Spaces:
Sleeping
Sleeping
File size: 3,094 Bytes
39bf5a3 b718109 39bf5a3 b718109 39bf5a3 b718109 39bf5a3 b718109 39bf5a3 b718109 dbfa8f5 39bf5a3 b718109 421076d b718109 421076d b718109 421076d b718109 421076d b718109 39bf5a3 b718109 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 |
import gradio as gr
from huggingface_hub import InferenceClient
import random
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
# Initialize conversation state
conversation_state = {"ask_question": False, "last_message": ""}
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
global conversation_state
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
# Check if the chatbot should pose a question based on the user's previous response
if conversation_state["ask_question"]:
conversation_state["ask_question"] = False
question = pose_follow_up_question(conversation_state["last_message"])
messages.append({"role": "assistant", "content": question})
response = ""
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
# Update conversation state with the last user message
conversation_state["last_message"] = message.choices[0].delta.content
# Check if the chatbot should ask a question based on the current response
if "ask a question" in token.lower():
conversation_state["ask_question"] = True
yield response
def pose_follow_up_question(user_response):
# Example follow-up questions based on user responses
follow_up_questions = {
"I believe scientists should prioritize ethical considerations in their research":
"That's great! What do you think are some specific ethical considerations scientists should keep in mind?",
"I'm not sure about the ethical implications of genetic engineering":
"It's okay! Genetic engineering can be complicated. What aspects of it are you uncertain about?",
"I think technology has the potential to both benefit and harm society":
"You're absolutely right! How do you think society can balance the benefits and risks of emerging technologies?"
}
return follow_up_questions.get(user_response, "Could you tell me more about your thoughts on this topic?")
# Gradio interface definition
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
),
],
)
if __name__ == "__main__":
demo.launch()
|