add chatbot inference interface

app.py

@@ -1,7 +1,42 @@
+# app.py
+
+
+# import pipelines
+# import datasets
+import os
+
+if not os.getenv('HF_TOKEN'):
+    raise ValueError('HF_TOKEN must be set')
+
+from huggingface_hub import InferenceClient
 import gradio as gr
+from gradio import ChatMessage
+
+MODEL = "meta-llama/Meta-Llama-3-8B-Instruct"
+# PROMPT = "What is happiness?"
+HF_TOKEN = os.getenv('HF_TOKEN')
+
+client = InferenceClient(MODEL, token=HF_TOKEN)
+# inputs = [{"role": "user", "content": PROMPT}]
+# output = client.chat_completion(messages, max_tokens=100)
+
+print(output.choices[0].message.content)
+print(output.model)
 
-def greet(name):
-    return "Hello " + name + "!!"
+def interact_with_agent(prompt, messages):
+    messages.append(ChatMessage(role="user", content=prompt))
+    yield messages
+    # for msg in stream_from_transformers_agent(agent, prompt):
+    for msg in client.chat_completion(messages, max_tokens=100):
+        messages.append(msg)
+        yield messages
+    yield messages
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+with gr.Blocks() as demo:
+    chatbot = gr.ChatMessage(label="Agent",
+                             msg_format="messages")
+    text_input = gr.Textbox(lines=1, label="Chat Message")
+    text_input.submit(interact_with_agent, [text_input, chatbot], [chatbot])
+    
+if __name__ == "__main__":
+    demo.launch()