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import uuid |
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import gradio as gr |
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import re |
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from diffusers.utils import load_image |
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import requests |
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from awesome_chat import chat_huggingface |
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import os |
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os.makedirs("public/images", exist_ok=True) |
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os.makedirs("public/audios", exist_ok=True) |
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os.makedirs("public/videos", exist_ok=True) |
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HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN") |
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OPENAI_KEY = os.environ.get("OPENAI_KEY") |
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class Client: |
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def __init__(self) -> None: |
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self.OPENAI_KEY = OPENAI_KEY |
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self.HUGGINGFACE_TOKEN = HUGGINGFACE_TOKEN |
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self.all_messages = [] |
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def set_key(self, openai_key): |
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self.OPENAI_KEY = openai_key |
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return self.OPENAI_KEY |
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def set_token(self, huggingface_token): |
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self.HUGGINGFACE_TOKEN = huggingface_token |
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return self.HUGGINGFACE_TOKEN |
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def add_message(self, content, role): |
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message = {"role":role, "content":content} |
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self.all_messages.append(message) |
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def extract_medias(self, message): |
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urls = [] |
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image_pattern = re.compile(r"(http(s?):|\/)?([\.\/_\w:-])*?\.(jpg|jpeg|tiff|gif|png)") |
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image_urls = [] |
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for match in image_pattern.finditer(message): |
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if match.group(0) not in image_urls: |
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image_urls.append(match.group(0)) |
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audio_pattern = re.compile(r"(http(s?):|\/)?([\.\/_\w:-])*?\.(flac|wav)") |
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audio_urls = [] |
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for match in audio_pattern.finditer(message): |
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if match.group(0) not in audio_urls: |
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audio_urls.append(match.group(0)) |
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video_pattern = re.compile(r"(http(s?):|\/)?([\.\/_\w:-])*?\.(mp4)") |
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video_urls = [] |
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for match in video_pattern.finditer(message): |
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if match.group(0) not in video_urls: |
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video_urls.append(match.group(0)) |
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return urls, image_urls, audio_urls, video_urls |
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def add_text(self, messages, message): |
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if not self.OPENAI_KEY or not self.OPENAI_KEY.startswith("sk-") or not self.HUGGINGFACE_TOKEN or not self.HUGGINGFACE_TOKEN.startswith("hf_"): |
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return messages, "Please set your OpenAI API key and Hugging Face token first!!!" |
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self.add_message(message, "user") |
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messages = messages + [(message, None)] |
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urls, image_urls, audio_urls, video_urls = self.extract_medias(message) |
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for image_url in image_urls: |
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if not image_url.startswith("http") and not image_url.startswith("public"): |
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image_url = "public/" + image_url |
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image = load_image(image_url) |
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name = f"public/images/{str(uuid.uuid4())[:4]}.jpg" |
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image.save(name) |
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messages = messages + [((f"{name}",), None)] |
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for audio_url in audio_urls and not audio_url.startswith("public"): |
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if not audio_url.startswith("http"): |
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audio_url = "public/" + audio_url |
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ext = audio_url.split(".")[-1] |
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name = f"public/audios/{str(uuid.uuid4()[:4])}.{ext}" |
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response = requests.get(audio_url) |
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with open(name, "wb") as f: |
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f.write(response.content) |
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messages = messages + [((f"{name}",), None)] |
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for video_url in video_urls and not video_url.startswith("public"): |
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if not video_url.startswith("http"): |
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video_url = "public/" + video_url |
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ext = video_url.split(".")[-1] |
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name = f"public/audios/{str(uuid.uuid4()[:4])}.{ext}" |
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response = requests.get(video_url) |
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with open(name, "wb") as f: |
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f.write(response.content) |
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messages = messages + [((f"{name}",), None)] |
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return messages, "" |
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def bot(self, messages): |
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if not self.OPENAI_KEY or not self.OPENAI_KEY.startswith("sk-") or not self.HUGGINGFACE_TOKEN or not self.HUGGINGFACE_TOKEN.startswith("hf_"): |
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return messages, {} |
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message, results = chat_huggingface(self.all_messages, self.OPENAI_KEY, self.HUGGINGFACE_TOKEN) |
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urls, image_urls, audio_urls, video_urls = self.extract_medias(message) |
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self.add_message(message, "assistant") |
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messages[-1][1] = message |
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for image_url in image_urls: |
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if not image_url.startswith("http"): |
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image_url = image_url.replace("public/", "") |
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messages = messages + [((None, (f"public/{image_url}",)))] |
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for audio_url in audio_urls: |
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if not audio_url.startswith("http"): |
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audio_url = audio_url.replace("public/", "") |
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messages = messages + [((None, (f"public/{audio_url}",)))] |
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for video_url in video_urls: |
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if not video_url.startswith("http"): |
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video_url = video_url.replace("public/", "") |
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messages = messages + [((None, (f"public/{video_url}",)))] |
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results = {str(k): v for k, v in results.items()} |
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return messages, results |
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css = ".json {height: 527px; overflow: scroll;} .json-holder {height: 527px; overflow: scroll;}" |
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with gr.Blocks(css=css) as demo: |
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state = gr.State(value={"client": Client()}) |
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gr.Markdown("<h1><center>HuggingGPT</center></h1>") |
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gr.Markdown("<p align='center'><img src='https://i.ibb.co/qNH3Jym/logo.png' height='25' width='95'></p>") |
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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>") |
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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>''') |
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if not OPENAI_KEY: |
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with gr.Row().style(): |
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with gr.Column(scale=0.85): |
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openai_api_key = gr.Textbox( |
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show_label=False, |
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placeholder="Set your OpenAI API key here and press Enter", |
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lines=1, |
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type="password" |
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).style(container=False) |
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with gr.Column(scale=0.15, min_width=0): |
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btn1 = gr.Button("Submit").style(full_height=True) |
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if not HUGGINGFACE_TOKEN: |
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with gr.Row().style(): |
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with gr.Column(scale=0.85): |
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hugging_face_token = gr.Textbox( |
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show_label=False, |
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placeholder="Set your Hugging Face Token here and press Enter", |
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lines=1, |
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type="password" |
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).style(container=False) |
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with gr.Column(scale=0.15, min_width=0): |
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btn3 = gr.Button("Submit").style(full_height=True) |
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with gr.Row().style(): |
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with gr.Column(scale=0.6): |
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chatbot = gr.Chatbot([], elem_id="chatbot").style(height=500) |
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with gr.Column(scale=0.4): |
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results = gr.JSON(elem_classes="json") |
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with gr.Row().style(): |
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with gr.Column(scale=0.85): |
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txt = gr.Textbox( |
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show_label=False, |
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placeholder="Enter text and press enter. The url must contain the media type. e.g, https://example.com/example.jpg", |
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lines=1, |
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).style(container=False) |
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with gr.Column(scale=0.15, min_width=0): |
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btn2 = gr.Button("Send").style(full_height=True) |
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def set_key(state, openai_api_key): |
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return state["client"].set_key(openai_api_key) |
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def add_text(state, chatbot, txt): |
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return state["client"].add_text(chatbot, txt) |
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def set_token(state, hugging_face_token): |
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return state["client"].set_token(hugging_face_token) |
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def bot(state, chatbot): |
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return state["client"].bot(chatbot) |
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if not OPENAI_KEY: |
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openai_api_key.submit(set_key, [state, openai_api_key], [openai_api_key]) |
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btn1.click(set_key, [state, openai_api_key], [openai_api_key]) |
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if not HUGGINGFACE_TOKEN: |
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hugging_face_token.submit(set_token, [state, hugging_face_token], [hugging_face_token]) |
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btn3.click(set_token, [state, hugging_face_token], [hugging_face_token]) |
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txt.submit(add_text, [state, chatbot, txt], [chatbot, txt]).then(bot, [state, chatbot], [chatbot, results]) |
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btn2.click(add_text, [state, chatbot, txt], [chatbot, txt]).then(bot, [state, chatbot], [chatbot, results]) |
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gr.Examples( |
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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?", |
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"Please generate a canny image based on /examples/f.jpg", |
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"show me a joke and an image of cat", |
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"what is in the examples/a.jpg", |
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"based on the /examples/a.jpg, please generate a video and audio", |
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"based on pose of /examples/d.jpg and content of /examples/e.jpg, please show me a new image", |
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], |
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inputs=txt |
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) |
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demo.launch() |