**Description: a description of the change**
Fixed `make docs_build` and related scripts which caused errors. There
are several changes.
First, I made the build of the documentation and the API Reference into
two separate commands. This is because it takes less time to build. The
commands for documents are `make docs_build`, `make docs_clean`, and
`make docs_linkcheck`. The commands for API Reference are `make
api_docs_build`, `api_docs_clean`, and `api_docs_linkcheck`.
It looked like `docs/.local_build.sh` could be used to build the
documentation, so I used that. Since `.local_build.sh` was also building
API Rerefence internally, I removed that process. `.local_build.sh` also
added some Bash options to stop in error or so. Futher more added `cd
"${SCRIPT_DIR}"` at the beginning so that the script will work no matter
which directory it is executed in.
`docs/api_reference/api_reference.rst` is removed, because which is
generated by `docs/api_reference/create_api_rst.py`, and added it to
.gitignore.
Finally, the description of CONTRIBUTING.md was modified.
**Issue: the issue # it fixes (if applicable)**
https://github.com/hwchase17/langchain/issues/6413
**Dependencies: any dependencies required for this change**
`nbdoc` was missing in group docs so it was added. I installed it with
the `poetry add --group docs nbdoc` command. I am concerned if any
modifications are needed to poetry.lock. I would greatly appreciate it
if you could pay close attention to this file during the review.
**Tag maintainer**
- General / Misc / if you don't know who to tag: @baskaryan
If this PR needs any additional changes, I'll be happy to make them!
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
### Description
Adding a callback handler for Context. Context is a product analytics
platform for AI chat experiences to help you understand how users are
interacting with your product.
I've added the callback library + an example notebook showing its use.
### Dependencies
Requires the user to install the `context-python` library. The library
is lazily-loaded when the callback is instantiated.
### Announcing the feature
We spoke with Harrison a few weeks ago about also doing a blog post
announcing our integration, so will coordinate this with him. Our
Twitter handle for the company is @getcontextai, and the founders are
@_agamble and @HenrySG.
Thanks in advance!
**Description:** Add a documentation page for the Streamlit Callback
Handler integration (#6315)
Notes:
- Implemented as a markdown file instead of a notebook since example
code runs in a Streamlit app (happy to discuss / consider alternatives
now or later)
- Contains an embedded Streamlit app ->
https://mrkl-minimal.streamlit.app/ Currently this app is hosted out of
a Streamlit repo but we're working to migrate the code to a LangChain
owned repo
cc @dev2049 @tconkling
### Integration of Infino with LangChain for Enhanced Observability
This PR aims to integrate [Infino](https://github.com/infinohq/infino),
an open source observability platform written in rust for storing
metrics and logs at scale, with LangChain, providing users with a
streamlined and efficient method of tracking and recording LangChain
experiments. By incorporating Infino into LangChain, users will be able
to gain valuable insights and easily analyze the behavior of their
language models.
#### Please refer to the following files related to integration:
- `InfinoCallbackHandler`: A [callback
handler](https://github.com/naman-modi/langchain/blob/feature/infino-integration/langchain/callbacks/infino_callback.py)
specifically designed for storing chain responses within Infino.
- Example `infino.ipynb` file: A comprehensive notebook named
[infino.ipynb](https://github.com/naman-modi/langchain/blob/feature/infino-integration/docs/extras/modules/callbacks/integrations/infino.ipynb)
has been included to guide users on effectively leveraging Infino for
tracking LangChain requests.
- [Integration
Doc](https://github.com/naman-modi/langchain/blob/feature/infino-integration/docs/extras/ecosystem/integrations/infino.mdx)
for Infino integration.
By integrating Infino, LangChain users will gain access to powerful
visualization and debugging capabilities. Infino enables easy tracking
of inputs, outputs, token usage, execution time of LLMs. This
comprehensive observability ensures a deeper understanding of individual
executions and facilitates effective debugging.
Co-authors: @vinaykakade @savannahar68
---------
Co-authored-by: Vinay Kakade <vinaykakade@gmail.com>
