Using Document to perform question answering task#11
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aaroosh-07 wants to merge 3 commits intomainfrom
Open
Using Document to perform question answering task#11aaroosh-07 wants to merge 3 commits intomainfrom
aaroosh-07 wants to merge 3 commits intomainfrom
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3 tasks
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| Activate the python virtual environment | ||
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| ### hfQnA.py |
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You need to give a hint to the reader what these two different scripts are used for?
| import os | ||
| import sys | ||
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| def load_and_split_doc(path: str): |
Collaborator
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You should be type hinting at the returns of each method too
| return context | ||
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| def run_rag(): | ||
| choice = input("Do you want to load the document(y/n): ") |
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Is this not - Do you want to upload a new document?
| chunks = text_splitter.split_documents(docs) | ||
| return chunks | ||
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| def load_chunks_to_vectorstore(chunks): |
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What type is chunks?
prattyushmangal
requested changes
Sep 7, 2024
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prattyushmangal
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prattyushmangal
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Good work, but almost all the functions in DocQnA are unit testable - so please add them along withsome other minor changes.
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In this PR, we are adding a script to perform question answering task using document pdf file provided by the user. To achieve this we have implemented a RAG which breaks down document into multiple chunks and stores them in Chroma DB using hugging Face embedding model. and uses question to query for relevant chunks and perform QnA task on those chunks.