Update app.py

app.py

@@ -6,20 +6,31 @@ import gradio as gr
 import numpy as np
 import torch
 import nltk  # we'll use this to split into sentences
-nltk.download('punkt')
 import uuid
+import soundfile as SF
 
 from TTS.api import TTS
-# By using XTTS you agree to CPML license https://coqui.ai/cpml
-os.environ["COQUI_TOS_AGREED"] = "1"
-
 tts = TTS("tts_models/multilingual/multi-dataset/xtts_v1", gpu=True)
 
-DESCRIPTION = """# Speak with Llama2
-TODO
+title = "Speak with Llama2 70B"
+
+DESCRIPTION = """# Speak with Llama2 70B
+
+This Space demonstrates how to speak to a chatbot, based solely on open-source models.
+It relies on 3 models:
+1. [Whisper-large-v2](https://huggingface.co/spaces/sanchit-gandhi/whisper-large-v2) as an ASR model, to transcribe recorded audio to text. It is called through a [gradio client](https://www.gradio.app/docs/client).
+2. [Llama-2-70b-chat-hf](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) as the chat model, the actual chat model. It is also called through a [gradio client](https://www.gradio.app/docs/client).
+3. [Coqui's XTTS](https://huggingface.co/spaces/coqui/xtts) as a TTS model, to generate the chatbot answers. This time, the model is hosted locally.
+
+
+Note: 
+- As a derivate work of [Llama-2-70b-chat](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) by Meta,
+this demo is governed by the original [license](https://huggingface.co/spaces/ysharma/Explore_llamav2_with_TGI/blob/main/LICENSE.txt) and [acceptable use policy](https://huggingface.co/spaces/ysharma/Explore_llamav2_with_TGI/blob/main/USE_POLICY.md).
+- By using this demo you agree to the terms of the Coqui Public Model License at https://coqui.ai/cpml
 """
+css = """.toast-wrap { display: none !important } """
+
 
-CACHE_EXAMPLES = os.getenv("CACHE_EXAMPLES") == "1"
 
 system_message = "\nYou are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe.  Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information."
 temperature = 0.9
@@ -40,6 +51,7 @@ from gradio_client import Client
 whisper_client = Client("https://sanchit-gandhi-whisper-large-v2.hf.space/")
 text_client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
 
+
 def transcribe(wav_path):
     
     return whisper_client.predict(
@@ -52,88 +64,122 @@ def transcribe(wav_path):
 # Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.
 
 
-def add_text(history, text):
-    history = history + [(text, None)]
-    return history, gr.update(value="", interactive=False)
+def add_text(history, text, agree):
+    if agree == True:
+        history = [] if history is None else history
+        history = history + [(text, None)]
+        return history, gr.update(value="", interactive=False)
+    else:
+        gr.Warning("Please accept the Terms & Condition!")
+        return None, gr.update(value="", interactive=True)
+
+def add_file(history, file, agree):
+    if agree == True:
+        history = [] if history is None else history
+        text = transcribe(
+            file
+        )
+        
+        history = history + [(text, None)]
+        return history
+    else:
+        gr.Warning("Please accept the Terms & Condition!")
+        return None
 
-def add_file(history, file):
-    text = transcribe(
-        file
-    )
-    
+
+def bot(history, agree, system_prompt=""):
     
-    history = history + [(text, None)]
-    return history
-
-
-def bot(history):
-
-    history[-1][1] = ""
-    for character in text_client.submit(
-                    history,
-                    system_message,
-                    temperature,
-                    4096,
-                    temperature,
-                    repetition_penalty,
-                    api_name="/chat"
-    ):
-        history[-1][1] = character
-        yield history
-
-def generate_speech(history):
-    text_to_generate = history[-1][1]
-    text_to_generate = text_to_generate.replace("\n", " ").strip()
-    text_to_generate = nltk.sent_tokenize(text_to_generate)
+    if agree==True:
+        history = [] if history is None else history
+
+        if system_prompt == "":
+            system_prompt = system_message
+            
+        history[-1][1] = ""
+        for character in text_client.submit(
+                        history,
+                        system_prompt,
+                        temperature,
+                        4096,
+                        temperature,
+                        repetition_penalty,
+                        api_name="/chat"
+        ):
+            history[-1][1] = character
+            yield history  
+    else:        
+        gr.Warning("Please accept the Terms & Condition!")
+        return None
     
-    filename = f"{uuid.uuid4()}.wav"
-    sampling_rate = tts.synthesizer.tts_config.audio["sample_rate"]
-    silence = [0] * int(0.25 * sampling_rate)
+def generate_speech(history, agree):
+    if agree==True:
+        text_to_generate = history[-1][1]
+        text_to_generate = text_to_generate.replace("\n", " ").strip()
+        text_to_generate = nltk.sent_tokenize(text_to_generate)
+        
+        filename = f"{uuid.uuid4()}.wav"
+        sampling_rate = tts.synthesizer.tts_config.audio["sample_rate"]
+        silence = [0] * int(0.25 * sampling_rate)
 
-    
-    for sentence in text_to_generate:
-        # generate speech by cloning a voice using default settings
-        wav = tts.tts(text=sentence,
-                    speaker_wav="examples/female.wav",
-                      speed=1.5,
-                    language="en")
         
-        yield (sampling_rate, np.array(wav)) #np.array(wav + silence))
+        for sentence in text_to_generate:
+            # generate speech by cloning a voice using default settings
+            wav = tts.tts(text=sentence,
+                        speaker_wav="examples/female.wav",
+                        decoder_iterations=20,
+                        speed=1.2,
+                        language="en")
+            
+            yield (sampling_rate, np.array(wav)) #np.array(wav + silence))
+    else:        
+        gr.Warning("Please accept the Terms & Condition!")
+        return None
         
+
+with gr.Blocks(title=title) as demo:
+    gr.Markdown(DESCRIPTION)
     
+    agree = gr.Checkbox(
+        label="Agree",
+        value=False,
+        info="I agree to the terms of the Coqui Public Model License at https://coqui.ai/cpml",
+    )
     
-
-with gr.Blocks() as demo:
     chatbot = gr.Chatbot(
         [],
         elem_id="chatbot",
+        avatar_images=('examples/lama.jpeg', 'examples/lama2.jpeg'),
         bubble_full_width=False,
-        avatar_images=(None, (os.path.join(os.path.dirname(__file__), "avatar.png"))),
     )
 
     with gr.Row():
         txt = gr.Textbox(
-            scale=4,
+            scale=1,
             show_label=False,
             placeholder="Enter text and press enter, or speak to your microphone",
             container=False,
         )
-        btn = gr.inputs.Audio(source="microphone", type="filepath", optional=True)
+        btn = gr.Audio(source="microphone", type="filepath", scale=2)
         
     with gr.Row():
-        audio = gr.Audio(type="numpy", streaming=True, autoplay=True)
+        audio = gr.Audio(type="numpy", streaming=True, autoplay=True, label="Generated audio response", show_label=True)
+
+    clear_btn = gr.ClearButton([chatbot, audio])
+    
 
-    txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
-        bot, chatbot, chatbot
-    ).then(generate_speech, chatbot, audio)
+    txt_msg = txt.submit(add_text, [chatbot, txt, agree], [chatbot, txt], queue=False).then(
+        bot, [chatbot, agree], chatbot
+    ).then(generate_speech, [chatbot, agree], audio)
     
     txt_msg.then(lambda: gr.update(interactive=True), None, [txt], queue=False)
     
-    file_msg = btn.stop_recording(add_file, [chatbot, btn], [chatbot], queue=False).then(
-        bot, chatbot, chatbot
-    ).then(generate_speech, chatbot, audio)
+    file_msg = btn.stop_recording(add_file, [chatbot, btn, agree], [chatbot], queue=False).then(
+        bot, [chatbot, agree], chatbot
+    ).then(generate_speech, [chatbot, agree], audio)
     
-    #file_msg.then(lambda: gr.update(interactive=True), None, [txt], queue=False)
 
+    gr.Markdown("""<div style='margin:20px auto;'>
+<p>By using this demo you agree to the terms of the Coqui Public Model License at https://coqui.ai/cpml</p>
+</div>""")
 demo.queue()
 demo.launch(debug=True)