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import os | |
import io | |
import openai | |
import gradio as gr | |
import IPython.display | |
from PIL import Image | |
import base64 | |
from dotenv import load_dotenv, find_dotenv | |
_ = load_dotenv(find_dotenv()) # read local .env file | |
hf_api_key ='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' | |
import requests | |
def query(payload): | |
response = requests.post(API_URL, headers=headers, json=payload) | |
return response.content | |
# Helper function | |
import requests, json | |
openai.api_key = "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" | |
def predict(message, history): | |
history_openai_format = [] | |
for human, assistant in history: | |
history_openai_format.append({"role": "user", "content": human }) | |
history_openai_format.append({"role": "assistant", "content":assistant}) | |
history_openai_format.append({"role": "user", "content": message}) | |
response = openai.ChatCompletion.create( | |
model='gpt-3.5-turbo', | |
messages= history_openai_format, | |
temperature=1.0, | |
stream=True | |
) | |
partial_message = "" | |
for chunk in response: | |
if len(chunk['choices'][0]['delta']) != 0: | |
partial_message = partial_message + chunk['choices'][0]['delta']['content'] | |
yield partial_message | |
A1 = gr.ChatInterface(predict, | |
title="PeachTalk+", | |
description="An AI Powered Chatbot with Computer Vision and Image Generation Capabilities Currently Under Development By Peach State Innovation and Technology. Ask Me About Question About Anything...From Georgia and Beyond...And I'll Give You An Answer!", | |
theme= gr.themes.Glass(primary_hue="amber", neutral_hue="lime"), | |
retry_btn=None, | |
clear_btn="Clear") | |
A2 = gr.load( | |
"huggingface/google/vit-base-patch16-224", | |
title="Upon Further Review - AI Vision and Identity Technology", | |
theme= gr.themes.Glass(primary_hue="amber", neutral_hue="lime")) | |
A3 = gr.load("huggingface/google/vit-base-patch16-224") | |
pcp = gr.TabbedInterface([A1, A2], ["Chat", "Describe", "Create"], theme= gr.themes.Glass(primary_hue="amber", neutral_hue="lime")) | |
pcp.queue().launch() |