Upload app.py

app.py

@@ -0,0 +1,111 @@
+import gradio as gr
+import json
+from uuid import uuid4
+import requests
+from pydantic import BaseModel
+from typing import List
+import ast
+import os
+
+
+QUEUE_MAX_SIZE = int(os.getenv("QUEUE_MAX_SIZE", 20))
+QUEUE_CONCURENCY_COUNT = int(os.getenv("QUEUE_CONCURENCY_COUNT", 10))
+USERNAME = os.getenv("USERNAME")
+PASSWORD = os.getenv("PASSWORD")
+
+
+class LearningBotRequest(BaseModel):
+    message: List[dict]
+    persona: str
+    session_id: str
+    context: dict
+    user_serial: str
+
+
+def generate_uuid():
+    return str(uuid4())
+
+
+def construct_message(list_message):
+    messages = []
+    for i, pair_message in enumerate(list_message):
+        if len(pair_message) < 2:
+            continue
+        content_user = {"human": pair_message[0]}
+        content_human = {"AI": pair_message[1]}
+        messages.append(content_user)
+        messages.append(content_human)
+
+    return messages
+
+
+def send_message(url, request):
+    response = requests.post(url, data=request.json())
+    if response.status_code != 200:
+        raise gr.Error(response.text)
+    else:
+        result = response.json()["data"]["reply"]
+        return result
+
+
+def respond(chat_history, message, session_id, user_serial, persona, context, endpoint):
+    if session_id is None:
+        session_id = generate_uuid()
+
+    context = ast.literal_eval(context)
+    messages = construct_message(chat_history)
+    messages.append(
+        {"human": message}
+    )
+
+    request = LearningBotRequest(
+        message=messages,
+        persona=persona,
+        session_id=session_id,
+        context=context,
+        user_serial=user_serial
+    )
+
+    response = send_message(endpoint, request)
+
+    return chat_history + [[message, response]], "Success", session_id
+
+
+def reset_textbox():
+    return gr.update(value='')
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column(scale=5):
+            clear = gr.Button("Clear all converstation")
+        with gr.Column(scale=5):
+            endpoint = gr.Textbox(label="Endpoint API")
+            with gr.Accordion("Parameters", open=False):
+                user_serial = gr.Textbox(label="User serial")
+                context = gr.Textbox(label="context", value={})
+                persona = gr.Textbox(label="persona")
+
+    chatbot = gr.Chatbot()
+    message = gr.Textbox(placeholder="Halo kak, aku mau bertanya", label="Chat Here")
+    session_id = gr.State(value=generate_uuid())
+    with gr.Row():
+        with gr.Column(scale=5):
+            send = gr.Button("Send")
+        with gr.Column(scale=5):
+            status_box = gr.Textbox(label="Status code from OpenAI server", )
+
+    message.submit(respond, [chatbot, message, session_id, user_serial, persona, context, endpoint], [chatbot, status_box, session_id])
+
+    clear.click(lambda: None, None, chatbot, queue=False)
+    clear.click(lambda: None, None, session_id, queue=False)
+
+    send.click(respond, [chatbot, message, session_id, user_serial, persona, context, endpoint], [chatbot, status_box, session_id])
+    send.click(reset_textbox, [], [message])
+    message.submit(reset_textbox, [], [message])
+
+    (
+        demo
+        .queue(max_size=QUEUE_MAX_SIZE, concurrency_count=QUEUE_CONCURENCY_COUNT)
+        # .launch(auth=(USERNAME, PASSWORD), debug=True)
+    )