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import gradio as gr
from llama_cpp import Llama
from typing import Optional
import gradio as gr
llm = Llama.from_pretrained(
repo_id="Haary/USK_Mistral_7B_Unsloth_GGUF",
filename="unsloth.Q4_K_M.gguf"
)
class Chat:
def __init__(self, system: Optional[str] = None):
self.system = system
self.messages = []
if system is not None:
self.messages.append({
"role": "system",
"content": system
})
def prompt(self, content: str) -> str:
self.messages.append({
"role": "user",
"content": content
})
response = llm.create_chat_completion(
messages = [
{
"role": "user",
"content": "sertifikat akreditasi bisa dicari dimana yaa?"
}
]
)
response_content = response["choices"][0]["message"]["content"]
self.messages.append({
"role": "assistant",
"content": response_content
})
return response_content
chat = Chat(system="You are a helpful assistant.")
def respond(message, chat_history):
bot_message = chat.prompt(content=message)
chat_history.append((message, bot_message))
return "", chat_history
with gr.Blocks() as demo:
chatbot = gr.Chatbot()
msg = gr.Textbox()
clear = gr.Button("Clear")
msg.submit(respond, [msg, chatbot], [msg, chatbot])
clear.click(lambda: None, None, chatbot, queue=False)
if __name__ == "__main__":
demo.launch(debug=True) |