Last week I added the `PDFMinerPDFasHTMLLoader`. I am adding some
example code in the notebook to serve as a tutorial for how that loader
can be used to create snippets of a pdf that are structured within
sections. All the other loaders only provide the `Document` objects
segmented by pages but that's pretty loose given the amount of other
metadata that can be extracted.
With the new loader, one can leverage font-size of the text to decide
when a new sections starts and can segment the text more semantically as
shown in the tutorial notebook. The cell shows that we are able to find
the content of entire section under **Related Work** for the example pdf
which is spread across 2 pages and hence is stored as two separate
documents by other loaders
Add SVM retriever class, based on
https://github.com/karpathy/randomfun/blob/master/knn_vs_svm.ipynb.
Testing still WIP, but the logic is correct (I have a local
implementation outside of Langchain working).
---------
Co-authored-by: Lance Martin <122662504+PineappleExpress808@users.noreply.github.com>
Co-authored-by: rlm <31treehaus@31s-MacBook-Pro.local>
Minor cosmetic changes
- Activeloop environment cred authentication in notebooks with
`getpass.getpass` (instead of CLI which not always works)
- much faster tests with Deep Lake pytest mode on
- Deep Lake kwargs pass
Notes
- I put pytest environment creds inside `vectorstores/conftest.py`, but
feel free to suggest a better location. For context, if I put in
`test_deeplake.py`, `ruff` doesn't let me to set them before import
deeplake
---------
Co-authored-by: Davit Buniatyan <d@activeloop.ai>
Note to self: Always run integration tests, even on "that last minute
change you thought would be safe" :)
---------
Co-authored-by: Mike Lambert <mike.lambert@anthropic.com>
**About**
Specify encoding to avoid UnicodeDecodeError when reading .txt for users
who are following the tutorial.
**Reference**
```
return codecs.charmap_decode(input,self.errors,decoding_table)[0]
UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position 1205: character maps to <undefined>
```
**Environment**
OS: Win 11
Python: 3.8
Allows users to specify what files should be loaded instead of
indiscriminately loading the entire repo.
extends #2851
NOTE: for reviewers, `hide whitespace` option recommended since I
changed the indentation of an if-block to use `continue` instead so it
looks less like a Christmas tree :)
Fixes linting issue from #2835
Adds a loader for Slack Exports which can be a very valuable source of
knowledge to use for internal QA bots and other use cases.
```py
# Export data from your Slack Workspace first.
from langchain.document_loaders import SLackDirectoryLoader
SLACK_WORKSPACE_URL = "https://awesome.slack.com"
loader = ("Slack_Exports", SLACK_WORKSPACE_URL)
docs = loader.load()
```
Have seen questions about whether or not the `SQLDatabaseChain` supports
more than just sqlite, which was unclear in the docs, so tried to
clarify that and how to connect to other dialects.
The doc loaders index was picking up a bunch of subheadings because I
mistakenly made the MD titles H1s. Fixed that.
also the easy minor warnings from docs_build
I was testing out the WhatsApp Document loader, and noticed that
sometimes the date is of the following format (notice the additional
underscore):
```
3/24/23, 1:54_PM - +91 99999 99999 joined using this group's invite link
3/24/23, 6:29_PM - +91 99999 99999: When are we starting then?
```
Wierdly, the underscore is visible in Vim, but not on editors like
VSCode. I presume it is some unusual character/line terminator.
Nevertheless, I think handling this edge case will make the document
loader more robust.
Adds a loader for Slack Exports which can be a very valuable source of
knowledge to use for internal QA bots and other use cases.
```py
# Export data from your Slack Workspace first.
from langchain.document_loaders import SLackDirectoryLoader
SLACK_WORKSPACE_URL = "https://awesome.slack.com"
loader = ("Slack_Exports", SLACK_WORKSPACE_URL)
docs = loader.load()
```
---------
Co-authored-by: Mikhail Dubov <mikhail@chattermill.io>
I've added a bilibili loader, bilibili is a very active video site in
China and I think we need this loader.
Example:
```python
from langchain.document_loaders.bilibili import BiliBiliLoader
loader = BiliBiliLoader(
["https://www.bilibili.com/video/BV1xt411o7Xu/",
"https://www.bilibili.com/video/av330407025/"]
)
docs = loader.load()
```
Co-authored-by: 了空 <568250549@qq.com>
**Description**
Add custom vector field name and text field name while indexing and
querying for OpenSearch
**Issues**
https://github.com/hwchase17/langchain/issues/2500
Signed-off-by: Naveen Tatikonda <navtat@amazon.com>
Took me a bit to find the proper places to get the API keys. The link
earlier provided to setup search is still good, but why not provide
direct link to the Google cloud tools that give you ability to create
keys?
`combine_docs` does not go through the standard chain call path which
means that chain callbacks won't be triggered, meaning QA chains won't
be traced properly, this fixes that.
Also fix several errors in the chat_vector_db notebook
