langchain

Commit Graph

Author	SHA1	Message	Date
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
Toshish Jawale	852722ea45	Improvements in Nebula LLM (#9226 ) - Description: Added improvements in Nebula LLM to perform auto-retry; more generation parameters supported. Conversation is no longer required to be passed in the LLM object. Examples are updated. - Issue: N/A - Dependencies: N/A - Tag maintainer: @baskaryan - Twitter handle: symbldotai --------- Co-authored-by: toshishjawale <toshish@symbl.ai>	1 year ago
fanyou-wbd	5e43768f61	docs: update LlamaCpp max_tokens args (#9238 ) This PR updates documentations only, `max_length` should be `max_tokens` according to latest LlamaCpp API doc: https://api.python.langchain.com/en/latest/llms/langchain.llms.llamacpp.LlamaCpp.html	1 year ago
Lance Martin	17ae2998e7	Update Ollama docs (#9220 ) Based on discussion w/ team.	1 year ago
Emmanuel Gautier	f11e5442d6	docs: update LlamaCpp input args (#9173 ) This PR only updates the LlamaCpp args documentation. The input arg has been flattened.	1 year ago
Massimiliano Pronesti	d95eeaedbe	feat(llms): support vLLM's OpenAI-compatible server (#9179 ) This PR aims at supporting [vLLM's OpenAI-compatible server feature](https://vllm.readthedocs.io/en/latest/getting_started/quickstart.html#openai-compatible-server), i.e. allowing to call vLLM's LLMs like if they were OpenAI's. I've also udpated the related notebook providing an example usage. At the moment, vLLM only supports the `Completion` API.	1 year ago
Michael Goin	621da3c164	Adds DeepSparse as an LLM (#9184 ) Adds [DeepSparse](https://github.com/neuralmagic/deepsparse) as an LLM backend. DeepSparse supports running various open-source sparsified models hosted on [SparseZoo](https://sparsezoo.neuralmagic.com/) for performance gains on CPUs. Twitter handles: @mgoin_ @neuralmagic --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Chenyu Zhao	c0acbdca1b	Update Fireworks model names (#9085 )	1 year ago
Piyush Jain	8eea46ed0e	Bedrock embeddings async methods (#9024 ) ## Description This PR adds the `aembed_query` and `aembed_documents` async methods for improving the embeddings generation for large documents. The implementation uses asyncio tasks and gather to achieve concurrency as there is no bedrock async API in boto3. ### Maintainers @agola11 @aarora79 ### Open questions To avoid throttling from the Bedrock API, should there be an option to limit the concurrency of the calls?	1 year ago
Blake (Yung Cher Ho)	8d351bfc20	Takeoff integration (#9045 ) ## Description: This PR adds the Titan Takeoff Server to the available LLMs in LangChain. 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) #### Testing As Titan Takeoff runs locally on port 8000 by default, no network access is needed. Responses are mocked for testing. - [x] Make Lint - [x] Make Format - [x] Make Test #### 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	1 year ago
David vonThenen	bf4a112aa6	Fixes to the Nebula LLM Integration (#8918 ) This addresses some issues with introducing the Nebula LLM to LangChain in this PR: https://github.com/langchain-ai/langchain/pull/8876 This fixes the following: - Removes `SYMBLAI` from variable names - Fixes bug with `Bearer` for the API KEY Thanks again in advance for your help! cc: @hwchase17, @baskaryan --------- Co-authored-by: dvonthenen <david.vonthenen@gmail.com>	1 year ago
Jacob Lee	fa30a57034	Adds Ollama as an LLM (#8829 ) Adds Ollama as an LLM. Ollama can run various open source models locally e.g. Llama 2 and Vicuna, automatically configuring and GPU-optimizing them. @rlancemartin @hwchase17 --------- Co-authored-by: Lance Martin <lance@langchain.dev>	1 year ago
David vonThenen	40079d4936	Introduce Nebula LLM to LangChain (#8876 ) ## Description This PR adds Nebula to the available LLMs in LangChain. Nebula is an LLM focused on conversation understanding and enables users to extract conversation insights from video, audio, text, and chat-based conversations. These conversations can occur between any mix of human or AI participants. Examples of some questions you could ask Nebula from a given conversation are: - What could be the customer’s pain points based on the conversation? - What sales opportunities can be identified from this conversation? - What best practices can be derived from this conversation for future customer interactions? You can read more about Nebula here: https://symbl.ai/blog/extract-insights-symbl-ai-generative-ai-recall-ai-meetings/ #### Integration Test An integration test is added, but it requires network access. Since Nebula is fully managed like OpenAI, network access is required to exercise the integration test. #### Linting - [x] make lint - [x] make test (TODO: there seems to be a failure in another non-related test??? Need to check on this.) - [x] make format ### Dependencies No new dependencies were introduced. ### Twitter handle [@symbldotai](https://twitter.com/symbldotai) [@dvonthenen](https://twitter.com/dvonthenen) If you have any questions, please let me know. cc: @hwchase17, @baskaryan --------- Co-authored-by: dvonthenen <david.vonthenen@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Massimiliano Pronesti	a616e19975	feat(llms): add support for vLLM (#8806 ) Hello langchain maintainers, this PR aims at integrating [vllm](https://vllm.readthedocs.io/en/latest/#) into langchain. This PR closes #8729. This feature clearly depends on `vllm`, but I've seen other models supported here depend on packages that are not included in the pyproject.toml (e.g. `gpt4all`, `text-generation`) so I thought it was the case for this as well. @hwchase17, @baskaryan --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Dayou Liu	91a0817e39	docs: llamacpp minor fixes (#8738 ) - Description: minor updates on llama cpp doc	1 year ago
rjanardhan3	affaaea87b	Updates fireworks (#8765 ) <!-- Thank you for contributing to LangChain! Replace this comment with: - Description: Updates to Fireworks Documentation, - Issue: N/A, - Dependencies: N/A, - Tag maintainer: @rlancemartin, --------- Co-authored-by: Raj Janardhan <rajjanardhan@Rajs-Laptop.attlocal.net>	1 year ago
Bagatur	b2b71b0d35	Bagatur/eden llm (#8670 ) Co-authored-by: RedhaWassim <rwasssim@gmail.com> Co-authored-by: KyrianC <ckyrian@protonmail.com> Co-authored-by: sam <melaine.samy@gmail.com>	1 year ago
rjanardhan3	68113348cc	Fireworks integration (#8322 ) Description - Integrates Fireworks within Langchain LLMs to allow users to use Fireworks models with Langchain, mainly for summarization. Issue - Not applicable Dependencies - None Tag maintainer - @rlancemartin --------- Co-authored-by: Raj Janardhan <rajjanardhan@Rajs-Laptop.attlocal.net>	1 year ago
Leonid Kuligin	b4a126ae71	Updated docs on Vertex AI going GA (#8531 ) #8074 Co-authored-by: Leonid Kuligin <kuligin@google.com>	1 year ago
Matthew DeGuzman	844eca98d5	Add LLaMa Formatter and AzureML Chat Endpoint (#8382 ) ## Description Microsoft and Meta recently [announced their collaboration](https://blogs.microsoft.com/blog/2023/07/18/microsoft-and-meta-expand-their-ai-partnership-with-llama-2-on-azure-and-windows/) on LLaMa2. This PR extends the current LLM wrapper and introduces a new Chat Model wrapper for AzureML to support LLaMa2. ## Dependencies No dependencies added :) ## Twitter Handles [@matthew_d13](https://twitter.com/matthew_d13) [@prakhar_in](https://twitter.com/prakhar_in) maintainers - @hwchase17, @baskaryan	1 year ago
William FH	b7c0eb9ecb	Wfh/ref links (#8454 )	1 year ago
HeTaoPKU	d5884017a9	Add Minimax llm model to langchain (#7645 ) - Description: Minimax is a great AI startup from China, recently they released their latest model and chat API, and the API is widely-spread in China. As a result, I'd like to add the Minimax llm model to Langchain. - Tag maintainer: @hwchase17, @baskaryan --------- Co-authored-by: the <tao.he@hulu.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Jiayi Ni	1efb9bae5f	FEAT: Integrate Xinference LLMs and Embeddings (#8171 ) - [Xorbits Inference(Xinference)](https://github.com/xorbitsai/inference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. Xinference supports a variety of GGML-compatible models including chatglm, whisper, and vicuna, and utilizes heterogeneous hardware and a distributed architecture for seamless cross-device and cross-server model deployment. - This PR integrates Xinference models and Xinference embeddings into LangChain. - Dependencies: To install the depenedencies for this integration, run `pip install "xinference[all]"` - Example Usage: To start a local instance of Xinference, run `xinference`. To deploy Xinference in a distributed cluster, first start an Xinference supervisor using `xinference-supervisor`: `xinference-supervisor -H "${supervisor_host}"` Then, start the Xinference workers using `xinference-worker` on each server you want to run them on. `xinference-worker -e "http://${supervisor_host}:9997"` To use Xinference with LangChain, you also need to launch a model. You can use command line interface (CLI) to do so. Fo example: `xinference launch -n vicuna-v1.3 -f ggmlv3 -q q4_0`. This launches a model named vicuna-v1.3 with `model_format="ggmlv3"` and `quantization="q4_0"`. A model UID is returned for you to use. Now you can use Xinference with LangChain: ```python from langchain.llms import Xinference llm = Xinference( server_url="http://0.0.0.0:9997", # suppose the supervisor_host is "0.0.0.0" model_uid = {model_uid} # model UID returned from launching a model ) llm( prompt="Q: where can we visit in the capital of France? A:", generate_config={"max_tokens": 1024}, ) ``` You can also use RESTful client to launch a model: ```python from xinference.client import RESTfulClient client = RESTfulClient("http://0.0.0.0:9997") model_uid = client.launch_model(model_name="vicuna-v1.3", model_size_in_billions=7, quantization="q4_0") ``` The following code block demonstrates how to use Xinference embeddings with LangChain: ```python from langchain.embeddings import XinferenceEmbeddings xinference = XinferenceEmbeddings( server_url="http://0.0.0.0:9997", model_uid = model_uid ) ``` ```python query_result = xinference.embed_query("This is a test query") ``` ```python doc_result = xinference.embed_documents(["text A", "text B"]) ``` Xinference is still under rapid development. Feel free to [join our Slack community](https://xorbitsio.slack.com/join/shared_invite/zt-1z3zsm9ep-87yI9YZ_B79HLB2ccTq4WA) to get the latest updates! - Request for review: @hwchase17, @baskaryan - Twitter handle: https://twitter.com/Xorbitsio --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Karan V	a003a0baf6	fix(petals) allows to run models that aren't Bloom (Support for LLama and newer models) (#8356 ) In this PR: - Removed restricted model loading logic for Petals-Bloom - Removed petals imports (DistributedBloomForCausalLM, BloomTokenizerFast) - Instead imported more generalized versions of loader (AutoDistributedModelForCausalLM, AutoTokenizer) - Updated the Petals example notebook to allow for a successful installation of Petals in Apple Silicon Macs - Tag maintainer: @hwchase17, @baskaryan --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
William FH	01a9b06400	Add api cross ref linking (#8275 ) Example of how it would show up in our python docs: ![image](https://github.com/langchain-ai/langchain/assets/13333726/0f0a88cc-ba4a-4778-bc47-118c66807f15) Examples added to the reference docs: https://api.python.langchain.com/en/wfh-api_crosslink/vectorstores/langchain.vectorstores.chroma.Chroma.html#langchain.vectorstores.chroma.Chroma ![image](https://github.com/langchain-ai/langchain/assets/13333726/dcd150de-cb56-4d42-b49a-a76a002a5a52)	1 year ago
William FH	0a16b3d84b	Update Integrations links (#8206 )	1 year ago
Taqi Jaffri	8f158b72fc	Added stop sequence support to replicate (#8107 ) Stop sequences are useful if you are doing long-running completions and need to early-out rather than running for the full max_length... not only does this save inference cost on Replicate, it is also much faster if you are going to truncate the output later anyway. Other LLMs support stop sequences natively (e.g. OpenAI) but I didn't see this for Replicate so adding this via their prediction cancel method. Housekeeping: I ran `make format` and `make lint`, no issues reported in the files I touched. I did update the replicate integration test and ran `poetry run pytest tests/integration_tests/llms/test_replicate.py` successfully. Finally, I am @tjaffri https://twitter.com/tjaffri for feature announcement tweets... or if you could please tag @docugami https://twitter.com/docugami we would really appreciate that :-) Co-authored-by: Taqi Jaffri <tjaffri@docugami.com>	1 year ago
Liu Ming	24f889f2bc	Change with_history option to False for ChatGLM by default (#8076 ) ChatGLM LLM integration will by default accumulate conversation history(with_history=True) to ChatGLM backend api, which is not expected in most cases. This PR set with_history=False by default, user should explicitly set llm.with_history=True to turn this feature on. Related PR: #8048 #7774 --------- Co-authored-by: mlot <limpo2000@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	c8c8635dc9	mv module integrations docs (#8101 )	1 year ago

29 Commits (b9ca5cc5eabcd8ebf3d56cb8d422fd7003513a75)