185 Commits (cb642ef6584b1d6ec9bded6d207276e0e9e581d1)

Author	SHA1	Message	Date
Harrison Chase	c1badc1fa2	add gmail loader (#9810)	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
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
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
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
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	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	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
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
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
Zizhong Zhang	00eff8c4a7	feat: Add PromptGuard integration (#9481) ... Add PromptGuard integration ------- There are two approaches to integrate PromptGuard with a LangChain application. 1. PromptGuardLLMWrapper 2. functions that can be used in LangChain expression. ----- - Dependencies `promptguard` python package, which is a runtime requirement if you'd try out the demo. - @baskaryan @hwchase17 Thanks for the ideas and suggestions along the development process. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Matthew Zeiler	949b2cf177	Improvements to the Clarifai integration (#9290) ... - Improved docs - Improved performance in multiple ways through batching, threading, etc. - fixed error message - Added support for metadata filtering during similarity search. @baskaryan PTAL	1 year ago
ricki-epsilla	66a47d9a61	add Epsilla vectorstore (#9239) ... [Epsilla](https://github.com/epsilla-cloud/vectordb) vectordb is an open-source vector database that leverages the advanced academic parallel graph traversal techniques for vector indexing. This PR adds basic integration with [pyepsilla](https://github.com/epsilla-cloud/epsilla-python-client)(Epsilla vectordb python client) as a vectorstore. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
axiangcoding	05aa02005b	feat(llms): support ERNIE Embedding-V1 (#9370) ... - Description: support [ERNIE Embedding-V1](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/alj562vvu), which is part of ERNIE ecology - Issue: None - Dependencies: None - Tag maintainer: @baskaryan --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
José Ferraz Neto	f116e10d53	Add SharePoint Loader (#4284) ... - Added a loader (`SharePointLoader`) that can pull documents (`pdf`, `docx`, `doc`) from the [SharePoint Document Library](https://support.microsoft.com/en-us/office/what-is-a-document-library-3b5976dd-65cf-4c9e-bf5a-713c10ca2872). - Added a Base Loader (`O365BaseLoader`) to be used for all Loaders that use [O365](https://github.com/O365/python-o365) Package - Code refactoring on `OneDriveLoader` to use the new `O365BaseLoader`. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Utku Ege Tuluk	bb4f7936f9	feat(llms): add streaming support to textgen (#9295) ... - Description: Added streaming support to the textgen component in the llms module. - Dependencies: websocket-client = "^1.6.1"	1 year ago
Leonid Ganeline	fdbeb52756	`Qwen` model example (#9516) ... added an example for `Qwen-7B` model on `HugginfFaceHub` 🤗	1 year ago
Martin Schade	0c8a88b3fa	AmazonTextractPDFLoader documentation updates (#9415) ... Description: Updating documentation to add AmazonTextractPDFLoader according to [comment](https://github.com/langchain-ai/langchain/pull/8661#issuecomment-1666572992) from [baskaryan](https://github.com/baskaryan) Adding one notebook and instructions to the modules/data_connection/document_loaders/pdf.mdx --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Asif Ahmad	08feed3332	Changed the NIBittensorLLM API URL to the correct one (#9419) ... Changed https://api.neuralinterent.ai/ to https://api.neuralinternet.ai/ which is the valid URL for the API of NIBittensorLLM.	1 year ago
bsenst	a956b69720	fix typo in huggingface_hub.ipynb (#9499)	1 year ago
Taqi Jaffri	069c0a041f	comment update for poetry install	1 year ago
Taqi Jaffri	5cd244e9b7	CR feedback	1 year ago
Matt Robinson	83d2a871eb	fix: apply unstructured preprocess functions (#9473) ... ### Summary Fixes a bug from #7850 where post processing functions in Unstructured loaders were not apply. Adds a assertion to the test to verify the post processing function was applied and also updates the explanation in the example notebook.	1 year ago
Leonid Ganeline	99e5eaa9b1	`InternLM` example (#9465) ... Added `InternML` model example to the HubbingFace Hub notebook	1 year ago
William FH	d4f790fd40	Fix imports in notebook (#9458)	1 year ago
Angel Luis	2e8733cf54	Fix typo in huggingface_textgen_inference.ipynb (#9313) ... Replaced incorrect `stream` parameter by `streaming` on Integrations docs.	1 year ago
axiangcoding	63601551b1	fix(llms): improve the ernie chat model (#9289) ... - Description: improve the ernie chat model. - fix missing kwargs to payload - new test cases - add some debug level log - improve description - Issue: None - Dependencies: None - Tag maintainer: @baskaryan	1 year ago
Daniel Chalef	1d55141c50	zep/new ZepVectorStore (#9159) ... - new ZepVectorStore class - ZepVectorStore unit tests - ZepVectorStore demo notebook - update zep-python to ~1.0.2 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	9abf60acb6	Bagatur/vectara regression (#9276) ... Co-authored-by: Ofer Mendelevitch <ofer@vectara.com> Co-authored-by: Ofer Mendelevitch <ofermend@gmail.com>	1 year ago
Xiaoyu Xee	b30f449dae	Add dashvector vectorstore (#9163) ... ## Description Add `Dashvector` vectorstore for langchain - [dashvector quick start](https://help.aliyun.com/document_detail/2510223.html) - [dashvector package description](https://pypi.org/project/dashvector/) ## How to use ```python from langchain.vectorstores.dashvector import DashVector dashvector = DashVector.from_documents(docs, embeddings) ``` --------- Co-authored-by: smallrain.xuxy <smallrain.xuxy@alibaba-inc.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	bfbb97b74c	Bagatur/deeplake docs fixes (#9275) ... Co-authored-by: adilkhan <adilkhan.sarsen@nu.edu.kz>	1 year ago
Kunj-2206	1b3942ba74	Added BittensorLLM (#9250) ... Description: Adding NIBittensorLLM via Validator Endpoint to langchain llms Tag maintainer: @Kunj-2206 Maintainer responsibilities: Models / Prompts: @hwchase17, @baskaryan --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago