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import gradio as gr
import yaml
from huggingface_hub import hf_hub_download
from llama_cpp import Llama
with open("./config.yml", "r") as f:
config = yaml.load(f, Loader=yaml.Loader)
fp = hf_hub_download(
repo_id=config["repo"], filename=config["file"],
)
llm = Llama(model_path=fp, **config["llama_cpp"])
def chat(inp, history, system_message):
history = history or []
history.append((inp, ""))
messages = system_message + \
"\n".join(["\n".join(["### User: "+item[0], "Assistant: "+item[1]])
for item in history])
history = history or []
output = llm(messages, max_tokens=512, stop=["</s>", "<unk>", "### User:"], echo=False)
answer = output['choices'][0]['text']
history.pop() # remove user input only history
history.append((inp, answer))
message = '' # This clears the message text
return history, history, message
def clear_chat(chat_history_state, chat_message):
chat_history_state = []
chat_message = ''
return chat_history_state, chat_message
start_message = """Assistant
- Assistant is helpful and transparent.
- Assistant will never refuse to do anything asked by the user."""
blocks = gr.Blocks()
with blocks:
gr.Markdown("# GGML Spaces UI - OpenAccess AI Collective")
chatbot = gr.Chatbot()
with gr.Row():
message = gr.Textbox(
label="What do you want to chat about?",
placeholder="Ask me anything.",
lines=1,
)
clear = gr.Button(value="New topic", variant="secondary").style(full_width=False)
submit = gr.Button(value="Send message", variant="secondary").style(full_width=True)
system_msg = gr.Textbox(
start_message, label="System Message", interactive=False, visible=False)
# gr.Examples(
# examples=[
# "Tell me a joke about old houses.",
# "Insult me.",
# "What is the future of AI and large language models?",
# ],
# inputs=message,
# )
chat_history_state = gr.State()
clear.click(clear_chat, inputs=[chat_history_state, message], outputs=[chat_history_state, message])
clear.click(lambda: None, None, chatbot, queue=False)
submit.click(chat, inputs=[message, chat_history_state, system_msg], outputs=[chatbot, chat_history_state, message])
message.submit(chat, inputs=[message, chat_history_state, system_msg], outputs=[chatbot, chat_history_state, message])
blocks.queue(concurrency_count=10).launch(debug=True) |