Adds a cookbook for semi-structured RAG via Docugami. This follows the
same outline as the semi-structured RAG with Unstructured cookbook:
https://github.com/langchain-ai/langchain/blob/master/cookbook/Semi_Structured_RAG.ipynb
The main change is this cookbook uses Docugami instead of Unstructured
to find text and tables, and shows how XML markup in the output helps
with retrieval and generation.
We are \@docugami on twitter, I am \@tjaffri
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Co-authored-by: Taqi Jaffri <tjaffri@docugami.com>
The new ruff version fixed the blocking bugs, and I was able to fairly
easily us to a passing state: ruff fixed some issues on its own, I fixed
a handful by hand, and I added a list of narrowly-targeted exclusions
for files that are currently failing ruff rules that we probably should
look into eventually.
I went pretty lenient on the docs / cookbooks rules, allowing dead code
and such things. Perhaps in the future we may want to tighten the rules
further, but this is already a good set of checks that found real issues
and will prevent them going forward.
Hi,
this PR adds support for OpenAI API v1 for Azure OpenAI completion API.
@baskaryan @hwchase17
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Co-authored-by: Bagatur <baskaryan@gmail.com>
added Parallel Function Calling for Structured Data Extraction notebook
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---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This patch fixes a spelling typo in message
within wikibase_agent.ipynb.
Signed-off-by: Masanari Iida <standby24x7@gmail.com>
Signed-off-by: Masanari Iida <standby24x7@gmail.com>
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Replace this entire comment with:
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- **Issue:** the issue # it fixes (if applicable),
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maintainer (see below),
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gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
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If you're adding a new integration, please include:
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network access,
2. an example notebook showing its use. It lives in `docs/extras`
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Cookbook showing how to incoporate RAG search within a postgreSQL
database using pgvector.
---------
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
I have fixed some typos in file
`cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb`. I kindly
request the repo maintainers to review and merge it. Thanks!
