Duplicate from sanchit-gandhi/chatGPT

Co-authored-by: Sanchit Gandhi <sanchit-gandhi@users.noreply.huggingface.co>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
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+*.model filter=lfs diff=lfs merge=lfs -text
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+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+title: ChatGPT
+emoji: 🏃
+colorFrom: red
+colorTo: blue
+sdk: gradio
+sdk_version: 3.12.0
+app_file: app.py
+pinned: false
+duplicated_from: sanchit-gandhi/chatGPT
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import torch
+import os
+
+import gradio as gr
+from transformers import pipeline
+
+from pyChatGPT import ChatGPT
+
+from speechbrain.pretrained import Tacotron2
+from speechbrain.pretrained import HIFIGAN
+
+import json
+import soundfile as sf
+
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+print(f"Is CUDA available: {torch.cuda.is_available()}")
+print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
+
+# Intialise STT (Whisper)
+pipe = pipeline(
+    task="automatic-speech-recognition",
+    model="openai/whisper-base.en",
+    chunk_length_s=30,
+    device=device,
+)
+
+# Initialise ChatGPT session
+session_token = os.environ.get("SessionToken")
+api = ChatGPT(session_token=session_token)
+
+# Intialise TTS (tacotron2) and Vocoder (HiFIGAN)
+tacotron2 = Tacotron2.from_hparams(
+    source="speechbrain/tts-tacotron2-ljspeech",
+    savedir="tmpdir_tts",
+    overrides={"max_decoder_steps": 10000},
+    run_opts={"device": device},
+)
+hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-ljspeech", savedir="tmpdir_vocoder")
+
+
+def get_response_from_chatbot(text, reset_conversation):
+    try:
+        if reset_conversation:
+            api.refresh_auth()
+            api.reset_conversation()
+        resp = api.send_message(text)
+        response = resp["message"]
+    except:
+        response = "Sorry, the chatGPT queue is full. Please try again later."
+    return response
+
+
+def chat(input_audio, chat_history, reset_conversation):
+    # speech -> text (Whisper)
+    message = pipe(input_audio)["text"]
+
+    # text -> response (chatGPT)
+    response = get_response_from_chatbot(message, reset_conversation)
+
+    # response -> speech (tacotron2)
+    mel_output, mel_length, alignment = tacotron2.encode_text(response)
+    wav = hifi_gan.decode_batch(mel_output)
+    sf.write("out.wav", wav.squeeze().cpu().numpy(), 22050)
+
+    out_chat = []
+    chat_history = chat_history if not reset_conversation else ""
+    if chat_history != "":
+        out_chat = json.loads(chat_history)
+
+    out_chat.append((message, response))
+    chat_history = json.dumps(out_chat)
+
+    return out_chat, chat_history, "out.wav"
+
+
+start_work = """async() => {
+    function isMobile() {
+        try {
+            document.createEvent("TouchEvent"); return true;
+        } catch(e) {
+            return false; 
+        }
+    }
+	function getClientHeight()
+	{
+	  var clientHeight=0;
+	  if(document.body.clientHeight&&document.documentElement.clientHeight) {
+		var clientHeight = (document.body.clientHeight<document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight;
+	  } else {
+		var clientHeight = (document.body.clientHeight>document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight;
+	  }
+	  return clientHeight;
+	}
+
+    function setNativeValue(element, value) {
+      const valueSetter = Object.getOwnPropertyDescriptor(element.__proto__, 'value').set;
+      const prototype = Object.getPrototypeOf(element);
+      const prototypeValueSetter = Object.getOwnPropertyDescriptor(prototype, 'value').set;
+
+      if (valueSetter && valueSetter !== prototypeValueSetter) {
+            prototypeValueSetter.call(element, value);
+      } else {
+            valueSetter.call(element, value);
+      }
+    }
+    var gradioEl = document.querySelector('body > gradio-app').shadowRoot;
+    if (!gradioEl) {
+        gradioEl = document.querySelector('body > gradio-app');
+    }
+
+    if (typeof window['gradioEl'] === 'undefined') {
+        window['gradioEl'] = gradioEl;
+
+        const page1 = window['gradioEl'].querySelectorAll('#page_1')[0];
+        const page2 = window['gradioEl'].querySelectorAll('#page_2')[0]; 
+
+        page1.style.display = "none";
+        page2.style.display = "block"; 
+        window['div_count'] = 0;
+        window['chat_bot'] = window['gradioEl'].querySelectorAll('#chat_bot')[0];
+        window['chat_bot1'] = window['gradioEl'].querySelectorAll('#chat_bot1')[0];   
+        chat_row = window['gradioEl'].querySelectorAll('#chat_row')[0]; 
+        prompt_row = window['gradioEl'].querySelectorAll('#prompt_row')[0]; 
+        window['chat_bot1'].children[1].textContent = '';
+
+        clientHeight = getClientHeight();
+        new_height = (clientHeight-300) + 'px';
+        chat_row.style.height = new_height;
+        window['chat_bot'].style.height = new_height;
+        window['chat_bot'].children[2].style.height = new_height;
+        window['chat_bot1'].style.height = new_height;
+        window['chat_bot1'].children[2].style.height = new_height;
+        prompt_row.children[0].style.flex = 'auto';
+        prompt_row.children[0].style.width = '100%';
+
+        window['checkChange'] = function checkChange() {
+            try {
+                if (window['chat_bot'].children[2].children[0].children.length > window['div_count']) {
+                    new_len = window['chat_bot'].children[2].children[0].children.length - window['div_count'];
+                    for (var i = 0; i < new_len; i++) { 
+                        new_div = window['chat_bot'].children[2].children[0].children[window['div_count'] + i].cloneNode(true);
+                        window['chat_bot1'].children[2].children[0].appendChild(new_div);
+                    }
+                    window['div_count'] = chat_bot.children[2].children[0].children.length;
+                }
+                if (window['chat_bot'].children[0].children.length > 1) {
+                     window['chat_bot1'].children[1].textContent = window['chat_bot'].children[0].children[1].textContent;
+                } else {
+                    window['chat_bot1'].children[1].textContent = '';
+                }
+
+            } catch(e) {
+            }        
+        }
+        window['checkChange_interval'] = window.setInterval("window.checkChange()", 500);         
+    }
+
+    return false;
+}"""
+
+with gr.Blocks(title="Talk to chatGPT") as demo:
+    gr.Markdown("## Talk to chatGPT ##")
+    gr.HTML(
+        "<p> Demo uses <a href='https://huggingface.co/openai/whisper-base.en' class='underline'>Whisper</a> to convert the input speech"
+        " to transcribed text, <a href='https://chat.openai.com/chat' class='underline'>chatGPT</a> to generate responses, and <a"
+        " href='https://huggingface.co/speechbrain/tts-tacotron2-ljspeech' class='underline'>tacotron2</a> to convert the response to"
+        " output speech: </p>"
+    )
+    gr.HTML("<p> <center><img src='https://raw.githubusercontent.com/sanchit-gandhi/codesnippets/main/pipeline.png' width='870'></center> </p>")
+    gr.HTML(
+        "<p>You can duplicate this space and use your own session token: <a style='display:inline-block'"
+        " href='https://huggingface.co/spaces/sanchit-gandhi/chatGPT?duplicate=true'><img"
+        " src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=10'"
+        " alt='Duplicate Space'></a></p>"
+    )
+    gr.HTML(
+        "<p> Instructions on how to obtain your session token can be found in the video <a style='display:inline-block'"
+        " href='https://youtu.be/TdNSj_qgdFk?t=175'><font style='color:blue;weight:bold;'>here</font></a>."
+        " Add your session token by going to <i>Settings</i> -> <i>New secret</i> and add the token under the name <i>SessionToken</i>. </p>"
+    )
+    with gr.Group(elem_id="page_1", visible=True) as page_1:
+        with gr.Box():
+            with gr.Row():
+                start_button = gr.Button("Let's talk to chatGPT! 🗣", elem_id="start-btn", visible=True)
+                start_button.click(fn=None, inputs=[], outputs=[], _js=start_work)
+
+    with gr.Group(elem_id="page_2", visible=False) as page_2:
+        with gr.Row(elem_id="chat_row"):
+            chatbot = gr.Chatbot(elem_id="chat_bot", visible=False).style(color_map=("green", "blue"))
+            chatbot1 = gr.Chatbot(elem_id="chat_bot1").style(color_map=("green", "blue"))
+        with gr.Row():
+            prompt_input_audio = gr.Audio(
+                source="microphone",
+                type="filepath",
+                label="Record Audio Input",
+            )
+            prompt_output_audio = gr.Audio()
+
+        reset_conversation = gr.Checkbox(label="Reset conversation?", value=False)
+        with gr.Row(elem_id="prompt_row"):
+            chat_history = gr.Textbox(lines=4, label="prompt", visible=False)
+            submit_btn = gr.Button(value="Send to chatGPT", elem_id="submit-btn").style(
+                margin=True,
+                rounded=(True, True, True, True),
+                width=100,
+            )
+
+        submit_btn.click(
+            fn=chat,
+            inputs=[prompt_input_audio, chat_history, reset_conversation],
+            outputs=[chatbot, chat_history, prompt_output_audio],
+        )
+
+demo.launch(debug=True)

packages.txt

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+libsndfile1

requirements.txt

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+git+https://github.com/huggingface/transformers
+--extra-index-url https://download.pytorch.org/whl/cu113
+torch
+speechbrain
+soundfile
+pychatGPT