBlobLoader`). The only implementation proposed for BlobLoader is `FileSystemBlobLoader`. Many projects retrieve files from cloud storage. We propose a new implementation of `BlobLoader` to read files from the three cloud storage systems. The interface is strictly identical to `FileSystemBlobLoader`. The only difference is the constructor, which takes a cloud "url" object such as `s3://my-bucket`, `az://my-bucket`, or `gs://my-bucket`. By streamlining the process, this novel implementation eliminates the requirement to pre-download files from cloud storage to local temporary files (which are seldom removed). The code relies on the [CloudPathLib](https://cloudpathlib.drivendata.org/stable/) library to interpret cloud URLs. This has been added as an optional dependency. ```Python loader = CloudBlobLoader("s3://mybucket/id") for blob in loader.yield_blobs(): print(blob) ``` - [X] **Dependencies:** CloudPathLib - [X] **Twitter handle:** pprados - [X] **Add tests and docs**: Add unit test, but it's easy to convert to integration test, with some files in a cloud storage (see `test_cloud_blob_loader.py`) - [X] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. Hello from Paris @hwchase17. Can you review this PR? --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>	5 months ago
Christophe Bornet	74947ec894	community[minor]: Add Cassandra ByteStore (#22064)	5 months ago
Christophe Bornet	fea6b99b16	community[minor]: Add async methods to CassandraChatMessageHistory (#21975)	5 months ago
Bruno Alvisio	5eabe90494	community[patch]: Adding HEADER to the list of supported locations (#21946) ... **Description:** adds headers to the list of supported locations when generating the openai function schema	5 months ago
Bagatur	50186da0a1	infra: rm unused # noqa violations (#22049) ... Updating #21137	5 months ago
acho98	45ed5f3f51	community[minor]: Add Clova Embeddings for LangChain Community (#21890) ... - [ ] **PR title**: "Add Naver ClovaX embedding to LangChain community" - HyperClovaX is a large language model developed by [Naver](https://clova-x.naver.com/welcome). It's a powerful and purpose-trained LLM. - You can visit the embedding service provided by [ClovaX](https://www.ncloud.com/product/aiService/clovaStudio) - You may get CLOVA_EMB_API_KEY, CLOVA_EMB_APIGW_API_KEY, CLOVA_EMB_APP_ID From https://www.ncloud.com/product/aiService/clovaStudio --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
MSubik	d948783a4c	community[patch]: standardize init args, update for javelin sdk release. (#21980) ... Related to [20085](https://github.com/langchain-ai/langchain/issues/20085) Updated the Javelin chat model to standardize the initialization argument. Also fixed an existing bug, where code was initialized with incorrect call to the JavelinClient defined in the javelin_sdk, resulting in an initialization error. See related [Javelin Documentation](https://docs.getjavelin.io/docs/javelin-python/quickstart).	5 months ago
Mazen Ramadan	3c1d77dd64	community[minor]: Add Scrapfly Loader community integration (#22036) ... Added [Scrapfly](https://scrapfly.io/) Web Loader integration. Scrapfly is a web scraping API that allows extracting web page data into accessible markdown or text datasets. - __Description__: Added Scrapfly web loader for retrieving web page data as markdown or text. - Dependencies: scrapfly-sdk - Twitter: @thealchemi1st --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
SaschaStoll	709664a079	community[patch]: Performant filter columns option for Hanavector (#21971) ... **Description:** Backwards compatible extension of the initialisation interface of HanaDB to allow the user to specify specific_metadata_columns that are used for metadata storage of selected keys which yields increased filter performance. Any not-mentioned metadata remains in the general metadata column as part of a JSON string. Furthermore switched to executemany for batch inserts into HanaDB. **Issue:** N/A **Dependencies:** no new dependencies added **Twitter handle:** @sapopensource --------- Co-authored-by: Martin Kolb <martin.kolb@sap.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Eric Zhang	e7e41eaabe	langchain: add RankLLM Reranker (#21171) ... Integrate RankLLM reranker (https://github.com/castorini/rank_llm) into LangChain An example notebook is given in `docs/docs/integrations/retrievers/rankllm-reranker.ipynb` --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	5 months ago
maang-h	fc93bed8c4	community: Fix CSVLoader columns is None (#20701) ... - **Bug code**: In langchain_community/document_loaders/csv_loader.py:100 - **Description**: currently, when 'CSVLoader' reads the column as None in the 'csv' file, it will report an error because the 'CSVLoader' does not verify whether the column is of str type and does not consider how to handle the corresponding 'row_data' when the column is' None 'in the csv. This pr provides a solution. - **Issue:** Fix #20699 - **thinking:** 1. Refer to the processing method for 'langchain_community/document_loaders/csv_loader.py:100' when **'v'** equals'None', and apply the same method to '**k**'. (Reference`csv.DictReader` ,**'k'** will only be None when ` len(columns) < len(number_row_data)` is established) 2. **‘k’** equals None only holds when it is the last column, and its corresponding **'v'** type is a list. Therefore, I referred to the data format in 'Document' and used ',' to concatenated the elements in the list.(But I'm not sure if you accept this form, if you have any other ideas, communicate) --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	5 months ago
Eugene Yurtsev	36813d2f00	community[patch]: Fix remaining __inits__ in community (#22037) ... Fixes the __init__ files in community to use __all__ which is statically defined.	5 months ago
Eugene Yurtsev	58360a1e53	community[patch]: Add unit test to verify that init is correctly defined (#22030) ... Fix some __init__ files and add a unit test	5 months ago
Matthew Hoffman	4f2e3bd7fd	community[patch]: fix public interface for embeddings module (#21650) ... ## Description The existing public interface for `langchain_community.emeddings` is broken. In this file, `__all__` is statically defined, but is subsequently overwritten with a dynamic expression, which type checkers like pyright do not support. pyright actually gives the following diagnostic on the line I am requesting we remove: [reportUnsupportedDunderAll](https://github.com/microsoft/pyright/blob/main/docs/configuration.md#reportUnsupportedDunderAll): ``` Operation on "__all__" is not supported, so exported symbol list may be incorrect ``` Currently, I get the following errors when attempting to use publicablly exported classes in `langchain_community.emeddings`: ```python import langchain_community.embeddings langchain_community.embeddings.HuggingFaceEmbeddings(...) # error: "HuggingFaceEmbeddings" is not exported from module "langchain_community.embeddings" (reportPrivateImportUsage) ``` This is solved easily by removing the dynamic expression.	5 months ago
Eugene Yurtsev	8d82160a8a	community[patch]: Clean up logic in import checking unit test (#22026) ... Clean up unit test	5 months ago
Tomaz Bratanic	d8a1f1114d	community[patch]: Handle exceptions where node props aren't consistent in neo4j schema (#22027)	5 months ago
Eugene Yurtsev	aed64daabb	community[patch]: Add unit test to catch bad __all__ definitions (#21996) ... This will catch all dynamic __all__ definitions.	5 months ago
Pengcheng Liu	4cf523949a	community[patch]: Update model client to support vision model in Tong… (#21474) ... - **Description:** Tongyi uses different client for chat model and vision model. This PR chooses proper client based on model name to support both chat model and vision model. Reference [tongyi document](https://help.aliyun.com/zh/dashscope/developer-reference/tongyi-qianwen-vl-plus-api?spm=a2c4g.11186623.0.0.27404c9a7upm11) for details. ``` from langchain_core.messages import HumanMessage from langchain_community.chat_models import ChatTongyi llm = ChatTongyi(model_name='qwen-vl-max') image_message = { "image": "https://lilianweng.github.io/posts/2023-06-23-agent/agent-overview.png" } text_message = { "text": "summarize this picture", } message = HumanMessage(content=[text_message, image_message]) llm.invoke([message]) ``` - **Issue:** None - **Dependencies:** None - **Twitter handle:** None	5 months ago
Sevin F. Varoglu	1bc0ea5496	community[patch]: update OctoAIEmbeddings to subclass OpenAIEmbeddings (#21805)	5 months ago
Robert Caulk	54adcd9e82	community[minor]: add AskNews retriever and AskNews tool (#21581) ... We add a tool and retriever for the [AskNews](https://asknews.app) platform with example notebooks. The retriever can be invoked with: ```py from langchain_community.retrievers import AskNewsRetriever retriever = AskNewsRetriever(k=3) retriever.invoke("impact of fed policy on the tech sector") ``` To retrieve 3 documents in then news related to fed policy impacts on the tech sector. The included notebook also includes deeper details about controlling filters such as category and time, as well as including the retriever in a chain. The tool is quite interesting, as it allows the agent to decide how to obtain the news by forming a query and deciding how far back in time to look for the news: ```py from langchain_community.tools.asknews import AskNewsSearch from langchain import hub from langchain.agents import AgentExecutor, create_openai_functions_agent from langchain_openai import ChatOpenAI tool = AskNewsSearch() instructions = """You are an assistant.""" base_prompt = hub.pull("langchain-ai/openai-functions-template") prompt = base_prompt.partial(instructions=instructions) llm = ChatOpenAI(temperature=0) asknews_tool = AskNewsSearch() tools = [asknews_tool] agent = create_openai_functions_agent(llm, tools, prompt) agent_executor = AgentExecutor( agent=agent, tools=tools, verbose=True, ) agent_executor.invoke({"input": "How is the tech sector being affected by fed policy?"}) ``` --------- Co-authored-by: Emre <e@emre.pm>	5 months ago
Jesse S	fc79b372cb	community[minor]: add aerospike vectorstore integration (#21735) ... Please let me know if you see any possible areas of improvement. I would very much appreciate your constructive criticism if time allows. **Description:** - Added a aerospike vector store integration that utilizes [Aerospike-Vector-Search](https://aerospike.com/products/vector-database-search-llm/) add-on. - Added both unit tests and integration tests - Added a docker compose file for spinning up a test environment - Added a notebook **Dependencies:** any dependencies required for this change - aerospike-vector-search **Twitter handle:** - No twitter, you can use my GitHub handle or LinkedIn if you'd like Thanks! --------- Co-authored-by: Jesse Schumacher <jschumacher@aerospike.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Param Singh	d07885f8b7	community[patch]: standardized sparkllm init args (#21633) ... Related to #20085 @baskaryan Thank you for contributing to LangChain! community:sparkllm[patch]: standardized init args updated `spark_api_key` so that aliased to `api_key`. Added integration test for `sparkllm` to test that it continues to set the same underlying attribute. updated temperature with Pydantic Field, added to the integration test. Ran `make format`,`make test`, `make lint`, `make spell_check`	5 months ago
Liuww	332ffed393	community[patch]: Adopting the lighter-weight xinference_client (#21900) ... While integrating the xinference_embedding, we observed that the downloaded dependency package is quite substantial in size. With a focus on resource optimization and efficiency, if the project requirements are limited to its vector processing capabilities, we recommend migrating to the xinference_client package. This package is more streamlined, significantly reducing the storage space requirements of the project and maintaining a feature focus, making it particularly suitable for scenarios that demand lightweight integration. Such an approach not only boosts deployment efficiency but also enhances the application's maintainability, rendering it an optimal choice for our current context. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Eugene Yurtsev	8607735b80	langchain[patch],community[patch]: Move unit tests that depend on community to community (#21685)	5 months ago
Stefano Lottini	040597e832	community: init signature revision for Cassandra LLM cache classes + small maintenance (#17765) ... This PR improves on the `CassandraCache` and `CassandraSemanticCache` classes, mainly in the constructor signature, and also introduces several minor improvements around these classes. ### Init signature A (sigh) breaking change is tentatively introduced to the constructor. To me, the advantages outweigh the possible discomfort: the new syntax places the DB-connection objects `session` and `keyspace` later in the param list, so that they can be given a default value. This is what enables the pattern of _not_ specifying them, provided one has previously initialized the Cassandra connection through the versatile utility method `cassio.init(...)`. In this way, a much less unwieldy instantiation can be done, such as `CassandraCache()` and `CassandraSemanticCache(embedding=xyz)`, everything else falling back to defaults. A downside is that, compared to the earlier signature, this might turn out to be breaking for those doing positional instantiation. As a way to mitigate this problem, this PR typechecks its first argument trying to detect the legacy usage. (And to make this point less tricky in the future, most arguments are left to be keyword-only). If this is considered too harsh, I'd like guidance on how to further smoothen this transition. **Our plan is to make the pattern of optional session/keyspace a standard across all Cassandra classes**, so that a repeatable strategy would be ideal. A possibility would be to keep positional arguments for legacy reasons but issue a deprecation warning if any of them is actually used, to later remove them with 0.2 - please advise on this point. ### Other changes - class docstrings: enriched, completely moved to class level, added note on `cassio.init(...)` pattern, added tiny sample usage code. - semantic cache: revised terminology to never mention "distance" (it is in fact a similarity!). Kept the legacy constructor param with a deprecation warning if used. - `llm_caching` notebook: uniform flow with the Cassandra and Astra DB separate cases; better and Cassandra-first description; all imports made explicit and from community where appropriate. - cache integration tests moved to community (incl. the imported tools), env var bugfix for `CASSANDRA_CONTACT_POINTS`. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	5 months ago
Kyle Cassidy	eca8c4bcc6	Standardized openai init params (#21739) ... ## Patch Summary community:openai[patch]: standardize init args ## Details I made changes to the OpenAI Chat API wrapper test in the Langchain open-source repository - **File**: `libs/community/tests/unit_tests/chat_models/test_openai.py` - **Changes**: - Updated `max_retries` with Pydantic Field - Updated the corresponding unit test - **Related Issues**: #20085 - Updated max_retries with Pydantic Field, updated the unit test. --------- Co-authored-by: JuHyung Son <sonju0427@gmail.com>	5 months ago
ccurme	19e6bf814b	community: fix CI (#21766)	5 months ago
Cheese	0ead09f84d	community: Implement `bind_tools` for ChatTongyi (#20725) ... ## Description Implement `bind_tools` in ChatTongyi. Usage example: ```py from langchain_core.tools import tool from langchain_community.chat_models.tongyi import ChatTongyi @tool def multiply(first_int: int, second_int: int) -> int: """Multiply two integers together.""" return first_int * second_int llm = ChatTongyi(model="qwen-turbo") llm_with_tools = llm.bind_tools([multiply]) msg = llm_with_tools.invoke("What's 5 times forty two") print(msg) ``` Streaming is also supported. ## Dependencies No Dependency is required for this change. --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Chester Curme <chester.curme@gmail.com>	5 months ago
Harrison Chase	15be439719	Harrison/move flashrank rerank (#21448) ... third party integration, should be in community	5 months ago
Rajendra Kadam	54e003268e	langchain[minor]: Add PebbloRetrievalQA chain with Identity & Semantic Enforcement support (#20641) ... - **Description:** PebbloRetrievalQA chain introduces identity enforcement using vector-db metadata filtering - **Dependencies:** None - **Issue:** None - **Documentation:** Adding documentation for PebbloRetrievalQA chain in a separate PR(https://github.com/langchain-ai/langchain/pull/20746) - **Unit tests:** New unit-tests added --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>	5 months ago
Eugene Yurtsev	25fbe356b4	community[patch]: upgrade to recent version of mypy (#21616) ... This PR upgrades community to a recent version of mypy. It inserts type: ignore on all existing failures.	5 months ago
ccurme	3bb9bec314	bedrock: add unit test for retriever (#21485) ... This was implemented in https://github.com/langchain-ai/langchain/pull/21349 but dropped before merge.	6 months ago
Yash	cb31c3611f	Ndb enterprise (#21233) ... Description: Adds NeuralDBClientVectorStore to the langchain, which is our enterprise client. --------- Co-authored-by: kartikTAI <129414343+kartikTAI@users.noreply.github.com> Co-authored-by: Kartik Sarangmath <kartik@thirdai.com>	6 months ago
Oguz Vuruskaner	5b35f077f9	[community][fix](DeepInfraEmbeddings): Implement chunking for large batches (#21189) ... **Description:** This PR introduces chunking logic to the `DeepInfraEmbeddings` class to handle large batch sizes without exceeding maximum batch size of the backend. This enhancement ensures that embedding generation processes large batches by breaking them down into smaller, manageable chunks, each conforming to the maximum batch size limit. **Issue:** Fixes #21189 **Dependencies:** No new dependencies introduced.	6 months ago
Sokolov Fedor	f4ddf64faa	community: Add MarkdownifyTransformer to langchain_community.document_transformers (#21247) ... - Added new document_transformer: MarkdonifyTransformer, that uses `markdonify` package with customizable options to convert HTML to Markdown. It's similar to Html2TextTransformer, but has more flexible options and also I've noticed that sometimes MarkdownifyTransformer performs better than html2text one, so that's why I use markdownify on my project. - Added docs and tests - Usage: ```python from langchain_community.document_transformers import MarkdownifyTransformer markdownify = MarkdownifyTransformer() docs_transform = markdownify.transform_documents(docs) ``` - Example of better performance on simple task, that I've noticed: ``` <html> <head><title>Reports on product movement</title></head> <body> <p data-block-key="2wst7">The reports on product movement will be useful for forming supplier orders and controlling outcomes.</p> </body> ``` **Html2TextTransformer**: ```python [Document(page_content='The reports on product movement will be useful for forming supplier orders and\ncontrolling outcomes.\n\n')] # Here we can see 'and\ncontrolling', which has extra '\n' in it ``` **MarkdownifyTranformer**: ```python [Document(page_content='Reports on product movement\n\nThe reports on product movement will be useful for forming supplier orders and controlling outcomes.')] ``` --------- Co-authored-by: Sokolov Fedor <f.sokolov@sokolov-macbook.bbrouter> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Sokolov Fedor <f.sokolov@sokolov-macbook.local> Co-authored-by: Sokolov Fedor <f.sokolov@192.168.1.6>	6 months ago
Eugene Yurtsev	f92006de3c	multiple: langchain 0.2 in master (#21191) ... 0.2rc migrations - [x] Move memory - [x] Move remaining retrievers - [x] graph_qa chains - [x] some dependency from evaluation code potentially on math utils - [x] Move openapi chain from `langchain.chains.api.openapi` to `langchain_community.chains.openapi` - [x] Migrate `langchain.chains.ernie_functions` to `langchain_community.chains.ernie_functions` - [x] migrate `langchain/chains/llm_requests.py` to `langchain_community.chains.llm_requests` - [x] Moving `langchain_community.cross_enoders.base:BaseCrossEncoder` -> `langchain_community.retrievers.document_compressors.cross_encoder:BaseCrossEncoder` (namespace not ideal, but it needs to be moved to `langchain` to avoid circular deps) - [x] unit tests langchain -- add pytest.mark.community to some unit tests that will stay in langchain - [x] unit tests community -- move unit tests that depend on community to community - [x] mv integration tests that depend on community to community - [x] mypy checks Other todo - [x] Make deprecation warnings not noisy (need to use warn deprecated and check that things are implemented properly) - [x] Update deprecation messages with timeline for code removal (likely we actually won't be removing things until 0.4 release) -- will give people more time to transition their code. - [ ] Add information to deprecation warning to show users how to migrate their code base using langchain-cli - [ ] Remove any unnecessary requirements in langchain (e.g., is SQLALchemy required?) --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Eugene Yurtsev	6a1d61dbf1	community[patch]: Fix in memory vectorstore to take into account ids when adding docs (#21384) ... Should respect `ids` if passed	6 months ago
nrpd25	95cc8e3fc3	premai[patch]:Standardized model init args (#21308) ... [Standardized model init args #20085](https://github.com/langchain-ai/langchain/issues/20085) - Enable premai chat model to be initialized with `model_name` as an alias for `model`, `api_key` as an alias for `premai_api_key`. - Add initialization test `test_premai_initialization` --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>	6 months ago
Jorge Piedrahita Ortiz	e65652c3e8	community: add SambaNova embeddings integration (#21227) ... - **Description:** SambaNova hosted embeddings integration	6 months ago
Jorge Piedrahita Ortiz	df1c10260c	community: minor changes sambanova integration (#21231) ... - **Description:** fix: variable names in root validator not allowing pass credentials as named parameters in llm instancing, also added sambanova's sambaverse and sambastudio llms to __init__.py for module import	6 months ago
Mark Cusack	060987d755	community[minor]: Add indexing via locality sensitive hashing to the Yellowbrick vector store (#20856) ... - **Description:** Add LSH-based indexing to the Yellowbrick vector store module - **Twitter handle:** @markcusack --------- Co-authored-by: markcusack <markcusack@markcusacksmac.lan> Co-authored-by: markcusack <markcusack@Mark-Cusack-sMac.local> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	6 months ago
Param Singh	fee91d43b7	baichuan[patch]:standardize chat init args (#21298) ... Thank you for contributing to LangChain! community:baichuan[patch]: standardize init args updated `baichuan_api_key` so that aliased to `api_key`. Added test that it continues to set the same underlying attribute. Test checks for `SecretStr` updated `temperature` with Pydantic Field, added unit test. Related to https://github.com/langchain-ai/langchain/issues/20085	6 months ago
Rohan Aggarwal	8021d2a2ab	community[minor]: Oraclevs integration (#21123) ... Thank you for contributing to LangChain! - Oracle AI Vector Search Oracle AI Vector Search is designed for Artificial Intelligence (AI) workloads that allows you to query data based on semantics, rather than keywords. One of the biggest benefit of Oracle AI Vector Search is that semantic search on unstructured data can be combined with relational search on business data in one single system. This is not only powerful but also significantly more effective because you don't need to add a specialized vector database, eliminating the pain of data fragmentation between multiple systems. - Oracle AI Vector Search is designed for Artificial Intelligence (AI) workloads that allows you to query data based on semantics, rather than keywords. One of the biggest benefit of Oracle AI Vector Search is that semantic search on unstructured data can be combined with relational search on business data in one single system. This is not only powerful but also significantly more effective because you don't need to add a specialized vector database, eliminating the pain of data fragmentation between multiple systems. This Pull Requests Adds the following functionalities Oracle AI Vector Search : Vector Store Oracle AI Vector Search : Document Loader Oracle AI Vector Search : Document Splitter Oracle AI Vector Search : Summary Oracle AI Vector Search : Oracle Embeddings - We have added unit tests and have our own local unit test suite which verifies all the code is correct. We have made sure to add guides for each of the components and one end to end guide that shows how the entire thing runs. - We have made sure that make format and make lint run clean. Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17. --------- Co-authored-by: skmishraoracle <shailendra.mishra@oracle.com> Co-authored-by: hroyofc <harichandan.roy@oracle.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Eugene Yurtsev	c9119b0e75	langchain[patch],community[minor]: Move some unit tests from langchain to community, use core for fake models (#21190)	6 months ago
Eugene Yurtsev	bec3eee3fa	langchain[patch]: Migrate retrievers to use optional langchain community imports (#21155)	6 months ago
East Agile	2a6f78a53f	community[minor]: Rememberizer retriever (#20052) ... **Description:** This pull request introduces a new feature for LangChain: the integration with the Rememberizer API through a custom retriever. This enables LangChain applications to allow users to load and sync their data from Dropbox, Google Drive, Slack, their hard drive into a vector database that LangChain can query. Queries involve sending text chunks generated within LangChain and retrieving a collection of semantically relevant user data for inclusion in LLM prompts. User knowledge dramatically improved AI applications. The Rememberizer integration will also allow users to access general purpose vectorized data such as Reddit channel discussions and US patents. **Issue:** N/A **Dependencies:** N/A **Twitter handle:** https://twitter.com/Rememberizer	6 months ago
MacanPN	0f7f448603	community[patch]: add delete() method to AzureSearch vector store (#21127) ... **Issue:** Currently `AzureSearch` vector store does not implement `delete` method. This PR implements it. This also makes it compatible with LangChain indexer. **Dependencies:** None **Twitter handle:** @martintriska1 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Jakub Pawłowski	b0b1a67771	community[patch]: Skip unexpected 404 HTTP Error in Arxiv download (#21042) ... ### Description: When attempting to download PDF files from arXiv, an unexpected 404 error frequently occurs. This error halts the operation, regardless of whether there are additional documents to process. As a solution, I suggest implementing a mechanism to ignore and communicate this error and continue processing the next document from the list. Proposed Solution: To address the issue of unexpected 404 errors during PDF downloads from arXiv, I propose implementing the following solution: - Error Handling: Implement error handling mechanisms to catch and handle 404 errors gracefully. - Communication: Inform the user or logging system about the occurrence of the 404 error. - Continued Processing: After encountering a 404 error, continue processing the remaining documents from the list without interruption. This solution ensures that the application can handle unexpected errors without terminating the entire operation. It promotes resilience and robustness in the face of intermittent issues encountered during PDF downloads from arXiv. ### Issue: #20909 ### Dependencies: none --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
Cahid Arda Öz	cc6191cb90	community[minor]: Add support for Upstash Vector (#20824) ... ## Description Adding `UpstashVectorStore` to utilize [Upstash Vector](https://upstash.com/docs/vector/overall/getstarted)! #17012 was opened to add Upstash Vector to langchain but was closed to wait for filtering. Now filtering is added to Upstash vector and we open a new PR. Additionally, [embedding feature](https://upstash.com/docs/vector/features/embeddingmodels) was added and we add this to our vectorstore aswell. ## Dependencies [upstash-vector](https://pypi.org/project/upstash-vector/) should be installed to use `UpstashVectorStore`. Didn't update dependencies because of [this comment in the previous PR](https://github.com/langchain-ai/langchain/pull/17012#pullrequestreview-1876522450). ## Tests Tests are added and they pass. Tests are naturally network bound since Upstash Vector is offered through an API. There was [a discussion in the previous PR about mocking the unittests](https://github.com/langchain-ai/langchain/pull/17012#pullrequestreview-1891820567). We didn't make changes to this end yet. We can update the tests if you can explain how the tests should be mocked. --------- Co-authored-by: ytkimirti <yusuftaha9@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
chyroc	3e241956d3	community[minor]: add coze chat model (#20770) ... add coze chat model, to call coze.com apis	6 months ago