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A10G
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 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) | |
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() |