Create app.py

app.py

@@ -0,0 +1,53 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import gradio as gr
+import torch
+import json
+
+
+title = "AI ChatBot"
+description = "A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)"
+examples = [["How are you?"]]
+
+tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
+model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
+
+def predict(input, history=[], json_file_path=''):
+    if json_file_path:
+        # Read JSON data from file
+        with open(json_file_path, 'r') as file:
+            json_data = json.load(file)
+        
+        # Get prompt from JSON data
+        prompt = json_data["prompts"][0]["prompt"]
+        
+        # Use the prompt as input
+        input = prompt
+    
+    # tokenize the new input sentence
+    new_user_input_ids = tokenizer.encode(
+        input + tokenizer.eos_token, return_tensors="pt"
+    )
+
+    # append the new user input tokens to the chat history
+    bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
+
+    # generate a response
+    history = model.generate(
+        bot_input_ids, max_length=4000, pad_token_id=tokenizer.eos_token_id
+    ).tolist()
+
+    # convert the tokens to text, and then split the responses into lines
+    response = tokenizer.decode(history[0]).split("\n")
+    return response, history
+
+interface = gr.Interface(
+    fn=predict,
+    inputs=["text", "state", gr.inputs.File(label="JSON file")],  # Added File input for JSON file
+    outputs=["chatbot", "state"],
+    title=title,
+    description=description,
+    examples=examples,
+    theme="finlaymacklon/boxy_violet"
+)
+
+interface.launch()