sth4nth commited on
Commit
61e2cce
1 Parent(s): 73c13c3

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +18 -18
app.py CHANGED
@@ -1,13 +1,13 @@
1
  import os
2
  import re
3
  import gradio as gr
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- import edge_tts
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  import asyncio
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  import time
7
  import tempfile
8
  from huggingface_hub import InferenceClient
 
9
 
10
- DESCRIPTION = """ # <center><b>JARVIS⚡</b></center>
11
  ### <center>A personal Assistant of Tony Stark for YOU
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  ### <center>Currently It supports text input, But If this space completes 1k hearts than I starts working on Audio Input.</center>
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  """
@@ -43,11 +43,11 @@ async def generate1(prompt):
43
  for response in stream:
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  output += response.token.text
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46
- communicate = edge_tts.Communicate(output)
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- with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
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- tmp_path = tmp_file.name
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- await communicate.save(tmp_path)
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- yield tmp_path
51
 
52
  client2 = InferenceClient("meta-llama/Meta-Llama-3-70B-Instruct")
53
 
@@ -62,17 +62,17 @@ async def generate2(prompt):
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  do_sample=True,
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  )
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  formatted_prompt = system_instructions2 + prompt + "[ASSISTANT]"
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- stream = client2.text_generation(
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  formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
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  output = ""
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  for response in stream:
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  output += response.token.text
70
 
71
- communicate = edge_tts.Communicate(output)
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- with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
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- tmp_path = tmp_file.name
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- await communicate.save(tmp_path)
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- yield tmp_path
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  client3 = InferenceClient("meta-llama/Meta-Llama-3-70B-Instruct")
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@@ -93,11 +93,11 @@ async def generate3(prompt):
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  for response in stream:
94
  output += response.token.text
95
 
96
- communicate = edge_tts.Communicate(output)
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- with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
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- tmp_path = tmp_file.name
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- await communicate.save(tmp_path)
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- yield tmp_path
101
 
102
  with gr.Blocks(css="style.css") as demo:
103
  gr.Markdown(DESCRIPTION)
 
1
  import os
2
  import re
3
  import gradio as gr
 
4
  import asyncio
5
  import time
6
  import tempfile
7
  from huggingface_hub import InferenceClient
8
+ from gtts import gTTS
9
 
10
+ DESCRIPTION = """ # <center><b>JARVIS⚡ 수정본 </b></center>
11
  ### <center>A personal Assistant of Tony Stark for YOU
12
  ### <center>Currently It supports text input, But If this space completes 1k hearts than I starts working on Audio Input.</center>
13
  """
 
43
  for response in stream:
44
  output += response.token.text
45
 
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+ tts = gTTS(text=output, lang='ko')
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+ with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
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+ tmp_path = tmp_file.name
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+ tts.save(tmp_path)
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+ yield tmp_path
51
 
52
  client2 = InferenceClient("meta-llama/Meta-Llama-3-70B-Instruct")
53
 
 
62
  do_sample=True,
63
  )
64
  formatted_prompt = system_instructions2 + prompt + "[ASSISTANT]"
65
+ stream = client3.text_generation(
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  formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
67
  output = ""
68
  for response in stream:
69
  output += response.token.text
70
 
71
+ tts = gTTS(text=output, lang='ko')
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+ with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
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+ tmp_path = tmp_file.name
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+ tts.save(tmp_path)
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+ yield tmp_path
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77
  client3 = InferenceClient("meta-llama/Meta-Llama-3-70B-Instruct")
78
 
 
93
  for response in stream:
94
  output += response.token.text
95
 
96
+ tts = gTTS(text=output, lang='ko')
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+ with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
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+ tmp_path = tmp_file.name
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+ tts.save(tmp_path)
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+ yield tmp_path
101
 
102
  with gr.Blocks(css="style.css") as demo:
103
  gr.Markdown(DESCRIPTION)