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>
When the code ran by the PythonAstREPLTool contains multiple statements
it will fallback to exec() instead of using eval(). With this change, it
will also return the output of the code in the same way the
PythonREPLTool will.
In #2399 we added the ability to set `max_execution_time` when creating
an AgentExecutor. This PR adds the `max_execution_time` argument to the
built-in pandas, sql, and openapi agents.
Co-authored-by: Zachary Jones <zjones@zetaglobal.com>
### Summary
Adds support for processing non HTML document types in the URL loader.
For example, the URL loader can now process a PDF or markdown files
hosted at a URL.
### Testing
```python
from langchain.document_loaders import UnstructuredURLLoader
urls = ["https://www.understandingwar.org/sites/default/files/Russian%20Offensive%20Campaign%20Assessment%2C%20April%2011%2C%202023.pdf"]
loader = UnstructuredURLLoader(urls=urls, strategy="fast")
docs = loader.load()
print(docs[0].page_content[:1000])
```
Updated the "load_memory_variables" function of the
ConversationBufferWindowMemory to support a window size of 0 (k=0).
Previous behavior would return the full memory instead of an empty
array.
Eval chain is currently very sensitive to differences in phrasing,
punctuation, and tangential information. This prompt has worked better
for me on my examples.
More general q: Do we have any framework for evaluating default prompt
changes? Could maybe start doing some regression testing?
Currently, the output type of a number of OutputParser's `parse` methods
is `Any` when it can in fact be inferred.
This PR makes BaseOutputParser use a generic type and fixes the output
types of the following parsers:
- `PydanticOutputParser`
- `OutputFixingParser`
- `RetryOutputParser`
- `RetryWithErrorOutputParser`
The output of the `StructuredOutputParser` is corrected from `BaseModel`
to `Any` since there are no type guarantees provided by the parser.
Fixes issue #2715
This PR proposes
- An NLAToolkit method to instantiate from an AI Plugin URL
- A notebook that shows how to use that alongside an example of using a
Retriever object to lookup specs and route queries to them on the fly
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
**Problem:**
The `from_documents` method in Qdrant vectorstore is unnecessary because
it does not change any default behavior from the abstract base class
method of `from_documents` (contrast this with the method in Chroma
which makes a change from default and turns `embeddings` into an
Optional parameter).
Also, the docstrings need some cleanup.
**Solution:**
Remove unnecessary method and improve docstrings.
---------
Co-authored-by: Vijay Rajaram <vrajaram3@gatech.edu>
