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Rahul Bhoyar
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72c4532
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Parent(s):
0541d4f
Updated file
Browse files
app.py
CHANGED
@@ -15,40 +15,39 @@ def read_pdf(uploaded_file):
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return text
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main()
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return text
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st.title("PdfQuerier using LLAMA by Rahul Bhoyar")
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hf_token = st.text_input("Enter your Hugging Face token:")
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llm = HuggingFaceInferenceAPI(model_name="HuggingFaceH4/zephyr-7b-alpha", token=hf_token)
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st.markdown("Query your pdf file data with using this chatbot.")
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uploaded_file = st.file_uploader("Choose a PDF file", type=["pdf"])
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# Creation of Embedding model
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embed_model_uae = HuggingFaceEmbedding(model_name="WhereIsAI/UAE-Large-V1")
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service_context = ServiceContext.from_defaults(llm=llm, chunk_size=800, chunk_overlap=20, embed_model=embed_model_uae)
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file_contents = read_pdf(uploaded_file)
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documents = Document(text=file_contents)
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documents = [documents]
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st.success("Documents loaded successfully!")
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# Indexing the documents
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progress_container = st.empty()
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progress_container.text("Creating VectorStoreIndex...")
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# Code to create VectorStoreIndex
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index = VectorStoreIndex.from_documents(documents, service_context=service_context, show_progress=True)
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# Persist Storage Context
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index.storage_context.persist()
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st.success("VectorStoreIndex created successfully!")
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# Create Query Engine
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query = st.text_input("Ask a question:")
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query_engine = index.as_query_engine()
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if query:
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# Run Query
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progress_container.text("Fetching the response...")
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response = query_engine.query(query)
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st.markdown(f"**Response:** {response}")
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