- Description: Google Cloud Enterprise Search was renamed to Vertex AI
Search
-
https://cloud.google.com/blog/products/ai-machine-learning/vertex-ai-search-and-conversation-is-now-generally-available
- This PR updates the documentation and Retriever class to use the new
terminology.
- Changed retriever class from `GoogleCloudEnterpriseSearchRetriever` to
`GoogleVertexAISearchRetriever`
- Updated documentation to specify that `extractive_segments` requires
the new [Enterprise
edition](https://cloud.google.com/generative-ai-app-builder/docs/about-advanced-features#enterprise-features)
to be enabled.
- Fixed spelling errors in documentation.
- Change parameter for Retriever from `search_engine_id` to
`data_store_id`
- When this retriever was originally implemented, there was no
distinction between a data store and search engine, but now these have
been split.
- Fixed an issue blocking some users where the api_endpoint can't be set
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!!
The Graph Chains are different in the way that it uses two LLMChains
instead of one like the retrievalQA chains. Therefore, sometimes you
want to use different LLM to generate the database query and to generate
the final answer.
This feature would make it more convenient to use different LLMs in the
same chain.
I have also renamed the Graph DB QA Chain to Neo4j DB QA Chain in the
documentation only as it is used only for Neo4j. The naming was
ambigious as it was the first graphQA chain added and wasn't sure how do
you want to spin it.
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.
Update API reference documentation. This PR will pick up a number of missing classes, it also applies selective formatting based on the class / object type.
This change compacts the left-side Navbar (ToC) of the [API
Reference](https://api.python.langchain.com/en/latest/api_reference.html).
Now almost each namespace item is split into two lines. For example
`langchain.chat_models: Chat Models`
We remove the `Chat Models` and leave one the `langchain.chat_models`.
This effectively compacts the navbar and increases the main page's
usability. On my screen, it reduces # of lines in Toc from 28 t to 18,
which is huge.
Removing the namespace "title" (like `Chat Models`) does not remove any
information because the title is composed directly from the namespace.
API Reference users are developers. Usability for them is very
important. We see less text => we find faster.
Still don't have good "how to's", and the guides / examples section
could be further pruned and improved, but this PR adds a couple examples
for each of the common evaluator interfaces.
- [x] Example docs for each implemented evaluator
- [x] "how to make a custom evalutor" notebook for each low level APIs
(comparison, string, agent)
- [x] Move docs to modules area
- [x] Link to reference docs for more information
- [X] Still need to finish the evaluation index page
- ~[ ] Don't have good data generation section~
- ~[ ] Don't have good how to section for other common scenarios / FAQs
like regression testing, testing over similar inputs to measure
sensitivity, etc.~
- Migrate from deprecated langchainplus_sdk to `langsmith` package
- Update the `run_on_dataset()` API to use an eval config
- Update a number of evaluators, as well as the loading logic
- Update docstrings / reference docs
- Update tracer to share single HTTP session
**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>
- [Xorbits](https://doc.xorbits.io/en/latest/) is an open-source
computing framework that makes it easy to scale data science and machine
learning workloads in parallel. Xorbits can leverage multi cores or GPUs
to accelerate computation on a single machine, or scale out up to
thousands of machines to support processing terabytes of data.
- This PR added support for the Xorbits document loader, which allows
langchain to leverage Xorbits to parallelize and distribute the loading
of data.
- Dependencies: This change requires the Xorbits library to be installed
in order to be used.
`pip install xorbits`
- Request for review: @rlancemartin, @eyurtsev
- Twitter handle: https://twitter.com/Xorbitsio
Co-authored-by: Bagatur <baskaryan@gmail.com>
