Update app.py

app.py

@@ -1,29 +1,39 @@
-import gradio as gr
 import json
+from flask import Flask, request, jsonify
 from transformers import pipeline
 
-# Load JSON data
-with open("schemes.json", "r") as file:
-    scheme_data = json.load(file)
+# Load the model (use a public model)
+llm = pipeline("text-generation", model="mistralai/Mistral-7B-v0.1")
 
-# Function to search relevant scheme information
-def search_scheme(query):
-    for scheme in scheme_data:
+# Load the schemes data from JSON
+with open("schemes.json", "r", encoding="utf-8") as f:
+    schemes_data = json.load(f)
+
+app = Flask(__name__)
+
+# Function to search for relevant information
+def find_scheme_info(query):
+    for scheme in schemes_data["schemes"]:
         if query.lower() in scheme["name"].lower() or query.lower() in scheme["description"].lower():
-            return f"**Scheme Name:** {scheme['name']}\n\n**Description:** {scheme['description']}\n\n**Eligibility:** {scheme['eligibility']}\n\n**Benefits:** {scheme['benefits']}"
-    return "Sorry, I couldn't find details on that scheme."
+            return scheme["description"]
+    return "Sorry, I couldn't find information on that scheme."
 
-# Load LLM model
-llm = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct")
+# Function to generate a chatbot response
+def chatbot_response(query):
+    scheme_info = find_scheme_info(query)
+    if scheme_info != "Sorry, I couldn't find information on that scheme.":
+        return scheme_info
+    else:
+        response = llm(query, max_length=200, do_sample=True)
+        return response[0]['generated_text']
 
-# Chatbot function
-def chatbot(query):
-    relevant_info = search_scheme(query)
-    if "Sorry" in relevant_info:
-        return relevant_info
-    response = llm(f"Provide a concise summary of the following government scheme:\n{relevant_info}", max_length=200)
-    return response[0]["generated_text"]
+@app.route("/chat", methods=["POST"])
+def chat():
+    user_input = request.json.get("query", "")
+    if not user_input:
+        return jsonify({"error": "No query provided"}), 400
+    response = chatbot_response(user_input)
+    return jsonify({"response": response})
 
-# Gradio Interface
-demo = gr.Interface(fn=chatbot, inputs="text", outputs="text", title="Govt Scheme Chatbot", description="Ask about any government scheme!")
-demo.launch()
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860, debug=True)