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from langchain.callbacks.manager import CallbackManager | |
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler | |
from langchain_community.llms import LlamaCpp | |
from pprint import pprint | |
import gradio as gr | |
# Initialize callback manager and LLM | |
callback_manager = CallbackManager([StreamingStdOutCallbackHandler()]) | |
llm = LlamaCpp( | |
model_path="llama-2-7b-chat.Q3_K_M.gguf", | |
temperature=0.75, | |
max_tokens=2000, | |
top_p=1, | |
callback_manager=callback_manager, | |
verbose=True, # Verbose is required to pass to the callback manager | |
) | |
# Define the function to interact with the LLM | |
def llama_llm(prompt): | |
llama_prompt = f"<s>[INST]<<SYS>>\nEve lives in Hamburg.; Bob lives in Cape Town.; Alice lives in Mumbay.\n<</SYS>>\n{prompt}[/INST]" | |
response = llm(llama_prompt) | |
return response | |
# Create the Gradio interface | |
iface = gr.Interface( | |
fn=llama_llm, | |
inputs="text", | |
outputs="text", | |
title="Llama LLM Chat Interface", | |
description="Ask a question based on the system prompt: 'Eve lives in Hamburg.; Bob lives in Cape Town.; Alice lives in Mumbay.'" | |
) | |
# Launch the Gradio interface | |
iface.launch() | |