Create app.py

app.py

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+from __future__ import annotations
+
+import os
+
+import gradio as gr
+import numpy as np
+import torch
+import torchaudio
+
+DESCRIPTION = """# Speak with Llama2
+TODO
+"""
+
+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
+top_p = 0.6
+repetition_penalty = 1.2
+
+import gradio as gr
+import os
+import time
+
+import gradio as gr
+from transformers import pipeline
+import numpy as np
+
+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(
+				wav_path,	# str (filepath or URL to file) in 'inputs' Audio component
+				"transcribe",	# str in 'Task' Radio component
+				api_name="/predict"
+)
+    
+
+# 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_file(history, file):
+    text = transcribe(
+        file
+    )
+    
+    
+    history = history + [(text, None)]
+    return history
+
+
+def bot(history):
+
+   
+    history[-1][1] = ""
+    for character in text_client.predict(
+                    history,
+                    system_message,
+                    temperature,
+                    4096,
+                    temperature,
+                    repetition_penalty,
+                    api_name="/chat"
+    ):
+        history[-1][1] += character
+        yield history
+
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot(
+        [],
+        elem_id="chatbot",
+        bubble_full_width=False,
+        avatar_images=(None, (os.path.join(os.path.dirname(__file__), "avatar.png"))),
+    )
+
+    with gr.Row():
+        txt = gr.Textbox(
+            scale=4,
+            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)
+
+    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.stop_recording(add_file, [chatbot, btn], [chatbot], queue=False).then(
+        bot, chatbot, chatbot
+    )
+    
+    #file_msg.then(lambda: gr.update(interactive=True), None, [txt], queue=False)
+
+demo.queue()
+demo.launch(debug=True)