HuggingGPT / app.py
wowochkin's picture
Duplicate from microsoft/HuggingGPT
f718d71
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)
class Client:
def __init__(self) -> None:
self.OPENAI_KEY = ""
self.HUGGINGFACE_TOKEN = ""
self.all_messages = []
def set_key(self, openai_key):
self.OPENAI_KEY = openai_key
if len(self.HUGGINGFACE_TOKEN)>0:
gr.update(visible = True)
return self.OPENAI_KEY
def set_token(self, huggingface_token):
self.HUGGINGFACE_TOKEN = huggingface_token
if len(self.OPENAI_KEY)>0:
gr.update(visible = True)
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 len(self.OPENAI_KEY) == 0 or not self.OPENAI_KEY.startswith("sk-") or len(self.HUGGINGFACE_TOKEN) == 0 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 len(self.OPENAI_KEY) == 0 or not self.OPENAI_KEY.startswith("sk-") or len(self.HUGGINGFACE_TOKEN) == 0 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</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/microsoft/HuggingGPT?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>''')
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)
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 of the multimedia resource must contain the extension name.",
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)
openai_api_key.submit(set_key, [state, openai_api_key], [openai_api_key])
txt.submit(add_text, [state, chatbot, txt], [chatbot, txt]).then(bot, [state, chatbot], [chatbot, results])
hugging_face_token.submit(set_token, [state, hugging_face_token], [hugging_face_token])
btn1.click(set_key, [state, openai_api_key], [openai_api_key])
btn2.click(add_text, [state, chatbot, txt], [chatbot, txt]).then(bot, [state, chatbot], [chatbot, results])
btn3.click(set_token, [state, hugging_face_token], [hugging_face_token])
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?",
"Please generate a canny image based on /examples/f.jpg",
"show me a joke and an image of cat",
"what is in the examples/a.jpg",
"based on the /examples/a.jpg, please generate a video and audio",
"based on pose of /examples/d.jpg and content of /examples/e.jpg, please show me a new image",
],
inputs=txt
)
demo.launch()