This fix ensures that the chunk size is correctly determined when
processing text embeddings. Previously, the code did not properly handle
cases where chunk_size was None, potentially leading to incorrect
chunking behavior.
Now, chunk_size_ is explicitly set to either the provided chunk_size or
the default self.chunk_size, ensuring consistent chunking. This update
improves reliability when processing large text inputs in batches and
prevents unintended behavior when chunk_size is not specified.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- This pull request includes various changes to add a `user_agent`
parameter to Azure OpenAI, Azure Search and Whisper in the Community and
Partner packages. This helps in identifying the source of API requests
so we can better track usage and help support the community better. I
will also be adding the user_agent to the new `langchain-azure` repo as
well.
- No issue connected or updated dependencies.
- Utilises existing tests and docs
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR introduces a new `azure_ad_async_token_provider` attribute to
the `AzureOpenAI` and `AzureChatOpenAI` classes in `partners/openai` and
`community` packages, given it's currently supported on `openai` package
as
[AsyncAzureADTokenProvider](https://github.com/openai/openai-python/blob/main/src/openai/lib/azure.py#L33)
type.
The reason for creating a new attribute is to avoid breaking changes.
Let's say you have an existing code that uses a `AzureOpenAI` or
`AzureChatOpenAI` instance to perform both sync and async operations.
The `azure_ad_token_provider` will work exactly as it is today, while
`azure_ad_async_token_provider` will override it for async requests.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
Chunking of the input array controlled by `self.chunk_size` is being
ignored when `self.check_embedding_ctx_length` is disabled. Effectively,
the chunk size is assumed to be equal 1 in such a case. This is
suprising.
The PR takes into account `self.chunk_size` passed by the user.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- [ ] **PR title**: "langchain-openai: openai proxy added to base
embeddings"
- [ ] **PR message**:
- **Description:**
Dear langchain developers,
You've already supported proxy for ChatOpenAI implementation in your
package. At the same time, if somebody needed to use proxy for chat, it
also could be necessary to be able to use it for OpenAIEmbeddings.
That's why I think it's important to add proxy support for OpenAI
embeddings. That's what I've done in this PR.
@baskaryan
---------
Co-authored-by: karpov <karpov@dohod.ru>
Co-authored-by: Bagatur <baskaryan@gmail.com>
This fix is for #21726. When having other packages installed that
require the `openai_api_base` environment variable, users are not able
to instantiate the AzureChatModels or AzureEmbeddings.
This PR adds a new value `ignore_openai_api_base` which is a bool. When
set to True, it sets `openai_api_base` to `None`
Two new tests were added for the `test_azure` and a new file
`test_azure_embeddings`
A different approach may be better for this. If you can think of better
logic, let me know and I can adjust it.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
## Summary
I ran `ruff check --extend-select RUF100 -n` to identify `# noqa`
comments that weren't having any effect in Ruff, and then `ruff check
--extend-select RUF100 -n --fix` on select files to remove all of the
unnecessary `# noqa: F401` violations. It's possible that these were
needed at some point in the past, but they're not necessary in Ruff
v0.1.15 (used by LangChain) or in the latest release.
Co-authored-by: Erick Friis <erick@langchain.dev>
OpenAI API compatible server may not support `safe_len_embedding`，
use `disable_safe_len_embeddings=True` to disable it.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** Update the docstring of OpenAI, OpenAIEmbeddings and
ChatOpenAI classes
**Issue:** Update import module paths to the current LangChain API
**Dependencies:** None
**Lint and test**: `make format` and `make lint` were run
This incorporates the review comments from langchain-ai/langchain#18637
which I closed due to an issue I had in updating that pr branch
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
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
