this is final

app.py

@@ -1,41 +1,32 @@
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
 import gradio as gr
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+import torch
+
+# Load pre-trained model and tokenizer
+model_name = "gpt2"  # You can also try 'distilgpt2' for faster results
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+model = GPT2LMHeadModel.from_pretrained(model_name)
+model.eval()
 
-# Load the model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained("sagorsarker/bangla-gpt")
-model = AutoModelForCausalLM.from_pretrained("sagorsarker/bangla-gpt")
+# Chat function
+def chat_with_gpt2(message, history=[]):
+    # Combine history with current input
+    input_text = " ".join([msg for pair in history for msg in pair]) + " " + message
+    inputs = tokenizer.encode(input_text, return_tensors="pt")
 
-# Response generation function
-def bangla_chatbot(message, history):
-    history_text = " ".join([msg["content"] for msg in history])
-    prompt = f"ইউজার: {message}\nচ্যাটবট:"
-    inputs = tokenizer.encode(prompt, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=150, pad_token_id=tokenizer.eos_token_id,
+                             no_repeat_ngram_size=2, do_sample=True, top_p=0.9, temperature=0.8)
 
-    outputs = model.generate(
-        inputs,
-        max_length=100,
-        do_sample=True,
-        top_k=50,
-        top_p=0.95,
-        temperature=0.7,
-        pad_token_id=tokenizer.eos_token_id
-    )
-    
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    # Get only the generated part
-    reply = response.replace(prompt, "").strip()
-    
-    history.append({"role": "user", "content": message})
-    history.append({"role": "assistant", "content": reply})
-    return history
+    response = response[len(input_text):].strip()
+    history.append((message, response))
+    return response, history
 
-demo = gr.ChatInterface(
-    fn=bangla_chatbot,
-    title="📄 বাংলা CV সহায়তা বট",
-    chatbot=gr.Chatbot(type="messages"),
-    description="বাংলায় আপনার CV সম্পর্কিত প্রশ্ন করুন, আমরা উত্তর দেবো। (বিনামূল্যে মডেল ব্যবহার করা হয়েছে)",
-    theme="soft"
-)
+# Gradio Interface
+chat_interface = gr.ChatInterface(fn=chat_with_gpt2, title="GPT-2 Resume Chatbot",
+                                  description="A chatbot powered by GPT-2 for answering resume/CV-related queries.",
+                                  theme="default")
 
-demo.launch()
+# Launch
+if __name__ == "__main__":
+    chat_interface.launch()

requirements.txt

@@ -1,3 +1,3 @@
-transformers
 torch
-gradio
+transformers
+gradio