See discussion here:
https://github.com/langchain-ai/langchain/discussions/11680
The code is available for usage from langchain_experimental. The reason
for the deprecation is that the agents are relying on a Python REPL. The
code can only be run safely with appropriate sandboxing.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
The changes introduced in #12267 and #12190 broke the cost computation
of the `completion` tokens for fine-tuned models because of the early
return. This PR aims at fixing this.
@baskaryan.
Compare predicted json to reference. First canonicalize (sort keys, rm
whitespace separators), then return normalized string edit distance.
Not a silver bullet but maybe an easy way to capture structure
differences in a less flakey way
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
**Description**
This small change will make chunk_size a configurable parameter for
loading documents into a Supabase database.
**Issue**
https://github.com/langchain-ai/langchain/issues/11422
**Dependencies**
No chanages
**Twitter**
@ j1philli
**Reminder**
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
---------
Co-authored-by: Greg Richardson <greg.nmr@gmail.com>
Description
* Add _generate and _agenerate to support Fireworks batching.
* Add stop words test cases
* Opt out retry mechanism
Issue - Not applicable
Dependencies - None
Tag maintainer - @baskaryan
- **Description:** refactors the redis vector field schema to properly
handle default values, includes a new unit test suite.
- **Issue:** N/A
- **Dependencies:** nothing new.
- **Tag maintainer:** @baskaryan @Spartee
- **Twitter handle:** this is a tiny fix/improvement :)
This issue was causing some clients/cuatomers issues when building a
vector index on Redis on smaller db instances (due to fault default
values in index configuration). It would raise an error like:
```redis.exceptions.ResponseError: Vector index initial capacity 20000 exceeded server limit (852 with the given parameters)```
This PR will address this moving forward.
**Description:**
This PR adds support for the [Pro version of Titan Takeoff
Server](https://docs.titanml.co/docs/category/pro-features). Users of
the Pro version will have to import the TitanTakeoffPro model, which is
different from TitanTakeoff.
**Issue:**
Also minor fixes to docs for Titan Takeoff (Community version)
**Dependencies:**
No additional dependencies
**Twitter handle:** @becoming_blake
@baskaryan @hwchase17
If user function is wrapped as a traceable function, this will help hand
off the trace between the two.
Also update handling fields to reflect optional values
**Description:** When llms output leading or trailing whitespace for xml
(when using XMLOutputParser) the parser would raise a `ValueError: Could
not parse output: ...`. However, leading or trailing whitespace are
"ignorable" in the sense of XML standard.
**Issue:** I did not find an issue related.
**Dependencies:** None
**Tag maintainer:**
**Twitter handle:** donatoaz
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
Done, updated unit test and ran `make docker_test`.
**Description:**
Documents further usage of RetrievalQAWithSourcesChain in an existing
test. I'd not found much documented usage of RetrievalQAWithSourcesChain
and how to get the sources out. This additional code will hopefully be
useful to other potential users of this retriever.
**Issue:** No raised issue
**Dependencies:** No new dependencies needed to run the test (it already
needs `open-ai`, `faiss-cpu` and `unstructured`).
Note - `make lint` showed 8 linting errors in unrelated files
---------
Co-authored-by: richarda23 <richard.c.adams@infinityworks.com>
* Add a type literal for the generation and sub-classes for serialization purposes.
* Fix the root validator of ChatGeneration to return ValueError instead of KeyError or Attribute error if intialized improperly.
* This change is done for langserve to make sure that llm related callbacks can be serialized/deserialized properly.
**Description:**
Add cost calculation for fine tuned models (new and legacy), this is
required after OpenAI added new models for fine tuning and separated the
costs of I/O for fine tuned models.
Also I updated the relevant unit tests
see https://platform.openai.com/docs/guides/fine-tuning for more
information.
issue: https://github.com/langchain-ai/langchain/issues/11715
- **Issue:** 11715
- **Twitter handle:** @nirkopler
- replace `requests` package with `langchain.requests`
- add `_acall` support
- add `_stream` and `_astream`
- freshen up the documentation a bit
- update vendor doc
Allows for passing arguments into the LLM chains used by the
GraphCypherQAChain. This is to address a request by a user to include
memory in the Cypher creating chain. Will keep the prompt variables
as-is to be backward compatible. But, would be a good idea to deprecate
them and use the **kwargs variables. Added a test case.
In general, I think it would be good for any chain to automatically pass
in a readonlymemory(of its input) to its subchains whilist allowing for
an override. But, this would be a different change.
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
If non-pickleable objects (like locks) get passed to the tracing
callback, they'll fail in the deepcopy. Fallback to a shallow copy in
these instances .
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
This reverts commit a46eef64a7.
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
- **Description:** Provide a way to use different text for embedding.
- For example, if you are ingesting stack-overflow Q&As for RAG, you
would want to embed the questions and return the answer(s) for the hits.
With this change, the consumer of langchain can implement that easily.
- I noticed the similar function is added on faiss.py with #1912 which
was for performance reason, but I see the same function can be used to
achieve what I thought. So instead of changing Document class to have
embedding_content, I mimicked the implementation of faiss.py.
- The test should provide some guidance on how to use it. It would be
more intuitive if I just pass texts and embedding_texts as separate
arguments, but I chose to use `zip`-ed object for the consistency with
faiss.py implementation.
- I plan to make similar pull request for OpenSearch.
- **Issue:** N/A
- **Dependencies:** None other than the existing ones.
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** Adding Pydantic v2 support for OpenAPI Specs
- **Issue:**
- OpenAPI spec support was disabled because `openapi-schema-pydantic`
doesn't support Pydantic v2:
#9205
- Caused errors in `get_openapi_chain`
- This may be the cause of #9520.
- **Tag maintainer:** @eyurtsev
- **Twitter handle:** kreneskyp
The root cause was that `openapi-schema-pydantic` hasn't been updated in
some time but
[openapi-pydantic](https://github.com/mike-oakley/openapi-pydantic)
forked and updated the project.
Updated the elasticsearch self query retriever to use the match clause
for LIKE operator instead of the non-analyzed fuzzy search clause.
Other small updates include:
- fixing the stack inference integration test where the index's default
pipeline didn't use the inference pipeline created
- adding a user-agent to the old implementation to track usage
- improved the documentation for ElasticsearchStore filters
### Description:
To provide an eas llm service access methods in this pull request by
impletementing `PaiEasEndpoint` and `PaiEasChatEndpoint` classes in
`langchain.llms` and `langchain.chat_models` modules. Base on this pr,
langchain users can build up a chain to call remote eas llm service and
get the llm inference results.
### About EAS Service
EAS is a Alicloud product on Alibaba Cloud Machine Learning Platform for
AI which is short for AliCloud PAI. EAS provides model inference
deployment services for the users. We build up a llm inference services
on EAS with a general llm docker images. Therefore, end users can
quickly setup their llm remote instances to load majority of the
hugginface llm models, and serve as a backend for most of the llm apps.
### Dependencies
This pr does't involve any new dependencies.
---------
Co-authored-by: 子洪 <gaoyihong.gyh@alibaba-inc.com>
Minor lint dependency version upgrade to pick up latest functionality.
Ruff's new v0.1 version comes with lots of nice features, like
fix-safety guarantees and a preview mode for not-yet-stable features:
https://astral.sh/blog/ruff-v0.1.0
- **Description:** Chroma >= 0.4.10 added support for batch sizes
validation of add/upsert. This batch size is dependent on the SQLite
limits of the target system and varies. In this change, for
Chroma>=0.4.10 batch splitting was added as the aforementioned
validation is starting to surface in the Chroma community (users using
LC)
- **Issue:** N/A
- **Dependencies:** N/A
- **Tag maintainer:** @eyurtsev
- **Twitter handle:** t_azarov
Eugene Yurtsev