Commit Graph

2916 Commits (789cd5198d92f900a77f50c4117798a2edd35ee5)

Author SHA1 Message Date
Sridhar Ramaswamy 9f1cbbc6ed
community[minor]: Add pebblo safe document loader (#16862)
- **Description:** Pebblo opensource project enables developers to
safely load data to their Gen AI apps. It identifies semantic topics and
entities found in the loaded data and summarizes them in a
developer-friendly report.
  - **Dependencies:** none
  - **Twitter handle:** srics

@hwchase17
7 months ago
mhavey 1bbb64d956
community[minor], langchian[minor]: Add Neptune Rdf graph and chain (#16650)
**Description**: This PR adds a chain for Amazon Neptune graph database
RDF format. It complements the existing Neptune Cypher chain. The PR
also includes a Neptune RDF graph class to connect to, introspect, and
query a Neptune RDF graph database from the chain. A sample notebook is
provided under docs that demonstrates the overall effect: invoking the
chain to make natural language queries against Neptune using an LLM.

**Issue**: This is a new feature
 
**Dependencies**: The RDF graph class depends on the AWS boto3 library
if using IAM authentication to connect to the Neptune database.

---------

Co-authored-by: Piyush Jain <piyushjain@duck.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Michael Feil e1cfd0f3e7
community[patch]: infinity embeddings update incorrect default url (#16759)
The default url has always been incorrect (7797 instead 7997). Here is a
update to the correct url.
7 months ago
Massimiliano Pronesti df7cbd6fbb
community[minor]: add FlashRank ranker (#16785)
**Description:** This PR adds support for
[flashrank](https://github.com/PrithivirajDamodaran/FlashRank) for
reranking as alternative to Cohere.

I'm not sure `libs/langchain` is the right place for this change. At
first, I wanted to put it under `libs/community`. All the compressors
were under `libs/langchain/retrievers/document_compressors` though. Hope
this makes sense!
7 months ago
Andreas Motl 1fdd9bd980
community/SQLDatabase: Generalize and trim software tests (#16659)
- **Description:** Improve test cases for `SQLDatabase` adapter
component, see
[suggestion](https://github.com/langchain-ai/langchain/pull/16655#pullrequestreview-1846749474).
  - **Depends on:** GH-16655
  - **Addressed to:** @baskaryan, @cbornet, @eyurtsev

_Remark: This PR is stacked upon GH-16655, so that one will need to go
in first._

Edit: Thank you for bringing in GH-17191, @eyurtsev. This is a little
aftermath, improving/streamlining the corresponding test cases.
7 months ago
Theo / Taeyoon Kang 1987f905ed
core[patch]: Support .yml extension for YAML (#16783)
- **Description:**

[AS-IS] When dealing with a yaml file, the extension must be .yaml.  

[TO-BE] In the absence of extension length constraints in the OS, the
extension of the YAML file is yaml, but control over the yml extension
must still be made.

It's as if it's an error because it's a .jpg extension in jpeg support.

  - **Issue:** - 

  - **Dependencies:**
no dependencies required for this change,
7 months ago
Kapil Sachdeva cd00a87db7
community[patch] - in FAISS vector store, support passing custom DocStore implementation when using from_xxx methods (#16801)
- **Description:** The from__xx methods of FAISS class have hardcoded
InMemoryStore implementation and thereby not let users pass a custom
DocStore implementation,
  - **Issue:** no referenced issue,
  - **Dependencies:** none,
  - **Twitter handle:** ksachdeva
7 months ago
Chris f9f5626ca4
community[patch]: Fix github search issues and PRs PaginatedList has no len() error (#16806)
**Description:** 
Bugfix: Langchain_community's GitHub Api wrapper throws a TypeError when
searching for issues and/or PRs (the `search_issues_and_prs` method).
This is because PyGithub's PageinatedList type does not support the
len() method. See https://github.com/PyGithub/PyGithub/issues/1476

![image](https://github.com/langchain-ai/langchain/assets/8849021/57390b11-ed41-4f48-ba50-f3028610789c)
  **Dependencies:** None 
  **Twitter handle**: @ChrisKeoghNZ
  
I haven't registered an issue as it would take me longer to fill the
template out than to make the fix, but I'm happy to if that's deemed
essential.

I've added a simple integration test to cover this as there were no
existing unit tests and it was going to be tricky to set them up.

Co-authored-by: Chris Keogh <chris.keogh@xero.com>
7 months ago
morgana 722aae4fd1
community: add delete method to rocksetdb vectorstore to support recordmanager (#17030)
- **Description:** This adds a delete method so that rocksetdb can be
used with `RecordManager`.
  - **Issue:** N/A
  - **Dependencies:** N/A
  - **Twitter handle:** `@_morgan_adams_`

---------

Co-authored-by: Rockset API Bot <admin@rockset.io>
7 months ago
yin1991 c454dc36fc
community[proxy]: Enhancement/add proxy support playwrighturlloader 16751 (#16822)
- **Description:** Enhancement/add proxy support playwrighturlloader
16751
- **Issue:** [Enhancement: Add Proxy Support to PlaywrightURLLoader
Class](https://github.com/langchain-ai/langchain/issues/16751)
  - **Dependencies:** 
  - **Twitter handle:** @ootR77013489

---------

Co-authored-by: root <root@ip-172-31-46-160.ap-southeast-1.compute.internal>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Bhupesh Varshney e3b775e035
infra: make `.gitignore` consistent with standard python gitignore (#16828)
- The new .gitignore version is inherited from the one maintained by the
github community over at
https://github.com/github/gitignore/blob/main/Python.gitignore
- This should cover all the cases of how a langchain app can be used.
7 months ago
James Braza 64938ae6f2
infra: unit testing `check_package_version` (#16825)
Wrote a unit test for `check_package_version` in the core package.

Note that this is a revival of
https://github.com/langchain-ai/langchain/pull/16387 after GitHub
incident (see
https://github.com/langchain-ai/langchain/discussions/16796).
7 months ago
Lingzhen Chen 30af711c34
community[patch]: update AzureSearch class to work with azure-search-documents=11.4.0 (#15659)
- **Description:** Updates
`libs/community/langchain_community/vectorstores/azuresearch.py` to
support the stable version `azure-search-documents=11.4.0`
- **Issue:** https://github.com/langchain-ai/langchain/issues/14534,
https://github.com/langchain-ai/langchain/issues/15039,
https://github.com/langchain-ai/langchain/issues/15355
  - **Dependencies:** azure-search-documents>=11.4.0

---------

Co-authored-by: Clément Tamines <Skar0@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Robby e135dc70c3
community[patch]: Invoke callback prior to yielding token (#17348)
**Description:** Invoke callback prior to yielding token in stream
method for Ollama.
**Issue:** [Callback for on_llm_new_token should be invoked before the
token is yielded by the model
#16913](https://github.com/langchain-ai/langchain/issues/16913)

Co-authored-by: Robby <h0rv@users.noreply.github.com>
7 months ago
Christophe Bornet ab025507bc
community[patch]: Add async methods to VectorStoreQATool (#16949) 7 months ago
Christophe Bornet fb7552bfcf
Add async methods to InMemoryCache (#17425)
Add async methods to InMemoryCache
7 months ago
Eugene Yurtsev 93472ee9e6
core[patch]: Replace memory stream implementation used by LogStreamCallbackHandler (#17185)
This PR replaces the memory stream implementation used by the 
LogStreamCallbackHandler.

This implementation resolves an issue in which streamed logs and
streamed events originating from sync code would arrive only after the
entire sync code would finish execution (rather than arriving in real
time as they're generated).

One example is if trying to stream tokens from an llm within a tool. If
the tool was an async tool, but the llm was invoked via stream (sync
variant) rather than astream (async variant), then the tokens would fail
to stream in real time and would all arrived bunched up after the tool
invocation completed.
7 months ago
yin1991 37ef6ac113
community[patch]: Add Pagination to GitHubIssuesLoader for Efficient GitHub Issues Retrieval (#16934)
- **Description:** Add Pagination to GitHubIssuesLoader for Efficient
GitHub Issues Retrieval
- **Issue:** [the issue # it fixes if
applicable,](https://github.com/langchain-ai/langchain/issues/16864)

---------

Co-authored-by: root <root@ip-172-31-46-160.ap-southeast-1.compute.internal>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Bagatur 22638e5927
community[patch]: give reranker default client val (#17289) 7 months ago
Robby ece4b43a81
community[patch]: doc loaders mypy fixes (#17368)
**Description:** Fixed `type: ignore`'s for mypy for some
document_loaders.
**Issue:** [Remove "type: ignore" comments #17048
](https://github.com/langchain-ai/langchain/issues/17048)

---------

Co-authored-by: Robby <h0rv@users.noreply.github.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
7 months ago
Robby 0653aa469a
community[patch]: Invoke callback prior to yielding token (#17346)
**Description:** Invoke callback prior to yielding token in stream
method for watsonx.
**Issue:** [Callback for on_llm_new_token should be invoked before the
token is yielded by the model
#16913](https://github.com/langchain-ai/langchain/issues/16913)

Co-authored-by: Robby <h0rv@users.noreply.github.com>
7 months ago
Bagatur f7e453971d
community[patch]: remove print (#17435) 7 months ago
Spencer Kelly 54fa78c887
community[patch]: fixed vector similarity filtering (#16967)
**Description:** changed filtering so that failed filter doesn't add
document to results. Currently filtering is entirely broken and all
documents are returned whether or not they pass the filter.

fixes issue introduced in
https://github.com/langchain-ai/langchain/pull/16190
7 months ago
Aditya a23c719c8b
google-genai[minor]: add safety settings (#16836)
Replace this entire comment with:
- **Description:Expose safety_settings for Gemini integrations on
google-generativeai
  - **Issue:NA,
  - **Dependencies:NA
  - **Twitter handle:@aditya_rane

@lkuligin for review

---------

Co-authored-by: adityarane@google.com <adityarane@google.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Abhijeeth Padarthi 584b647b96
community[minor]: AWS Athena Document Loader (#15625)
- **Description:** Adds the document loader for [AWS
Athena](https://aws.amazon.com/athena/), a serverless and interactive
analytics service.
  - **Dependencies:** Added boto3 as a dependency
7 months ago
david-tempelmann 93da18b667
community[minor]: Add mmr and similarity_score_threshold retrieval to DatabricksVectorSearch (#16829)
- **Description:** This PR adds support for `search_types="mmr"` and
`search_type="similarity_score_threshold"` to retrievers using
`DatabricksVectorSearch`,
  - **Issue:** 
  - **Dependencies:**
  - **Twitter handle:**

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Erick Friis 42648061ad
openai[patch]: code cleaning (#17355)
h/t @tdene for finding cleanup op in #17047
7 months ago
Massimiliano Pronesti 3894b4d9a5
community: add gpt-4-turbo and gpt-4-0125 costs (#17349)
Ref: https://openai.com/pricing
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7 months ago
Tomaz Bratanic 19a1c9183d
Improve graph cypher qa prompt (#17380)
Unlike vector results, the LLM has to completely trust the context of a
graph database result, even if it doesn't provide whole context. We
tried with instructions, but it seems that adding a single example is
the way to go to solve this issue.
7 months ago
Sandeep Banerjee 183daa6e6f
google-genai[patch]: on_llm_new_token fix (#16924)
### This pull request makes the following changes:
* Fixed issue #16913

Fixed the google gen ai chat_models.py code to make sure that the
callback is called before the token is yielded

<!-- Thank you for contributing to LangChain!

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---------

Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Bagatur 10c10f2dea
cli[patch]: integration template nits (#14691)
Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Erick Friis 99540d3d75
infra: no print in newer partner packages (#17353)
<!-- Thank you for contributing to LangChain!

Please title your PR "<package>: <description>", where <package> is
whichever of langchain, community, core, experimental, etc. is being
modified.

Replace this entire comment with:
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  - **Issue:** the issue # it fixes if applicable,
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of the package you've modified to check this locally.

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tests, lint, etc: https://python.langchain.com/docs/contributing/

If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
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2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.

If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
 -->
7 months ago
William FH 7c03cc5ed4
Support serialization when inputs/outputs contain generators (#17338)
Pydantic's `dict()` function raises an error here if you pass in a
generator. We have a more robust serialization function in lagnsmith
that we will use instead.
7 months ago
Erick Friis 3a2eb6e12b
infra: add print rule to ruff (#16221)
Added noqa for existing prints. Can slowly remove / will prevent more
being intro'd
7 months ago
Jael Gu c07c0da01a
community[patch]: Fix Milvus add texts when ids=None (#17021)
- **Description:** Fix Milvus add texts when ids=None (auto_id=True)

Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Quang Hoa 54c1fb3f25
community[patch]: Make some functions work with Milvus (#10695)
**Description**
Make some functions work with Milvus:
1. get_ids: Get primary keys by field in the metadata
2. delete: Delete one or more entities by ids
3. upsert: Update/Insert one or more entities

**Issue**
None
**Dependencies**
None
**Tag maintainer:**
@hwchase17 
**Twitter handle:**
None

---------

Co-authored-by: HoaNQ9 <hoanq.1811@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
kYLe c9999557bf
community[patch]: Modify LLMs/Anyscale work with OpenAI API v1 (#14206)
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- **Description:** 
1. Modify LLMs/Anyscale to work with OAI v1
2. Get rid of openai_ prefixed variables in Chat_model/ChatAnyscale
3. Modify `anyscale_api_base` to `anyscale_base_url` to follow OAI name
convention (reverted)

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Charlie Marsh 24c0bab57b
infra, multiple: Upgrade configuration for Ruff v0.2.0 (#16905)
## Summary

This PR upgrades LangChain's Ruff configuration in preparation for
Ruff's v0.2.0 release. (The changes are compatible with Ruff v0.1.5,
which LangChain uses today.) Specifically, we're now warning when
linter-only options are specified under `[tool.ruff]` instead of
`[tool.ruff.lint]`.

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Bagatur 01409add5a
google-vertexai[patch]: rm deps (#17077)
Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Erick Friis 1c2facf88d
nvidia-ai-endpoints[patch]: release 0.0.3 (#17345) 7 months ago
Vadim Kudlay 5f9ac6986e
nvidia-ai-endpoints[patch]: model arguments (e.g. temperature) on construction bug (#17290)
- **Issue:** Issue with model argument support (been there for a while
actually):
- Non-specially-handled arguments like temperature don't work when
passed through constructor.
- Such arguments DO work quite well with `bind`, but also do not abide
by field requirements.
- Since initial push, server-side error messages have gotten better and
v0.0.2 raises better exceptions. So maybe it's better to let server-side
handle such issues?
- **Description:**
- Removed ChatNVIDIA's argument fields in favor of
`model_kwargs`/`model_kws` arguments which aggregates constructor kwargs
(from constructor pathway) and merges them with call kwargs (bind
pathway).
- Shuffled a few functions from `_NVIDIAClient` to `ChatNVIDIA` to
streamline construction for future integrations.
- Minor/Optional: Old services didn't have stop support, so client-side
stopping was implemented. Now do both.
- **Any Breaking Changes:** Minor breaking changes if you strongly rely
on chat_model.temperature, etc. This is captured by
chat_model.model_kwargs.

PR passes tests and example notebooks and example testing. Still gonna
chat with some people, so leaving as draft for now.

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Leonid Ganeline 932c52c333
community[patch]: docstrings (#16810)
- added missed docstrings
- formated docstrings to the consistent form
7 months ago
Leonid Ganeline ae66bcbc10
core[patch]: docstring update (#16813)
- added missed docstrings
- formated docstrings to consistent form
7 months ago
Eugene Yurtsev e10030e241
core[patch]: Add unit test to cover different streaming format for json parsing (#17063)
Add unit test to cover this issue:

https://github.com/langchain-ai/langchain/issues/16423

which was resolved by this PR:

https://github.com/langchain-ai/langchain/pull/16670/files

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Kononov Pavel 15bc201967
langchain_community: Fix typo bug (#17324)
Problem from #17095

This error wasn't in the v1.4.0
7 months ago
Erick Friis e660a1685b
google-genai[patch]: release 0.0.8 (#17285) 7 months ago
Erick Friis febf9540b9
google-genai[patch]: fix tool format, use protos (#17284) 7 months ago
German Martin 1032faba5f
langchain_google_genai : Add missing _identifying_params property. (#17224)
Description: Missing _identifying_params create issues when dealing with
callbacks to get current run model parameters.
All other model partners implementation provide this property and also
provide _default_params. I'm not sure about the default values to
include or if we can re-use the same as for _VertexAICommon(), this
change allows you to access the model parameters correctly.
Issue: Not exactly this issue but could be related
https://github.com/langchain-ai/langchain/issues/14711
Twitter handle:@musicaoriginal2
7 months ago
Erick Friis e4da7918f3
google-genai[patch]: fix streaming, function calling (#17268) 7 months ago
Ruben Hakopian 96b5711a0c
google-vertexai[patch]: Fixed SafetySettings handling in streaming API in VertexAI (#17278)
The streaming API doesn't separate safety_settings from the
generation_config payload. As the result the following error is observed
when using `stream` API. The functionality is correct with `invoke` API.

The fix separates the `safety_settings` from params and sets it as
argument to the `send_message` method.

```
ERROR:         Unknown field for GenerationConfig: safety_settings
Traceback (most recent call last):
  File "/Users/user/Library/Caches/pypoetry/virtualenvs/chatbot-worker-main-Ju-qIM-X-py3.12/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py", line 250, in stream
    raise e
  File "/Users/user/Library/Caches/pypoetry/virtualenvs/chatbot-worker-main-Ju-qIM-X-py3.12/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py", line 234, in stream
    for chunk in self._stream(
  File "/Users/user/Library/Caches/pypoetry/virtualenvs/chatbot-worker-main-Ju-qIM-X-py3.12/lib/python3.12/site-packages/langchain_google_vertexai/chat_models.py", line 501, in _stream
    for response in responses:
  File "/Users/user/Library/Caches/pypoetry/virtualenvs/chatbot-worker-main-Ju-qIM-X-py3.12/lib/python3.12/site-packages/vertexai/generative_models/_generative_models.py", line 921, in _send_message_streaming
    for chunk in stream:
  File "/Users/user/Library/Caches/pypoetry/virtualenvs/chatbot-worker-main-Ju-qIM-X-py3.12/lib/python3.12/site-packages/vertexai/generative_models/_generative_models.py", line 514, in _generate_content_streaming
    request = self._prepare_request(
              ^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/user/Library/Caches/pypoetry/virtualenvs/chatbot-worker-main-Ju-qIM-X-py3.12/lib/python3.12/site-packages/vertexai/generative_models/_generative_models.py", line 256, in _prepare_request
    gapic_generation_config = gapic_content_types.GenerationConfig(
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/user/Library/Caches/pypoetry/virtualenvs/chatbot-worker-main-Ju-qIM-X-py3.12/lib/python3.12/site-packages/proto/message.py", line 576, in __init__
    raise ValueError(
ValueError: Unknown field for GenerationConfig: safety_settings
```

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Bagatur 65e97c9b53
infra: mv SQLDatabase tests to community (#17276) 7 months ago
Bagatur 72c7af0bc0
langchain[patch]: undo redis cache import (#17275) 7 months ago
Bagatur 8bad4157ad
langchain[patch]: Release 0.1.6 (#17133) 7 months ago
Bagatur 7fa4dc593f
core[patch]: Release 0.1.22 (#17274) 7 months ago
Bagatur 02ef9164b5
langchain[patch]: expose cohere rerank score, add parent doc param (#16887) 7 months ago
Bagatur 35c1bf339d
infra: rm boto3, gcaip from pyproject (#17270) 7 months ago
Alex de5e96b5f9
community[patch]: updated openai prices in mapping (#17009)
- **Description:** there are january prices update for chatgpt
[blog](https://openai.com/blog/new-embedding-models-and-api-updates),
also there are updates on their website on page
[pricing](https://openai.com/pricing)
- **Issue:** N/A

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Mohammad Mohtashim e35c7fa3b2
[Langchain_core]: Added Docstring for RunnableConfigurableAlternatives (#17263)
I noticed that RunnableConfigurableAlternatives which is an important
composition in LCEL has no Docstring. Therefore I added the detailed
Docstring for it.
@baskaryan, @eyurtsev, @hwchase17 please have a look and let me if the
docstring is looking good.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Armin Stepanyan 641efcf41c
community: add runtime kwargs to HuggingFacePipeline (#17005)
This PR enables changing the behaviour of huggingface pipeline between
different calls. For example, before this PR there's no way of changing
maximum generation length between different invocations of the chain.
This is desirable in cases, such as when we want to scale the maximum
output size depending on a dynamic prompt size.

Usage example:

```python
from langchain_community.llms.huggingface_pipeline import HuggingFacePipeline
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

model_id = "gpt2"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
hf = HuggingFacePipeline(pipeline=pipe)

hf("Say foo:", pipeline_kwargs={"max_new_tokens": 42})
```

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Scott Nath a32798abd7
community: Add you.com utility, update you retriever integration docs (#17014)
<!-- Thank you for contributing to LangChain!

Please title your PR "<package>: <description>", where <package> is
whichever of langchain, community, core, experimental, etc. is being
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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,
- **Twitter handle:** we announce bigger features on Twitter. If your PR
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1. a test for the integration, preferably unit tests that do not rely on
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2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.

If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
 -->

- **Description: changes to you.com files** 
    - general cleanup
- adds community/utilities/you.py, moving bulk of code from retriever ->
utility
    - removes `snippet` as endpoint
    - adds `news` as endpoint
    - adds more tests

<s>**Description: update community MAKE file** 
    - adds `integration_tests`
    - adds `coverage`</s>

- **Issue:** the issue # it fixes if applicable,
- [For New Contributors: Update Integration
Documentation](https://github.com/langchain-ai/langchain/issues/15664#issuecomment-1920099868)
- **Dependencies:** n/a
- **Twitter handle:** @scottnath
- **Mastodon handle:** scottnath@mastodon.social

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
joelsprunger 3984f6604f
langchain: adds recursive json splitter (#17144)
- **Description:** This adds a recursive json splitter class to the
existing text_splitters as well as unit tests
- **Issue:** splitting text from structured data can cause issues if you
have a large nested json object and you split it as regular text you may
end up losing the structure of the json. To mitigate against this you
can split the nested json into large chunks and overlap them, but this
causes unnecessary text processing and there will still be times where
the nested json is so big that the chunks get separated from the parent
keys.

As an example you wouldn't want the following to be split in half:
```shell
{'val0': 'DFWeNdWhapbR',
 'val1': {'val10': 'QdJo',
          'val11': 'FWSDVFHClW',
          'val12': 'bkVnXMMlTiQh',
          'val13': 'tdDMKRrOY',
          'val14': 'zybPALvL',
          'val15': 'JMzGMNH',
          'val16': {'val160': 'qLuLKusFw',
                    'val161': 'DGuotLh',
                    'val162': 'KztlcSBropT',
-----------------------------------------------------------------------split-----
                    'val163': 'YlHHDrN',
                    'val164': 'CtzsxlGBZKf',
                    'val165': 'bXzhcrWLmBFp',
                    'val166': 'zZAqC',
                    'val167': 'ZtyWno',
                    'val168': 'nQQZRsLnaBhb',
                    'val169': 'gSpMbJwA'},
          'val17': 'JhgiyF',
          'val18': 'aJaqjUSFFrI',
          'val19': 'glqNSvoyxdg'}}
```
Any llm processing the second chunk of text may not have the context of
val1, and val16 reducing accuracy. Embeddings will also lack this
context and this makes retrieval less accurate.

Instead you want it to be split into chunks that retain the json
structure.
```shell
{'val0': 'DFWeNdWhapbR',
 'val1': {'val10': 'QdJo',
          'val11': 'FWSDVFHClW',
          'val12': 'bkVnXMMlTiQh',
          'val13': 'tdDMKRrOY',
          'val14': 'zybPALvL',
          'val15': 'JMzGMNH',
          'val16': {'val160': 'qLuLKusFw',
                    'val161': 'DGuotLh',
                    'val162': 'KztlcSBropT',
                    'val163': 'YlHHDrN',
                    'val164': 'CtzsxlGBZKf'}}}
```
and
```shell
{'val1':{'val16':{
                    'val165': 'bXzhcrWLmBFp',
                    'val166': 'zZAqC',
                    'val167': 'ZtyWno',
                    'val168': 'nQQZRsLnaBhb',
                    'val169': 'gSpMbJwA'},
          'val17': 'JhgiyF',
          'val18': 'aJaqjUSFFrI',
          'val19': 'glqNSvoyxdg'}}
```
This recursive json text splitter does this. Values that contain a list
can be converted to dict first by using split(... convert_lists=True)
otherwise long lists will not be split and you may end up with chunks
larger than the max chunk.

In my testing large json objects could be split into small chunks with 
   Increased question answering accuracy
 The ability to split into smaller chunks meant retrieval queries can
use fewer tokens


- **Dependencies:** json import added to text_splitter.py, and random
added to the unit test
  - **Twitter handle:** @joelsprunger

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
7 months ago
Leonid Kuligin 1862900078
google-genai[patch]: added parsing of function call / response (#17245) 7 months ago
Cailin Wang a210a8bc53
langchain[patch]: Fix create_retriever_tool missing on_retriever_end Document content (#16933)
- **Description:** In create_retriever_tool create_tool, fix
create_retriever_tool's missing Document content for on_retriever_end,
caused by create_retriever_tool's missing callbacks parameter,
  - **Twitter handle:** @CailinWang_

---------

Co-authored-by: root <root@Bluedot-AI>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Sparsh Jain a2167614b7
google-genai[patch]: Invoke callback prior to yielding token (#17092)
- **Description:** Invoke callback prior to yielding token in stream and
astream methods for Google-genai,
  - **Issue:** the issue # 16913,
  - **Twitter handle:** Sparsh10649446

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
7 months ago
Liang Zhang 7306600e2f
community[patch]: Support SerDe transform functions in Databricks LLM (#16752)
**Description:** Databricks LLM does not support SerDe the
transform_input_fn and transform_output_fn. After saving and loading,
the LLM will be broken. This PR serialize these functions into a hex
string using pickle, and saving the hex string in the yaml file. Using
pickle to serialize a function can be flaky, but this is a simple
workaround that unblocks many use cases. If more sophisticated SerDe is
needed, we can improve it later.

Test:
Added a simple unit test.
I did manual test on Databricks and it works well.
The saved yaml looks like:
```
llm:
      _type: databricks
      cluster_driver_port: null
      cluster_id: null
      databricks_uri: databricks
      endpoint_name: databricks-mixtral-8x7b-instruct
      extra_params: {}
      host: e2-dogfood.staging.cloud.databricks.com
      max_tokens: null
      model_kwargs: null
      n: 1
      stop: null
      task: null
      temperature: 0.0
      transform_input_fn: 80049520000000000000008c085f5f6d61696e5f5f948c0f7472616e73666f726d5f696e7075749493942e
      transform_output_fn: null
```

@baskaryan

```python
from langchain_community.embeddings import DatabricksEmbeddings
from langchain_community.llms import Databricks
from langchain.chains import RetrievalQA
from langchain.document_loaders import TextLoader
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import FAISS
import mlflow

embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en")

def transform_input(**request):
  request["messages"] = [
    {
      "role": "user",
      "content": request["prompt"]
    }
  ]
  del request["prompt"]
  return request

llm = Databricks(endpoint_name="databricks-mixtral-8x7b-instruct", transform_input_fn=transform_input)

persist_dir = "faiss_databricks_embedding"

# Create the vector db, persist the db to a local fs folder
loader = TextLoader("state_of_the_union.txt")
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
docs = text_splitter.split_documents(documents)
db = FAISS.from_documents(docs, embeddings)
db.save_local(persist_dir)

def load_retriever(persist_directory):
    embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en")
    vectorstore = FAISS.load_local(persist_directory, embeddings)
    return vectorstore.as_retriever()

retriever = load_retriever(persist_dir)
retrievalQA = RetrievalQA.from_llm(llm=llm, retriever=retriever)
with mlflow.start_run() as run:
    logged_model = mlflow.langchain.log_model(
        retrievalQA,
        artifact_path="retrieval_qa",
        loader_fn=load_retriever,
        persist_dir=persist_dir,
    )

# Load the retrievalQA chain
loaded_model = mlflow.pyfunc.load_model(logged_model.model_uri)
print(loaded_model.predict([{"query": "What did the president say about Ketanji Brown Jackson"}]))

```
7 months ago
cjpark-data ce22e10c4b
community[patch]: Fix KeyError 'embedding' (MongoDBAtlasVectorSearch) (#17178)
- **Description:**
Embedding field name was hard-coded named "embedding".
So I suggest that change `res["embedding"]` into
`res[self._embedding_key]`.
  - **Issue:** #17177,
- **Twitter handle:**
[@bagcheoljun17](https://twitter.com/bagcheoljun17)
7 months ago
Neli Hateva 9bb5157a3d
langchain[patch], community[patch]: Fixes in the Ontotext GraphDB Graph and QA Chain (#17239)
- **Description:** Fixes in the Ontotext GraphDB Graph and QA Chain
related to the error handling in case of invalid SPARQL queries, for
which `prepareQuery` doesn't throw an exception, but the server returns
400 and the query is indeed invalid
  - **Issue:** N/A
  - **Dependencies:** N/A
  - **Twitter handle:** @OntotextGraphDB
7 months ago
ByeongUk Choi b88329e9a5
community[patch]: Implement Unique ID Enforcement in FAISS (#17244)
**Description:**
Implemented unique ID validation in the FAISS component to ensure all
document IDs are distinct. This update resolves issues related to
non-unique IDs, such as inconsistent behavior during deletion processes.
7 months ago
Bagatur 852973d616
langchain[minor], core[minor]: update json, pydantic parser. add openai-json structured output runnable (#16914) 7 months ago
hsuyuming e22c4d4eb0
google-vertexai[patch]: fix _parse_response_candidate issue (#16647)
**Description:** enable _parse_response_candidate to support complex
structure format.
  **Issue:** 
currently, if Gemini response complex args format, people will get
"TypeError: Object of type RepeatedComposite is not JSON serializable"
error from _parse_response_candidate.
  
 response candidate example
```
content {
  role: "model"
  parts {
    function_call {
      name: "Information"
      args {
        fields {
          key: "people"
          value {
            list_value {
              values {
                string_value: "Joe is 30, his mom is Martha"
              }
            }
          }
        }
      }
    }
  }
}
finish_reason: STOP
safety_ratings {
  category: HARM_CATEGORY_HARASSMENT
  probability: NEGLIGIBLE
}
safety_ratings {
  category: HARM_CATEGORY_HATE_SPEECH
  probability: NEGLIGIBLE
}
safety_ratings {
  category: HARM_CATEGORY_SEXUALLY_EXPLICIT
  probability: NEGLIGIBLE
}
safety_ratings {
  category: HARM_CATEGORY_DANGEROUS_CONTENT
  probability: NEGLIGIBLE
}
```
 
error msg:
```
Traceback (most recent call last):
  File "/home/jupyter/user/abehsu/gemini_langchain_tools/example2.py", line 36, in <module>
    print(tagging_chain.invoke({"input": "Joe is 30, his mom is Martha"}))
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 2053, in invoke
    input = step.invoke(
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 3887, in invoke
    return self.bound.invoke(
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py", line 165, in invoke
    self.generate_prompt(
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py", line 543, in generate_prompt
    return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs)
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py", line 407, in generate
    raise e
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py", line 397, in generate
    self._generate_with_cache(
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py", line 576, in _generate_with_cache
    return self._generate(
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_google_vertexai/chat_models.py", line 406, in _generate
    generations = [
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_google_vertexai/chat_models.py", line 408, in <listcomp>
    message=_parse_response_candidate(c),
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/site-packages/langchain_google_vertexai/chat_models.py", line 280, in _parse_response_candidate
    function_call["arguments"] = json.dumps(
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/json/__init__.py", line 231, in dumps
    return _default_encoder.encode(obj)
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/json/encoder.py", line 199, in encode
    chunks = self.iterencode(o, _one_shot=True)
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/json/encoder.py", line 257, in iterencode
    return _iterencode(o, 0)
  File "/opt/conda/envs/gemini_langchain_tools/lib/python3.10/json/encoder.py", line 179, in default
    raise TypeError(f'Object of type {o.__class__.__name__} '
TypeError: Object of type RepeatedComposite is not JSON serializable
```
  

  **Twitter handle:**  @abehsu1992626
7 months ago
Erick Friis d77bb7b4e9
google-vertexai[patch]: integration test fix, release 0.0.5 (#17258) 7 months ago
Aditya 98176ac982
langchain_google_vertexai : added logic to override get_num_tokens_from_messages() for ChatVertexAI (#16784)
<!-- Thank you for contributing to LangChain!

Replace this entire comment with:
- **Description: added logic to override get_num_tokens_from_messages()
for ChatVertexAI. Currently ChatVertexAI was inheriting
get_num_tokens_from_messages() from BaseChatModel which in-turn was
calling GPT-2 tokenizer
  - **Issue: NA
  - **Dependencies: NA
  - **Twitter handle:@aditya_rane

@lkuligin for review

---------

Co-authored-by: adityarane@google.com <adityarane@google.com>
Co-authored-by: Leonid Kuligin <lkuligin@yandex.ru>
7 months ago
Bassem Yacoube 4e3ed7f043
community[patch]: octoai embeddings bug fix (#17216)
fixes a bug in octoa_embeddings provider
7 months ago
Eugene Yurtsev 780e84ae79
community[minor]: SQLDatabase Add fetch mode `cursor`, query parameters, query by selectable, expose execution options, and documentation (#17191)
- **Description:** Improve `SQLDatabase` adapter component to promote
code re-use, see
[suggestion](https://github.com/langchain-ai/langchain/pull/16246#pullrequestreview-1846590962).
  - **Needed by:** GH-16246
  - **Addressed to:** @baskaryan, @cbornet 

## Details
- Add `cursor` fetch mode
- Accept SQL query parameters
- Accept both `str` and SQLAlchemy selectables as query expression
- Expose `execution_options`
- Documentation page (notebook) about `SQLDatabase` [^1]
See [About
SQLDatabase](https://github.com/langchain-ai/langchain/blob/c1c7b763/docs/docs/integrations/tools/sql_database.ipynb).

[^1]: Apparently there hasn't been any yet?

---------

Co-authored-by: Andreas Motl <andreas.motl@crate.io>
7 months ago
Tomaz Bratanic 7e4b676d53
community[patch]: Better error propagation for neo4jgraph (#17190)
There are other errors that could happen when refreshing the schema, so
we want to propagate specific errors for more clarity
7 months ago
Luiz Ferreira 34d2daffb3
community[patch]: Fix chat openai unit test (#17124)
- **Description:** 
Actually the test named `test_openai_apredict` isn't testing the
apredict method from ChatOpenAI.
  - **Twitter handle:**
  https://twitter.com/OAlmofadas
7 months ago
Dmitry Kankalovich f92738a6f6
langchain[minor], community[minor], core[minor]: Async Cache support and AsyncRedisCache (#15817)
* This PR adds async methods to the LLM cache. 
* Adds an implementation using Redis called AsyncRedisCache.
* Adds a docker compose file at the /docker to help spin up docker
* Updates redis tests to use a context manager so flushing always happens by default
7 months ago
Erick Friis 4153837502
google-genai[patch]: release 0.0.7 (#17193) 7 months ago
Erick Friis 927ab77d6e
google-genai[patch]: no error for FunctionMessage (#17215)
Both should eventually match this:
https://github.com/langchain-ai/langchain/blob/master/libs/partners/google-vertexai/langchain_google_vertexai/chat_models.py#L179

But seems undocumented / can't find types in genai package
7 months ago
Erick Friis 2ecf318218
google-genai[patch]: match function call interface (#17213)
should match vertex
7 months ago
Erick Friis e17173c403
google-vertexai[patch]: function calling integration test (#17209) 7 months ago
Erick Friis 52be84a603
google-vertexai[patch]: serializable citation metadata, release 0.0.4 (#17145)
was breaking in langserve before
7 months ago
Nuno Campos 19ff81e74f
Fix stream events/log with some kinds of non addable output (#17205)
<!-- Thank you for contributing to LangChain!

Please title your PR "<package>: <description>", where <package> is
whichever of langchain, community, core, experimental, etc. is being
modified.

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,
- **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` from the root
of the package you've modified to check this locally.

See contribution guidelines for more information on how to write/run
tests, lint, etc: https://python.langchain.com/docs/contributing/

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.

If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
 -->
7 months ago
Bagatur 6f1403b9b6
community[patch]: Release 0.0.19 (#17207)
Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Erick Friis a13dc47a08
cli[patch]: copyright 2024 default (#17204) 7 months ago
Bagatur 00757567ba
core[patch]: Release 0.1.21 (#17202) 7 months ago
Bagatur af74301ab9
core[patch], community[patch]: link extraction continue on failure (#17200) 7 months ago
Henry 2281f00198
langchain: Standardize `output_parser.py` across all agent types for custom `FORMAT_INSTRUCTIONS` (#17168)
- **Description:** 
This PR standardizes the `output_parser.py` file across all agent types
to ensure a uniform parsing mechanism is implemented. It introduces a
cohesive structure and common interface for output parsing, facilitating
easier modifications and extensions by users. The standardized approach
enhances maintainability and scalability of the codebase by providing a
consistent pattern for output parsing, which can be easily understood
and utilized across different agent types.

This PR builds upon the foundation set by a previously merged PR, which
focused exclusively on standardizing the `output_parser.py` for the
`conversational_agent` ([PR
#16945](https://github.com/langchain-ai/langchain/pull/16945)). With
this new update, I extend the standardization efforts to encompass
`output_parser.py` files across all agent types. This enhancement not
only unifies the parsing mechanism across the board but also introduces
the flexibility for users to incorporate custom `FORMAT_INSTRUCTIONS`.

  - **Issue:** 
https://github.com/langchain-ai/langchain/issues/10721
https://github.com/langchain-ai/langchain/issues/4044

  - **Dependencies:**
No new dependencies required for this change

  - **Twitter handle:**
With my github user is enough. Thanks

I hope you accept my PR.
7 months ago
Bagatur 78409634fe
core[patch]: Release 0.1.20 (#17194) 7 months ago
Nuno Campos 65798289a4
core[minor]: Use batched tracing in sdk (#16305)
Remove threadpool executor usage in langchain tracer, this is now
handled by sdk
7 months ago
chyroc f87b38a559
google-genai[minor]: support functions call (#15146)
Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Tomaz Bratanic 302989a2b1
allow optional newline in the action responses of JSON Agent parser (#17186)
Based on my experiments, the newline isn't always there, so we can make
the regex slightly more robust by allowing an optional newline after the
bacticks
7 months ago
William FH 9fa07076da
Add trace_as_chain_group metadata (#17187) 7 months ago
Erick Friis 3e58df43c2
mistralai[patch]: release 0.0.4 (#17139) 7 months ago
Erick Friis 22b6a03a28
infra: read min versions (#17135) 7 months ago
Erick Friis f881a3330c
mistralai[patch]: 16k token batching logic embed (#17136) 7 months ago
Bagatur 226f376d59
community[patch]: Release 0.0.18 (#17129)
Co-authored-by: Erick Friis <erick@langchain.dev>
7 months ago
Erick Friis 980e30c361
nvidia-ai-endpoints[patch]: release 0.0.2 (#17125) 7 months ago
Erick Friis 15bd1154a7
pinecone[patch]: integration test new namespace (#17121) 7 months ago
Mikhail Khludnev 14ff1438e6
nvidia-trt[patch]: propagate InferenceClientException to the caller. (#16936)
- **Description:**  
 
before the change I've got

1. propagate InferenceClientException to the caller.
2. stop grpc receiver thread on exception 

```
        for token in result_queue:
>           result_str += token
E           TypeError: can only concatenate str (not "InferenceServerException") to str

../../langchain_nvidia_trt/llms.py:207: TypeError
```
And stream thread keeps running. 

after the change request thread stops correctly and caller got a root
cause exception:

```
E                   tritonclient.utils.InferenceServerException: [request id: 4529729] expected number of inputs between 2 and 3 but got 10 inputs for model 'vllm_model'

../../langchain_nvidia_trt/llms.py:205: InferenceServerException
```

  - **Issue:** the issue # it fixes if applicable,
  - **Dependencies:** any dependencies required for this change,
  - **Twitter handle:** [t.me/mkhl_spb](https://t.me/mkhl_spb)
 
I'm not sure about test coverage. Should I setup deep mocks or there's a
kind of triton stub via testcontainers or so.
7 months ago