Update app.py

app.py

@@ -2,9 +2,11 @@ import os
 import json
 import random
 import datetime
+from flask import Flask, request, jsonify
 from transformers import pipeline
 from geopy.geocoders import Nominatim
-import gradio as gr
+
+app = Flask(__name__)
 
 # ------------------------------
 # 💬 Emotion Analyzer Pipeline
@@ -54,6 +56,7 @@ def detect_crisis(text):
     ]
     return any(signal in text.lower() for signal in crisis_signals)
 
+# Geo-based crisis helpline lookup
 def get_geo_helpline(location_query="world"):
     helplines = {
         "india": "AASRA Helpline: 91-9820466726 or 91-22-27546669",
@@ -99,19 +102,16 @@ def enrich_response(reply_text):
     return reply_text
 
 # ------------------------------
-# 🧠 Generate AI Response
+# 🧠 Generate AI Response (Simulated)
 # ------------------------------
-def generate_supportive_reply(user_input, user_name="Friend", user_age="20"):
+def generate_supportive_reply(user_input, user_name, user_age):
     emotions = emotion_analyzer(user_input)[0]
     dominant_emotion = max(emotions, key=lambda x: x["score"])["label"].lower()
 
     # Crisis response
     if detect_crisis(user_input):
-        try:
-            geo = Nominatim(user_agent="support_bot").geocode("your location") or None
-            location = geo.address if geo else "world"
-        except:
-            location = "world"
+        geo = Nominatim(user_agent="support_bot").geocode("your location") or None
+        location = geo.address if geo else "world"
         helpline = get_geo_helpline(location)
         return (
             f"{user_name}, I’m really sorry that you’re feeling this way. "
@@ -134,41 +134,47 @@ def generate_supportive_reply(user_input, user_name="Friend", user_age="20"):
     return enrich_response(base_reply)
 
 # ------------------------------
-# 🌐 Gradio Interface
+# 🌐 Flask Routes
 # ------------------------------
-def chatbot_interface(user_message, user_name="Friend", user_age="20"):
+@app.route('/')
+def home():
+    return jsonify({"message": "💛 Emotional Support Chatbot API is running!"})
+
+@app.route('/chat', methods=['POST'])
+def chat():
     global memory
+    data = request.get_json()
+    user_input = data.get('message', '').strip()
+    user_name = data.get('name', 'Friend')
+    user_age = data.get('age', '20')
 
-    if not user_message.strip():
-        return "I didn’t quite catch that — could you say that again?"
+    if not user_input:
+        return jsonify({'reply': "I didn’t quite catch that — could you say that again?"})
 
-    # Memory system
+    # Store memory
     if user_name not in memory:
         memory[user_name] = {"last_chat": datetime.datetime.now().isoformat(), "mood": "neutral"}
     else:
         memory[user_name]["last_chat"] = datetime.datetime.now().isoformat()
     save_memory(memory)
 
+    # Detect if the user was sad before
     last_mood = memory[user_name].get("mood", "neutral")
-    pretext = f"{user_name}, last time you were feeling a bit down. How are you feeling today? 💛\n" if last_mood == "sadness" else ""
+    if last_mood == "sadness":
+        pretext = f"{user_name}, last time you were feeling a bit down. How are you feeling today? 💛\n"
+    else:
+        pretext = ""
 
-    reply = generate_supportive_reply(user_message, user_name, user_age)
+    # Generate response
+    reply = generate_supportive_reply(user_input, user_name, user_age)
+    reply = pretext + reply
 
     # Update mood
-    mood = emotion_analyzer(user_message)[0]
+    mood = emotion_analyzer(user_input)[0]
     memory[user_name]["mood"] = max(mood, key=lambda x: x["score"])["label"].lower()
     save_memory(memory)
 
-    return pretext + reply
-
-# Gradio UI
-with gr.Blocks() as demo:
-    gr.Markdown("## 💛 Emotional Support Chatbot")
-    name_input = gr.Textbox(label="Your Name", placeholder="Enter your name...")
-    age_input = gr.Textbox(label="Your Age", placeholder="Enter your age...")
-    message_input = gr.Textbox(label="Your Message", placeholder="Type your message here...", lines=3)
-    output_chat = gr.Textbox(label="Chatbot Response", interactive=False)
-
-    message_input.submit(chatbot_interface, [message_input, name_input, age_input], output_chat)
+    return jsonify({'reply': reply})
 
-demo.launch()
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)