Update app.py

app.py

@@ -1,9 +1,10 @@
-
 import gradio as gr
 from gradio_client import Client
 
-title = "Llama2 70B Chatbot"
 
+
+
+title = "Llama2 70B Chatbot"
 description = """
 This Space demonstrates model [Llama-2-70b-chat-hf](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) by Meta, a Llama 2 model with 70B parameters fine-tuned for chat instructions. 
 | Model | Llama2 | Llama2-hf | Llama2-chat | Llama2-chat-hf |
@@ -11,40 +12,50 @@ This Space demonstrates model [Llama-2-70b-chat-hf](https://huggingface.co/meta-
 | 70B | [Link](https://huggingface.co/meta-llama/Llama-2-70b) | [Link](https://huggingface.co/meta-llama/Llama-2-70b-hf) | [Link](https://huggingface.co/meta-llama/Llama-2-70b-chat) | [Link](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) |
 """
 css = """.toast-wrap { display: none !important } """
-
-# examples=[
-#     ['Hello there! How are you doing?'],
-#     ['Can you explain to me briefly what is Python programming language?'],
-#     ['Explain the plot of Cinderella in a sentence.'],
-#     ['How many hours does it take a man to eat a Helicopter?'],
-#     ["Write a 100-word article on 'Benefits of Open-Source in AI research'"],
-#     ]
+examples=[
+    ['Hello there! How are you doing?'],
+    ['Can you explain to me briefly what is Python programming language?'],
+    ['Explain the plot of Cinderella in a sentence.'],
+    ['How many hours does it take a man to eat a Helicopter?'],
+    ["Write a 100-word article on 'Benefits of Open-Source in AI research'"],
+    ]
 
 
+# Stream text
+def predict(message, chatbot, system_prompt="", temperature=0.9, max_new_tokens=4096):
+    
+    client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
+    return client.predict(
+			message,	# str in 'Message' Textbox component
+            system_prompt,	# str in 'Optional system prompt' Textbox component
+			temperature,	# int | float (numeric value between 0.0 and 1.0)
+			max_new_tokens,	# int | float (numeric value between 0 and 4096)
+			0.3,	# int | float (numeric value between 0.0 and 1)
+			1,	# int | float (numeric value between 1.0 and 2.0)
+			api_name="/chat"
+    )
+        
 
 
 def transcribe(audio):
     whisper_client = Client("https://sanchit-gandhi-whisper-large-v2.hf.space/")
-    with open("audio.wav", "wb") as f:
-            f.write(audio[0])
+
     return whisper_client.predict(
-				"audio.wav",	# str (filepath or URL to file) in 'inputs' Audio component
+				audio,	# str (filepath or URL to file) in 'inputs' Audio component
 				"transcribe",	# str in 'Task' Radio component
 				api_name="/predict"
     )
 
 
-# Stream text
-def predict(message, chatbot, system_prompt="", temperature=0.9, max_new_tokens=4096):
-    
-    client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
-    return client.predict(transcribe(message),	# str in 'Message' Textbox component
-            system_prompt,	# str in 'Optional system prompt' Textbox component
-			temperature,	# int | float (numeric value between 0.0 and 1.0)
-			max_new_tokens,	# int | float (numeric value between 0 and 4096)
-			0.3,	# int | float (numeric value between 0.0 and 1)
-			1,	# int | float (numeric value between 1.0 and 2.0)
-			api_name="/chat_1")
+# Gradio Demo 
+with gr.Blocks(theme=gr.themes.Base()) as demo:
+    gr.DuplicateButton()
+    text = gr.Textbox()
+    micro = gradio.Microphone()
+    micro.stop_recording(transcribe, [micro],[text])
+    gr.ChatInterface(predict,text, title=title, description=description, css=css, examples=examples) 
         
-demo = gr.Interface(predict, title=title, inputs="microphone", outputs="text", description=description, css=css,theme=gr.themes.Base())#, examples=examples)
-demo.launch()
+demo.queue().launch(debug=True)
+
+
+