Update app.py

app.py

@@ -1,27 +1,18 @@
-from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
-import time
 import gradio as gr
-
-
-
-
-
-
-
-prompt=''' Review the Following text as a human, who is tasked to Extract `Code Snippets` ,if any. If there are no Code Snippets in the below Text then return No CODE HIDDEN:
-
-"{}"
-'''
-def reply(message, history):
-    model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-ul2")
-    tokenizer = AutoTokenizer.from_pretrained("google/flan-ul2")
-    m=message.replace('\n','')
-    m=m.replace('\t','')
-    inputs = tokenizer(prompt.format(m), return_tensors="pt")
-    outputs = model.generate(**inputs)
-    code=tokenizer.batch_decode(outputs, skip_special_tokens=True)
-    for i in range(len(code)):
-        time.sleep(0.3)
-        yield  code[: i+1]
-
-gr.ChatInterface(reply).queue().launch()
+from transformers import AutoModelForCausalLM, AutoTokenizer
+ # Load pretrained model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("flan-t5-large")
+model = AutoModelForCausalLM.from_pretrained("flan-t5-large")
+
+def chatbot_model(prompt):
+   
+    # Encode the prompt and generate response
+    input_ids = tokenizer.encode(prompt + tokenizer.eos_token, return_tensors='pt')
+    output = model.generate(input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
+
+    # Decode the output
+    decoded_output = tokenizer.decode(output[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
+    return decoded_output
+
+iface = gr.Interface(fn=chatbot_model, inputs="text", outputs="text")
+iface.launch()