Update app.py

app.py

@@ -1,50 +1,49 @@
-import os
 import subprocess
 import sys
-from flask import Flask, request, jsonify
+import gradio as gr
 from transformers import pipeline
 
-# Function to ensure the required library is installed
+# Function to ensure required libraries are installed
 def install_and_import(package):
     try:
         __import__(package)
     except ImportError:
         subprocess.check_call([sys.executable, "-m", "pip", "install", package])
 
-# Install transformers and flask if not installed
+# Install transformers and gradio if not installed
 install_and_import("transformers")
-install_and_import("flask")
-
-# Initialize Flask app
-app = Flask(__name__)
-
-# Load Transformers pipeline
-def load_transformer_pipeline():
-    global model
-    model = pipeline("text-generation", model="gpt2")
+install_and_import("gradio")
+
+# Load DeepSeek-R1 model pipeline
+def load_pipeline():
+    global pipe
+    pipe = pipeline(
+        "text-generation",
+        model="deepseek-ai/DeepSeek-R1",
+        trust_remote_code=True
+    )
     print("Model loaded successfully.")
 
-load_transformer_pipeline()
-
-@app.route("/", methods=["GET"])
-def home():
-    return jsonify({"message": "Welcome to Gardio with Transformers!"})
+load_pipeline()
 
-@app.route("/generate", methods=["POST"])
-def generate_text():
+# Function to handle user prompts and generate responses
+def generate_response(prompt):
     try:
-        data = request.get_json()
-        prompt = data.get("prompt", "")
-        if not prompt:
-            return jsonify({"error": "Prompt is required"}), 400
-
-        # Generate text using the model
-        result = model(prompt, max_length=50, num_return_sequences=1)
-        return jsonify({"generated_text": result[0]["generated_text"]})
-
+        # Generate response from the model
+        response = pipe(prompt, max_length=100, num_return_sequences=1)
+        return response[0]["generated_text"]
     except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
+        return f"Error: {str(e)}"
+
+# Gradio Interface
+interface = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here..."),
+    outputs=gr.Textbox(label="Generated Text"),
+    title="DeepSeek-R1 Text Generator",
+    description="Generate text using the DeepSeek-R1 model hosted on Hugging Face.",
+)
+
+# Launch the Gradio app
 if __name__ == "__main__":
-    port = int(os.environ.get("PORT", 7086))  # Default port is 7086
-    app.run(host="0.0.0.0", port=port)
+    interface.launch()