Update app.py

app.py

@@ -1,5 +1,3 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
 from flask import Flask, render_template, request, jsonify
 from simple_salesforce import Salesforce
 from dotenv import load_dotenv
@@ -13,10 +11,9 @@ load_dotenv()
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
-# Initialize Flask app
 app = Flask(__name__, template_folder='templates', static_folder='static')
 
-# Initialize Salesforce connection
+# Function to get Salesforce connection
 def get_salesforce_connection():
     try:
         sf = Salesforce(
@@ -31,56 +28,9 @@ def get_salesforce_connection():
         logger.error(f"Error connecting to Salesforce: {e}")
         return None
 
-# Connect to HuggingFace model
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-# Define Gradio respond function for chatbot
-def respond(
-    message,
-    history,
-    system_message="You are a helpful assistant.",
-    max_tokens=512,
-    temperature=0.7,
-    top_p=0.95,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-        response += token
-        yield response
-
-# Create Gradio chat interface
-demo = gr.Interface(
-    fn=respond,
-    inputs=[
-        gr.Textbox(label="User Input", placeholder="Type your message here..."),
-        gr.State()  # State input to maintain conversation history
-    ],
-    outputs=[
-        gr.Chatbot(type='messages'),  # Corrected to use 'messages' type for the chat
-        gr.State()  # State output to maintain conversation history
-    ],
-    live=True
-)
+# Initialize Salesforce connection
+sf = get_salesforce_connection()
 
-# Flask routes
 @app.route('/')
 def index():
     return render_template('index.html')
@@ -122,10 +72,5 @@ def get_ingredients():
         logger.error(f"Failed to fetch ingredients: {str(e)}")
         return jsonify({"error": f"Failed to fetch ingredients: {str(e)}"}), 500
 
-# Start Flask and Gradio app
 if __name__ == '__main__':
-    # Launch Gradio chat interface
-    gradio_thread = demo.launch(share=True, inbrowser=True, server_port=7860, debug=True)
-
-    # Start Flask app
-    app.run(debug=True, host='0.0.0.0', port=7860)
+    app.run(debug=True, host='0.0.0.0', port=7860)