Update app.py

app.py

@@ -1,47 +1,69 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import json
 
 client = InferenceClient(
     "meta-llama/Meta-Llama-3-8B-Instruct",
 )
 
-def chat_mem(message,chat_history):
+def chat_llama(chat_history):
+    chat_completion = client.chat_completion(
+        messages=chat_history,
+        max_tokens=500,
+    )
+    chat_history.append({"role": "assistant", "content": chat_completion.choices[0].message.content})
+    print(chat_history)
+    return chat_history
 
-  print(len(chat_history))
-  chat_history_role = [{"role": "system", "content": "You are a helpful assistant." },]
-  if chat_history != []:
-    for i in range(len(chat_history)):
-      chat_history_role.append({"role": "user", "content": chat_history[i][0]})
-      chat_history_role.append({"role": "assistant", "content": chat_history[i][1]})
-  chat_history_role.append({"role": "user", "content": message})
-  
+def chat_mem(message, chat_history):
+    print(len(chat_history))
+    chat_history_role = [{"role": "system", "content": "You are a helpful assistant."},]
+    if chat_history != []:
+        for i in range(len(chat_history)):
+            chat_history_role.append({"role": "user", "content": chat_history[i][0]})
+            chat_history_role.append({"role": "assistant", "content": chat_history[i][1]})
+    chat_history_role.append({"role": "user", "content": message})
+    
+    chat_completion = client.chat_completion(
+        messages=chat_history_role,
+        max_tokens=500,
+    )
+    chat_history_role.append({"role": "assistant", "content": chat_completion.choices[0].message.content})
+    print(chat_history_role)
 
-  chat_completion = client.chat_completion(
-  messages=chat_history_role,
-  max_tokens=500,
-  # stream=True
-  )
-  chat_history_role.append({"role": "assistant", "content": chat_completion.choices[0].message.content})
-  print(chat_history_role)
+    modified = map(lambda x: x["content"], chat_history_role)
+    a = list(modified)
+    chat_history = [(a[i*2+1], a[i*2+2]) for i in range(len(a)//2)]
 
-  modified = map(lambda x: x["content"], chat_history_role)
-  a = list(modified)
-  chat_history=[(a[i*2+1], a[i*2+2]) for i in range(len(a)//2)]
-
-  return "", chat_history
+    return "", chat_history
 
+def process_json(json_input):
+    try:
+        chat_history = json.loads(json_input)
+        if not isinstance(chat_history, list):
+            raise ValueError("Input should be a list of message dictionaries.")
+    except (json.JSONDecodeError, ValueError) as e:
+        return f"Error parsing JSON: {str(e)}", ""
+    
+    chat_history = chat_llama(chat_history)
+    return json.dumps(chat_history, indent=2), ""
 
 with gr.Blocks() as demo:
-  with gr.Row():
-    with gr.Column():
-      chatbot = gr.Chatbot()
-      msg =  gr.Textbox(interactive=True, )
-      with gr.Row():
-        clear = gr.ClearButton([msg, chatbot], icon="https://img.icons8.com/?size=100&id=Xnx8cxDef16O&format=png&color=000000")
-        send_btn = gr.Button("Send", variant='primary', icon="https://img.icons8.com/?size=100&id=g8ltXTwIfJ1n&format=png&color=000000")
-      msg.submit(fn=chat_mem, inputs=[msg, chatbot], outputs=[msg, chatbot])
-      send_btn.click(fn=chat_mem, inputs=[msg, chatbot], outputs=[msg, chatbot])
-
+    with gr.Row():
+        with gr.Column():
+            chatbot = gr.Chatbot()
+            msg = gr.Textbox(interactive=True, )
+            with gr.Row():
+                clear = gr.ClearButton([msg, chatbot], icon="https://img.icons8.com/?size=100&id=Xnx8cxDef16O&format=png&color=000000")
+                send_btn = gr.Button("Send", variant='primary', icon="https://img.icons8.com/?size=100&id=g8ltXTwIfJ1n&format=png&color=000000")
+            msg.submit(fn=chat_mem, inputs=[msg, chatbot], outputs=[msg, chatbot])
+            send_btn.click(fn=chat_mem, inputs=[msg, chatbot], outputs=[msg, chatbot])
+        
+        with gr.Column():
+            json_input = gr.Textbox(placeholder='Input JSON here...', interactive=True, lines=10)
+            json_output = gr.Textbox(label='Output JSON', interactive=False, lines=10)
+            process_btn = gr.Button("Process JSON", variant='primary', icon="https://img.icons8.com/?size=100&id=g8ltXTwIfJ1n&format=png&color=000000")
+            process_btn.click(fn=process_json, inputs=json_input, outputs=[json_output])
 
 if __name__ == "__main__":
     demo.launch()