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import gradio as gr | |
from huggingface_hub import hf_hub_download | |
from llama_cpp import Llama | |
llm = Llama(model_path=hf_hub_download(repo_id="TheBloke/airoboros-l2-13b-gpt4-m2.0-GGML", filename="airoboros-l2-13b-gpt4-m2.0.ggmlv3.q6_K.bin"), n_ctx=2048) | |
history = [] | |
history.append(["Hi there!", "Hello, how can I help you?"]) | |
def generate_text(input_text, history): | |
conversation_context = " ".join([f"{pair[0]} {pair[1]}" for pair in history]) | |
full_conversation = f"{conversation_context} Q: {input_text} \n A:" | |
output = llm(full_conversation, max_tokens=1024, stop=["Q:", "\n"], echo=True) | |
response = output['choices'][0]['text'] | |
history.append([input_text, response]) | |
return "", history | |
with gr.Blocks() as demo: | |
chatbot = gr.Chatbot() | |
msg = gr.Textbox() | |
clear = gr.ClearButton([msg, chatbot]) | |
msg.submit(generate_text, [msg, chatbot], [msg, chatbot]) | |
demo.launch() | |