Update system to use remote Ollama host with graceful fallback handling and sync with remote changes

app.py

@@ -1,77 +1,63 @@
-# 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():
+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()
+    
     try:
-        response = requests.get("http://localhost:8000/api/ollama-status")
-        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}")
+        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
     
-    # 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}")
+    response = ai_coach(prompt)
+    return jsonify({'response': response})
 
-            # Send to backend
-            with st.spinner("AI Coach is thinking..."):
-                try:
-                    response = requests.post(
-                        "http://localhost:8000/api/chat",
-                        json={"user_id": user, "message": user_input}
-                    )
-                    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}")
+# Required for Hugging Face Spaces
+if __name__ == '__main__':
+    app.run(debug=False, host='0.0.0.0', port=int(os.environ.get('PORT', 7860)))

requirements.txt

@@ -1,9 +1,3 @@
-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
+flask==3.1.2
+python-dotenv==1.1.1
+openai==1.106.1