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import streamlit as st |
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from src.pipeline import QAPipeline |
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from langchain_community.document_loaders import CSVLoader |
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import os |
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import tempfile |
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import asyncio |
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import nest_asyncio |
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nest_asyncio.apply() |
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os.environ["STREAMLIT_WATCHER_IGNORE_PATTERNS"] = "*/torch/*" |
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pipeline = QAPipeline() |
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st.title("Recipe Q&A") |
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st.header("Upload CSV") |
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uploaded_file = st.file_uploader("Choose a CSV file", type="csv") |
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if uploaded_file is not None: |
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if st.button("Add Documents"): |
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with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as tmp_file: |
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tmp_file.write(uploaded_file.read()) |
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tmp_path = tmp_file.name |
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loader = CSVLoader(file_path=tmp_path) |
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data = loader.load() |
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with st.spinner("Uploading documents..."): |
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asyncio.run(pipeline.upload_documents(data)) |
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os.remove(tmp_path) |
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st.success("Documents uploaded successfully.") |
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st.header("Ask a Question") |
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query = st.text_input("Enter your question:") |
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if "response" not in st.session_state: |
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st.session_state.response = None |
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if st.button("Get Answer") and query: |
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with st.spinner("Getting answer..."): |
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response = asyncio.run(pipeline.answer_query_(query)) |
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st.session_state.response = response |
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st.write("**Answer:**") |
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st.write(response.answer) |
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if st.session_state.response: |
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if st.session_state.response.web_search: |
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if st.button("Search the web for this?"): |
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with st.spinner("Searching web..."): |
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web_response = asyncio.run(pipeline.search_web(query)) |
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if web_response: |
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st.write("**Web Search Result:**") |
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st.write(web_response) |
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else: |
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st.write("No web search result found.") |
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