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from huggingface_hub import InferenceClient
import gradio as gr
import json
client = InferenceClient(
"mistralai/Mistral-7B-Instruct-v0.1"
)
DATABASE_PATH = "database.json"
def load_database():
try:
with open(DATABASE_PATH, "r") as file:
return json.load(file)
except FileNotFoundError:
return {}
def save_database(database):
with open(DATABASE_PATH, "w") as file:
json.dump(database, file)
def format_prompt(message, history):
prompt = "<s>"
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response}</s> "
prompt += f"[INST] {message} [/INST]"
return prompt
def generate_response(prompt, database):
if prompt in database:
return database[prompt]
else:
response = next(client.text_generation(prompt, details=True, return_full_text=False)).token.text
database[prompt] = response
save_database(database)
return response
def generate(
prompt, history, database, temperature=0.9, max_new_tokens=2000, top_p=0.9, repetition_penalty=1.2,
):
temperature = float(temperature)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(top_p)
formatted_prompt = format_prompt(prompt, history)
response = generate_response(formatted_prompt, database)
yield response
database = load_database()
css = """
#mkd {
height: 500px;
overflow: auto;
border: 1px solid #ccc;
}
"""
with gr.Blocks(css=css) as demo:
gr.ChatInterface(
generate,
examples=[["What is the secret to life?"], ["Write me a recipe for pancakes."], ["Write a short story about Paris."]],
database=database
)
demo.launch(debug=True)
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