Create app.py

app.py

@@ -0,0 +1,79 @@
+import aiohttp
+import asyncio
+import json
+import gradio as gr
+
+# Define the API URLs
+BASE_URL = "https://free-duck-duck-go-assist-coral.vercel.app/api"
+TOKEN_URL = BASE_URL + "/get-token"
+CHAT_URL = BASE_URL + "/conversation"
+
+# Initialize the token and message history
+token = ""
+messHistory: list = []
+
+async def chat(messList):
+    """Async function to send and receive messages with the server."""
+    global token
+    async with aiohttp.ClientSession() as session:
+        # Request token if not already set
+        if token == "":
+            async with session.get(TOKEN_URL) as resp:
+                data = await resp.json()
+                token = data["token"]
+
+        body = {
+            "token": token,
+            "message": messList,
+            "stream": True
+        }
+
+        # Make the POST request to the chat API
+        async with session.post(CHAT_URL, json=body) as resp:
+            if resp.status != 200:
+                return "Error occurred during the chat process."
+
+            fullmessage = ""
+            # Stream and decode response chunks
+            async for chunk in resp.content.iter_any():
+                data_str = chunk.decode("utf-8")
+                json_str = data_str.replace("data: ", "")
+                if json_str.strip() == "[DONE]":
+                    break
+                else:
+                    try:
+                        data_dict = json.loads(json_str)
+                        fullmessage += data_dict["message"]
+                        token = data_dict["resp_token"]  # Update token
+                    except KeyError:
+                        pass
+            
+            messHistory.append({"role": "assistant", "content": fullmessage})  # Append assistant response
+            return fullmessage
+
+
+def gradio_chat(user_input, mode):
+    """Synchronous wrapper for the async chat function, integrated with Gradio."""
+    messHistory.append({"role": "user", "content": f"[{mode}] {user_input}"})
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+    assistant_response = loop.run_until_complete(chat(messHistory))
+    return assistant_response
+
+
+# Gradio interface for user interaction
+with gr.Blocks() as demo:
+    gr.Markdown("# Chat with AI")
+    chat_box = gr.ChatInterface(fn=gradio_chat, label="Assistant")
+
+    # Radio button for selecting modes
+    radio_mode = gr.Radio(["Friendly", "Formal", "Humorous"], label="Chat Mode", value="Friendly")
+
+    # Chatbot UI setup with mode and user input
+    chat_ui = gr.ChatInterface(fn=lambda user_input: gradio_chat(user_input, radio_mode.value))
+
+    # Link mode selection to chat interface
+    chat_box.submit(gradio_chat, [chat_box, radio_mode], chat_box)
+
+# Launch the Gradio app
+demo.launch()