Create app.py

app.py

@@ -0,0 +1,56 @@
+import torch
+from transformers import pipeline
+import gradio as gr
+
+# Initialize the model pipeline
+pipe = pipeline("text-generation", model="umarmajeedofficial/TinyLlama-1.1B-Chat-v1.0-FineTuned-By-MixedIntelligence", torch_dtype=torch.bfloat16, device_map="auto")
+
+# Function to generate response
+def generate_response(question):
+    # Define messages with a clear prompt for a concise answer
+    messages = [
+        {"role": "system", "content": "You are an expert in emergency situations and environmental issues. Provide concise and direct answers."},
+        {"role": "user", "content": question}
+    ]
+
+    # Generate the prompt
+    prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+    # Generate the output
+    outputs = pipe(prompt, max_new_tokens=150, do_sample=False)  # Reduced tokens for concise answers
+
+    # Post-process the output to clean up the response
+    generated_text = outputs[0]["generated_text"]
+
+    # Clean up the response
+    # If the response starts with system prompt or question, strip it out
+    start_index = generated_text.find(question)
+    if start_index != -1:
+        clean_response = generated_text[start_index:].strip()
+    else:
+        clean_response = generated_text.strip()
+    
+    # Optional: Remove any unwanted ending marks like `</s>`
+    clean_response = clean_response.replace("</s>", "").strip()
+
+    return clean_response
+
+# Gradio UI
+def qa_interface():
+    with gr.Blocks() as demo:
+        gr.Markdown("# Emergency Helper")
+        gr.Markdown("Developed by Mixed Intelligence Team")
+        
+        with gr.Row():
+            with gr.Column():
+                emergency_question = gr.Textbox(label="Ask your question about emergency situations or environmental issues", placeholder="e.g., How to survive in an earthquake?")
+                submit_btn = gr.Button("Submit")
+                output = gr.Textbox(label="Response", placeholder="The answer will appear here...", lines=5)
+
+        submit_btn.click(generate_response, inputs=emergency_question, outputs=output)
+
+    return demo
+
+# Launch the Gradio UI
+demo = qa_interface()
+demo.launch()