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Update app.py
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app.py
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import streamlit as st
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from services.claude_service import ClaudeService
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def show_chart_analysis_tab(claude_service, analysis_service):
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"""Display chart analysis functionality"""
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# Get user expertise level
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expertise_level = create_expertise_selector()
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# Create sidebar and get inputs
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upload_option, uploaded_files, patterns, indicators, comparison_type = create_sidebar()
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# Main content area
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col1, col2 = st.columns([2, 1])
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with col1:
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st.title("📈 Stock Chart Analysis Assistant")
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if upload_option == "Ask Question":
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question = st.text_input(
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"What would you like to know?",
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key="main_question_input"
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)
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# Main analysis section
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if uploaded_files:
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# Store all uploaded images
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st.session_state.current_images = [file.getvalue() for file in uploaded_files]
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analyze_clicked = show_analysis_section(uploaded_files)
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# Store analysis results in session state
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if 'analysis_results' not in st.session_state:
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st.session_state.analysis_results = []
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if analyze_clicked:
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if not uploaded_files:
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st.warning("Please upload at least one chart.")
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else:
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with st.spinner("Analyzing charts..."):
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results = analysis_service.analyze_multiple_charts(
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st.session_state.current_images,
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patterns,
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indicators,
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comparison_type,
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expertise_level
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)
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if results:
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st.session_state.current_analysis = results[-1]['analysis']
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st.session_state.chat_history.extend(results)
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st.session_state.analysis_results = results
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# Display analysis results from session state
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if st.session_state.analysis_results:
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results = st.session_state.analysis_results
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# First show comparative analysis if it exists
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for result in results:
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if result.get('analysis_type') != 'Individual':
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with st.container():
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st.subheader(f"{result['analysis_type']} Results")
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st.markdown(result['analysis'])
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# Add follow-up section immediately after analysis
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follow_up = show_follow_up_section(f"comparative_followup")
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if follow_up:
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with st.spinner("Processing follow-up..."):
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response = analysis_service.handle_follow_up_question(
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follow_up,
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result['analysis'],
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st.session_state.current_images
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)
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if response:
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st.session_state.chat_history.append(response)
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st.markdown(response['analysis'])
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# Then show individual analyses
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individual_analyses = [r for r in results if r.get('analysis_type') == 'Individual']
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for idx, result in enumerate(individual_analyses):
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with st.container():
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st.subheader(f"Analysis Results - Chart {idx + 1}")
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st.markdown(result['analysis'])
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# Add follow-up section for each analysis
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container_key = f"individual_followup_{idx}"
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follow_up = show_follow_up_section(container_key)
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if follow_up:
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with st.spinner("Processing follow-up..."):
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response = analysis_service.handle_follow_up_question(
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follow_up,
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result['analysis'],
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st.session_state.current_images[idx] if idx < len(st.session_state.current_images) else None
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)
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if response:
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st.session_state.chat_history.append(response)
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st.markdown(response['analysis'])
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# Risk warning at the bottom
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st.warning(
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"⚠️ This analysis is AI-generated and for informational purposes only. "
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"Do not make trading decisions solely based on this information."
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)
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with col2:
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# Chat history
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show_chat_history(st.session_state.chat_history)
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# Save options
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save_name = show_save_options()
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if save_name and st.session_state.chat_history:
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filename = save_chat_history(
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st.session_state.chat_history,
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st.session_state.current_images[0] if st.session_state.current_images else None,
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f"{save_name}.json" if save_name else None
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)
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if filename:
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st.success(f"Chat saved as {filename}")
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else:
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st.info("Chat saved to session state")# app.py
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import streamlit as st
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from services.claude_service import ClaudeService
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