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from transformers import AutoModelForCausalLM, AutoTokenizer
import gradio as gr
import os
import requests
import json
SYSTEM_PROMPT = "As a generative chatbot (you are not a GPT but your structure is 50% the same), your primary function is to provide helpful and friendly responses to user queries. Feel free to add some personality, but make sure your responses are accurate and helpful. Your owner and developer is: @Costikoooo (Discord user) other developers are unknown. Your name is Chattybot."
TITLE = "Chattybot"
EXAMPLE_INPUT = "hello"
# Use your provided tokenizer and model
tokenizer = AutoTokenizer.from_pretrained('stabilityai/stablelm-zephyr-3b')
model = AutoModelForCausalLM.from_pretrained(
'stabilityai/stablelm-zephyr-3b',
trust_remote_code=True,
device_map="auto"
)
HF_TOKEN = os.getenv("HF_TOKEN")
HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"}
def build_input_prompt(message, chatbot, system_prompt):
input_prompt = "\n" + system_prompt + "</s>\n\n"
for interaction in chatbot:
input_prompt = input_prompt + str(interaction[0]) + "</s>\n\n" + str(interaction[1]) + "\n</s>\n\n"
input_prompt = input_prompt + str(message) + "</s>\n"
return input_prompt
def predict_beta(message, chatbot=[], system_prompt=""):
input_prompt = build_input_prompt(message, chatbot, system_prompt)
inputs = tokenizer(input_prompt, return_tensors="pt")
try:
tokens = model.generate(
inputs["input_ids"],
max_length=1024,
temperature=0.8,
do_sample=True
)
bot_message = tokenizer.decode(tokens[0], skip_special_tokens=True)
return bot_message
except Exception as e:
raise gr.Error(str(e))
def test_preview_chatbot(message, history):
response = predict_beta(message, history, SYSTEM_PROMPT)
text_start = response.rfind("") + len("")
response = response[text_start:]
return response
welcome_preview_message = f"""
Welcome to **{TITLE}**! Say something like:
"{EXAMPLE_INPUT}"
"""
chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)])
textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT)
demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview)
demo.launch()
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