Add chat endpoint, model selector, and improved AI analysis

app.py

@@ -966,6 +966,41 @@ Report generated by IT Site Survey AI<br>
     return jsonify({'email_body': email_body})
 
 
+@app.route("/api/surveys/<survey_id>/chat", methods=["POST"])
+def chat_with_ai(survey_id):
+    survey = surveys_db.get(survey_id)
+    if not survey:
+        return jsonify({"error": "Survey not found"}), 404
+    
+    data = request.get_json() or {}
+    user_message = data.get("message", "")
+    chat_history = data.get("history", [])
+    model = data.get("model", DEFAULT_MODEL)
+    
+    latest_response = survey["responses"][-1] if survey["responses"] else None
+    responses = latest_response["responses"] if latest_response else {}
+    
+    survey_context = f"Client: {survey.get("client_name", "Unknown")}\nSite: {survey.get("site_name", "Unknown")}\n\nSurvey Responses:\n"
+    for q in survey["questions"]:
+        qid = q["id"]
+        answer = responses.get(qid, "Not answered")
+        survey_context += f"{q["question"]}: {answer}\n"
+    
+    messages = [{"role": "system", "content": f"You are a network infrastructure expert reviewing this survey: {survey_context}"}]
+    for msg in chat_history:
+        messages.append(msg)
+    messages.append({"role": "user", "content": user_message})
+    
+    try:
+        resp = requests.post(f"{OLLAMA_BASE}/api/chat", json={"model": model, "messages": messages, "stream": False}, timeout=120)
+        if resp.status_code == 200:
+            result = resp.json()
+            return jsonify({"response": result.get("message", {}).get("content", "No response")})
+        else:
+            return jsonify({"error": f"Ollama error: {resp.status_code}"}), 500
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
 if __name__ == '__main__':
     port = int(os.environ.get('PORT', 3003))
     print("───────────────────────────────────────")