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>
- **Description:** This is a **one line change**. the
`self.async_client.with_raw_response.create(**payload)` call is not
properly awaited within the `_astream` method. In `_agenerate` this is
done already, but likely forgotten in the other method.
- **Issue:** Not applicable
- **Dependencies:** No dependencies required.
(If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.)
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- [ ] **PR message**:
- **Description:** Compatible with other llm (eg: deepseek-chat, glm-4)
usage meta data
- **Issue:** N/A
- **Dependencies:** no new dependencies added
- [ ] **Add tests and docs**:
libs/partners/openai/tests/unit_tests/chat_models/test_base.py
```shell
cd libs/partners/openai
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_openai_astream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_openai_stream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_deepseek_astream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_deepseek_stream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_glm4_astream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_glm4_stream
```
---------
Co-authored-by: hyman <hyman@xiaozancloud.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Remove the period after the hyperlink in the docstring of
BaseChatOpenAI.with_structured_output.
I have repeatedly copied the extra period at the end of the hyperlink,
which results in a "Page not found" page when pasted into the browser.
- Description: As described in the related issue: There is an error
occuring when using langchain-openai>=0.1.17 which can be attributed to
the following PR: #23691
Here, the parameter logprobs is added to requests per default.
However, AzureOpenAI takes issue with this parameter as stated here:
https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/chatgpt?tabs=python-new&pivots=programming-language-chat-completions
-> "If you set any of these parameters, you get an error."
Therefore, this PR changes the default value of logprobs parameter to
None instead of False. This results in it being filtered before the
request is sent.
- Issue: #24880
- Dependencies: /
Co-authored-by: blaufink <sebastian.brueckner@outlook.de>
supports following UX
```python
class SubTool(TypedDict):
"""Subtool docstring"""
args: Annotated[Dict[str, Any], {}, "this does bar"]
class Tool(TypedDict):
"""Docstring
Args:
arg1: foo
"""
arg1: str
arg2: Union[int, str]
arg3: Optional[List[SubTool]]
arg4: Annotated[Literal["bar", "baz"], ..., "this does foo"]
arg5: Annotated[Optional[float], None]
```
- can parse google style docstring
- can use Annotated to specify default value (second arg)
- can use Annotated to specify arg description (third arg)
- can have nested complex types
- [ ] **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>
**Description:** Explicitly add parameters from openai API
- [X] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
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>
- add test for structured output
- fix bug with structured output for Azure
- better testing on Groq (break out Mixtral + Llama3 and add xfails
where needed)
Discovered alongside @t968914
- **Description:**
According to OpenAI docs, tool messages (response from calling tools)
must have a 'name' field.
https://cookbook.openai.com/examples/how_to_call_functions_with_chat_models
- **Issue:** N/A (as of right now)
- **Dependencies:** N/A
- **Twitter handle:** N/A
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
