**Issue:** Added support for creating indexes in the SAP HANA Vector
engine.
**Changes**:
1. Introduced a new function `create_hnsw_index` in `hanavector.py` that
enables the creation of indexes for SAP HANA Vector.
2. Added integration tests for the index creation function to ensure
functionality.
3. Updated the documentation to reflect the new index creation feature,
including examples and output from the notebook.
4. Fix the operator issue in ` _process_filter_object` function and
change the array argument to a placeholder in the similarity search SQL
statement.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description**:
> Without an API key, any site (IP address) posting more than 3 requests
per second to the E-utilities will receive an error message. By
including an API key, a site can post up to 10 requests per second by
default.
quoted from A General Introduction to the E-utilities,NCBI :
https://www.ncbi.nlm.nih.gov/books/NBK25497/
I have simply added a api_key parameter to the PubMedAPIWrapper that can
be used to increase the number of requests per second from 3 to 10.
**Twitter handle** : @KORmaori
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Updated the kwargs for the structured query from
filters to filter due to deprecation of 'filters' for Databricks Vector
Search. Also changed the error messages as the allowed operators and
comparators are different which can cause issues with functions such as
get_query_constructor_prompt()
- **Issue:** Fixes the Key Error for filters due to deprecation in favor
for 'filter':
LangChainDeprecationWarning: DatabricksVectorSearch received a key
`filters` in search_kwargs. `filters` was deprecated since
langchain-community 0.2.11 and will be removed in 0.3. Please use
`filter` instead.
- **Dependencies:** N/A
- **Twitter handle:** N/A
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- [x] **PR title**: "community: add Needle retriever and document loader
integration"
- Where "package" is whichever of langchain, community, core, etc. is
being modified. Use "docs: ..." for purely docs changes, "infra: ..."
for CI changes.
- Example: "community: add foobar LLM"
- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** This PR adds a new integration for Needle, which
includes:
- **NeedleRetriever**: A retriever for fetching documents from Needle
collections.
- **NeedleLoader**: A document loader for managing and loading documents
into Needle collections.
- Example notebooks demonstrating usage have been added in:
- `docs/docs/integrations/retrievers/needle.ipynb`
- `docs/docs/integrations/document_loaders/needle.ipynb`.
- **Dependencies:** The `needle-python` package is required as an
external dependency for accessing Needle's API. It has been added to the
extended testing dependencies list.
- **Twitter handle:** Feel free to mention me if this PR gets announced:
[needlexai](https://x.com/NeedlexAI).
- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. Unit tests have been added for both `NeedleRetriever` and
`NeedleLoader` in `libs/community/tests/unit_tests`. These tests mock
API calls to avoid relying on network access.
2. Example notebooks have been added to `docs/docs/integrations/`,
showcasing both retriever and loader functionality.
- [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/
- `make format`: Passed
- `make lint`: Passed
- `make test`: Passed (requires `needle-python` to be installed locally;
this package is not added to LangChain dependencies).
Additional guidelines:
- [x] Optional dependencies are imported only within functions.
- [x] No dependencies have been added to pyproject.toml files except for
those required for unit tests.
- [x] The PR does not touch more than one package.
- [x] Changes are fully backwards compatible.
- [x] Community additions are not re-imported into LangChain core.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR updates the Pinecone client to `5.4.0`, as well as its
dependencies (`pinecone-plugin-inference` and
`pinecone-plugin-interface`).
Note: `pinecone-client` is now simply called `pinecone`.
**Question for reviewer(s):** should this PR also update the `pinecone`
dep in [the root dir's `poetry.lock`
file](https://github.com/langchain-ai/langchain/blob/master/poetry.lock#L6729)?
Was unsure. (I don't believe so b/c it seems pinned to a lower version
likely based on 3rd-party deps (e.g. Unstructured).)
--
TW: @audrey_sage_
---
- To see the specific tasks where the Asana app for GitHub is being
used, see below:
- https://app.asana.com/0/0/1208693659122374
Follows on from #27991, updates the langchain-community package to
support numpy 2 versions
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description:** When an OpenAI assistant is invoked, it creates a run
by default, allowing users to set only a few request fields. The
truncation strategy is set to auto, which includes previous messages in
the thread along with the current question until the context length is
reached. This causes token usage to grow incrementally:
consumed_tokens = previous_consumed_tokens + current_consumed_tokens.
This PR adds support for user-defined truncation strategies, giving
better control over token consumption.
**Issue:** High token consumption.
- **Description:** `add_texts` was using `get_setting` for marqo client
which was being used according to 1.5.x API version. However, this PR
updates the `add_text` accounting for updated response payload for 2.x
and later while maintaining backward compatibility. Plus I have verified
this was the only place where marqo client was not accounting for
updated API version.
- **Issue:** #28323
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
Adds deprecation notices for Neo4j components moving to the
`langchain_neo4j` partner package.
- Adds deprecation warnings to all Neo4j-related classes and functions
that have been migrated to the new `langchain_neo4j` partner package
- Updates documentation to reference the new `langchain_neo4j` package
instead of `langchain_community`
**Description:**
Currently, the docstring for `LanceDB.__init__()` provides the default
value for `mode`, but not the list of valid values. This PR adds that
list to the docstring.
**Issue:**
N/A
**Dependencies:**
N/A
**Twitter handle:**
`@metadaddy`
[Leaving as a reminder: If no one reviews your PR within a few days,
please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda,
hwchase17.]
Fixed a compatibility issue in the `load_messages_from_context()`
function for the Kinetica chat model integration. The issue was caused
by stricter validation introduced in Pydantic 2.
In collaboration with @rlouf I build an
[outlines](https://dottxt-ai.github.io/outlines/latest/) integration for
langchain!
I think this is really useful for doing any type of structured output
locally.
[Dottxt](https://dottxt.co) spend alot of work optimising this process
at a lower level
([outlines-core](https://pypi.org/project/outlines-core/0.1.14/) written
in rust) so I think this is a better alternative over all current
approaches in langchain to do structured output.
It also implements the `.with_structured_output` method so it should be
a drop in replacement for a lot of applications.
The integration includes:
- **Outlines LLM class**
- **ChatOutlines class**
- **Tutorial Cookbooks**
- **Documentation Page**
- **Validation and error messages**
- **Exposes Outlines Structured output features**
- **Support for multiple backends**
- **Integration and Unit Tests**
Dependencies: `outlines` + additional (depending on backend used)
I am not sure if the unit-tests comply with all requirements, if not I
suggest to just remove them since I don't see a useful way to do it
differently.
### Quick overview:
Chat Models:
<img width="698" alt="image"
src="https://github.com/user-attachments/assets/05a499b9-858c-4397-a9ff-165c2b3e7acc">
Structured Output:
<img width="955" alt="image"
src="https://github.com/user-attachments/assets/b9fcac11-d3e5-4698-b1ae-8c4cb3d54c45">
---------
Co-authored-by: Vadym Barda <vadym@langchain.dev>
- **Description:** We have released the
[langchain-gigachat](https://github.com/ai-forever/langchain-gigachat?tab=readme-ov-file)
with new GigaChat integration that support's function/tool calling. This
PR deprecated legacy GigaChat class in community package.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for reading my first PR!
**Description:**
Deduplicate content in AzureSearch vectorstore.
Currently, by default, the content of the retrieval is placed both in
metadata and page_content of a Document.
This PR removes the content from metadata, and leaves it in
page_content.
**Issue:**:
Previously, the content was popped from result before metadata was
populated.
In #25828 , the order was changed which leads to a response with
duplicated content.
This was not the intention of that PR and seems undesirable.
Looking forward to seeing my contribution in the next version!
Cheers,
Renzo
**Description:** Add tool calling and structured output support for
SambaNovaCloud chat models, docs included
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
# Description
- adding stopReason to response_metadata to call stream and astream
- excluding NCP_APIGW_API_KEY input required validation
- to remove warning Field "model_name" has conflict with protected
namespace "model_".
cc. @vbarda
Description:
* Updated the OpenSearchVectorStore to use the `engine` parameter
captured at `init()` time as the default when adding documents to the
store.
Formatted, Linted, and Tested.
Last week Anthropic released version 0.39.0 of its python sdk, which
enabled support for Python 3.13. This release deleted a legacy
`client.count_tokens` method, which we currently access during init of
the `Anthropic` LLM. Anthropic has replaced this functionality with the
[client.beta.messages.count_tokens()
API](https://github.com/anthropics/anthropic-sdk-python/pull/726).
To enable support for `anthropic >= 0.39.0` and Python 3.13, here we
drop support for the legacy token counting method, and add support for
the new method via `ChatAnthropic.get_num_tokens_from_messages`.
To fully support the token counting API, we update the signature of
`get_num_tokens_from_message` to accept tools everywhere.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Description:
* When working with OpenSearchVectorSearch to make
OpenSearchGraphVectorStore (coming soon), I noticed that there wasn't
type hinting for the underlying OpenSearch clients. This fixes that
issue.
* Confirmed tests are still passing with code changes.
Note that there is some additional code duplication now, but I think
this approach is cleaner overall.
## Description
As proposed in our earlier discussion #26977 we have introduced a Google
Books API Tool that leverages the Google Books API found at
[https://developers.google.com/books/docs/v1/using](https://developers.google.com/books/docs/v1/using)
to generate book recommendations.
### Sample Usage
```python
from langchain_community.tools import GoogleBooksQueryRun
from langchain_community.utilities import GoogleBooksAPIWrapper
api_wrapper = GoogleBooksAPIWrapper()
tool = GoogleBooksQueryRun(api_wrapper=api_wrapper)
tool.run('ai')
```
### Sample Output
```txt
Here are 5 suggestions based off your search for books related to ai:
1. "AI's Take on the Stigma Against AI-Generated Content" by Sandy Y. Greenleaf: In a world where artificial intelligence (AI) is rapidly advancing and transforming various industries, a new form of content creation has emerged: AI-generated content. However, despite its potential to revolutionize the way we produce and consume information, AI-generated content often faces a significant stigma. "AI's Take on the Stigma Against AI-Generated Content" is a groundbreaking book that delves into the heart of this issue, exploring the reasons behind the stigma and offering a fresh, unbiased perspective on the topic. Written from the unique viewpoint of an AI, this book provides readers with a comprehensive understanding of the challenges and opportunities surrounding AI-generated content. Through engaging narratives, thought-provoking insights, and real-world examples, this book challenges readers to reconsider their preconceptions about AI-generated content. It explores the potential benefits of embracing this technology, such as increased efficiency, creativity, and accessibility, while also addressing the concerns and drawbacks that contribute to the stigma. As you journey through the pages of this book, you'll gain a deeper understanding of the complex relationship between humans and AI in the realm of content creation. You'll discover how AI can be used as a tool to enhance human creativity, rather than replace it, and how collaboration between humans and machines can lead to unprecedented levels of innovation. Whether you're a content creator, marketer, business owner, or simply someone curious about the future of AI and its impact on our society, "AI's Take on the Stigma Against AI-Generated Content" is an essential read. With its engaging writing style, well-researched insights, and practical strategies for navigating this new landscape, this book will leave you equipped with the knowledge and tools needed to embrace the AI revolution and harness its potential for success. Prepare to have your assumptions challenged, your mind expanded, and your perspective on AI-generated content forever changed. Get ready to embark on a captivating journey that will redefine the way you think about the future of content creation.
Read more at https://play.google.com/store/books/details?id=4iH-EAAAQBAJ&source=gbs_api
2. "AI Strategies For Web Development" by Anderson Soares Furtado Oliveira: From fundamental to advanced strategies, unlock useful insights for creating innovative, user-centric websites while navigating the evolving landscape of AI ethics and security Key Features Explore AI's role in web development, from shaping projects to architecting solutions Master advanced AI strategies to build cutting-edge applications Anticipate future trends by exploring next-gen development environments, emerging interfaces, and security considerations in AI web development Purchase of the print or Kindle book includes a free PDF eBook Book Description If you're a web developer looking to leverage the power of AI in your projects, then this book is for you. Written by an AI and ML expert with more than 15 years of experience, AI Strategies for Web Development takes you on a transformative journey through the dynamic intersection of AI and web development, offering a hands-on learning experience.The first part of the book focuses on uncovering the profound impact of AI on web projects, exploring fundamental concepts, and navigating popular frameworks and tools. As you progress, you'll learn how to build smart AI applications with design intelligence, personalized user journeys, and coding assistants. Later, you'll explore how to future-proof your web development projects using advanced AI strategies and understand AI's impact on jobs. Toward the end, you'll immerse yourself in AI-augmented development, crafting intelligent web applications and navigating the ethical landscape.Packed with insights into next-gen development environments, AI-augmented practices, emerging realities, interfaces, and security governance, this web development book acts as your roadmap to staying ahead in the AI and web development domain. What you will learn Build AI-powered web projects with optimized models Personalize UX dynamically with AI, NLP, chatbots, and recommendations Explore AI coding assistants and other tools for advanced web development Craft data-driven, personalized experiences using pattern recognition Architect effective AI solutions while exploring the future of web development Build secure and ethical AI applications following TRiSM best practices Explore cutting-edge AI and web development trends Who this book is for This book is for web developers with experience in programming languages and an interest in keeping up with the latest trends in AI-powered web development. Full-stack, front-end, and back-end developers, UI/UX designers, software engineers, and web development enthusiasts will also find valuable information and practical guidelines for developing smarter websites with AI. To get the most out of this book, it is recommended that you have basic knowledge of programming languages such as HTML, CSS, and JavaScript, as well as a familiarity with machine learning concepts.
Read more at https://play.google.com/store/books/details?id=FzYZEQAAQBAJ&source=gbs_api
3. "Artificial Intelligence for Students" by Vibha Pandey: A multifaceted approach to develop an understanding of AI and its potential applications KEY FEATURES ● AI-informed focuses on AI foundation, applications, and methodologies. ● AI-inquired focuses on computational thinking and bias awareness. ● AI-innovate focuses on creative and critical thinking and the Capstone project. DESCRIPTION AI is a discipline in Computer Science that focuses on developing intelligent machines, machines that can learn and then teach themselves. If you are interested in AI, this book can definitely help you prepare for future careers in AI and related fields. The book is aligned with the CBSE course, which focuses on developing employability and vocational competencies of students in skill subjects. The book is an introduction to the basics of AI. It is divided into three parts – AI-informed, AI-inquired and AI-innovate. It will help you understand AI's implications on society and the world. You will also develop a deeper understanding of how it works and how it can be used to solve complex real-world problems. Additionally, the book will also focus on important skills such as problem scoping, goal setting, data analysis, and visualization, which are essential for success in AI projects. Lastly, you will learn how decision trees, neural networks, and other AI concepts are commonly used in real-world applications. By the end of the book, you will develop the skills and competencies required to pursue a career in AI. WHAT YOU WILL LEARN ● Get familiar with the basics of AI and Machine Learning. ● Understand how and where AI can be applied. ● Explore different applications of mathematical methods in AI. ● Get tips for improving your skills in Data Storytelling. ● Understand what is AI bias and how it can affect human rights. WHO THIS BOOK IS FOR This book is for CBSE class XI and XII students who want to learn and explore more about AI. Basic knowledge of Statistical concepts, Algebra, and Plotting of equations is a must. TABLE OF CONTENTS 1. Introduction: AI for Everyone 2. AI Applications and Methodologies 3. Mathematics in Artificial Intelligence 4. AI Values (Ethical Decision-Making) 5. Introduction to Storytelling 6. Critical and Creative Thinking 7. Data Analysis 8. Regression 9. Classification and Clustering 10. AI Values (Bias Awareness) 11. Capstone Project 12. Model Lifecycle (Knowledge) 13. Storytelling Through Data 14. AI Applications in Use in Real-World
Read more at https://play.google.com/store/books/details?id=ptq1EAAAQBAJ&source=gbs_api
4. "The AI Book" by Ivana Bartoletti, Anne Leslie and Shân M. Millie: Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important
Read more at http://books.google.ca/books?id=oE3YDwAAQBAJ&dq=ai&hl=&source=gbs_api
5. "Artificial Intelligence in Society" by OECD: The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises.
Read more at https://play.google.com/store/books/details?id=eRmdDwAAQBAJ&source=gbs_api
```
## Issue
This closes#27276
## Dependencies
No additional dependencies were added
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
- [x] **PR title**: "community: chat models wrapper for Cloudflare
Workers AI"
- [x] **PR message**:
- **Description:** Add chat models wrapper for Cloudflare Workers AI.
Enables Langgraph intergration via ChatModel for tool usage, agentic
usage.
- [x] **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.
- [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/
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.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- **Description:** This PR adds functionality to pass in in-memory bytes
as a source to `AzureAIDocumentIntelligenceLoader`.
- **Issue:** I needed the functionality, so I added it.
- **Dependencies:** NA
- **Twitter handle:** @akseljoonas if this is a big enough change :)
---------
Co-authored-by: Aksel Joonas Reedi <aksel@klippa.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
# OCR-based PDF loader
This implements [Zerox](https://github.com/getomni-ai/zerox) PDF
document loader.
Zerox utilizes simple but very powerful (even though slower and more
costly) approach to parsing PDF documents: it converts PDF to series of
images and passes it to a vision model requesting the contents in
markdown.
It is especially suitable for complex PDFs that are not parsed well by
other alternatives.
## Example use:
```python
from langchain_community.document_loaders.pdf import ZeroxPDFLoader
os.environ["OPENAI_API_KEY"] = "" ## your-api-key
model = "gpt-4o-mini" ## openai model
pdf_url = "https://assets.ctfassets.net/f1df9zr7wr1a/soP1fjvG1Wu66HJhu3FBS/034d6ca48edb119ae77dec5ce01a8612/OpenAI_Sacra_Teardown.pdf"
loader = ZeroxPDFLoader(file_path=pdf_url, model=model)
docs = loader.load()
```
The Zerox library supports wide range of provides/models. See Zerox
documentation for details.
- **Dependencies:** `zerox`
- **Twitter handle:** @martintriska1
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Erick Friis <erickfriis@gmail.com>
## Description
This PR adds support for Memcached as a usable LLM model cache by adding
the ```MemcachedCache``` implementation relying on the
[pymemcache](https://github.com/pinterest/pymemcache) client.
Unit test-wise, the new integration is generally covered under existing
import testing. All new functionality depends on pymemcache if
instantiated and used, so to comply with the other cache implementations
the PR also adds optional integration tests for ```MemcachedCache```.
Since this is a new integration, documentation is added for Memcached as
an integration and as an LLM Cache.
## Issue
This PR closes#27275 which was originally raised as a discussion in
#27035
## Dependencies
There are no new required dependencies for langchain, but
[pymemcache](https://github.com/pinterest/pymemcache) is required to
instantiate the new ```MemcachedCache```.
## Example Usage
```python3
from langchain.globals import set_llm_cache
from langchain_openai import OpenAI
from langchain_community.cache import MemcachedCache
from pymemcache.client.base import Client
llm = OpenAI(model="gpt-3.5-turbo-instruct", n=2, best_of=2)
set_llm_cache(MemcachedCache(Client('localhost')))
# The first time, it is not yet in cache, so it should take longer
llm.invoke("Which city is the most crowded city in the USA?")
# The second time it is, so it goes faster
llm.invoke("Which city is the most crowded city in the USA?")
```
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
## What this PR does?
### Currently `O365BaseLoader` (and consequently both derived loaders)
are limited to `pdf`, `doc`, `docx` files.
- **Solution: here we introduce _handlers_ attribute that allows for
custom handlers to be passed in. This is done in _dict_ form:**
**Example:**
```python
from langchain_community.document_loaders.parsers.documentloader_adapter import DocumentLoaderAsParser
# PR for DocumentLoaderAsParser here: https://github.com/langchain-ai/langchain/pull/27749
from langchain_community.document_loaders.excel import UnstructuredExcelLoader
xlsx_parser = DocumentLoaderAsParser(UnstructuredExcelLoader, mode="paged")
# create dictionary mapping file types to handlers (parsers)
handlers = {
"doc": MsWordParser()
"pdf": PDFMinerParser()
"txt": TextParser()
"xlsx": xlsx_parser
}
loader = SharePointLoader(document_library_id="...",
handlers=handlers # pass handlers to SharePointLoader
)
documents = loader.load()
# works the same in OneDriveLoader
loader = OneDriveLoader(document_library_id="...",
handlers=handlers
)
```
This dictionary is then passed to `MimeTypeBasedParser` same as in the
[current
implementation](5a2cfb49e0/libs/community/langchain_community/document_loaders/parsers/registry.py (L13)).
### Currently `SharePointLoader` and `OneDriveLoader` are separate
loaders that both inherit from `O365BaseLoader`
However both of these implement the same functionality. The only
differences are:
- `SharePointLoader` requires argument `document_library_id` whereas
`OneDriveLoader` requires `drive_id`. These are just different names for
the same thing.
- `SharePointLoader` implements significantly more features.
- **Solution: `OneDriveLoader` is replaced with an empty shell just
renaming `drive_id` to `document_library_id` and inheriting from
`SharePointLoader`**
**Dependencies:** None
**Twitter handle:** @martintriska1
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
There was a change of attribute name which was "max_batch_size". It's
now "get_max_batch_size" method.
I want to use "create_batches" which is right down below.
Please check this PR link.
reference: https://github.com/chroma-core/chroma/pull/2305
---------
Signed-off-by: Prithvi Kannan <prithvi.kannan@databricks.com>
Co-authored-by: Prithvi Kannan <46332835+prithvikannan@users.noreply.github.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Jun Yamog <jkyamog@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: ono-hiroki <86904208+ono-hiroki@users.noreply.github.com>
Co-authored-by: Dobiichi-Origami <56953648+Dobiichi-Origami@users.noreply.github.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Co-authored-by: Duy Huynh <vndee.huynh@gmail.com>
Co-authored-by: Rashmi Pawar <168514198+raspawar@users.noreply.github.com>
Co-authored-by: sifatj <26035630+sifatj@users.noreply.github.com>
Co-authored-by: Eric Pinzur <2641606+epinzur@users.noreply.github.com>
Co-authored-by: Daniel Vu Dao <danielvdao@users.noreply.github.com>
Co-authored-by: Ofer Mendelevitch <ofermend@gmail.com>
Co-authored-by: Stéphane Philippart <wildagsx@gmail.com>
- **Description:** change to do the batch embedding server side and not
client side
- **Twitter handle:** @wildagsx
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
Description:
This fixes an issue that mistakenly created in
https://github.com/langchain-ai/langchain/pull/27253. The issue
currently exists only in `langchain-community==0.3.4`.
Test cases were added to prevent this issue in the future.
Co-authored-by: Erick Friis <erick@langchain.dev>
### Description:
This PR sets a default value of `output_token_limit = 4000` for the
`PowerBIToolkit` to fix the unintentionally validation error.
### Problem:
When attempting to run a code snippet from [Langchain's PowerBI toolkit
documentation](https://python.langchain.com/v0.1/docs/integrations/toolkits/powerbi/)
to interact with a `PowerBIDataset`, the following error occurs:
```
pydantic.v1.error_wrappers.ValidationError: 1 validation error for QueryPowerBITool
output_token_limit
none is not an allowed value (type=type_error.none.not_allowed)
```
### Root Cause:
The issue arises because when creating a `QueryPowerBITool`, the
`output_token_limit` parameter is unintentionally set to `None`, which
is the current default for `PowerBIToolkit`. However, `QueryPowerBITool`
expects a default value of `4000` for `output_token_limit`. This
unintended override causes the error.
17659ca2cd/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py (L63)17659ca2cd/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py (L72-L79)17659ca2cd/libs/community/langchain_community/tools/powerbi/tool.py (L39)
### Solution:
To resolve this, the default value of `output_token_limit` is now
explicitly set to `4000` in `PowerBIToolkit` to prevent the accidental
assignment of `None`.
Co-authored-by: ccurme <chester.curme@gmail.com>
PR title: “langchain: add batch request support for text-embedding-v3
model”
PR message:
• Description: This PR introduces batch request support for the
text-embedding-v3 model within LangChain. The new functionality allows
users to process multiple text inputs in a single request, improving
efficiency and performance for high-volume applications.
• Issue: This PR addresses #<issue_number> (if applicable).
• Dependencies: No new external dependencies are required for this
change.
• Twitter handle: If announced on Twitter, please mention me at
@yourhandle.
Add tests and docs:
1. Added unit tests to cover the batch request functionality, ensuring
it operates without requiring network access.
2. Included an example notebook demonstrating the batch request feature,
located in docs/docs/integrations.
Lint and test: All required formatting and linting checks have been
performed using make format and make lint. The changes have been
verified with make test to ensure compatibility.
Additional notes:
• The changes are fully backwards compatible.
• No modifications were made to pyproject.toml, ensuring no new
dependencies were added.
• The update only affects the langchain package and does not involve
other packages.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
…ING} {code: Neo.ClientNotification.Statement.FeatureDeprecationWarning}
{category: DEPRECATION} {title: This feature is deprecated and will be
removed in future versions.} {description: CALL subquery without a
variable scope clause is now deprecated." this warning
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, 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.
Co-authored-by: putao520 <putao520@putao282.com>
The metadata["source"] value for the web paths was being set to
temporary path (/tmp).
Fixed it by creating a new variable self.original_file_path, which will
store the original path.
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, 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.
I will keep this PR as small as the changes made.
**Description:** fixes a fatal bug syntax error in
AzureCosmosDBNoSqlVectorSearch
**Issue:** #27269#25468
**Description:**
Update the wrapper to support the Polygon API if not you get an error. I
keeped `STOCKBUSINESS` for retro-compatbility with older endpoints /
other uses
Old Code:
```
if status not in ("OK", "STOCKBUSINESS"):
raise ValueError(f"API Error: {data}")
```
API Respond:
```
API Error: {'results': {'P': 0.22, 'S': 0, 'T': 'ZOM', 'X': 5, 'p': 0.123, 'q': 0, 's': 200, 't': 1729614422813395456, 'x': 1, 'z': 1}, 'status': 'STOCKSBUSINESS', 'request_id': 'XXXXXX'}
```
- **Issue:** N/A Polygon API update
- **Dependencies:** N/A
- **Twitter handle:** @wgcv
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
- **Description:** add missing tool_calls kwargs of delta message in
openai adapter, then tool call will work correctly via adapter's stream
chat completion
- **Issue:** Fixes
https://github.com/langchain-ai/langchain/issues/25436
- **Dependencies:** None
- **Description:** Change `MoonshotCommon.client` type from
`_MoonshotClient` to `Any`.
- **Issue:** Fix the issue #27058
- **Dependencies:** No
- **Twitter handle:** TaoWang2218
In PR #17100, the implementation for Moonshot was added, which defined
two classes:
- `MoonshotChat(MoonshotCommon, ChatOpenAI)` in
`langchain_community.chat_models.moonshot`;
- Here, `validate_environment()` assigns **client** as
`openai.OpenAI().chat.completions`
- Note that **client** here is actually a member variable defined in
`ChatOpenAI`;
- `MoonshotCommon` in `langchain_community.llms.moonshot`;
- And here, `validate_environment()` assigns **_client** as
`_MoonshotClient`;
- Note that this is the underscored **_client**, which is defined within
`MoonshotCommon` itself;
At this time, there was no conflict between the two, one being `client`
and the other `_client`.
However, in PR #25878 which fixed#24390, `_client` in `MoonshotCommon`
was changed to `client`. Since then, a conflict in the definition of
`client` has arisen between `MoonshotCommon` and `MoonshotChat`, which
caused `pydantic` validation error.
To fix this issue, the type of `client` in `MoonshotCommon` should be
changed to `Any`.
Signed-off-by: Tao Wang <twang2218@gmail.com>
Thank you for contributing to LangChain!
- **Description:** Adding an empty metadata field when metadata is not
present in the data
- **Issue:** This PR fixes the issue when the data items doesn't contain
the metadata field. This happens when there is already data in the
container, or cx uses CosmosDB Python SDK to insert data.
- **Dependencies:** No dependencies required
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.
- [x] **PR title**:
"community: OCI Generative AI tool calling bug fix
- [x] **PR message**:
- **Description:** bug fix for streaming chat responses with tool calls.
Update to PR 24693
- **Issue:** chat response content is repeated when streaming
- **Dependencies:** NA
- **Twitter handle:** NA
- [x] **Add tests and docs**: NA
- [x] **Lint and test**: make format, make lint and make test we run
successfully
---------
Co-authored-by: Arthur Cheng <arthur.cheng@oracle.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
### About
- **Description:** In the Gitlab utilities used for the Gitlab tool
there is no check to prevent pushing to the main branch, as this is
already done for Github (for example here:
5a2cfb49e0/libs/community/langchain_community/utilities/github.py (L587)).
This PR add this check as already done for Github.
- **Issue:** None
- **Dependencies:** None
**Description:** Add support for Writer chat models
**Issue:** N/A
**Dependencies:** Add `writer-sdk` to optional dependencies.
**Twitter handle:** Please tag `@samjulien` and `@Get_Writer`
**Tests and docs**
- [x] Unit test
- [x] Example notebook in `docs/docs/integrations` directory.
**Lint and test**
- [x] Run `make format`
- [x] Run `make lint`
- [x] Run `make test`
---------
Co-authored-by: Johannes <tolstoy.work@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:**
- Fix bug in Replicate LLM class, where it was looking for parameter
names in a place where they no longer exist in pydantic 2, resulting in
the "Field required" validation error described in the issue.
- Fix Replicate LLM integration tests to:
- Use active models on Replicate.
- Use the correct model parameter `max_new_tokens` as shown in the
[Replicate
docs](https://replicate.com/docs/guides/language-models/how-to-use#minimum-and-maximum-new-tokens).
- Use callbacks instead of deprecated callback_manager.
**Issue:** #26937
**Dependencies:** n/a
**Twitter handle:** n/a
---------
Signed-off-by: Fayvor Love <fayvor@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Thank you for contributing to LangChain!
**Description:** Added the model parameters to be passed in the OpenAI
Assistant. Enabled it at the `OpenAIAssistantV2Runnable` class.
**Issue:** NA
**Dependencies:** None
**Twitter handle:** luizf0992
Thank you for contributing to LangChain!
- **Description:** Add token_usage and model_name metadata to
ChatZhipuAI stream() and astream() response
- **Issue:** None
- **Dependencies:** None
- **Twitter handle:** None
- [ ] **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.
Co-authored-by: jianfehuang <jianfehuang@tencent.com>
**Description:**
- Add the `lora_request` parameter to the VLLM class to support LoRA
model configurations. This enhancement allows users to specify LoRA
requests directly when using VLLM, enabling more flexible and efficient
model customization.
**Issue:**
- No existing issue for `lora_adapter` in VLLM. This PR addresses the
need for configuring LoRA requests within the VLLM framework.
- Reference : [Using LoRA Adapters in
vLLM](https://docs.vllm.ai/en/stable/models/lora.html#using-lora-adapters)
**Example Code :**
Before this change, the `lora_request` parameter was not applied
correctly:
```python
ADAPTER_PATH = "/path/of/lora_adapter"
llm = VLLM(model="Bllossom/llama-3.2-Korean-Bllossom-3B",
max_new_tokens=512,
top_k=2,
top_p=0.90,
temperature=0.1,
vllm_kwargs={
"gpu_memory_utilization":0.5,
"enable_lora":True,
"max_model_len":1024,
}
)
print(llm.invoke(
["...prompt_content..."],
lora_request=LoRARequest("lora_adapter", 1, ADAPTER_PATH)
))
```
**Before Change Output:**
```bash
response was not applied lora_request
```
So, I attempted to apply the lora_adapter to
langchain_community.llms.vllm.VLLM.
**current output:**
```bash
response applied lora_request
```
**Dependencies:**
- None
**Lint and test:**
- All tests and lint checks have passed.
---------
Co-authored-by: Um Changyong <changyong.um@sfa.co.kr>
**Description:**
The `aiohttp.ClientSession` is closed at the end of the with statement,
which causes an error during a second call.
The implemented fix is to define the session directly within the with
block, exactly like in the textembed code:
c6350d636e/libs/community/langchain_community/embeddings/textembed.py (L335-L346)
**Issue:** Fix#26932
Co-authored-by: ccurme <chester.curme@gmail.com>
Reopened as a personal repo outside the organization.
## Description
- Naver HyperCLOVA X community package
- Add chat model & embeddings
- Add unit test & integration test
- Add chat model & embeddings docs
- I changed partner
package(https://github.com/langchain-ai/langchain/pull/24252) to
community package on this PR
- Could this
embeddings(https://github.com/langchain-ai/langchain/pull/21890) be
deprecated? We are trying to replace it with embedding
model(**ClovaXEmbeddings**) in this PR.
Twitter handle: None. (if needed, contact with
joonha.jeon@navercorp.com)
---
you can check our previous discussion below:
> one question on namespaces - would it make sense to have these in
.clova namespaces instead of .naver?
I would like to keep it as is, unless it is essential to unify the
package name.
(ClovaX is a branding for the model, and I plan to add other models and
components. They need to be managed as separate classes.)
> also, could you clarify the difference between ClovaEmbeddings and
ClovaXEmbeddings?
There are 3 models that are being serviced by embedding, and all are
supported in the current PR. In addition, all the functionality of CLOVA
Studio that serves actual models, such as distinguishing between test
apps and service apps, is supported. The existing PR does not support
this content because it is hard-coded.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Vadym Barda <vadym@langchain.dev>
**Issue:** : https://github.com/langchain-ai/langchain/issues/22961
**Description:**
Previously, the documentation for `DuckDuckGoSearchResults` said that it
returns a JSON string, however the code returns a regular string that
can't be parsed as is.
for example running
```python
from langchain_community.tools import DuckDuckGoSearchResults
# Create a DuckDuckGo search instance
search = DuckDuckGoSearchResults()
# Invoke the search
result = search.invoke("Obama")
# Print the result
print(result)
# Print the type of the result
print("Result Type:", type(result))
```
will return
```
snippet: Harris will hold a campaign event with former President Barack Obama in Georgia next Thursday, the first time the pair has campaigned side by side, a senior campaign official said. A week from ..., title: Obamas to hit the campaign trail in first joint appearances with Harris, link: https://www.nbcnews.com/politics/2024-election/obamas-hit-campaign-trail-first-joint-appearances-harris-rcna176034, snippet: Item 1 of 3 Former U.S. first lady Michelle Obama and her husband, former U.S. President Barack Obama, stand on stage during Day 2 of the Democratic National Convention (DNC) in Chicago, Illinois ..., title: Obamas set to hit campaign trail with Kamala Harris for first time, link: https://www.reuters.com/world/us/obamas-set-hit-campaign-trail-with-kamala-harris-first-time-2024-10-18/, snippet: Barack and Michelle Obama will make their first campaign appearances alongside Kamala Harris at rallies in Georgia and Michigan. By Reid J. Epstein Reporting from Ashwaubenon, Wis. Here come the ..., title: Harris Will Join Michelle Obama and Barack Obama on Campaign Trail, link: https://www.nytimes.com/2024/10/18/us/politics/kamala-harris-michelle-obama-barack-obama.html, snippet: Obama's leaving office was "a turning point," Mirsky said. "That was the last time anybody felt normal." A few feet over, a 64-year-old physics professor named Eric Swanson who had grown ..., title: Obama's reemergence on the campaign trail for Harris comes as he ..., link: https://www.cnn.com/2024/10/13/politics/obama-campaign-trail-harris-biden/index.html
Result Type: <class 'str'>
```
After the change in this PR, `DuckDuckGoSearchResults` takes an
additional `output_format = "list" | "json" | "string"` ("string" =
current behavior, default). For example, invoking
`DuckDuckGoSearchResults(output_format="list")` return a list of
dictionaries in the format
```
[{'snippet': '...', 'title': '...', 'link': '...'}, ...]
```
e.g.
```
[{'snippet': "Obama has in a sense been wrestling with Trump's impact since the real estate magnate broke onto the political stage in 2015. Trump's victory the next year, defeating Obama's secretary of ...", 'title': "Obama's fears about Trump drive his stepped-up campaigning", 'link': 'https://www.washingtonpost.com/politics/2024/10/18/obama-trump-anxiety-harris-campaign/'}, {'snippet': 'Harris will hold a campaign event with former President Barack Obama in Georgia next Thursday, the first time the pair has campaigned side by side, a senior campaign official said. A week from ...', 'title': 'Obamas to hit the campaign trail in first joint appearances with Harris', 'link': 'https://www.nbcnews.com/politics/2024-election/obamas-hit-campaign-trail-first-joint-appearances-harris-rcna176034'}, {'snippet': 'Item 1 of 3 Former U.S. first lady Michelle Obama and her husband, former U.S. President Barack Obama, stand on stage during Day 2 of the Democratic National Convention (DNC) in Chicago, Illinois ...', 'title': 'Obamas set to hit campaign trail with Kamala Harris for first time', 'link': 'https://www.reuters.com/world/us/obamas-set-hit-campaign-trail-with-kamala-harris-first-time-2024-10-18/'}, {'snippet': 'Barack and Michelle Obama will make their first campaign appearances alongside Kamala Harris at rallies in Georgia and Michigan. By Reid J. Epstein Reporting from Ashwaubenon, Wis. Here come the ...', 'title': 'Harris Will Join Michelle Obama and Barack Obama on Campaign Trail', 'link': 'https://www.nytimes.com/2024/10/18/us/politics/kamala-harris-michelle-obama-barack-obama.html'}]
Result Type: <class 'list'>
```
---------
Co-authored-by: vbarda <vadym@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.
**Description:**
This PR updates `CassandraGraphVectorStore` to be based off
`CassandraVectorStore`, instead of using a custom CQL implementation.
This allows users using a `CassandraVectorStore` to upgrade to a
`GraphVectorStore` without having to change their database schema or
re-embed documents.
This PR also updates the documentation of the `GraphVectorStore` base
class and contains native async implementations for the standard graph
methods: `traversal_search` and `mmr_traversal_search` in
`CassandraVectorStore`.
**Issue:** No issue number.
**Dependencies:** https://github.com/langchain-ai/langchain/pull/27078
(already-merged)
**Lint and test**:
- Lint and tests all pass, including existing
`CassandraGraphVectorStore` tests.
- Also added numerous additional tests based of the tests in
`langchain-astradb` which cover many more scenarios than the existing
tests for `Cassandra` and `CassandraGraphVectorStore`
** BREAKING CHANGE**
Note that this is a breaking change for existing users of
`CassandraGraphVectorStore`. They will need to wipe their database table
and restart.
However:
- The interfaces have not changed. Just the underlying storage
mechanism.
- Any one using `langchain_community.vectorstores.Cassandra` can instead
use `langchain_community.graph_vectorstores.CassandraGraphVectorStore`
and they will gain Graph capabilities without having to re-embed their
existing documents. This is the primary goal of this PR.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
- [ X] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, etc. is
being modified. Use "docs: ..." for purely docs changes, "templates:
..." for template changes, "infra: ..." for CI changes.
- Example: "community: add foobar LLM"
- [ X]
- **Issue:** issue #26941
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.
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description**
This PR introduces the proxies parameter to the RecursiveUrlLoader
class, allowing the user to specify proxy servers for requests. This
update enables crawling through proxy servers, providing enhanced
flexibility for network configurations.
The key changes include:
1.Added an optional proxies parameter to the constructor (__init__).
2.Updated the documentation to explain the proxies parameter usage with
an example.
3.Modified the _get_child_links_recursive method to pass the proxies
parameter to the requests.get function.
**Sample Usage**
```python
from bs4 import BeautifulSoup as Soup
from langchain_community.document_loaders.recursive_url_loader import RecursiveUrlLoader
proxies = {
"http": "http://localhost:1080",
"https": "http://localhost:1080",
}
url = "https://python.langchain.com/docs/concepts/#langchain-expression-language-lcel"
loader = RecursiveUrlLoader(
url=url, max_depth=1, extractor=lambda x: Soup(x, "html.parser").text,proxies=proxies
)
docs = loader.load()
```
---------
Co-authored-by: root <root@thb>
We have released the
[langchain-databricks](https://github.com/langchain-ai/langchain-databricks)
package for Databricks integration. This PR deprecates the legacy
classes within `langchain-community`.
---------
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description**:
This PR add support of clob/blob data type for oracle document loader,
clob/blob can only be read by oracledb package when connection is open,
so reformat code to process data before connection closes.
**Dependencies**:
oracledb package same as before. pip install oracledb
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:**
- This pull request addresses a bug in Langchain's VLLM integration,
where the use_beam_search parameter was erroneously passed to
SamplingParams. The SamplingParams class in vLLM does not support the
use_beam_search argument, which caused a TypeError.
- This PR introduces logic to filter out unsupported parameters,
ensuring that only valid parameters are passed to SamplingParams. As a
result, the integration now functions as expected without errors.
- The bug was reproduced by running the code sample from Langchain’s
documentation, which triggered the error due to the invalid parameter.
This fix resolves that error by implementing proper parameter filtering.
**VLLM Sampling Params Class:**
https://github.com/vllm-project/vllm/blob/main/vllm/sampling_params.py
**Issue:**
I could not found an Issue that belongs to this. Fixes "TypeError:
Unexpected keyword argument 'use_beam_search'" error when using VLLM
from Langchain.
**Dependencies:**
None.
**Tests and Documentation**:
Tests:
No new functionality was added, but I tested the changes by running
multiple prompts through the VLLM integration with various parameter
configurations. All tests passed successfully without breaking
compatibility.
Docs
No documentation changes were necessary as this is a bug fix.
**Reproducing the Error:**
https://python.langchain.com/docs/integrations/llms/vllm/
The code sample from the original documentation can be used to reproduce
the error I got.
from langchain_community.llms import VLLM
llm = VLLM(
model="mosaicml/mpt-7b",
trust_remote_code=True, # mandatory for hf models
max_new_tokens=128,
top_k=10,
top_p=0.95,
temperature=0.8,
)
print(llm.invoke("What is the capital of France ?"))
This PR resolves the issue by ensuring that only valid parameters are
passed to SamplingParams.
**Description**: PR fixes some formatting errors in deprecation message
in the `langchain_community.vectorstores.pgvector` module, where it was
missing spaces between a few words, and one word was misspelled.
**Issue**: n/a
**Dependencies**: n/a
Signed-off-by: mpeveler@timescale.com
Co-authored-by: Erick Friis <erick@langchain.dev>
PR message:
Description:
This PR refactors the Arxiv API wrapper by extracting the Arxiv search
logic into a helper function (_fetch_results) to reduce code duplication
and improve maintainability. The helper function is used in methods like
get_summaries_as_docs, run, and lazy_load, streamlining the code and
making it easier to maintain in the future.
Issue:
This is a minor refactor, so no specific issue is being fixed.
Dependencies:
No new dependencies are introduced with this change.
Add tests and docs:
No new integrations were added, so no additional tests or docs are
necessary for this PR.
Lint and test:
I have run make format, make lint, and make test to ensure all checks
pass successfully.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR updates the integration with OCI data science model deployment
service.
- Update LLM to support streaming and async calls.
- Added chat model.
- Updated tests and docs.
- Updated `libs/community/scripts/check_pydantic.sh` since the use of
`@pre_init` is removed from existing integration.
- Updated `libs/community/extended_testing_deps.txt` as this integration
requires `langchain_openai`.
---------
Co-authored-by: MING KANG <ming.kang@oracle.com>
Co-authored-by: Dmitrii Cherkasov <dmitrii.cherkasov@oracle.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR updates the Firecrawl Document Loader to use the recently
released V1 API of Firecrawl.
**Key Updates:**
**Firecrawl V1 Integration:** Updated the document loader to leverage
the new Firecrawl V1 API for improved performance, reliability, and
developer experience.
**Map Functionality Added:** Introduced the map mode for more flexible
document loading options.
These updates enhance the integration and provide access to the latest
features of Firecrawl.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, etc. is
being modified. Use "docs: ..." for purely docs changes, "templates:
..." for template changes, "infra: ..." for CI changes.
- Example: "community: add foobar LLM"
Updated
- [ ] **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!
twitter: @MaxHTran
- [ ] **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.
Not needed due to small change
- [ ] **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.
---------
Co-authored-by: Max Tran <maxtra@amazon.com>
Starting with Clickhouse version 24.8, a different type of configuration
has been introduced in the vectorized data ingestion, and if this
configuration occurs, an error occurs when generating the table. As can
be seen below:
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description**:
this PR enable VectorStore TLS and authentication (digest, basic) with
HTTP/2 for Infinispan server.
Based on httpx.
Added docker-compose facilities for testing
Added documentation
**Dependencies:**
requires `pip install httpx[http2]` if HTTP2 is needed
**Twitter handle:**
https://twitter.com/infinispan
**Description:** this PR adds a set of methods to deal with metadata
associated to the vector store entries. These, while essential to the
Graph-related extension of the `Cassandra` vector store, are also useful
in themselves. These are (all come in their sync+async versions):
- `[a]delete_by_metadata_filter`
- `[a]replace_metadata`
- `[a]get_by_document_id`
- `[a]metadata_search`
Additionally, a `[a]similarity_search_with_embedding_id_by_vector`
method is introduced to better serve the store's internal working (esp.
related to reranking logic).
**Issue:** no issue number, but now all Document's returned bear their
`.id` consistently (as a consequence of a slight refactoring in how the
raw entries read from DB are made back into `Document` instances).
**Dependencies:** (no new deps: packaging comes through langchain-core
already; `cassio` is now required to be version 0.1.10+)
**Add tests and docs**
Added integration tests for the relevant newly-introduced methods.
(Docs will be updated in a separate PR).
**Lint and test** Lint and (updated) test all pass.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Add timeout at client side for UCFunctionToolkit and add retry logic.
Users could specify environment variable
`UC_TOOL_CLIENT_EXECUTION_TIMEOUT` to increase the timeout value for
retrying to get the execution response if the status is pending. Default
timeout value is 120s.
- [ ] **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.
Tested in Databricks:
<img width="1200" alt="image"
src="https://github.com/user-attachments/assets/54ab5dfc-5e57-4941-b7d9-bfe3f8ad3f62">
- [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/
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.
---------
Signed-off-by: serena-ruan <serena.rxy@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- [ ] **PR title**: docs: fix typo in SQLStore import path
- [ ] **PR message**:
- **Description:** This PR corrects a typo in the docstrings for the
class SQLStore(BaseStore[str, bytes]). The import path in the docstring
currently reads from langchain_rag.storage import SQLStore, which should
be changed to langchain_community.storage import SQLStore. This typo is
also reflected in the official documentation.
- **Issue:** N/A
- **Dependencies:** None
- **Twitter handle:** N/A
Co-authored-by: Erick Friis <erick@langchain.dev>
Given the current erroring behavior, every time we've moved a kwarg from
model_kwargs and made it its own field that was a breaking change.
Updating this behavior to support the old instantiations /
serializations.
Assuming build_extra_kwargs was not something that itself is being used
externally and needs to be kept backwards compatible
These allow converting linked documents (such as those used with
GraphVectorStore) to networkx for rendering and/or in-memory graph
algorithms such as community detection.
**Description:** Moves callback to before yield for `_stream` and
`_astream` function for the textgen model in the community llm package
**Issue:** #16913
**Description**:
Adds a vector store integration with
[sqlite-vec](https://alexgarcia.xyz/sqlite-vec/), the successor to
sqlite-vss that is a single C file with no external dependencies.
Pretty straightforward, just copy-pasted the sqlite-vss integration and
made a few tweaks and added integration tests. Only question is whether
all documentation should be directed away from sqlite-vss if it is
defacto deprecated (cc @asg017).
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: philippe-oger <philippe.oger@adevinta.com>
**Description:** Moves yield to after callback for `_stream` and
`_astream` function for the gigachat model in the community llm package
**Issue:** #16913
- **Description:** This pull request addresses the validation error in
`SettingsConfigDict` due to extra fields in the `.env` file. The issue
is prevalent across multiple Langchain modules. This fix ensures that
extra fields in the `.env` file are ignored, preventing validation
errors.
**Changes include:**
- Applied fixes to modules using `SettingsConfigDict`.
- **Issue:** NA, similar
https://github.com/langchain-ai/langchain/issues/26850
- **Dependencies:** NA
- **Description:** The flag is named `anonymize_snippets`. When set to
true, the Pebblo server will anonymize snippets by redacting all
personally identifiable information (PII) from the snippets going into
VectorDB and the generated reports
- **Issue:** NA
- **Dependencies:** NA
- **docs**: Updated
**Description:** Moves yield to after callback for `_stream` and
`_astream` function for the deepsparse model in the community package
**Issue:** #16913
- **Description:** This PR fixes the response parsing logic for
`ChatDeepInfra`, more specifially `_convert_delta_to_message_chunk()`,
which is invoked when streaming via `ChatDeepInfra`.
- **Issue:** Streaming from DeepInfra via `ChatDeepInfra` is currently
broken because the response parsing logic doesn't handle that
`tool_calls` can be `None`. (There is no GitHub issue for this problem
yet.)
- **Dependencies:** –
- **Twitter handle:** –
Keeping this here as a reminder:
> If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
**Description:** Moves yield to after callback for
`_prepare_input_and_invoke_stream` and
`_aprepare_input_and_invoke_stream` for bedrock llm in community
package.
**Issue:** #16913
without this `model_config` importing this package produces warnings
about "model_name" having conflicts with protected namespace "model_".
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.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description:**
When PR body is empty `get_pull_request` method fails with bellow
exception.
**Issue:**
```
TypeError('expected string or buffer')Traceback (most recent call last):
File ".../.venv/lib/python3.9/site-packages/langchain_core/tools/base.py", line 661, in run
response = context.run(self._run, *tool_args, **tool_kwargs)
File ".../.venv/lib/python3.9/site-packages/langchain_community/tools/github/tool.py", line 52, in _run
return self.api_wrapper.run(self.mode, query)
File ".../.venv/lib/python3.9/site-packages/langchain_community/utilities/github.py", line 816, in run
return json.dumps(self.get_pull_request(int(query)))
File ".../.venv/lib/python3.9/site-packages/langchain_community/utilities/github.py", line 495, in get_pull_request
add_to_dict(response_dict, "body", pull.body)
File ".../.venv/lib/python3.9/site-packages/langchain_community/utilities/github.py", line 487, in add_to_dict
tokens = get_tokens(value)
File ".../.venv/lib/python3.9/site-packages/langchain_community/utilities/github.py", line 483, in get_tokens
return len(tiktoken.get_encoding("cl100k_base").encode(text))
File "....venv/lib/python3.9/site-packages/tiktoken/core.py", line 116, in encode
if match := _special_token_regex(disallowed_special).search(text):
TypeError: expected string or buffer
```
**Twitter:** __gorros__
Thank you for contributing to LangChain!
Fix error like
<img width="1167" alt="image"
src="https://github.com/user-attachments/assets/2e219b26-ec7e-48ef-8111-e0ff2f5ac4c0">
After the fix:
<img width="584" alt="image"
src="https://github.com/user-attachments/assets/48f36fe7-628c-48b6-81b2-7fe741e4ca85">
- [ ] **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.
---------
Signed-off-by: serena-ruan <serena.rxy@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Added PebbloTextLoader for loading text in
PebbloSafeLoader.
- Since PebbloSafeLoader wraps document loaders, this new loader enables
direct loading of text into Documents using PebbloSafeLoader.
- **Issue:** NA
- **Dependencies:** NA
- [x] **Tests**: Added/Updated tests
# Description
[Vector store base
class](4cdaca67dc/libs/core/langchain_core/vectorstores/base.py (L65))
currently expects `ids` to be passed in and that is what it passes along
to the AzureSearch vector store when attempting to `add_texts()`.
However AzureSearch expects `keys` to be passed in. When they are not
present, AzureSearch `add_embeddings()` makes up new uuids. This is a
problem when trying to run indexing. [Indexing code
expects](b297af5482/libs/core/langchain_core/indexing/api.py (L371))
the documents to be uploaded using provided ids. Currently AzureSearch
ignores `ids` passed from `indexing` and makes up new ones. Later when
`indexer` attempts to delete removed file, it uses the `id` it had
stored when uploading the document, however it was uploaded under
different `id`.
**Twitter handle: @martintriska1**
Page content sometimes is empty when PyMuPDF can not find text on pages.
For example, this can happen when the text of the PDF is not copyable
"by hand". Then an OCR solution is need - which is not integrated here.
This warning should accurately warn the user that some pages are lost
during this process.
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.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Fixes#26212: replaced the raw string with backslashes. Alternative:
raw-stringif the full docstring.
---------
Co-authored-by: Erick Friis <erickfriis@gmail.com>
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.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
### Description:
This pull request significantly enhances the MongodbLoader class in the
LangChain community package by adding robust metadata customization and
improved field extraction capabilities. The updated class now allows
users to specify additional metadata fields through the metadata_names
parameter, enabling the extraction of both top-level and deeply nested
document attributes as metadata. This flexibility is crucial for users
who need to include detailed contextual information without altering the
database schema.
Moreover, the include_db_collection_in_metadata flag offers optional
inclusion of database and collection names in the metadata, allowing for
even greater customization depending on the user's needs.
The loader's field extraction logic has been refined to handle missing
or nested fields more gracefully. It now employs a safe access mechanism
that avoids the KeyError previously encountered when a specified nested
field was absent in a document. This update ensures that the loader can
handle diverse and complex data structures without failure, making it
more resilient and user-friendly.
### Issue:
This pull request addresses a critical issue where the MongodbLoader
class in the LangChain community package could throw a KeyError when
attempting to access nested fields that may not exist in some documents.
The previous implementation did not handle the absence of specified
nested fields gracefully, leading to runtime errors and interruptions in
data processing workflows.
This enhancement ensures robust error handling by safely accessing
nested document fields, using default values for missing data, thus
preventing KeyError and ensuring smoother operation across various data
structures in MongoDB. This improvement is crucial for users working
with diverse and complex data sets, ensuring the loader can adapt to
documents with varying structures without failing.
### Dependencies:
Requires motor for asynchronous MongoDB interaction.
### Twitter handle:
N/A
### Add tests and docs
Tests: Unit tests have been added to verify that the metadata inclusion
toggle works as expected and that the field extraction correctly handles
nested fields.
Docs: An example notebook demonstrating the use of the enhanced
MongodbLoader is included in the docs/docs/integrations directory. This
notebook includes setup instructions, example usage, and outputs.
(Here is the notebook link : [colab
link](https://colab.research.google.com/drive/1tp7nyUnzZa3dxEFF4Kc3KS7ACuNF6jzH?usp=sharing))
Lint and test
Before submitting, I ran make format, make lint, and make test as per
the contribution guidelines. All tests pass, and the code style adheres
to the LangChain standards.
```python
import unittest
from unittest.mock import patch, MagicMock
import asyncio
from langchain_community.document_loaders.mongodb import MongodbLoader
class TestMongodbLoader(unittest.TestCase):
def setUp(self):
"""Setup the MongodbLoader test environment by mocking the motor client
and database collection interactions."""
# Mocking the AsyncIOMotorClient
self.mock_client = MagicMock()
self.mock_db = MagicMock()
self.mock_collection = MagicMock()
self.mock_client.get_database.return_value = self.mock_db
self.mock_db.get_collection.return_value = self.mock_collection
# Initialize the MongodbLoader with test data
self.loader = MongodbLoader(
connection_string="mongodb://localhost:27017",
db_name="testdb",
collection_name="testcol"
)
@patch('langchain_community.document_loaders.mongodb.AsyncIOMotorClient', return_value=MagicMock())
def test_constructor(self, mock_motor_client):
"""Test if the constructor properly initializes with the correct database and collection names."""
loader = MongodbLoader(
connection_string="mongodb://localhost:27017",
db_name="testdb",
collection_name="testcol"
)
self.assertEqual(loader.db_name, "testdb")
self.assertEqual(loader.collection_name, "testcol")
def test_aload(self):
"""Test the aload method to ensure it correctly queries and processes documents."""
# Setup mock data and responses for the database operations
self.mock_collection.count_documents.return_value = asyncio.Future()
self.mock_collection.count_documents.return_value.set_result(1)
self.mock_collection.find.return_value = [
{"_id": "1", "content": "Test document content"}
]
# Run the aload method and check responses
loop = asyncio.get_event_loop()
results = loop.run_until_complete(self.loader.aload())
self.assertEqual(len(results), 1)
self.assertEqual(results[0].page_content, "Test document content")
def test_construct_projection(self):
"""Verify that the projection dictionary is constructed correctly based on field names."""
self.loader.field_names = ['content', 'author']
self.loader.metadata_names = ['timestamp']
expected_projection = {'content': 1, 'author': 1, 'timestamp': 1}
projection = self.loader._construct_projection()
self.assertEqual(projection, expected_projection)
if __name__ == '__main__':
unittest.main()
```
### Additional Example for Documentation
Sample Data:
```json
[
{
"_id": "1",
"title": "Artificial Intelligence in Medicine",
"content": "AI is transforming the medical industry by providing personalized medicine solutions.",
"author": {
"name": "John Doe",
"email": "john.doe@example.com"
},
"tags": ["AI", "Healthcare", "Innovation"]
},
{
"_id": "2",
"title": "Data Science in Sports",
"content": "Data science provides insights into player performance and strategic planning in sports.",
"author": {
"name": "Jane Smith",
"email": "jane.smith@example.com"
},
"tags": ["Data Science", "Sports", "Analytics"]
}
]
```
Example Code:
```python
loader = MongodbLoader(
connection_string="mongodb://localhost:27017",
db_name="example_db",
collection_name="articles",
filter_criteria={"tags": "AI"},
field_names=["title", "content"],
metadata_names=["author.name", "author.email"],
include_db_collection_in_metadata=True
)
documents = loader.load()
for doc in documents:
print("Page Content:", doc.page_content)
print("Metadata:", doc.metadata)
```
Expected Output:
```
Page Content: Artificial Intelligence in Medicine AI is transforming the medical industry by providing personalized medicine solutions.
Metadata: {'author_name': 'John Doe', 'author_email': 'john.doe@example.com', 'database': 'example_db', 'collection': 'articles'}
```
Thank you.
---
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.
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
The object extends from
langchain_community.chat_models.openai.ChatOpenAI which doesn't have
`bind_tools` defined. I tried extending from
`langchain_openai.ChatOpenAI` in
https://github.com/langchain-ai/langchain/pull/25975 but that PR got
closed because this is not correct.
So adding our own `bind_tools` (which for now copying from ChatOpenAI is
good enough) will solve the tool calling issue we are having now.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
- [X ] **PR title**
- [X ] **PR message**:
**Description:** adds a handler for when delta choice is None
**Issue:** Fixes#25951
**Dependencies:** Not applicable
- [ X] **Add tests and docs**: Not applicable
- [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/
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.
Co-authored-by: Grande <Tom.Daniel.Grande@statsbygg.no>
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:**
Change the default Neo4j username/password (when not supplied as
environment variable or in code) from `None` to `""`.
Neo4j has an option to [disable
auth](https://neo4j.com/docs/operations-manual/current/configuration/configuration-settings/#config_dbms.security.auth_enabled)
which is helpful when developing. When auth is disabled, the username /
password through the `neo4j` module should be `""` (ie an empty string).
Empty strings get marked as false in
`langchain_core.utils.env.get_from_dict_or_env` -- changing this code /
behaviour would have a wide impact and is undesirable.
In order to both _allow_ access to Neo4j with auth disabled and _not_
impact `langchain_core` this patch is presented. The downside would be
that if a user forgets to set NEO4J_USERNAME or NEO4J_PASSWORD they
would see an invalid credentials error rather than missing credentials
error. This could be mitigated but would result in a less elegant patch!
**Issue:**
Fix issue where langchain cannot communicate with Neo4j if Neo4j auth is
disabled.
- **PR title**: "community: add Jina Search tool"
- **Description:** Added the Jina Search tool for querying the Jina
search API. This includes the implementation of the JinaSearchAPIWrapper
and the JinaSearch tool, along with a Jupyter notebook example
demonstrating its usage.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** [Twitter
handle](https://x.com/yashp3020?t=7wM0gQ7XjGciFoh9xaBtqA&s=09)
- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. 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/
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Returns an array of results which is more specific and easier for later
use.
Tested locally:
```
resp = tool.invoke("what's the weather like in Shanghai?")
for item in resp:
print(item)
```
returns
```
{'snippet': '<b>Shanghai</b>, <b>Shanghai</b>, China <b>Weather</b> Forecast, with current conditions, wind, air quality, and what to expect for the next 3 days.', 'title': 'Shanghai, Shanghai, China Weather Forecast | AccuWeather', 'link': 'https://www.accuweather.com/en/cn/shanghai/106577/weather-forecast/106577'}
{'snippet': '5. 99 / 87 °F. 6. 99 / 86 °F. 7. Detailed forecast for 14 days. Need some help? Current <b>weather</b> <b>in Shanghai</b> and forecast for today, tomorrow, and next 14 days.', 'title': 'Weather for Shanghai, Shanghai Municipality, China - timeanddate.com', 'link': 'https://www.timeanddate.com/weather/china/shanghai'}
{'snippet': '<b>Shanghai</b> - <b>Weather</b> warnings issued 14-day forecast. <b>Weather</b> warnings issued. Forecast - <b>Shanghai</b>. Day by day forecast. Last updated Friday at 01:05. Tonight, ... Temperature feels <b>like</b> 34 ...', 'title': 'Shanghai - BBC Weather', 'link': 'https://www.bbc.com/weather/1796236'}
{'snippet': 'Current <b>weather</b> <b>in Shanghai</b>, <b>Shanghai</b>, China. Check current conditions <b>in Shanghai</b>, <b>Shanghai</b>, China with radar, hourly, and more.', 'title': 'Shanghai, Shanghai, China Current Weather | AccuWeather', 'link': 'https://www.accuweather.com/en/cn/shanghai/106577/current-weather/106577'}
13-Day Beijing, Xi'an, Chengdu, <b>Shanghai</b> Chinese Language and Culture Immersion Tour. <b>Shanghai</b> in September. Average daily temperature range: 23–29°C (73–84°F) Average rainy days: 10. Average sunny days: 20. September ushers in pleasant autumn <b>weather</b>, making it one of the best months to visit <b>Shanghai</b>. <b>Weather</b> in <b>Shanghai</b>: Climate, Seasons, and Average Monthly Temperature. <b>Shanghai</b> has a subtropical maritime monsoon climate, meaning high humidity and lots of rain. Hot muggy summers, cool falls, cold winters with little snow, and warm springs are the norm. Midsummer through early fall is the best time to visit <b>Shanghai</b>. <b>Shanghai</b>, <b>Shanghai</b>, China <b>Weather</b> Forecast, with current conditions, wind, air quality, and what to expect for the next 3 days. 1165. 45.9. 121. Winter, from December to February, is quite cold: the average January temperature is 5 °C (41 °F). There may be cold periods, with highs around 5 °C (41 °F) or below, and occasionally, even snow can fall. The temperature dropped to -10 °C (14 °F) in January 1977 and to -7 °C (19.5 °F) in January 2016. 5. 99 / 87 °F. 6. 99 / 86 °F. 7. Detailed forecast for 14 days. Need some help? Current <b>weather</b> in <b>Shanghai</b> and forecast for today, tomorrow, and next 14 days. Everything you need to know about today's <b>weather</b> in <b>Shanghai</b>, <b>Shanghai</b>, China. High/Low, Precipitation Chances, Sunrise/Sunset, and today's Temperature History. <b>Shanghai</b> - <b>Weather</b> warnings issued 14-day forecast. <b>Weather</b> warnings issued. Forecast - <b>Shanghai</b>. Day by day forecast. Last updated Friday at 01:05. Tonight, ... Temperature feels <b>like</b> 34 ... <b>Shanghai</b> 14 Day Extended Forecast. <b>Weather</b> Today <b>Weather</b> Hourly 14 Day Forecast Yesterday/Past <b>Weather</b> Climate (Averages) Currently: 84 °F. Passing clouds. (<b>Weather</b> station: <b>Shanghai</b> Hongqiao Airport, China). See more current <b>weather</b>. Current <b>weather</b> in <b>Shanghai</b>, <b>Shanghai</b>, China. Check current conditions in <b>Shanghai</b>, <b>Shanghai</b>, China with radar, hourly, and more. <b>Shanghai</b> <b>Weather</b> Forecasts. <b>Weather Underground</b> provides local & long-range <b>weather</b> forecasts, weatherreports, maps & tropical <b>weather</b> conditions for the <b>Shanghai</b> area.
```
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:**
Adding a new option to the CSVLoader that allows us to implicitly
specify the columns that are used for generating the Document content.
Currently these are implicitly set as "all fields not part of the
metadata_columns".
In some cases however it is useful to have a field both as a metadata
and as part of the document content.
- **Description:** The function `_is_assistants_builtin_tool` didn't had
support for `file_search` from OpenAI. This was creating conflict and
blocking the usage of such. OpenAI Assistant changed from`retrieval` to
`file_search`.
The following code
```
agent = OpenAIAssistantV2Runnable.create_assistant(
name="Data Analysis Assistant",
instructions=prompt[0].content,
tools={'type': 'file_search'},
model=self.chat_config.connection.deployment_name,
client=llm,
as_agent=True,
tool_resources={
"file_search": {
"vector_store_ids": vector_store_id
}
}
)
```
Was throwing the following error
```
Traceback (most recent call last):
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/chat_decorators.py",
line 500, in get_response
return await super().get_response(post, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/chat_decorators.py",
line 96, in get_response
response = await self.inner_chat.get_response(post, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/chat_decorators.py",
line 96, in get_response
response = await self.inner_chat.get_response(post, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/chat_decorators.py",
line 96, in get_response
response = await self.inner_chat.get_response(post, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[Previous line repeated 4 more times]
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/azure_open_ai_chat.py",
line 147, in get_response
chain = chain_factory.get_chain(prompts, post.conversation.id,
overrides, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/llm_connections/chains.py",
line 1324, in get_chain
agent = OpenAIAssistantV2Runnable.create_assistant(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_community/agents/openai_assistant/base.py",
line 256, in create_assistant
tools=[_get_assistants_tool(tool) for tool in tools], # type: ignore
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_community/agents/openai_assistant/base.py",
line 256, in <listcomp>
tools=[_get_assistants_tool(tool) for tool in tools], # type: ignore
^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_community/agents/openai_assistant/base.py",
line 119, in _get_assistants_tool
return convert_to_openai_tool(tool)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_core/utils/function_calling.py",
line 255, in convert_to_openai_tool
function = convert_to_openai_function(tool)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_core/utils/function_calling.py",
line 230, in convert_to_openai_function
raise ValueError(
ValueError: Unsupported function
{'type': 'file_search'}
Functions must be passed in as Dict, pydantic.BaseModel, or Callable. If
they're a dict they must either be in OpenAI function format or valid
JSON schema with top-level 'title' and 'description' keys.
```
With the proposed changes, this is fixed and the function will have support for `file_search`.
This was the only place missing the support for `file_search`.
Reference doc
https://platform.openai.com/docs/assistants/tools/file-search
- **Twitter handle:** luizf0992
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Description:
- Add system templates and user templates in integration testing
- initialize the response id field value to request_id
- Adjust the default model to hunyuan-pro
- Remove the default values of Temperature and TopP
- Add SystemMessage
all the integration tests have passed.
1、Execute integration tests for the first time
<img width="1359" alt="71ca77a2-e9be-4af6-acdc-4d665002bd9b"
src="https://github.com/user-attachments/assets/9298dc3a-aa26-4bfa-968b-c011a4e699c9">
2、Run the integration test a second time
<img width="1501" alt="image"
src="https://github.com/user-attachments/assets/61335416-4a67-4840-bb89-090ba668e237">
Issue: None
Dependencies: None
Twitter handle: None
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description:** [IPEX-LLM](https://github.com/intel-analytics/ipex-llm)
is a PyTorch library for running LLM on Intel CPU and GPU (e.g., local
PC with iGPU, discrete GPU such as Arc, Flex and Max) with very low
latency. This PR adds Intel GPU support to `ipex-llm` llm integration.
**Dependencies:** `ipex-llm`
**Contribution maintainer**: @ivy-lv11 @Oscilloscope98
**tests and docs**:
- Add: langchain/docs/docs/integrations/llms/ipex_llm_gpu.ipynb
- Update: langchain/docs/docs/integrations/llms/ipex_llm_gpu.ipynb
- Update: langchain/libs/community/tests/llms/test_ipex_llm.py
---------
Co-authored-by: ivy-lv11 <zhicunlv@gmail.com>
- **Description:**
Improve llamacpp embedding class by adding the `device` parameter so it
can be passed to the model and used with `gpu`, `cpu` or Apple metal
(`mps`).
Improve performance by making use of the bulk client api to compute
embeddings in batches.
- **Dependencies:** none
- **Tag maintainer:**
@hwchase17
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description:**
Starting from Neo4j 5.23 (22 August 2024), with vector-2.0 indexes,
`vector.dimensions` is not required to be set, which will cause it the
key not exist error in index config if it's not set.
Since the existence of vector.dimensions will only ensure additional
checks, this commit turns embedding dimension check optional, and only
do checks when it exists (not None).
https://neo4j.com/release-notes/database/neo4j-5/
**Twitter handle:** @HollowM186
Signed-off-by: Hollow Man <hollowman@opensuse.org>
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Added `ref` query parameter so data is not loaded
only from the default branch but any branch passed
---------
Co-authored-by: Osama Mehdi <mehdi@hm.edu>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
- [x] **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"
- [x] **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!
- [x] **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.
- [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/
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
- Updates the self-query retriever factory to check for the new Qdrant
vector store class. i.e. `langchain_qdrant.QdrantVectorstore`.
- Deprecates `QdrantSparseVectorRetriever`, since the vector store
implementation natively supports it now.
Resolves#25798
- **Description:** When useing LLM integration moonshot,it's occurring
error "'Moonshot' object has no attribute '_client'",it's because of the
"_client" that is private in pydantic v1.0 so that we can't use it.I
turn "_client" into "client" , the error to be resolved!
- **Issue:** the issue #24390
- **Dependencies:** none
- **Twitter handle:** @Rainsubtime
- [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: Cyue <Cyue_work2001@163.com>
- [x] **PR title - community: add neo4j query constructor for self
query**
- [x] **PR message**
- **Description:** adding a Neo4jTranslator so that the Neo4j vector
database can use SelfQueryRetriever
- **Issue:** this issue had been raised before in #19748
- **Dependencies:** none.
- **Twitter handle:** @moyi_dang
- p.s. I have not added the query constructor in BUILTIN_TRANSLATORS in
this PR, I want to make changes to only one package at a time.
- [x] **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.
- [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/
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.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- [ ] **PR title**: community: add tests for ChatOctoAI
- [ ] **PR message**:
Description: Added unit tests for the ChatOctoAI class in the community
package to ensure proper validation and default values. These tests
verify the correct initialization of fields, the handling of missing
required parameters, and the proper setting of aliases.
Issue: N/A
Dependencies: None
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
Thank you for contributing to LangChain!
community:premai[patch]: standardize init args
- updated `temperature` with Pydantic Field, updated the unit test.
- updated `max_tokens` with Pydantic Field, updated the unit test.
- updated `max_retries` with Pydantic Field, updated the unit test.
Related to #20085
---------
Co-authored-by: Isaac Francisco <78627776+isahers1@users.noreply.github.com>
Co-authored-by: ccurme <chester.curme@gmail.com>
Description: Moves yield to after callback for _astream for gigachat in
the community package
Issue: #16913
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- [x] **PR title**: "community: Patch enable to use Amazon OpenSearch
Serverless for Semantic Cache store"
- [x] **PR message**:
- **Description:** OpenSearchSemanticCache class support Amazon
OpenSearch Serverless for Semantic Cache store, it's only required to
pass auth(http_auth) parameter to initializer
- **Dependencies:** none
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Jinoos Lee <jinoos@amazon.com>
it fixes two issues:
### YGPTs are broken #25575
```
File ....conda/lib/python3.11/site-packages/langchain_community/embeddings/yandex.py:211, in _make_request(self, texts, **kwargs)
..
--> 211 res = stub.TextEmbedding(request, metadata=self._grpc_metadata) # type: ignore[attr-defined]
AttributeError: 'YandexGPTEmbeddings' object has no attribute '_grpc_metadata'
```
My gut feeling that #23841 is the cause.
I have to drop leading underscore from `_grpc_metadata` for quickfix,
but I just don't know how to do it _pydantic_ enough.
### minor issue:
if we use `api_key`, which is not the best practice the code fails with
```
File ~/git/...../python3.11/site-packages/langchain_community/embeddings/yandex.py:119, in YandexGPTEmbeddings.validate_environment(cls, values)
...
AttributeError: 'tuple' object has no attribute 'append'
```
- Added new integration test. But it requires YGPT env available and
active account. I don't know how int tests dis\enabled in CI.
- added small unit tests with mocks. Should be fine.
---------
Co-authored-by: mikhail-khludnev <mikhail_khludnev@rntgroup.com>
Thank you for contributing to LangChain!
- [x] **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"
Support passing extra params when executing UC functions:
The params should be a dictionary with key EXECUTE_FUNCTION_ARG_NAME,
the assumption is that the function itself doesn't use such variable
name (starting and ending with double underscores), and if it does we
raise Exception.
If invalid params passing to the execute_statement, we raise Exception
as well.
- [x] **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.
- [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/
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.
---------
Signed-off-by: Serena Ruan <serena.rxy@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "community: optimize xinference llm import"
- [ ] **PR message**:
- **Description:** from xinferece_client import RESTfulClient when there
is no importing xinference.
- **Dependencies:** xinferece_client
- **Why do so:** the total xinference(pip install xinference[all]) is
too heavy for installing, let alone it is useless for langchain user
except RESTfulClient. The modification has maintained consistency with
the xinference embeddings
[embeddings/xinference](../blob/master/libs/community/langchain_community/embeddings/xinference.py#L89).
**Description:**
Adds the 'score' returned by Pinecone to the
`PineconeHybridSearchRetriever` list of returned Documents.
There is currently no way to return the score when using Pinecone hybrid
search, so in this PR I include it by default.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
### Description
adds an init method to ChatDeepInfra to set the model_name attribute
accordings to the argument
### Issue
currently, the model_name specified by the user during initialization of
the ChatDeepInfra class is never set. Therefore, it always chooses the
default model (meta-llama/Llama-2-70b-chat-hf, however probably since
this is deprecated it always uses meta-llama/Llama-3-70b-Instruct). We
stumbled across this issue and fixed it as proposed in this pull
request. Feel free to change the fix according to your coding guidelines
and style, this is just a proposal and we want to draw attention to this
problem.
### Dependencies
no additional dependencies required
Feel free to contact me or @timo282 and @finitearth if you have any
questions.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
**Description:** Make the hyperlink only appear once in the
extract_hyperlinks tool output. (for some websites output contains
meaningless '#' hyperlinks multiple times which will extend the tokens
of context window without any advantage)
**Issue:** None
**Dependencies:** None
Added Azure Search Access Token Authentication instead of API KEY auth.
Fixes Issue: https://github.com/langchain-ai/langchain/issues/24263
Dependencies: None
Twitter: @levalencia
@baskaryan
Could you please review? First time creating a PR that fixes some code.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This addresses the issue mentioned in #25702
I have updated the endpoint used in validating the endpoint API type in
the AzureMLBaseEndpoint class from `/v1/completions` to `/completions`
and `/v1/chat/completions` to `/chat/completions`.
Co-authored-by: = <=>
- **Description:** Added langchain version while calling discover API
during both ingestion and retrieval
- **Issue:** NA
- **Dependencies:** NA
- **Tests:** NA
- **Docs** NA
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Co-authored-by: dristy.cd <dristy@clouddefense.io>
- **Description:** Updating source path and file path in Pebblo safe
loader for SharePoint apps during loading
- **Issue:** NA
- **Dependencies:** NA
- **Tests:** NA
- **Docs** NA
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Co-authored-by: dristy.cd <dristy@clouddefense.io>
