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import streamlit as st
from huggingface_hub import InferenceClient
client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.1")
def format_prompt(message, history):
prompt = "<s>"
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response}</s> "
prompt += f"[INST] {message} [/INST]"
return prompt
def generate(prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
temperature = float(temperature)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(top_p)
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=max_new_tokens,
top_p=top_p,
repetition_penalty=repetition_penalty,
do_sample=True,
seed=42,
)
formatted_prompt = format_prompt(prompt, history)
response = client.text_generation(formatted_prompt, **generate_kwargs)
if isinstance(response, list) and len(response) > 0 and 'choices' in response[0]:
return response[0]['choices'][0]['text']
elif 'choices' in response:
return response['choices'][0]['text']
else:
return response['text']
def main():
st.title("Mistral 7B Chat Interface")
# Sidebar for adjusting parameters
st.sidebar.header("Adjust Parameters")
temperature = st.sidebar.slider("Temperature", 0.0, 1.0, 0.9, step=0.05)
max_new_tokens = st.sidebar.slider("Max new tokens", 0, 1048, 256, step=64)
top_p = st.sidebar.slider("Top-p (nucleus sampling)", 0.0, 1.0, 0.90, step=0.05)
repetition_penalty = st.sidebar.slider("Repetition penalty", 1.0, 2.0, 1.2, step=0.05)
# Chat interface
user_input = st.text_area("User Input:", "")
history = [] # You need to manage the conversation history here
if st.button("Send"):
history.append(("User", user_input))
bot_response = generate(user_input, history, temperature, max_new_tokens, top_p, repetition_penalty)
history.append(("Bot", bot_response))
st.text("Chat History:")
for role, message in history:
st.write(f"{role}: {message}")
if __name__ == "__main__":
main()
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