Create app.py

app.py

@@ -0,0 +1,50 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load the Mistral-7B-v0.2 model and tokenizer
+model_name = "mistralai/Mistral-7B-v0.2"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Define the chatbot function
+def chatbot(input_text, history=[]):
+    # Combine history and current input
+    chat_history = " ".join([f"User: {h[0]} Assistant: {h[1]}" for h in history])
+    input_prompt = f"{chat_history} User: {input_text} Assistant:"
+    inputs = tokenizer(input_prompt, return_tensors="pt", truncation=True)
+    
+    # Generate response
+    outputs = model.generate(
+        **inputs,
+        max_length=512,
+        do_sample=True,
+        temperature=0.7,
+        top_p=0.9
+    )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True).split("Assistant:")[-1].strip()
+    
+    # Update history
+    history.append((input_text, response))
+    return response, history
+
+# Gradio Interface
+with gr.Blocks() as interface:
+    gr.Markdown("### Mistral-7B-v0.2 Chatbot")
+    gr.Markdown("This chatbot is powered by the Mistral-7B-v0.2 model for summarization and general conversation.")
+
+    with gr.Row():
+        chatbot_box = gr.Chatbot(label="Chatbot")
+    
+    with gr.Row():
+        user_input = gr.Textbox(label="Your Input", placeholder="Type your message here...")
+        submit_button = gr.Button("Submit")
+
+    with gr.Row():
+        reset_button = gr.Button("Reset Chat")
+    
+    # Functionality
+    submit_button.click(chatbot, inputs=[user_input, chatbot_box], outputs=[chatbot_box, chatbot_box])
+    reset_button.click(lambda: [], inputs=[], outputs=[chatbot_box])
+
+# Launch the app
+interface.launch()