`ChatAnthropic` can get `stop_reason` from the resulting `AIMessage` in
`invoke` and `ainvoke`, but not in `stream` and `astream`.
This is a different behavior from `ChatOpenAI`.
It is possible to get `stop_reason` from `stream` as well, since it is
needed to determine the next action after the LLM call. This would be
easier to handle in situations where only `stop_reason` is needed.
- Issue: NA
- Dependencies: NA
- Twitter handle: https://x.com/kiarina37
Description:
1. partners/HuggingFace module support reading params from env. Not
adjust langchain_community/.../huggingfaceXX modules since they are
deprecated.
2. pydantic 2 @root_validator migration.
Issue: #22448#22819
---------
Co-authored-by: gongwn1 <gongwn1@lenovo.com>
# Fix streaming in mistral with ainvoke
- [x] **PR title**
- [x] **PR message**
- [x] **Add tests and docs**:
1. [x] Added a test for the fixed integration.
2. [x] An example notebook showing its use. It lives in
`docs/docs/integrations` directory.
- [x] **Lint and test**: Ran `make format`, `make lint` and `make test`
from the root of the package(s) I've modified.
Hello
* I Identified an issue in the mistral package where the callback
streaming (see on_llm_new_token) was not functioning correctly when the
streaming parameter was set to True and call with `ainvoke`.
* The root cause of the problem was the streaming not taking into
account. ( I think it's an oversight )
* To resolve the issue, I added the `streaming` attribut.
* Now, the callback with streaming works as expected when the streaming
parameter is set to True.
## How to reproduce
```
from langchain_mistralai.chat_models import ChatMistralAI
chain = ChatMistralAI(streaming=True)
# Add a callback
chain.ainvoke(..)
# Oberve on_llm_new_token
# Now, the callback is given as streaming tokens, before it was in grouped format.
```
Co-authored-by: Erick Friis <erick@langchain.dev>
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)
- **Description:** A small fix where I moved the `available_endpoints`
in order to avoid the token error in the below issue. Also I have added
conftest file and updated the `scripy`,`numpy` versions to support newer
python versions in poetry files.
- **Issue:** #22804
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: ccurme <chester.curme@gmail.com>
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.
## Description
Created a helper method to make vector search indexes via client-side
pymongo.
**Recent Update** -- Removed error suppressing/overwriting layer in
favor of letting the original exception provide information.
## ToDo's
- [x] Make _wait_untils for integration test delete index
functionalities.
- [x] Add documentation for its use. Highlight it's experimental
- [x] Post Integration Test Results in a screenshot
- [x] Get review from MongoDB internal team (@shaneharvey, @blink1073 ,
@NoahStapp , @caseyclements)
- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. Added new integration tests. Not eligible for unit testing since the
operation is Atlas Cloud specific.
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.
- [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/
**Description:** Adds options for configuring MongoDBChatMessageHistory
(no breaking changes):
- session_id_key: name of the field that stores the session id
- history_key: name of the field that stores the chat history
- create_index: whether to create an index on the session id field
- index_kwargs: additional keyword arguments to pass to the index
creation
**Discussion:**
https://github.com/langchain-ai/langchain/discussions/22918
**Twitter handle:** @userlerueda
---------
Co-authored-by: Jib <Jibzade@gmail.com>
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
**Description:**
Currently, the `langchain_pinecone` library forces the `async_req`
(asynchronous required) argument to Pinecone to `True`. This design
choice causes problems when deploying to environments that do not
support multiprocessing, such as AWS Lambda. In such environments, this
restriction can prevent users from successfully using
`langchain_pinecone`.
This PR introduces a change that allows users to specify whether they
want to use asynchronous requests by passing the `async_req` parameter
through `**kwargs`. By doing so, users can set `async_req=False` to
utilize synchronous processing, making the library compatible with AWS
Lambda and other environments that do not support multithreading.
**Issue:**
This PR does not address a specific issue number but aims to resolve
compatibility issues with AWS Lambda by allowing synchronous processing.
**Dependencies:**
None, that I'm aware of.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
**Description**
The current code snippet for `Fireworks` had incorrect parameters. This
PR fixes those parameters.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Added missed docstrings. Format docstrings to the consistent format
(used in the API Reference)
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
