File size: 2,491 Bytes
18b49fe 8f595d7 7c3ee06 883f196 7c3ee06 18b49fe 8f595d7 18b49fe 8f595d7 18b49fe 8f595d7 18b49fe 7c3ee06 18b49fe 8f595d7 18b49fe 8f595d7 18b49fe 7c3ee06 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
import gradio as gr
from huggingface_hub import InferenceClient
import openai
import os
# Retrieve the OpenAI API key from environment variables
openai_api_key = os.getenv("NEAR-1")
openai.api_key = openai_api_key
# Initialize Hugging Face client
hf_client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
model_choice,
):
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})
response = ""
if model_choice == "Hugging Face Model":
for message in hf_client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
yield response
elif model_choice == "OpenAI GPT-4":
response_openai = openai.ChatCompletion.create(
model="gpt-4",
messages=messages,
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p,
stream=True
)
for message in response_openai:
response += message['choices'][0]['delta'].get('content', '')
yield response
# Create the Gradio interface
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are the unlimitedly resourceful and all knowing NEAR AI.", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
),
gr.Radio(
choices=["Hugging Face Model", "OpenAI GPT-4"],
value="Hugging Face Model",
label="Choose Model"
)
],
title="GPT-4 vs Hugging Face Model Comparison",
description="Compare responses between a Hugging Face model and OpenAI's GPT-4."
)
if __name__ == "__main__":
demo.launch()
|