Delete financial-advisor.py

financial-advisor.py

@@ -1,210 +0,0 @@
-def render_ai_financial_advisor(startup_data):
-    """
-    Render the AI financial advisor page with voice chat capabilities.
-    
-    This feature provides conversational financial guidance to founders through a 
-    natural chat interface with both text and voice responses.
-    """
-    st.markdown("<h1 class='main-header'>AI Financial Advisor</h1>", unsafe_allow_html=True)
-    st.markdown("<p class='sub-header'>Get expert financial guidance through our AI-powered advisor</p>", unsafe_allow_html=True)
-    
-    # How AI helps with financial advisory
-    with st.expander("ℹ️ How AI powers your financial advisor"):
-        st.markdown("""
-        ### How AI Powers Your Financial Advisor
-        
-        Our AI financial advisor combines advanced language models with financial expertise:
-        
-        - **Natural Language Understanding**: The system interprets complex financial questions in plain English
-        - **Domain-Specific Knowledge**: Our AI is trained on startup finance, venture capital, and financial modeling
-        - **Context-Aware Responses**: The advisor takes into account your specific financial situation and history
-        - **Voice Synthesis**: ElevenLabs voice technology creates natural, high-quality voice responses
-        - **Customized Guidance**: AI tailors advice specifically to your stage, industry, and financial position
-        
-        This gives founders 24/7 access to high-quality financial guidance without the high cost of consultants.
-        """)
-    
-    # Chat container
-    st.markdown("<div style='background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;'>", unsafe_allow_html=True)
-    
-    # Display chat history
-    st.subheader("Chat with your Financial Advisor")
-    
-    # Initialize chat history if needed
-    if 'chat_history' not in st.session_state:
-        st.session_state.chat_history = [
-            {"role": "assistant", "content": "Hi there! I'm your AI financial advisor. How can I help with your startup's finances today?"}
-        ]
-    
-    # Display chat messages
-    for message in st.session_state.chat_history:
-        if message["role"] == "user":
-            st.markdown(f"<div style='background-color: #e6f7ff; padding: 10px; border-radius: 10px; margin-bottom: 10px;'><strong>You:</strong> {message['content']}</div>", unsafe_allow_html=True)
-        else:
-            st.markdown(f"<div style='background-color: #f0f7ff; padding: 10px; border-radius: 10px; margin-bottom: 10px;'><strong>Financial Advisor:</strong> {message['content']}</div>", unsafe_allow_html=True)
-            
-            # Show play button for voice if it exists
-            if 'audio' in message and message['audio']:
-                st.audio(message['audio'], format='audio/mp3')
-    
-    # Input for new message
-    col1, col2 = st.columns([5, 1])
-    
-    with col1:
-        user_input = st.text_input("Ask a financial question", key="user_question")
-    
-    with col2:
-        use_voice = st.checkbox("Enable voice", value=True)
-    
-    # Common financial questions
-    st.markdown("### Common Questions")
-    question_cols = st.columns(3)
-    
-    common_questions = [
-        "How much runway do we have at our current burn rate?",
-        "Should we increase our marketing spend given our growth rate?",
-        "When should we start preparing for our next fundraising round?",
-        "How can we optimize our burn rate without impacting growth?",
-        "What metrics should we focus on improving right now?",
-        "How do our unit economics compare to similar startups?"
-    ]
-    
-    selected_question = None
-    
-    for i, question in enumerate(common_questions):
-        with question_cols[i % 3]:
-            if st.button(question, key=f"q_{i}"):
-                selected_question = question
-    
-    # Process user input (either from text input or selected question)
-    if user_input or selected_question:
-        question = user_input or selected_question
-        
-        # Add user message to chat history
-        st.session_state.chat_history.append({"role": "user", "content": question})
-        
-        # Get AI response
-        response = get_advisory_guidance(question, startup_data)
-        
-        # Generate voice response if enabled
-        audio_data = None
-        if use_voice:
-            audio_data = generate_voice_response(response)
-        
-        # Add AI response to chat history
-        st.session_state.chat_history.append({
-            "role": "assistant", 
-            "content": response,
-            "audio": audio_data
-        })
-        
-        # Rerun to display updated chat
-        st.experimental_rerun()
-    
-    st.markdown("</div>", unsafe_allow_html=True)
-    
-    # Advanced options
-    st.subheader("Advanced Tools")
-    
-    tool_cols = st.columns(3)
-    
-    with tool_cols[0]:
-        st.markdown("""
-        <div style='background-color: white; padding: 15px; border-radius: 10px; height: 200px; box-shadow: 0 4px 6px rgba(0,0,0,0.1);'>
-            <h4>Financial Model Review</h4>
-            <p>Upload your financial model for AI analysis and recommendations.</p>
-            <div style='position: absolute; bottom: 15px;'>
-                <input type='file' disabled/>
-            </div>
-        </div>
-        """, unsafe_allow_html=True)
-    
-    with tool_cols[1]:
-        st.markdown("""
-        <div style='background-color: white; padding: 15px; border-radius: 10px; height: 200px; box-shadow: 0 4px 6px rgba(0,0,0,0.1);'>
-            <h4>Investor Pitch Review</h4>
-            <p>Get AI feedback on your investor pitch deck and financial projections.</p>
-            <div style='position: absolute; bottom: 15px;'>
-                <input type='file' disabled/>
-            </div>
-        </div>
-        """, unsafe_allow_html=True)
-    
-    with tool_cols[2]:
-        st.markdown("""
-        <div style='background-color: white; padding: 15px; border-radius: 10px; height: 200px; box-shadow: 0 4px 6px rgba(0,0,0,0.1);'>
-            <h4>Fundraising Strategy</h4>
-            <p>Generate a customized fundraising strategy based on your metrics.</p>
-            <div style='position: absolute; bottom: 15px;'>
-                <button disabled>Generate Strategy</button>
-            </div>
-        </div>
-        """, unsafe_allow_html=True)
-    
-    # Book a session CTA
-    st.markdown("""
-    <div style='background-color: #e6f7ff; padding: 20px; border-radius: 10px; margin-top: 30px;'>
-        <h3>Need more in-depth guidance?</h3>
-        <p>Book a dedicated session with our AI financial advisor for comprehensive analysis and personalized advice.</p>
-        <a href='#book-a-session'><button>Book a Session</button></a>
-    </div>
-    """, unsafe_allow_html=True)
-
-def get_advisory_guidance(question, financial_data):
-    """Get strategic guidance for a startup question."""
-    prompt = f"""
-    You are a strategic financial advisor for startups. A founder asks:
-    "{question}"
-
-    Here's their current financial situation:
-    - Stage: {financial_data['stage']}
-    - Current cash: ${financial_data['cash']}
-    - Monthly burn rate: ${financial_data['burn_rate']}
-    - Monthly revenue: ${financial_data['revenue']}
-    - Monthly growth rate: {financial_data['growth_rate'] * 100}%
-    - Last funding: {financial_data['last_funding']}
-    - Team size: {financial_data['employees']}
-
-    Provide detailed, actionable advice addressing their question. Include:
-    1. Clear assessment of their current situation
-    2. 3-5 specific, actionable recommendations with expected outcomes
-    3. Relevant metrics they should track
-    4. Industry benchmarks for comparison
-    5. Timeline for implementation and results
-
-    Be specific with numbers, timeframes, and expected outcomes.
-    """
-    
-    return generate_ai_response(prompt)
-
-def generate_voice_response(text):
-    """Generate voice response using ElevenLabs API (simulated)."""
-    try:
-        # In a real implementation, this would call the ElevenLabs API
-        # For demonstration, we'll simulate an audio response
-        
-        # Simulated audio data (just an empty response)
-        audio_data = b''
-        
-        # In a real implementation, you would do something like:
-        # url = "https://api.elevenlabs.io/v1/text-to-speech/{voice_id}"
-        # headers = {
-        #     "Accept": "audio/mpeg",
-        #     "Content-Type": "application/json",
-        #     "xi-api-key": st.secrets["ELEVENLABS_API_KEY"]
-        # }
-        # data = {
-        #     "text": text,
-        #     "model_id": "eleven_monolingual_v1",
-        #     "voice_settings": {
-        #         "stability": 0.5,
-        #         "similarity_boost": 0.5
-        #     }
-        # }
-        # response = requests.post(url, json=data, headers=headers)
-        # audio_data = response.content
-        
-        return audio_data
-    except Exception as e:
-        st.warning(f"Error generating voice response: {e}")
-        return None