Update app.py

app.py

@@ -1,23 +1,51 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
 
+# Load model from Hugging Face Hub (replace with your username/model name)
 model_name = "hari7261/TechChat"
+
+# Load tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
 
-def chat(prompt, max_new_tokens=150):
+# Chat function
+def chat(prompt, max_new_tokens=200, temperature=0.7, top_p=0.9):
     inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
-    outputs = model.generate(**inputs, max_new_tokens=max_new_tokens)
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=max_new_tokens,
+            temperature=temperature,
+            top_p=top_p,
+            pad_token_id=tokenizer.eos_token_id
+        )
     return tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-iface = gr.Interface(
-    fn=chat,
-    inputs=[
-        gr.Textbox(label="Your Question"),
-        gr.Slider(50, 500, value=150, step=10, label="Max New Tokens")
-    ],
-    outputs="text",
-    title="TechChat - Domain Specific Chatbot"
-)
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("# 💬 TechChat - Domain Chatbot")
+    gr.Markdown("Fine-tuned from Mistral-7B for technical Q&A")
+
+    with gr.Row():
+        with gr.Column(scale=3):
+            user_input = gr.Textbox(lines=3, placeholder="Ask me something technical...", label="Your Question")
+            max_tokens = gr.Slider(50, 500, value=200, step=10, label="Max New Tokens")
+            temperature = gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature")
+            top_p = gr.Slider(0.1, 1.0, value=0.9, step=0.05, label="Top-p Sampling")
+            submit_btn = gr.Button("Generate Answer")
+
+        with gr.Column(scale=5):
+            output_box = gr.Textbox(label="TechChat Response")
+
+    submit_btn.click(
+        fn=chat,
+        inputs=[user_input, max_tokens, temperature, top_p],
+        outputs=output_box
+    )
 
-iface.launch()
+demo.launch()