# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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## Screenshots (if appropriate):
- Added a new file `basic_rag_workflow.yaml` to the `examples/chatbot`
directory.
- Configured a standard RAG workflow with multiple nodes and edges.
- Set the maximum number of previous conversation iterations to include
in the answer context.
- Added configuration for the LLM (Language Model) with maximum output
tokens and temperature.
# Description
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## Checklist before requesting a review
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## Screenshots (if appropriate):
# Description
This PR includes far too many new features:
- detection of user intent (closes CORE-211)
- treating multiple questions in parallel (closes CORE-212)
- using the chat history when answering a question (closes CORE-213)
- filtering of retrieved chunks by relevance threshold (closes CORE-217)
- dynamic retrieval of chunks (closes CORE-218)
- enabling web search via Tavily (closes CORE-220)
- enabling agent / assistant to activate tools when relevant to complete
the user task (closes CORE-224)
Also closes CORE-205
## Checklist before requesting a review
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## Screenshots (if appropriate):
---------
Co-authored-by: Stan Girard <stan@quivr.app>
# Description
Added some initial documentation on RAG workflows, including also some
nice Excalidraw diagrams
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## Checklist before requesting a review
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## Screenshots (if appropriate):
# Description
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## Checklist before requesting a review
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## Screenshots (if appropriate):
# Description
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## Screenshots (if appropriate):
# Description
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# Description
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## Checklist before requesting a review
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# Description
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## Checklist before requesting a review
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## Screenshots (if appropriate):
# Description
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## Checklist before requesting a review
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# Description
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## Checklist before requesting a review
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# Description
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## Checklist before requesting a review
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# Description
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## Checklist before requesting a review
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# Description
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# Description
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## Checklist before requesting a review
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## Screenshots (if appropriate):
Refactor the get_user_credits method in the Users class to improve the
calculation of monthly chat credits for a user. This change ensures that
the user's monthly chat credit is correctly deducted based on their
usage. If no user settings or monthly chat credit is found, a default
value of 25 is returned.
# Description
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## Checklist before requesting a review
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## Screenshots (if appropriate):
Our default pdf parser is Unstructured, for which we were using the
'fast' strategy, which fails in parsing some pdf. We instead use the
'auto' strategy which is more flexible and powerful.
Closes TICK-86
# Description
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## Checklist before requesting a review
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## Screenshots (if appropriate):
---------
Co-authored-by: chloedia <chloedaems0@gmail.com>