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| from panda_gpt import PandaGPT | |
| import gradio as gr | |
| from huggingface_hub import hf_hub_download | |
| vicuna_path = hf_hub_download(repo_id="ningshanwutuobang/ggml-pandagpt-vicuna-merge", filename="ggml-pandagpt-vicuna-q4_1.bin") | |
| panda_path = hf_hub_download(repo_id="openllmplayground/pandagpt_13b_max_len_400", filename="pytorch_model.pt") | |
| a = PandaGPT((vicuna_path,)) | |
| a.load_projection(panda_path) | |
| def add_text(history, text): | |
| history = history + [(text, None)] | |
| return history, gr.update(value="", interactive=False) | |
| def add_file(history, file): | |
| history = history + [((file.name,), None)] | |
| return history | |
| def bot(history): | |
| text = history[-1][0] | |
| image_paths = [] | |
| audio_paths = [] | |
| video_paths = [] | |
| for i in history[:-1]: | |
| if i[1] is None: | |
| if i[0][:4] in [".png", "jpeg"]: | |
| image_paths += list(i[0]) | |
| if i[0][:3] in ["mp3", "wav"]: | |
| audio_paths += list(i[0]) | |
| if i[0][:3] in ["mp4", "avi", "mkv"]: | |
| video_paths += list(i[0]) | |
| else: | |
| image_paths = [] | |
| audio_paths = [] | |
| video_paths = [] | |
| if len(image_paths) == 0 and len(audio_paths) == 0 and len(video_paths) == 0: | |
| response = a.eval_with_image(None, text) | |
| else: | |
| response = a.eval_with_image({"image_paths": image_paths,"audio_paths": audio_paths, "video_paths": video_paths}, text) | |
| history[-1][1] = "" | |
| for i in a.generate(): | |
| history[-1][1] += i | |
| yield history | |
| if history[-1][1].endswith("###"): | |
| history[-1][1] = history[-1][1][:-3] | |
| yield history | |
| with gr.Blocks() as demo: | |
| chatbot = gr.Chatbot([], elem_id="chatbot").style(height=750) | |
| with gr.Row(): | |
| with gr.Column(scale=0.65): | |
| txt = gr.Textbox( | |
| show_label=False, | |
| placeholder="Enter text and press enter, or upload an image", | |
| ).style(container=False) | |
| with gr.Column(scale=0.15, min_width=0): | |
| btn = gr.UploadButton("π", file_types=["image", "video", "audio"]) | |
| with gr.Column(scale=0.15, min_width=0): | |
| btn2 = gr.Button("reset") | |
| txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then( | |
| bot, chatbot, chatbot | |
| ) | |
| txt_msg.then(lambda: gr.update(interactive=True), None, [txt], queue=False) | |
| file_msg = btn.upload(add_file, [chatbot, btn], [chatbot], queue=False) | |
| btn2.click(a.reset, None, chatbot, queue=False) | |
| demo.queue() | |
| demo.launch() | |
| # a.chat_with | |