- **Description:** This PR implements a new LLM API to
https://gradient.ai
- **Issue:** Feature request for LLM #10745
- **Dependencies**: No additional dependencies are introduced.
- **Tag maintainer:** I am opening this PR for visibility, once ready
for review I'll tag.
- ```make format && make lint && make test``` is running.
- added a `integration` and `mock unit` test.
Co-authored-by: michaelfeil <me@michaelfeil.eu>
Co-authored-by: Bagatur <baskaryan@gmail.com>
We are introducing the py integration to Javelin AI Gateway
www.getjavelin.io. Javelin is an enterprise-scale fast llm router &
gateway. Could you please review and let us know if there is anything
missing.
Javelin AI Gateway wraps Embedding, Chat and Completion LLMs. Uses
javelin_sdk under the covers (pip install javelin_sdk).
Author: Sharath Rajasekar, Twitter: @sharathr, @javelinai
Thanks!!
### Description
- Add support for streaming with `Bedrock` LLM and `BedrockChat` Chat
Model.
- Bedrock as of now supports streaming for the `anthropic.claude-*` and
`amazon.titan-*` models only, hence support for those have been built.
- Also increased the default `max_token_to_sample` for Bedrock
`anthropic` model provider to `256` from `50` to keep in line with the
`Anthropic` defaults.
- Added examples for streaming responses to the bedrock example
notebooks.
**_NOTE:_**: This PR fixes the issues mentioned in #9897 and makes that
PR redundant.
- **Description:** QianfanEndpoint bugs for SystemMessages. When the
`SystemMessage` is input as the messages to
`chat_models.QianfanEndpoint`. A `TypeError` will be raised.
- **Issue:** #10643
- **Dependencies:**
- **Tag maintainer:** @baskaryan
- **Twitter handle:** no
### Description
Implements synthetic data generation with the fields and preferences
given by the user. Adds showcase notebook.
Corresponding prompt was proposed for langchain-hub.
### Example
```
output = chain({"fields": {"colors": ["blue", "yellow"]}, "preferences": {"style": "Make it in a style of a weather forecast."}})
print(output)
# {'fields': {'colors': ['blue', 'yellow']},
'preferences': {'style': 'Make it in a style of a weather forecast.'},
'text': "Good morning! Today's weather forecast brings a beautiful combination of colors to the sky, with hues of blue and yellow gently blending together like a mesmerizing painting."}
```
### Twitter handle
@deepsense_ai @matt_wosinski
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description**
Adds new output parser, this time enabling the output of LLM to be of an
XML format. Seems to be particularly useful together with Claude model.
Addresses [issue
9820](https://github.com/langchain-ai/langchain/issues/9820).
**Twitter handle**
@deepsense_ai @matt_wosinski
- **Description:** Added integration instructions for Remembrall.
- **Tag maintainer:** @hwchase17
- **Twitter handle:** @raunakdoesdev
Fun fact, this project originated at the Modal Hackathon in NYC where it
won the Best LLM App prize sponsored by Langchain. Thanks for your
support 🦜
~~Because we can't pass extra parameters into a prompt, we have to
prepend a function before the runnable calls in the branch and it's a
bit less elegant than I'd like.~~
All good now that #10765 has landed!
@eyurtsev @hwchase17
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
- This pr adds `llm_kwargs` to the initialization of Xinference LLMs
(integrated in #8171 ).
- With this enhancement, users can not only provide `generate_configs`
when calling the llms for generation but also during the initialization
process. This allows users to include custom configurations when
utilizing LangChain features like LLMChain.
- It also fixes some format issues for the docstrings.
This PR is a documentation fix.
Description:
* fixes imports in the code samples in the docstrings of
`create_openai_fn_chain` and `create_structured_output_chain`
* fixes imports in
`docs/extras/modules/chains/how_to/openai_functions.ipynb`
* removes unused imports from the notebook
Issues:
* the docstrings use `from pydantic_v1 import BaseModel, Field` which
this PR changes to `from langchain.pydantic_v1 import BaseModel, Field`
* importing `pydantic` instead of `langchain.pydantic_v1` leads to
errors later in the notebook
Description: This PR changes the import section of the
`PydanticOutputParser` notebook.
* Import from `langchain.pydantic_v1` instead of `pydantic`
* Remove unused imports
Issue: running the notebook as written, when pydantic v2 is installed,
results in the following:
```python
PydanticDeprecatedSince20: Pydantic V1 style `@validator` validators are deprecated. You should migrate to Pydantic V2 style `@field_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.3/migration/
```
[...]
```python
PydanticUserError: The `field` and `config` parameters are not available in Pydantic V2, please use the `info` parameter instead.
For further information visit https://errors.pydantic.dev/2.3/u/validator-field-config-info
```
**Description:**
I've added a new use-case to the Web scraping docs. I also fixed some
typos in the existing text.
---------
Co-authored-by: davidjohnbarton <41335923+davidjohnbarton@users.noreply.github.com>
- Description: Added support for Ollama embeddings
- Issue: the issue # it fixes (if applicable),
- Dependencies: N/A
- Tag maintainer: for a quicker response, tag the relevant maintainer
(see below),
- Twitter handle: @herrjemand
cc https://github.com/jmorganca/ollama/issues/436
Adding support for Neo4j vector index hybrid search option. In Neo4j,
you can achieve hybrid search by using a combination of vector and
fulltext indexes.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
