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): 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 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 or Hugging Face token first!!!" self.add_message(message, "user") messages = messages + [(message, None)] 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 = chat_huggingface(self.all_messages, self.OPENAI_KEY, self.HUGGINGFACE_TOKEN)["message"] 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: image_url = image_url.replace("public/", "") messages = messages + [((None, (f"public/{image_url}",)))] for audio_url in audio_urls: audio_url = audio_url.replace("public/", "") messages = messages + [((None, (f"public/{audio_url}",)))] for video_url in video_urls: video_url = video_url.replace("public/", "") messages = messages + [((None, (f"public/{video_url}",)))] return messages with gr.Blocks() as demo: state = gr.State(value={"client": Client()}) gr.Markdown("

HuggingGPT

") gr.Markdown("

") gr.Markdown("

A system to connect LLMs with ML community. See our Project and Paper.

") 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 ).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 ).style(container=False) with gr.Column(scale=0.15, min_width=0): btn3 = gr.Button("Submit").style(full_height=True) chatbot = gr.Chatbot([], elem_id="chatbot").style(height=500) 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) hugging_face_token.submit(set_token, [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) 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", "generate a video and audio about a dog is running on the grass", "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()