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**Description:** Implement stream and astream methods for RunnableLambda
to make streaming work for functions returning Runnable
- **Issue:** https://github.com/langchain-ai/langchain/issues/11998
- **Dependencies:** No new dependencies
- **Twitter handle:** https://twitter.com/qtangs
---------
Co-authored-by: Nuno Campos <nuno@langchain.dev>
**Description:**
Adding async methods to booth OllamaLLM and ChatOllama to enable async
streaming and async .on_llm_new_token callbacks.
**Issue:**
ChatOllama is not working in combination with an AsyncCallbackManager
because the .on_llm_new_token method is not awaited.
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- Added ensure_ascii property to ElasticsearchChatMessageHistory
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---------
Co-authored-by: Ivan Chetverikov <ivan.chetverikov@raftds.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
**Description**: The parameter chunk_type was being hard coded to
"extractive_answers", so that when "snippet" was being passed, it was
being ignored. This change simply doesn't do that.
Added the call function get_summaries_as_docs inside of Arxivloader
- **Description:** Added a function that returns the documents from
get_summaries_as_docs, as the call signature is present in the parent
file but never used from Arxivloader, this can be used from Arxivloader
itself just like .load() as both the signatures are same.
- **Issue:** Reduces time to load papers as no pdf is processed only
metadata is pulled from Arxiv allowing users for faster load times on
bulk loads. Users can then choose one or more paper and use ID directly
with .load() to load pdf thereby loading all the contents of the paper.
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## Description
Changes the behavior of `add_user_message` and `add_ai_message` to allow
for messages of those types to be passed in. Currently, if you want to
use the `add_user_message` or `add_ai_message` methods, you have to pass
in a string. For `add_message` on `ChatMessageHistory`, however, you
have to pass a `BaseMessage`. This behavior seems a bit inconsistent.
Personally, I'd love to be able to be explicit that I want to
`add_user_message` and pass in a `HumanMessage` without having to grab
the `content` attribute. This PR allows `add_user_message` to accept
`HumanMessage`s or `str`s and `add_ai_message` to accept `AIMessage`s or
`str`s to add that functionality and ensure backwards compatibility.
## Issue
* None
## Dependencies
* None
## Tag maintainer
@hinthornw
@baskaryan
## Note
`make test` results in `make: *** No rule to make target 'test'. Stop.`
- **Description:** `tools.gmail.send_message` implements a
`SendMessageSchema` that is not used anywhere. `GmailSendMessage` also
does not have an `args_schema` attribute (this led to issues when
invoking the tool with an OpenAI functions agent, at least for me). Here
we add the missing attribute and a minimal test for the tool.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** N/A
---------
Co-authored-by: Chester Curme <chestercurme@microsoft.com>
- **Description:** In response to user feedback, this PR refactors the
Baseten integration with updated model endpoints, as well as updates
relevant documentation. This PR has been tested by end users in
production and works as expected.
- **Issue:** N/A
- **Dependencies:** This PR actually removes the dependency on the
`baseten` package!
- **Twitter handle:** https://twitter.com/basetenco
# Description
This PR adds the ability to pass a `botocore.config.Config` instance to
the boto3 client instantiated by the Bedrock LLM.
Currently, the Bedrock LLM doesn't support a way to pass a Config, which
means that some settings (e.g., timeouts and retry configuration)
require instantiating a new boto3 client with a Config and then
replacing the LLM's client:
```python
llm = Bedrock(
region_name='us-west-2',
model_id="anthropic.claude-v2",
model_kwargs={'max_tokens_to_sample': 4096, 'temperature': 0},
)
llm.client = boto_client('bedrock-runtime', region_name='us-west-2', config=Config({'read_timeout': 300}))
```
# Issue
N/A
# Dependencies
N/A
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fix spellings
**seperate -> separate**: found more occurrences, see
https://github.com/langchain-ai/langchain/pull/14602
**initialise -> intialize**: the latter is more common in the repo
**pre-defined > predefined**: adding a comma after a prefix is a
delicate matter, but this is a generally accepted word
also, another word that appears in the repo is "fs" (stands for
filesystem), e.g., in `libs/core/langchain_core/prompts/loading.py`
` """Unified method for loading a prompt from LangChainHub or local
fs."""`
Isn't "filesystem" better?
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---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Ran <rccalman@gmail.com>
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- **Description:** This PR fixes test failures on Windows caused by path
handling differences and unescaped special characters in regex. The
failing tests are:
```
FAILED tests/unit_tests/storage/test_filesystem.py::test_yield_keys - AssertionError: assert ['key1', 'subdir\\key2'] == ['key1', 'subdir/key2']
FAILED tests/unit_tests/test_imports.py::test_importable_all - ModuleNotFoundError: No module named 'langchain_community.langchain_community\\adapters'
FAILED tests/unit_tests/tools/file_management/test_utils.py::test_get_validated_relative_path_errs_on_absolute - re.error: incomplete escape \U at position 53
FAILED tests/unit_tests/tools/file_management/test_utils.py::test_get_validated_relative_path_errs_on_parent_dir - re.error: incomplete escape \U at position 69
FAILED tests/unit_tests/tools/file_management/test_utils.py::test_get_validated_relative_path_errs_for_symlink_outside_root - re.error: incomplete escape \U at position 64
```
- **Issue:** fixes
https://github.com/langchain-ai/langchain/issues/11775 (partially)
- **Dependencies:** none
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Builds on #14040 with community refactor merged and notebook updated.
Note that with this refactor, models will be imported from
`langchain_community.chat_models.huggingface` rather than the main
`langchain` repo.
---------
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: ugm2 <unaigaraymaestre@gmail.com>
Signed-off-by: Yuchen Liang <yuchenl3@andrew.cmu.edu>
Co-authored-by: Andrew Reed <andrew.reed.r@gmail.com>
Co-authored-by: Andrew Reed <areed1242@gmail.com>
Co-authored-by: A-Roucher <aymeric.roucher@gmail.com>
Co-authored-by: Aymeric Roucher <69208727+A-Roucher@users.noreply.github.com>
Replace this entire comment with:
- **Description:** @kurtisvg has raised a point that it's a good idea to
have a fixed version for embeddings (since otherwise a user might run a
query with one version vs a vectorstore where another version was used).
In order to avoid breaking changes, I'd suggest to give users a warning,
and make a `model_name` a required argument in 1.5 months.
Surrealdb client changes from 0.3.1 to 0.3.2 broke the surrealdb vectore
integration.
This PR updates the code to work with the updated client. The change is
backwards compatible with previous versions of surrealdb client.
Also expanded the vector store implementation to store and retrieve
metadata that's included with the document object.
- **Description:** Fixed jaguar.py to import JaguarHttpClient with try
and catch
- **Issue:** the issue # Unable to use the JaguarHttpClient at run time
- **Dependencies:** It requires "pip install -U jaguardb-http-client"
- **Twitter handle:** workbot
---------
Co-authored-by: JY <jyjy@jaguardb>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description**
For the Momento Vector Index (MVI) vector store implementation, pass
through `filter_expression` kwarg to the MVI client, if specified. This
change will enable the MVI self query implementation in a future PR.
Also fixes some integration tests.