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import gradio as gr
from openai import OpenAI
import os
ACCESS_TOKEN = os.getenv("HF_TOKEN")
print("Access token loaded.")
client = OpenAI(
base_url="https://api-inference.huggingface.co/v1/",
api_key=ACCESS_TOKEN,
)
print("OpenAI client initialized.")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
frequency_penalty,
seed,
custom_model
):
print(f"Received message: {message}")
print(f"History: {history}")
print(f"System message: {system_message}")
if seed == -1:
seed = None
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
model_to_use = custom_model.strip() if custom_model.strip() != "" else "meta-llama/Llama-3.1-8B-Instruct"
response = ""
for message_chunk in client.chat.completions.create(
model=model_to_use,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
frequency_penalty=frequency_penalty,
seed=seed,
messages=messages,
):
token_text = message_chunk.choices[0].delta.content
response += token_text
yield response
chatbot = gr.Chatbot(height=600, show_copy_button=True, placeholder="ChatGPT is initializing...", likeable=True, layout="panel")
system_message_box = gr.Label(value="You can select Max Tokens, Temperature, Top-P, Seed")
max_tokens_slider = 2048,
temperature_slider = 0.7,
top_p_slider = 0.95,
frequency_penalty_slider = 0.0,
seed_slider = -1
custom_model_box = gr.Textbox(value="meta-llama/Llama-3.2-3B-Instruct", label="AI Mode is ")
demo = gr.ChatInterface(
fn=respond,
additional_inputs=[
system_message_box,
max_tokens_slider,
temperature_slider,
top_p_slider,
frequency_penalty_slider,
seed_slider,
custom_model_box,
],
fill_height=True,
chatbot=chatbot,
theme="Nymbo/Nymbo_Theme",
)
if __name__ == "__main__":
print("Launching the ChatGPT-Llama...")
demo.launch()
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