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import streamlit as st
from llama_cpp import Llama
# Initialize the model
llm = Llama.from_pretrained(
repo_id="Divyansh12/check",
filename="unsloth.F16.gguf", # Ensure this matches your model file name
verbose=True,
n_ctx=32768,
n_threads=2,
chat_format="chatml"
)
# Define the function to get responses from the model
def respond(message, history, system_message, max_tokens, temperature, top_p):
messages = [{"role": "system", "content": system_message}]
for user_message, assistant_message in history:
if user_message:
messages.append({"role": "user", "content": user_message})
if assistant_message:
messages.append({"role": "assistant", "content": assistant_message})
messages.append({"role": "user", "content": message})
response = ""
# Stream the response from the model
response_stream = llm.create_chat_completion(
messages=messages,
stream=True,
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p
)
for chunk in response_stream:
if len(chunk['choices'][0]["delta"]) != 0 and "content" in chunk['choices'][0]["delta"]:
response += chunk['choices'][0]["delta"]["content"]
yield response
# Streamlit UI
st.title("Chatbot Application")
st.write("### Interact with the chatbot!")
# User input fields
system_message = st.text_input("System Message", value="You are a friendly Chatbot.")
user_message = st.text_area("Your Message:")
max_tokens = st.slider("Max New Tokens", min_value=1, max_value=2048, value=512)
temperature = st.slider("Temperature", min_value=0.1, max_value=4.0, value=0.7)
top_p = st.slider("Top-p (Nucleus Sampling)", min_value=0.1, max_value=1.0, value=0.95)
# Chat history
if 'history' not in st.session_state:
st.session_state.history = []
if st.button("Send"):
# Get the response from the model
response = respond(user_message, st.session_state.history, system_message, max_tokens, temperature, top_p)
# Add user message and model response to history
st.session_state.history.append((user_message, response))
# Display the chat history
st.write("### Chat History")
for user_msg, assistant_msg in st.session_state.history:
st.write(f"**User:** {user_msg}")
st.write(f"**Assistant:** {assistant_msg}")
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