This is useful if you rely on the `on_tool_end` callback to detect which
tool has finished in a multi agents scenario.
For example, I'm working on a project where I consume the `on_tool_end`
event where the event could be emitted by many agents or tools. Right
now the only way to know which tool has finished would be set a marker
on the `on_tool_start` and catch it on `on_tool_end`.
I didn't want to break the signature of the function, but what would
have been cleaner would be to pass the same details as in
`on_tool_start`
Co-authored-by: blob42 <spike@w530>
seems linkchecker isn't catching them because it runs on generated html.
at that point the links are already missing.
the generation process seems to strip invalid references when they can't
be re-written from md to html.
I used https://github.com/tcort/markdown-link-check to check the doc
source directly.
There are a few false positives on localhost for development.
I have found that when the user has not asked an explicit question the
agent might have trouble answering the latest comment and might instead
try to answer a question that came before in the conversation which
would not be what is desired.
I also found that the agent might get confused with the current prompt
and talk about the tools themselves instead of the results obtained from
them.
I added two changes to the tool prompt so that the agent answers only
the last comment/question and only returns information from tool
results.
# Description
***
Add function similarity_search_limit_score and
similarity_search_with_score
# How to use
***
``
rds = Redis.from_existing_index(embeddings,
redis_url="redis://localhost:6379", index_name='link')
rds.similarity_search_limit_score(query, k=3, score=0.2)
rds.similarity_search_with_score(query, k=3)
``
---------
Co-authored-by: Peter <peter.shi@alephf.com>
I have changed the name of the argument from `where` to `filter` which
is expected by `similarity_search_with_score`.
Fixes#1838
---------
Co-authored-by: Rajat Saxena <hi@rajatsaxena.dev>
Hi, first and foremost, I would like to express my gratitude for your
outstanding work; it's truly remarkable!
https://github.com/hwchase17/langchain/blob/master/langchain/vectorstores/qdrant.py#L134
It appears that there might be a minor issue with the `limit` parameter
being passed incorrectly in the `Qdrant.maximal_marginal_relevance`
function. This seems to be a typographical error.
Signed-off-by: weiyang <weiyang.ones@gmail.com>
I noticed that the "getting started" guide section on agents included an
example test where the agent was getting the question wrong 😅
I guess Olivia Wilde's dating life is too tough to keep track of for
this simple agent example. Let's change it to something a little easier,
so users who are running their agent for the first time are less likely
to be confused by a result that doesn't match that which is on the docs.
Added support for document loaders for Azure Blob Storage using a
connection string. Fixes#1805
---------
Co-authored-by: Mick Vleeshouwer <mick@imick.nl>
Ran into a broken build if bs4 wasn't installed in the project.
Minor tweak to follow the other doc loaders optional package-loading
conventions.
Also updated html docs to include reference to this new html loader.
side note: Should there be 2 different html-to-text document loaders?
This new one only handles local files, while the existing unstructured
html loader handles HTML from local and remote. So it seems like the
improvement was adding the title to the metadata, which is useful but
could also be added to `html.py`
