Fix app.py to use Streamlit implementation and update requirements

app.py

@@ -1,63 +1,88 @@
-from flask import Flask, render_template, request, jsonify
-import os
-import sys
-from datetime import datetime
-
-# Add src to Python path to import models
-sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
-
-app = Flask(__name__)
-
-# Try to import dotenv, if not available, create a simple fallback
-try:
-    from dotenv import load_dotenv
-    load_dotenv()
-except ImportError:
-    def load_dotenv():
-        pass
-
-# Path to your Obsidian vault (synced via OneDrive)
-OBSIDIAN_PATH = os.path.expanduser("~/OneDrive/ObsidianVault")
-
-def get_todays_journal():
-    """"Retrieve today's journal entry from Obsidian vault"""
-    today = datetime.now().strftime("%Y-%m-%d")
-    journal_path = os.path.join(OBSIDIAN_PATH, "Journal", f"{today}.md")
-    
-    if os.path.exists(journal_path):
-        with open(journal_path, "r", encoding="utf-8") as f:
-            return f.read()
-    else:
-        return f"No journal entry found for {today}. Create one in your Obsidian vault!"
-
-# Import and initialize the AI model
-from src.models.model_factory import get_model
-ai_model = get_model()
-
-def ai_coach(prompt):
-    """"Main AI coaching function using the model factory"""
-    context = get_todays_journal()
-    
+# Force redeploy trigger - version 1.1
+import streamlit as st
+from utils.config import config
+import requests
+import json
+from core.memory import load_user_state
+
+# Set page config
+st.set_page_config(page_title="AI Life Coach", page_icon="🧘", layout="centered")
+
+# Sidebar for user selection
+st.sidebar.title("🧘 AI Life Coach")
+user = st.sidebar.selectbox("Select User", ["Rob", "Sarah"])
+st.sidebar.markdown("---")
+
+# Fetch Ollama status
+def get_ollama_status():
     try:
-        return ai_model.generate_response(prompt, context)
-    except Exception as e:
-        return f"Error generating response: {str(e)}"
-
-@app.route('/')
-def index():
-    return render_template('index.html')
-
-@app.route('/coach', methods=['POST'])
-def coach():
-    data = request.get_json()
-    prompt = data.get('prompt', '')
-    
-    if not prompt:
-        return jsonify({'error': 'No prompt provided'}), 400
-    
-    response = ai_coach(prompt)
-    return jsonify({'response': response})
-
-# Required for Hugging Face Spaces
-if __name__ == '__main__':
-    app.run(debug=False, host='0.0.0.0', port=int(os.environ.get('PORT', 7860)))
+        # Add headers to skip ngrok browser warning
+        headers = {
+            "ngrok-skip-browser-warning": "true",
+            "User-Agent": "AI-Life-Coach-App"
+        }
+        response = requests.get("http://localhost:8000/api/ollama-status", headers=headers)
+        if response.status_code == 200:
+            return response.json()
+    except Exception:
+        return {"running": False, "model_loaded": None}
+
+# After user selects name, load conversation history
+def get_conversation_history(user_id):
+    user_state = load_user_state(user_id)
+    if user_state and "conversation" in user_state:
+        return json.loads(user_state["conversation"])
+    return []
+
+ollama_status = get_ollama_status()
+
+# Display Ollama status
+if ollama_status["running"]:
+    st.sidebar.success(f"🧠 Model Running: {ollama_status['model_loaded']}")
+else:
+    st.sidebar.error("🧠 Ollama is not running or no model loaded.")
+
+# Main chat interface
+st.title("🧘 AI Life Coach")
+st.markdown("Talk to your personal development assistant.")
+
+if not ollama_status["running"]:
+    st.warning("⚠️ Ollama is not running. Please start Ollama to use the AI Life Coach.")
+else:
+    # Display conversation history
+    conversation = get_conversation_history(user)
+    for msg in conversation:
+        role = msg["role"].capitalize()
+        content = msg["content"]
+        st.markdown(f"**{role}:** {content}")
+
+    # Chat input
+    user_input = st.text_input("Your message...", key="input")
+    if st.button("Send"):
+        if user_input.strip() == "":
+            st.warning("Please enter a message.")
+        else:
+            # Display user message
+            st.markdown(f"**You:** {user_input}")
+
+            # Send to backend
+            with st.spinner("AI Coach is thinking..."):
+                try:
+                    # Add headers to skip ngrok browser warning
+                    headers = {
+                        "ngrok-skip-browser-warning": "true",
+                        "User-Agent": "AI-Life-Coach-App"
+                    }
+                    response = requests.post(
+                        "http://localhost:8000/api/chat",
+                        json={"user_id": user, "message": user_input},
+                        headers=headers
+                    )
+                    if response.status_code == 200:
+                        response_data = response.json()
+                        ai_response = response_data.get("response", "")
+                        st.markdown(f"**AI Coach:** {ai_response}")
+                    else:
+                        st.error("Failed to get response from AI Coach.")
+                except Exception as e:
+                    st.error(f"Connection error: {e}")

requirements.txt

@@ -1,3 +1,9 @@
-flask==3.1.2
-python-dotenv==1.1.1
-openai==1.106.1
+streamlit==1.24.0
+fastapi==0.95.0
+uvicorn==0.21.1
+redis==5.0.3
+python-dotenv==1.0.0
+openai==1.35.6
+tavily-python>=0.1.0,<1.0.0
+requests==2.31.0
+docker==6.1.3