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Update app.py
Browse files
app.py
CHANGED
@@ -11,32 +11,24 @@ headers = {
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"Content-Type": "application/json",
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}
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system_message,
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max_tokens,
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top_p,
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temperature,
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):
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messages = []
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for val in history:
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user_message, assistant_message, user_profile, assistant_profile, user_pic, assistant_pic = val
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if user_message:
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messages.append({
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"role": "user",
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"content": user_message,
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"profile": user_profile,
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"picture": user_pic
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})
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if assistant_message:
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messages.append({
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"role": "assistant",
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"content": assistant_message,
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"profile": assistant_profile,
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"picture":
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})
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data = {
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@@ -51,49 +43,53 @@ def respond(
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}
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response = requests.post(API_URL, headers=headers, data=json.dumps(data))
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if response.status_code == 200:
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response_json = response.json()
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else:
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yield "Error: " + response_json.get("error", "Unknown error occurred.")
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""
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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"""
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def custom_render(message, history):
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formatted_history = ""
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for user_message, assistant_message, user_profile, assistant_profile, user_pic, assistant_pic in history:
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if user_message:
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if user_pic:
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if assistant_message:
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if assistant_pic:
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return
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gr.Textbox(value="You are P-MSQ (Messaging Service Query), a friendly AI Chatbot that can help in any situations. Answer in user's language as concisely as possible.", label="System message"),
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gr.Slider(minimum=1, maximum=2048, value=1024, step=1, label="Max new tokens"),
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gr.Slider(minimum=0, maximum=2, value=0.8, step=0.1, label="Top P"),
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gr.Slider(minimum=0.1, maximum=1, value=0.7, step=0.1, label="Temperature"),
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gr.File(label="Upload User Profile Picture"),
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gr.File(label="Upload Assistant Profile Picture")
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],
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chatbot_ui=custom_render
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)
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if __name__ == "__main__":
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demo.launch()
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"Content-Type": "application/json",
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}
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ASSISTANT_PIC_PATH = "API.png"
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def respond(message, history, system_message, max_tokens, top_p, temperature):
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messages = []
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for user_message, assistant_message, user_profile, assistant_profile, user_pic, assistant_pic in history:
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if user_message:
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messages.append({
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"role": "user",
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"content": user_message,
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"profile": user_profile,
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"picture": user_pic
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})
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if assistant_message:
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messages.append({
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"role": "assistant",
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"content": assistant_message,
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"profile": assistant_profile,
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"picture": assistant_pic
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})
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data = {
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}
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response = requests.post(API_URL, headers=headers, data=json.dumps(data))
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if response.status_code == 200:
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response_json = response.json()
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assistant_reply = response_json["msq"]["message"][0]
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history.append((message, assistant_reply, "User", "Assistant", None, ASSISTANT_PIC_PATH))
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return history, assistant_reply
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else:
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return history, "Error: " + response.json().get("error", "Unknown error occurred.")
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def render_message(history):
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messages_html = ""
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for user_message, assistant_message, user_profile, assistant_profile, user_pic, assistant_pic in history:
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if user_message:
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messages_html += f"<div style='display: flex; align-items: center;'>"
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if user_pic:
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messages_html += f"<img src='{user_pic}' style='width: 40px; height: 40px; border-radius: 50%; margin-right: 10px;'>"
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messages_html += f"<b>{user_profile}:</b> {user_message}</div><br>"
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if assistant_message:
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messages_html += f"<div style='display: flex; align-items: center;'>"
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if assistant_pic:
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messages_html += f"<img src='{assistant_pic}' style='width: 40px; height: 40px; border-radius: 50%; margin-right: 10px;'>"
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messages_html += f"<b>{assistant_profile}:</b> {assistant_message}</div><br>"
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return messages_html
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with gr.Blocks() as demo:
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chatbot_output = gr.HTML()
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msg_input = gr.Textbox(show_label=False, placeholder="Type your message here...")
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system_message = gr.Textbox(value="You are P-MSQ (Messaging Service Query), a friendly AI Chatbot that can help in any situations.", label="System message")
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max_tokens = gr.Slider(minimum=1, maximum=2048, value=1024, step=1, label="Max new tokens")
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top_p = gr.Slider(minimum=0, maximum=2, value=0.8, step=0.1, label="Top P")
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temperature = gr.Slider(minimum=0.1, maximum=1, value=0.7, step=0.1, label="Temperature")
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history_state = gr.State([])
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def user_interaction(message, history, system_message, max_tokens, top_p, temperature):
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history, assistant_reply = respond(message, history, system_message, max_tokens, top_p, temperature)
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return render_message(history), history
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msg_input.submit(user_interaction,
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inputs=[msg_input, history_state, system_message, max_tokens, top_p, temperature],
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outputs=[chatbot_output, history_state])
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gr.Markdown("## Chat Interface with Profile Pictures")
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chatbot_output.render()
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msg_input.render()
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if __name__ == "__main__":
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demo.launch()
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