Commit Graph

58 Commits

Author SHA1 Message Date
Aaron Pham
12fced13f4
chore(community): update to OpenLLM 0.6 (#24609)
Update to OpenLLM 0.6, which we decides to make use of OpenLLM's
OpenAI-compatible endpoint. Thus, OpenLLM will now just become a thin
wrapper around OpenAI wrapper.

Signed-off-by: Aaron Pham <contact@aarnphm.xyz>

---------

Signed-off-by: Aaron Pham <contact@aarnphm.xyz>
Co-authored-by: ccurme <chester.curme@gmail.com>
2024-12-16 14:30:07 -05:00
Yan
c60695a1c7
community: fixed critical bugs at Writer provider (#27879) 2024-11-25 12:03:37 -05:00
shroominic
dee72c46c1
community: Outlines integration (#27449)
In collaboration with @rlouf I build an
[outlines](https://dottxt-ai.github.io/outlines/latest/) integration for
langchain!

I think this is really useful for doing any type of structured output
locally.
[Dottxt](https://dottxt.co) spend alot of work optimising this process
at a lower level
([outlines-core](https://pypi.org/project/outlines-core/0.1.14/) written
in rust) so I think this is a better alternative over all current
approaches in langchain to do structured output.
It also implements the `.with_structured_output` method so it should be
a drop in replacement for a lot of applications.

The integration includes:
- **Outlines LLM class**
- **ChatOutlines class**
- **Tutorial Cookbooks**
- **Documentation Page**
- **Validation and error messages** 
- **Exposes Outlines Structured output features**
- **Support for multiple backends**
- **Integration and Unit Tests**

Dependencies: `outlines` + additional (depending on backend used)

I am not sure if the unit-tests comply with all requirements, if not I
suggest to just remove them since I don't see a useful way to do it
differently.

### Quick overview:

Chat Models:
<img width="698" alt="image"
src="https://github.com/user-attachments/assets/05a499b9-858c-4397-a9ff-165c2b3e7acc">

Structured Output:
<img width="955" alt="image"
src="https://github.com/user-attachments/assets/b9fcac11-d3e5-4698-b1ae-8c4cb3d54c45">

---------

Co-authored-by: Vadym Barda <vadym@langchain.dev>
2024-11-20 16:31:31 -05:00
Jorge Piedrahita Ortiz
39956a3ef0
community: sambanovacloud llm integration (#27526)
- **Description:** SambaNovaCloud llm integration added, previously only
chat model integration

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-11-15 16:58:11 +00:00
fayvor
3b956b3a97
community: Update Replicate LLM and fix tests (#27655)
**Description:** 
- Fix bug in Replicate LLM class, where it was looking for parameter
names in a place where they no longer exist in pydantic 2, resulting in
the "Field required" validation error described in the issue.
- Fix Replicate LLM integration tests to:
  - Use active models on Replicate.
- Use the correct model parameter `max_new_tokens` as shown in the
[Replicate
docs](https://replicate.com/docs/guides/language-models/how-to-use#minimum-and-maximum-new-tokens).
  - Use callbacks instead of deprecated callback_manager.

**Issue:** #26937 

**Dependencies:** n/a

**Twitter handle:** n/a

---------

Signed-off-by: Fayvor Love <fayvor@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-10-30 16:07:08 +00:00
Erick Friis
92ae61bcc8
multiple: rely on asyncio_mode auto in tests (#27200) 2024-10-15 16:26:38 +00:00
Jorge Piedrahita Ortiz
37b72023fe
community: remove sambaverse (#26265)
removing Sambaverse llm model and references given is not available
after Sep/10/2024

<img width="1781" alt="image"
src="https://github.com/user-attachments/assets/4dcdb5f7-5264-4a03-b8e5-95c88304e059">
2024-09-19 09:56:30 -04:00
Erick Friis
c2a3021bb0
multiple: pydantic 2 compatibility, v0.3 (#26443)
Signed-off-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Dan O'Donovan <dan.odonovan@gmail.com>
Co-authored-by: Tom Daniel Grande <tomdgrande@gmail.com>
Co-authored-by: Grande <Tom.Daniel.Grande@statsbygg.no>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: ccurme <chester.curme@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Tomaz Bratanic <bratanic.tomaz@gmail.com>
Co-authored-by: ZhangShenao <15201440436@163.com>
Co-authored-by: Friso H. Kingma <fhkingma@gmail.com>
Co-authored-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Nuno Campos <nuno@langchain.dev>
Co-authored-by: Morgante Pell <morgantep@google.com>
2024-09-13 14:38:45 -07:00
Yuwen Hu
566e9ba164
community: add Intel GPU support to ipex-llm llm integration (#22458)
**Description:** [IPEX-LLM](https://github.com/intel-analytics/ipex-llm)
is a PyTorch library for running LLM on Intel CPU and GPU (e.g., local
PC with iGPU, discrete GPU such as Arc, Flex and Max) with very low
latency. This PR adds Intel GPU support to `ipex-llm` llm integration.
**Dependencies:** `ipex-llm`
**Contribution maintainer**: @ivy-lv11 @Oscilloscope98
**tests and docs**: 
- Add: langchain/docs/docs/integrations/llms/ipex_llm_gpu.ipynb
- Update: langchain/docs/docs/integrations/llms/ipex_llm_gpu.ipynb
- Update: langchain/libs/community/tests/llms/test_ipex_llm.py

---------

Co-authored-by: ivy-lv11 <zhicunlv@gmail.com>
2024-09-02 08:49:08 -04:00
maang-h
089f5e6cad
Standardize SparkLLM (#25239)
- **Description:** Standardize SparkLLM, include:
  - docs, the issue #24803 
  - to support stream
  - update api url
  - model init arg names, the issue #20085
2024-08-13 09:50:12 -04:00
Eugene Yurtsev
98779797fe
community[patch]: Use get_fields adapter for pydantic (#25191)
Change all usages of __fields__ with get_fields adapter merged into
langchain_core.

Code mod generated using the following grit pattern:

```
engine marzano(0.1)
language python


`$X.__fields__` => `get_fields($X)` where {
    add_import(source="langchain_core.utils.pydantic", name="get_fields")
}
```
2024-08-08 14:43:09 -04:00
maang-h
0ba125c3cd
docs: Standardize QianfanLLMEndpoint LLM (#25139)
- **Description:** Standardize QianfanLLMEndpoint LLM,include:
  - docs, the issue #24803 
  - model init arg names, the issue #20085
2024-08-07 10:57:27 -04:00
maang-h
1028af17e7
docs: Standardize Tongyi (#25103)
- **Description:** Standardize Tongyi LLM,include:
  - docs, the issue #24803
  - model init arg names, the issue #20085
2024-08-06 11:44:12 -04:00
Bagatur
8e2316b8c2
community[patch]: Release 0.2.11 (#24989) 2024-08-02 20:08:44 +00:00
Eugene Yurtsev
d24b82357f
community[patch]: Add missing annotations (#24890)
This PR adds annotations in comunity package.

Annotations are only strictly needed in subclasses of BaseModel for
pydantic 2 compatibility.

This PR adds some unnecessary annotations, but they're not bad to have
regardless for documentation pages.
2024-07-31 18:13:44 +00:00
Anas Khan
b5acb91080
Mask API keys for various LLM/ChatModel Modules (#13885)
**Description:** 
- Added masking of the API Keys for the modules:
  - `langchain/chat_models/openai.py`
  - `langchain/llms/openai.py`
  - `langchain/llms/google_palm.py`
  - `langchain/chat_models/google_palm.py`
  - `langchain/llms/edenai.py`

- Updated the modules to utilize `SecretStr` from pydantic to securely
manage API key.
- Added unit/integration tests
- `langchain/chat_models/asure_openai.py` used the `open_api_key` that
is derived from the `ChatOpenAI` Class and it was assuming
`openai_api_key` is a str so we changed it to expect `SecretStr`
instead.

**Issue:** https://github.com/langchain-ai/langchain/issues/12165 ,
**Dependencies:** none,
**Tag maintainer:** @eyurtsev

---------

Co-authored-by: HassanA01 <anikeboss@gmail.com>
Co-authored-by: Aneeq Hassan <aneeq.hassan@utoronto.ca>
Co-authored-by: kristinspenc <kristinspenc2003@gmail.com>
Co-authored-by: faisalt14 <faisalt14@gmail.com>
Co-authored-by: Harshil-Patel28 <76663814+Harshil-Patel28@users.noreply.github.com>
Co-authored-by: kristinspenc <146893228+kristinspenc@users.noreply.github.com>
Co-authored-by: faisalt14 <90787271+faisalt14@users.noreply.github.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-07-19 15:23:34 +00:00
Bagatur
a0c2281540
infra: update mypy 1.10, ruff 0.5 (#23721)
```python
"""python scripts/update_mypy_ruff.py"""
import glob
import tomllib
from pathlib import Path

import toml
import subprocess
import re

ROOT_DIR = Path(__file__).parents[1]


def main():
    for path in glob.glob(str(ROOT_DIR / "libs/**/pyproject.toml"), recursive=True):
        print(path)
        with open(path, "rb") as f:
            pyproject = tomllib.load(f)
        try:
            pyproject["tool"]["poetry"]["group"]["typing"]["dependencies"]["mypy"] = (
                "^1.10"
            )
            pyproject["tool"]["poetry"]["group"]["lint"]["dependencies"]["ruff"] = (
                "^0.5"
            )
        except KeyError:
            continue
        with open(path, "w") as f:
            toml.dump(pyproject, f)
        cwd = "/".join(path.split("/")[:-1])
        completed = subprocess.run(
            "poetry lock --no-update; poetry install --with typing; poetry run mypy . --no-color",
            cwd=cwd,
            shell=True,
            capture_output=True,
            text=True,
        )
        logs = completed.stdout.split("\n")

        to_ignore = {}
        for l in logs:
            if re.match("^(.*)\:(\d+)\: error:.*\[(.*)\]", l):
                path, line_no, error_type = re.match(
                    "^(.*)\:(\d+)\: error:.*\[(.*)\]", l
                ).groups()
                if (path, line_no) in to_ignore:
                    to_ignore[(path, line_no)].append(error_type)
                else:
                    to_ignore[(path, line_no)] = [error_type]
        print(len(to_ignore))
        for (error_path, line_no), error_types in to_ignore.items():
            all_errors = ", ".join(error_types)
            full_path = f"{cwd}/{error_path}"
            try:
                with open(full_path, "r") as f:
                    file_lines = f.readlines()
            except FileNotFoundError:
                continue
            file_lines[int(line_no) - 1] = (
                file_lines[int(line_no) - 1][:-1] + f"  # type: ignore[{all_errors}]\n"
            )
            with open(full_path, "w") as f:
                f.write("".join(file_lines))

        subprocess.run(
            "poetry run ruff format .; poetry run ruff --select I --fix .",
            cwd=cwd,
            shell=True,
            capture_output=True,
            text=True,
        )


if __name__ == "__main__":
    main()

```
2024-07-03 10:33:27 -07:00
Eugene Yurtsev
05d31a2f00
community[patch]: Add missing type annotations (#22758)
Add missing type annotations to objects in community.
These missing type annotations will raise type errors in pydantic 2.
2024-06-10 16:59:28 -04:00
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.
2024-05-13 14:55:07 -04:00
Jorge Piedrahita Ortiz
40b2e2916b
community[minor]: Sambanova llm integration (#20955)
- **Description:** Added [Sambanova systems](https://sambanova.ai/)
integration, including sambaverse and sambastudio LLMs
- **Dependencies:**   sseclient-py  (optional)

---------

Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-04-27 01:05:13 +00:00
Shengsheng Huang
fd1061e7bf
community[patch]: add more data types support to ipex-llm llm integration (#20833)
- **Description**:  
- **add support for more data types**: by default `IpexLLM` will load
the model in int4 format. This PR adds more data types support such as
`sym_in5`, `sym_int8`, etc. Data formats like NF3, NF4, FP4 and FP8 are
only supported on GPU and will be added in future PR.
    - Fix a small issue in saving/loading, update api docs
- **Dependencies**: `ipex-llm` library
- **Document**: In `docs/docs/integrations/llms/ipex_llm.ipynb`, added
instructions for saving/loading low-bit model.
- **Tests**: added new test cases to
`libs/community/tests/integration_tests/llms/test_ipex_llm.py`, added
config params.
- **Contribution maintainer**: @shane-huang
2024-04-25 12:58:18 -07:00
ccurme
481d3855dc
patch: remove usage of llm, chat model __call__ (#20788)
- `llm(prompt)` -> `llm.invoke(prompt)`
- `llm(prompt=prompt` -> `llm.invoke(prompt)` (same with `messages=`)
- `llm(prompt, callbacks=callbacks)` -> `llm.invoke(prompt,
config={"callbacks": callbacks})`
- `llm(prompt, **kwargs)` -> `llm.invoke(prompt, **kwargs)`
2024-04-24 19:39:23 -04:00
pjb157
479be3cc91
community[minor]: Unify Titan Takeoff Integrations and Adding Embedding Support (#18775)
**Community: Unify Titan Takeoff Integrations and Adding Embedding
Support**

 **Description:** 
Titan Takeoff no longer reflects this either of the integrations in the
community folder. The two integrations (TitanTakeoffPro and
TitanTakeoff) where causing confusion with clients, so have moved code
into one place and created an alias for backwards compatibility. Added
Takeoff Client python package to do the bulk of the work with the
requests, this is because this package is actively updated with new
versions of Takeoff. So this integration will be far more robust and
will not degrade as badly over time.

**Issue:**
Fixes bugs in the old Titan integrations and unified the code with added
unit test converge to avoid future problems.

**Dependencies:**
Added optional dependency takeoff-client, all imports still work without
dependency including the Titan Takeoff classes but just will fail on
initialisation if not pip installed takeoff-client

**Twitter**
@MeryemArik9

Thanks all :)

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2024-04-17 01:43:35 +00:00
Sevin F. Varoglu
54d388d898
community[patch]: update OctoAI endpoint to subclass BaseOpenAI (#19757)
This PR updates OctoAIEndpoint LLM to subclass BaseOpenAI as OctoAI is
an OpenAI-compatible service. The documentation and tests have also been
updated.
2024-04-16 17:32:20 -07:00
Prince Canuma
1f9f4d8742
community[minor]: Add support for MLX models (chat & llm) (#18152)
**Description:** This PR adds support for MLX models both chat (i.e.,
instruct) and llm (i.e., pretrained) types/
**Dependencies:** mlx, mlx_lm, transformers
**Twitter handle:** @Prince_Canuma

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2024-04-09 14:17:07 +00:00
Alex Sherstinsky
5f563e040a
community: extend Predibase integration to support fine-tuned LLM adapters (#19979)
- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
  - Example: "community: add foobar LLM"


- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** Langchain-Predibase integration was failing, because
it was not current with the Predibase SDK; in addition, Predibase
integration tests were instantiating the Langchain Community `Predibase`
class with one required argument (`model`) missing. This change updates
the Predibase SDK usage and fixes the integration tests.
    - **Twitter handle:** `@alexsherstinsky`


- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

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: Erick Friis <erick@langchain.dev>
2024-04-08 18:54:29 +00:00
Cheng, Penghui
cc407e8a1b
community[minor]: weight only quantization with intel-extension-for-transformers. (#14504)
Support weight only quantization with intel-extension-for-transformers.
[Intel® Extension for
Transformers](https://github.com/intel/intel-extension-for-transformers)
is an innovative toolkit to accelerate Transformer-based models on Intel
platforms, in particular effective on 4th Intel Xeon Scalable processor
[Sapphire
Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html)
(codenamed Sapphire Rapids). The toolkit provides the below key
features:

* Seamless user experience of model compressions on Transformer-based
models by extending [Hugging Face
transformers](https://github.com/huggingface/transformers) APIs and
leveraging [Intel® Neural
Compressor](https://github.com/intel/neural-compressor)
* Advanced software optimizations and unique compression-aware runtime.
* Optimized Transformer-based model packages.
*
[NeuralChat](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat),
a customizable chatbot framework to create your own chatbot within
minutes by leveraging a rich set of plugins and SOTA optimizations.
*
[Inference](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/llm/runtime/graph)
of Large Language Model (LLM) in pure C/C++ with weight-only
quantization kernels.
This PR is an integration of weight only quantization feature with
intel-extension-for-transformers.

Unit test is in
lib/langchain/tests/integration_tests/llm/test_weight_only_quantization.py
The notebook is in
docs/docs/integrations/llms/weight_only_quantization.ipynb.
The document is in
docs/docs/integrations/providers/weight_only_quantization.mdx.

---------

Signed-off-by: Cheng, Penghui <penghui.cheng@intel.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-04-03 16:21:34 +00:00
Jamsheed Mistri
4f70bc119d
community[minor]: add Layerup Security integration (#19787)
**Description:** adds integration with [Layerup
Security](https://uselayerup.com). Docs can be found
[here](https://docs.uselayerup.com). Integrates directly with our Python
SDK.

**Dependencies:**
[LayerupSecurity](https://pypi.org/project/LayerupSecurity/)

**Note**: all methods for our product require a paid API key, so I only
included 1 test which checks for an invalid API key response. I have
tested extensively locally.

**Twitter handle**: [@layerup_](https://twitter.com/layerup_)

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-04-01 23:49:00 +00:00
Alex Sherstinsky
a9bc212bf2
community[minor]: fix failing Predibase integration (#19776)
- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
  - Example: "community: add foobar LLM"


- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** Langchain-Predibase integration was failing, because
it was not current with the Predibase SDK; in addition, Predibase
integration tests were instantiating the Langchain Community `Predibase`
class with one required argument (`model`) missing. This change updates
the Predibase SDK usage and fixes the integration tests.
    - **Twitter handle:** `@alexsherstinsky`


---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-30 00:38:13 +00:00
wulixuan
b7c8bc8268
community[patch]: fix yuan2 errors in LLMs (#19004)
1. fix yuan2 errors while invoke Yuan2.
2. update tests.
2024-03-28 14:37:44 -07:00
Shengsheng Huang
ac1dd8ad94
community[minor]: migrate bigdl-llm to ipex-llm (#19518)
- **Description**: `bigdl-llm` library has been renamed to
[`ipex-llm`](https://github.com/intel-analytics/ipex-llm). This PR
migrates the `bigdl-llm` integration to `ipex-llm` .
- **Issue**: N/A. The original PR of `bigdl-llm` is
https://github.com/langchain-ai/langchain/pull/17953
- **Dependencies**: `ipex-llm` library
- **Contribution maintainer**: @shane-huang

Updated doc:   docs/docs/integrations/llms/ipex_llm.ipynb
Updated test:
libs/community/tests/integration_tests/llms/test_ipex_llm.py
2024-03-27 20:12:59 -07:00
Yunmo Koo
fee6f983ef
community[minor]: Integration for Friendli LLM and ChatFriendli ChatModel. (#17913)
## Description
- Add [Friendli](https://friendli.ai/) integration for `Friendli` LLM
and `ChatFriendli` chat model.
- Unit tests and integration tests corresponding to this change are
added.
- Documentations corresponding to this change are added.

## Dependencies
- Optional dependency
[`friendli-client`](https://pypi.org/project/friendli-client/) package
is added only for those who use `Frienldi` or `ChatFriendli` model.

## Twitter handle
- https://twitter.com/friendliai
2024-03-08 02:20:47 +00:00
Arun Sathiya
4adac20d7b
community[patch]: Make cohere_api_key a SecretStr (#12188)
This PR makes `cohere_api_key` in `llms/cohere` a SecretStr, so that the
API Key is not leaked when `Cohere.cohere_api_key` is represented as a
string.

---------

Signed-off-by: Arun <arun@arun.blog>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
2024-03-01 20:27:53 +00:00
Shengsheng Huang
ae471a7dcb
community[minor]: add BigDL-LLM integrations (#17953)
- **Description**:
[`bigdl-llm`](https://github.com/intel-analytics/BigDL) is a library for
running LLM on Intel XPU (from Laptop to GPU to Cloud) using
INT4/FP4/INT8/FP8 with very low latency (for any PyTorch model). This PR
adds bigdl-llm integrations to langchain.
- **Issue**: NA
- **Dependencies**: `bigdl-llm` library
- **Contribution maintainer**: @shane-huang 
 
Examples added:
- docs/docs/integrations/llms/bigdl.ipynb
2024-03-01 10:04:53 -08:00
Ethan Yang
f61cb8d407
community[minor]: Add openvino backend support (#11591)
- **Description:** add openvino backend support by HuggingFace Optimum
Intel,
  - **Dependencies:** “optimum[openvino]”,

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-01 10:04:24 -08:00
Guangdong Liu
47b1b7092d
community[minor]: Add SparkLLM to community (#17702) 2024-02-20 11:23:47 -08:00
Aymeric Roucher
0d294760e7
Community: Fuse HuggingFace Endpoint-related classes into one (#17254)
## Description
Fuse HuggingFace Endpoint-related classes into one:
-
[HuggingFaceHub](5ceaf784f3/libs/community/langchain_community/llms/huggingface_hub.py)
-
[HuggingFaceTextGenInference](5ceaf784f3/libs/community/langchain_community/llms/huggingface_text_gen_inference.py)
- and
[HuggingFaceEndpoint](5ceaf784f3/libs/community/langchain_community/llms/huggingface_endpoint.py)

Are fused into
- HuggingFaceEndpoint

## Issue
The deduplication of classes was creating a lack of clarity, and
additional effort to develop classes leads to issues like [this
hack](5ceaf784f3/libs/community/langchain_community/llms/huggingface_endpoint.py (L159)).

## Dependancies

None, this removes dependancies.

## Twitter handle

If you want to post about this: @AymericRoucher

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-02-19 10:33:15 -08:00
wulixuan
c776cfc599
community[minor]: integrate with model Yuan2.0 (#15411)
1. integrate with
[`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md)
2. update `langchain.llms`
3. add a new doc for [Yuan2.0
integration](docs/docs/integrations/llms/yuan2.ipynb)

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-02-14 11:46:20 -08:00
Kate Silverstein
0bc4a9b3fc
community[minor]: Adds Llamafile as an LLM (#17431)
* **Description:** Adds a simple LLM implementation for interacting with
[llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models.
* **Dependencies:** N/A
* **Issue:** N/A

**Detail**
[llamafile](https://github.com/Mozilla-Ocho/llamafile) lets you run LLMs
locally from a single file on most computers without installing any
dependencies.

To use the llamafile LLM implementation, the user needs to:

1. Download a llamafile e.g.
https://huggingface.co/jartine/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/TinyLlama-1.1B-Chat-v1.0.Q5_K_M.llamafile?download=true
2. Make the file executable.
3. Run the llamafile in 'server mode'. (All llamafiles come packaged
with a lightweight server; by default, the server listens at
`http://localhost:8080`.)


```bash
wget https://url/of/model.llamafile
chmod +x model.llamafile
./model.llamafile --server --nobrowser
```

Now, the user can invoke the LLM via the LangChain client:

```python
from langchain_community.llms.llamafile import Llamafile

llm = Llamafile()

llm.invoke("Tell me a joke.")
```
2024-02-14 11:15:24 -08:00
Erick Friis
3a2eb6e12b
infra: add print rule to ruff (#16221)
Added noqa for existing prints. Can slowly remove / will prevent more
being intro'd
2024-02-09 16:13:30 -08:00
Armin Stepanyan
641efcf41c
community: add runtime kwargs to HuggingFacePipeline (#17005)
This PR enables changing the behaviour of huggingface pipeline between
different calls. For example, before this PR there's no way of changing
maximum generation length between different invocations of the chain.
This is desirable in cases, such as when we want to scale the maximum
output size depending on a dynamic prompt size.

Usage example:

```python
from langchain_community.llms.huggingface_pipeline import HuggingFacePipeline
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

model_id = "gpt2"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
hf = HuggingFacePipeline(pipeline=pipe)

hf("Say foo:", pipeline_kwargs={"max_new_tokens": 42})
```

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-02-08 13:58:31 -08:00
Harrison Chase
4eda647fdd
infra: add -p to mkdir in lint steps (#17013)
Previously, if this did not find a mypy cache then it wouldnt run

this makes it always run

adding mypy ignore comments with existing uncaught issues to unblock other prs

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2024-02-05 11:22:06 -08:00
baichuan-assistant
f8f2649f12
community: Add Baichuan LLM to community (#16724)
Replace this entire comment with:
- **Description:** Add Baichuan LLM to integration/llm, also updated
related docs.

Co-authored-by: BaiChuanHelper <wintergyc@WinterGYCs-MacBook-Pro.local>
2024-01-29 20:08:24 -08:00
Harel Gal
a91181fe6d
community[minor]: add support for Guardrails for Amazon Bedrock (#15099)
Added support for optionally supplying 'Guardrails for Amazon Bedrock'
on both types of model invocations (batch/regular and streaming) and for
all models supported by the Amazon Bedrock service.

@baskaryan  @hwchase17

```python 
llm = Bedrock(model_id="<model_id>", client=bedrock,
                  model_kwargs={},
                  guardrails={"id": " <guardrail_id>",
                              "version": "<guardrail_version>",
                               "trace": True}, callbacks=[BedrockAsyncCallbackHandler()])

class BedrockAsyncCallbackHandler(AsyncCallbackHandler):
    """Async callback handler that can be used to handle callbacks from langchain."""

    async def on_llm_error(
            self,
            error: BaseException,
            **kwargs: Any,
    ) -> Any:
        reason = kwargs.get("reason")
        if reason == "GUARDRAIL_INTERVENED":
           # kwargs contains additional trace information sent by 'Guardrails for Bedrock' service.
            print(f"""Guardrails: {kwargs}""")


# streaming 
llm = Bedrock(model_id="<model_id>", client=bedrock,
                  model_kwargs={},
                  streaming=True,
                  guardrails={"id": "<guardrail_id>",
                              "version": "<guardrail_version>"})
```

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-01-24 14:44:19 -08:00
Shivani Modi
4e160540ff
community[minor]: Adding Konko Completion endpoint (#15570)
This PR introduces update to Konko Integration with LangChain.

1. **New Endpoint Addition**: Integration of a new endpoint to utilize
completion models hosted on Konko.

2. **Chat Model Updates for Backward Compatibility**: We have updated
the chat models to ensure backward compatibility with previous OpenAI
versions.

4. **Updated Documentation**: Comprehensive documentation has been
updated to reflect these new changes, providing clear guidance on
utilizing the new features and ensuring seamless integration.

Thank you to the LangChain team for their exceptional work and for
considering this PR. Please let me know if any additional information is
needed.

---------

Co-authored-by: Shivani Modi <shivanimodi@Shivanis-MacBook-Pro.local>
Co-authored-by: Shivani Modi <shivanimodi@Shivanis-MBP.lan>
2024-01-23 18:22:32 -08:00
Facundo Santiago
92e6a641fd
feat: adding paygo api support for Azure ML / Azure AI Studio (#14560)
- **Description:** Introducing support for LLMs and Chat models running
in Azure AI studio and Azure ML using the new deployment mode
pay-as-you-go (model as a service).
- **Issue:** NA
- **Dependencies:** None.
- **Tag maintainer:** @prakharg-msft @gdyre 
- **Twitter handle:** @santiagofacundo

Examples added:
*
[docs/docs/integrations/llms/azure_ml.ipynb](https://github.com/santiagxf/langchain/blob/santiagxf/azureml-endpoints-paygo-community/docs/docs/integrations/chat/azureml_endpoint.ipynb)
*
[docs/docs/integrations/chat/azureml_chat_endpoint.ipynb](https://github.com/santiagxf/langchain/blob/santiagxf/azureml-endpoints-paygo-community/docs/docs/integrations/chat/azureml_chat_endpoint.ipynb)

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
2024-01-23 17:08:51 -08:00
Iskren Ivov Chernev
fc196cab12
community[minor]: DeepInfra support for chat models (#16380)
Add deepinfra chat models support.

This is https://github.com/langchain-ai/langchain/pull/14234 re-opened
from my branch (so maintainers can edit).
2024-01-22 11:22:17 -08:00
Erick Friis
ebc75c5ca7
openai[minor]: implement langchain-openai package (#15503)
Todo

- [x] copy over integration tests
- [x] update docs with new instructions in #15513 
- [x] add linear ticket to bump core -> community, community->langchain,
and core->openai deps
- [ ] (optional): add `pip install langchain-openai` command to each
notebook using it
- [x] Update docstrings to not need `openai` install
- [x] Add serialization
- [x] deprecate old models

Contributor steps:

- [x] Add secret names to manual integrations workflow in
.github/workflows/_integration_test.yml
- [x] Add secrets to release workflow (for pre-release testing) in
.github/workflows/_release.yml

Maintainer steps (Contributors should not do these):

- [x] set up pypi and test pypi projects
- [x] add credential secrets to Github Actions
- [ ] add package to conda-forge


Functional changes to existing classes:

- now relies on openai client v1 (1.6.1) via concrete dep in
langchain-openai package

Codebase organization

- some function calling stuff moved to
`langchain_core.utils.function_calling` in order to be used in both
community and langchain-openai
2024-01-05 15:03:28 -08:00
Bagatur
baeac236b6
langchain[patch], experimental[patch]: update utilities imports (#15438) 2024-01-03 02:18:15 -05:00
NuODaniel
7773943a51
community:qianfan endpoint support init params & remove useless params definietion (#15381)
- **Description:**
- support custom kwargs in object initialization. For instantance, QPS
differs from multiple object(chat/completion/embedding with diverse
models), for which global env is not a good choice for configuration.
  - **Issue:** no
  - **Dependencies:** no
  - **Twitter handle:** no

@baskaryan PTAL
2024-01-01 13:12:31 -08:00