HuggingGPT-Lite / app.py
Alfasign's picture
Duplicate from taesiri/HuggingGPT-Lite
1381f86
import uuid
import gradio as gr
import re
from diffusers.utils import load_image
import requests
from awesome_chat import chat_huggingface
import os
os.makedirs("public/images", exist_ok=True)
os.makedirs("public/audios", exist_ok=True)
os.makedirs("public/videos", exist_ok=True)
HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
OPENAI_KEY = os.environ.get("OPENAI_KEY")
class Client:
def __init__(self) -> None:
self.OPENAI_KEY = OPENAI_KEY
self.HUGGINGFACE_TOKEN = HUGGINGFACE_TOKEN
self.all_messages = []
def set_key(self, openai_key):
self.OPENAI_KEY = openai_key
return self.OPENAI_KEY
def set_token(self, huggingface_token):
self.HUGGINGFACE_TOKEN = huggingface_token
return self.HUGGINGFACE_TOKEN
def add_message(self, content, role):
message = {"role": role, "content": content}
self.all_messages.append(message)
def extract_medias(self, message):
# url_pattern = re.compile(r"(http(s?):|\/)?([\.\/_\w:-])*?")
urls = []
# for match in url_pattern.finditer(message):
# if match.group(0) not in urls:
# urls.append(match.group(0))
image_pattern = re.compile(
r"(http(s?):|\/)?([\.\/_\w:-])*?\.(jpg|jpeg|tiff|gif|png)"
)
image_urls = []
for match in image_pattern.finditer(message):
if match.group(0) not in image_urls:
image_urls.append(match.group(0))
audio_pattern = re.compile(r"(http(s?):|\/)?([\.\/_\w:-])*?\.(flac|wav)")
audio_urls = []
for match in audio_pattern.finditer(message):
if match.group(0) not in audio_urls:
audio_urls.append(match.group(0))
video_pattern = re.compile(r"(http(s?):|\/)?([\.\/_\w:-])*?\.(mp4)")
video_urls = []
for match in video_pattern.finditer(message):
if match.group(0) not in video_urls:
video_urls.append(match.group(0))
return urls, image_urls, audio_urls, video_urls
def add_text(self, messages, message):
if (
not self.OPENAI_KEY
or not self.OPENAI_KEY.startswith("sk-")
or not self.HUGGINGFACE_TOKEN
or not self.HUGGINGFACE_TOKEN.startswith("hf_")
):
return (
messages,
"Please set your OpenAI API key and Hugging Face token first!!!",
)
self.add_message(message, "user")
messages = messages + [(message, None)]
urls, image_urls, audio_urls, video_urls = self.extract_medias(message)
for image_url in image_urls:
if not image_url.startswith("http") and not image_url.startswith("public"):
image_url = "public/" + image_url
image = load_image(image_url)
name = f"public/images/{str(uuid.uuid4())[:4]}.jpg"
image.save(name)
messages = messages + [((f"{name}",), None)]
for audio_url in audio_urls and not audio_url.startswith("public"):
if not audio_url.startswith("http"):
audio_url = "public/" + audio_url
ext = audio_url.split(".")[-1]
name = f"public/audios/{str(uuid.uuid4()[:4])}.{ext}"
response = requests.get(audio_url)
with open(name, "wb") as f:
f.write(response.content)
messages = messages + [((f"{name}",), None)]
for video_url in video_urls and not video_url.startswith("public"):
if not video_url.startswith("http"):
video_url = "public/" + video_url
ext = video_url.split(".")[-1]
name = f"public/audios/{str(uuid.uuid4()[:4])}.{ext}"
response = requests.get(video_url)
with open(name, "wb") as f:
f.write(response.content)
messages = messages + [((f"{name}",), None)]
return messages, ""
def bot(self, messages):
if (
not self.OPENAI_KEY
or not self.OPENAI_KEY.startswith("sk-")
or not self.HUGGINGFACE_TOKEN
or not self.HUGGINGFACE_TOKEN.startswith("hf_")
):
return messages, {}
message, results = chat_huggingface(
self.all_messages, self.OPENAI_KEY, self.HUGGINGFACE_TOKEN
)
urls, image_urls, audio_urls, video_urls = self.extract_medias(message)
self.add_message(message, "assistant")
messages[-1][1] = message
for image_url in image_urls:
if not image_url.startswith("http"):
image_url = image_url.replace("public/", "")
messages = messages + [((None, (f"public/{image_url}",)))]
# else:
# messages = messages + [((None, (f"{image_url}",)))]
for audio_url in audio_urls:
if not audio_url.startswith("http"):
audio_url = audio_url.replace("public/", "")
messages = messages + [((None, (f"public/{audio_url}",)))]
# else:
# messages = messages + [((None, (f"{audio_url}",)))]
for video_url in video_urls:
if not video_url.startswith("http"):
video_url = video_url.replace("public/", "")
messages = messages + [((None, (f"public/{video_url}",)))]
# else:
# messages = messages + [((None, (f"{video_url}",)))]
# replace int key to string key
results = {str(k): v for k, v in results.items()}
return messages, results
css = ".json {height: 527px; overflow: scroll;} .json-holder {height: 527px; overflow: scroll;}"
with gr.Blocks(css=css) as demo:
state = gr.State(value={"client": Client()})
gr.Markdown("<h1><center>HuggingGPT - Lite 🎐 </center></h1>")
gr.Markdown(
"<p align='center'><img src='https://i.ibb.co/qNH3Jym/logo.png' height='25' width='95'></p>"
)
gr.Markdown(
"<p align='center' style='font-size: 20px;'>A system to connect LLMs with ML community. See our <a href='https://github.com/microsoft/JARVIS'>Project</a> and <a href='http://arxiv.org/abs/2303.17580'>Paper</a>.</p>"
)
gr.HTML(
"""<center><a href="https://huggingface.co/spaces/taesiri/HuggingGPT-Lite?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key and Hugging Face Token</center>"""
)
gr.Markdown(
""">**Note**: This is a further lite version of the original HuggingGPT designed to run on CPU-only spaces. This model by default uses `gpt-3.5-turbo` which is much much cheaper than `text-davinci-003`. """
)
if not OPENAI_KEY:
with gr.Row().style():
with gr.Column(scale=0.85):
openai_api_key = gr.Textbox(
show_label=False,
placeholder="Set your OpenAI API key here and press Enter",
lines=1,
type="password",
).style(container=False)
with gr.Column(scale=0.15, min_width=0):
btn1 = gr.Button("Submit").style(full_height=True)
if not HUGGINGFACE_TOKEN:
with gr.Row().style():
with gr.Column(scale=0.85):
hugging_face_token = gr.Textbox(
show_label=False,
placeholder="Set your Hugging Face Token here and press Enter",
lines=1,
type="password",
).style(container=False)
with gr.Column(scale=0.15, min_width=0):
btn3 = gr.Button("Submit").style(full_height=True)
with gr.Row().style():
with gr.Column(scale=0.6):
chatbot = gr.Chatbot([], elem_id="chatbot").style(height=500)
with gr.Column(scale=0.4):
results = gr.JSON(elem_classes="json")
with gr.Row().style():
with gr.Column(scale=0.85):
txt = gr.Textbox(
show_label=False,
placeholder="Enter text and press enter. The url must contain the media type. e.g, https://example.com/example.jpg",
lines=1,
).style(container=False)
with gr.Column(scale=0.15, min_width=0):
btn2 = gr.Button("Send").style(full_height=True)
def set_key(state, openai_api_key):
return state["client"].set_key(openai_api_key)
def add_text(state, chatbot, txt):
return state["client"].add_text(chatbot, txt)
def set_token(state, hugging_face_token):
return state["client"].set_token(hugging_face_token)
def bot(state, chatbot):
return state["client"].bot(chatbot)
if not OPENAI_KEY:
openai_api_key.submit(set_key, [state, openai_api_key], [openai_api_key])
btn1.click(set_key, [state, openai_api_key], [openai_api_key])
if not HUGGINGFACE_TOKEN:
hugging_face_token.submit(
set_token, [state, hugging_face_token], [hugging_face_token]
)
btn3.click(set_token, [state, hugging_face_token], [hugging_face_token])
txt.submit(add_text, [state, chatbot, txt], [chatbot, txt]).then(
bot, [state, chatbot], [chatbot, results]
)
btn2.click(add_text, [state, chatbot, txt], [chatbot, txt]).then(
bot, [state, chatbot], [chatbot, results]
)
gr.Examples(
examples=[
"Given a collection of image A: /examples/a.jpg, B: /examples/b.jpg, C: /examples/c.jpg, please tell me how many zebras in these picture?",
"show me a joke and an image of cat",
"what is in the examples/a.jpg",
],
inputs=txt,
)
demo.launch()