# docs: updated `Supabase` notebook
- the title of the notebook was inconsistent (included redundant
"Vectorstore"). Removed this "Vectorstore"
- added `Postgress` to the title. It is important. The `Postgres` name
is much more popular than `Supabase`.
- added description for the `Postrgress`
- added more info to the `Supabase` description
# Fix bilibili api import error
bilibili-api package is depracated and there is no sync module.
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Fixes#2673#2724
## Before submitting
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# TextLoader auto detect encoding and enhanced exception handling
- Add an option to enable encoding detection on `TextLoader`.
- The detection is done using `chardet`
- The loading is done by trying all detected encodings by order of
confidence or raise an exception otherwise.
### New Dependencies:
- `chardet`
Fixes#4479
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---------
Co-authored-by: blob42 <spike@w530>
# Load specific file types from Google Drive (issue #4878)
Add the possibility to define what file types you want to load from
Google Drive.
```
loader = GoogleDriveLoader(
folder_id="1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5",
file_types=["document", "pdf"]
recursive=False
)
```
Fixes ##4878
## Who can review?
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DataLoaders
- @eyurtsev
Twitter: [@UmerHAdil](https://twitter.com/@UmerHAdil) | Discord:
RicChilligerDude#7589
---------
Co-authored-by: UmerHA <40663591+UmerHA@users.noreply.github.com>
#docs: text splitters improvements
Changes are only in the Jupyter notebooks.
- added links to the source packages and a short description of these
packages
- removed " Text Splitters" suffixes from the TOC elements (they made
the list of the text splitters messy)
- moved text splitters, based on the length function into a separate
list. They can be mixed with any classes from the "Text Splitters", so
it is a different classification.
## Who can review?
@hwchase17 - project lead
@eyurtsev
@vowelparrot
NOTE: please, check out the results of the `Python code` text splitter
example (text_splitters/examples/python.ipynb). It looks suboptimal.
# Docs: improvements in the `retrievers/examples/` notebooks
Its primary purpose is to make the Jupyter notebook examples
**consistent** and more suitable for first-time viewers.
- add links to the integration source (if applicable) with a short
description of this source;
- removed `_retriever` suffix from the file names (where it existed) for
consistency;
- removed ` retriever` from the notebook title (where it existed) for
consistency;
- added code to install necessary Python package(s);
- added code to set up the necessary API Key.
- very small fixes in notebooks from other folders (for consistency):
- docs/modules/indexes/vectorstores/examples/elasticsearch.ipynb
- docs/modules/indexes/vectorstores/examples/pinecone.ipynb
- docs/modules/models/llms/integrations/cohere.ipynb
- fixed misspelling in langchain/retrievers/time_weighted_retriever.py
comment (sorry, about this change in a .py file )
## Who can review
@dev2049
# Fixed typos (issues #4818 & #4668 & more typos)
- At some places, it said `model = ChatOpenAI(model='gpt-3.5-turbo')`
but should be `model = ChatOpenAI(model_name='gpt-3.5-turbo')`
- Fixes some other typos
Fixes#4818, #4668
## Who can review?
Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:
Models
- @hwchase17
- @agola11
Agents / Tools / Toolkits
- @vowelparrot
# Fix Telegram API loader + add tests.
I was testing this integration and it was broken with next error:
```python
message_threads = loader._get_message_threads(df)
KeyError: False
```
Also, this particular loader didn't have any tests / related group in
poetry, so I added those as well.
@hwchase17 / @eyurtsev please take a look on this fix PR.
---------
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
### Adds a document loader for Docugami
Specifically:
1. Adds a data loader that talks to the [Docugami](http://docugami.com)
API to download processed documents as semantic XML
2. Parses the semantic XML into chunks, with additional metadata
capturing chunk semantics
3. Adds a detailed notebook showing how you can use additional metadata
returned by Docugami for techniques like the [self-querying
retriever](https://python.langchain.com/en/latest/modules/indexes/retrievers/examples/self_query_retriever.html)
4. Adds an integration test, and related documentation
Here is an example of a result that is not possible without the
capabilities added by Docugami (from the notebook):
<img width="1585" alt="image"
src="https://github.com/hwchase17/langchain/assets/749277/bb6c1ce3-13dc-4349-a53b-de16681fdd5b">
---------
Co-authored-by: Taqi Jaffri <tjaffri@docugami.com>
Co-authored-by: Taqi Jaffri <tjaffri@gmail.com>
**Problem statement:** the
[document_loaders](https://python.langchain.com/en/latest/modules/indexes/document_loaders.html#)
section is too long and hard to comprehend.
**Proposal:** group document_loaders by 3 classes: (see `Files changed`
tab)
UPDATE: I've completely reworked the document_loader classification.
Now this PR changes only one file!
FYI @eyurtsev @hwchase17
Thanks to @anna-charlotte and @jupyterjazz for the contribution! Made
few small changes to get it across the finish line
---------
Signed-off-by: anna-charlotte <charlotte.gerhaher@jina.ai>
Signed-off-by: jupyterjazz <saba.sturua@jina.ai>
Co-authored-by: anna-charlotte <charlotte.gerhaher@jina.ai>
Co-authored-by: jupyterjazz <saba.sturua@jina.ai>
Co-authored-by: Saba Sturua <45267439+jupyterjazz@users.noreply.github.com>
# ODF File Loader
Adds a data loader for handling Open Office ODT files. Requires
`unstructured>=0.6.3`.
### Testing
The following should work using the `fake.odt` example doc from the
[`unstructured` repo](https://github.com/Unstructured-IO/unstructured).
```python
from langchain.document_loaders import UnstructuredODTLoader
loader = UnstructuredODTLoader(file_path="fake.odt", mode="elements")
loader.load()
loader = UnstructuredODTLoader(file_path="fake.odt", mode="single")
loader.load()
```
- added `Wikipedia` retriever. It is effectively a wrapper for
`WikipediaAPIWrapper`. It wrapps load() into get_relevant_documents()
- sorted `__all__` in the `retrievers/__init__`
- added integration tests for the WikipediaRetriever
- added an example (as Jupyter notebook) for the WikipediaRetriever
# Fix grammar in Text Splitters docs
Just a small fix of grammar in the documentation:
"That means there two different axes" -> "That means there are two
different axes"
- Added the `Wikipedia` document loader. It is based on the existing
`unilities/WikipediaAPIWrapper`
- Added a respective ut-s and example notebook
- Sorted list of classes in __init__
- made notebooks consistent: titles, service/format descriptions.
- corrected short names to full names, for example, `Word` -> `Microsoft
Word`
- added missed descriptions
- renamed notebook files to make ToC correctly sorted
This implements a loader of text passages in JSON format. The `jq`
syntax is used to define a schema for accessing the relevant contents
from the JSON file. This requires dependency on the `jq` package:
https://pypi.org/project/jq/.
---------
Signed-off-by: Aivin V. Solatorio <avsolatorio@gmail.com>
