# 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>
- **Description:** Update UC toolkit documentation to show an example of
using recommended LangGraph agent APIs before the existing LangChain
AgentExecutor example. Tested by manually running the updated example
notebook
- **Dependencies:** No new dependencies
---------
Signed-off-by: Sid Murching <sid.murching@databricks.com>
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.
- **Description:** Adding in the first pass of documentation for the CDP
Agentkit Toolkit
- **Issue:** N/a
- **Dependencies:** cdp-langchain
- **Twitter handle:** @CoinbaseDev
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: John Peterson <john.peterson@coinbase.com>
…Toolkit" in "playwright.ipynb" integration.
- Completed the incomplete sentence in the Langchain Playwright
documentation.
- Enhanced documentation clarity to guide users on best practices for
instantiating browser instances with Langchain Playwright.
Example before:
> "It's always recommended to instantiate using the from_browser method
so that the
Example after:
> "It's always recommended to instantiate using the `from_browser`
method so that the browser context is properly initialized and managed,
ensuring seamless interaction and resource optimization."
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:**
This PR addresses an issue in the CSVLoader example where data is not
defined, causing a NameError. The line `data = loader.load()` is added
to correctly assign the output of loader.load() to the data variable.
Thank you for contributing to LangChain!
Update references in Databricks integration page to reference our new
partner package databricks-langchain
https://github.com/databricks/databricks-ai-bridge/tree/main/integrations/langchain
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: Prithvi Kannan <prithvi.kannan@databricks.com>
**Description:**
I added code for lora_request in the community package, but I forgot to
add content to the VLLM page. So, I will do that now. #27731
---------
Co-authored-by: Um Changyong <changyong.um@sfa.co.kr>
**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>
`ChatDatabricks` added support for structured output and JSON mode in
the last release. This PR updates the feature table accordingly.
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
### Description/Issue:
I had problems filtering when setting up a local Milvus db and noticed
that the `filter` option in the `similarity_search` and
`similarity_search_with_score` appeared to do nothing. Instead, the
`expr` option should be used.
The `expr` option is correctly used in the retriever example further
down in the documentation.
The `expr` option seems to be correctly passed on, for example
[here](447c0dd2f0/libs/community/langchain_community/vectorstores/milvus.py (L701))
### Solution:
Update the documentation for the functions mentioned to show intended
behavior.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
* **PR title**: "docs: Replaced langchain import with
langchain-nvidia-ai-endpoints in NVIDIA Endpoints Tab"
* **PR message**:
+ **Description:** Replaced the import of `langchain` with
`langchain-nvidia-ai-endpoints` in the NVIDIA Endpoints Tab to resolve
an error caused by the documentation attempting to import the generic
`langchain` module despite the targeted import.
+ **Issue:**
+ **Dependencies:** No additional dependencies introduced; simply
updated the existing import to a more specific module.
+ **Twitter handle:** https://x.com/nawaz0x1
* **Add tests and docs**:
+ **Applicability:** Not applicable in this case, as the change is a fix
to an existing integration rather than the addition of a new one.
+ **Rationale:** No new functionality or integrations are introduced,
only a corrective import change.
* **Lint and test**:
+ **Status:** Completed
+ **Outcome:**
- `make format`: **Passed**
- `make lint`: **Passed**
- `make test`: **Passed**
Thank you for contributing to LangChain!
Add notice of upcoming package consolidation of `langchain-databricks`
into `databricks-langchain`.
<img width="1047" alt="image"
src="https://github.com/user-attachments/assets/18eaa394-4e82-444b-85d5-7812be322674">
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: Prithvi Kannan <prithvi.kannan@databricks.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Updated the documentation to fix some grammar errors
- **Description:** Some language errors exist in the documentation
- **Issue:** the issue # Changed the structure of some sentences
**PR Title**: `docs: fix typo in query analysis documentation`
**Description**: This PR corrects a typo on line 68 in the query
analysis documentation, changing **"pharsings"** to **"phrasings"** for
clarity and accuracy. Only one instance of the typo was fixed in the
last merge, and this PR fixes the second instance.
**Issue**: N/A
**Dependencies**: None
**Additional Notes**: No functional changes were made; this is a
documentation fix only.
Edited various notebooks in the tutorial section to fix:
* Grammatical Errors
* Improve Readability by changing the sentence structure or reducing
repeated words which bears the same meaning
* Edited a code block to follow the PEP 8 Standard
* Added more information in some sentences to make the concept more
clear and reduce ambiguity
---------
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
**PR Title**: `docs: fix typo in query analysis documentation`
**Description**: This PR corrects a typo on line 68 in the query
analysis documentation, changing **"pharsings"** to **"phrasings"** for
clarity and accuracy.
**Issue**: N/A
**Dependencies**: None
**Additional Notes**: No functional changes were made; this is a
documentation fix only.
