Ravishankarsharma commited on
Commit
2ae31a4
·
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1 Parent(s): 899f576

Update app.py

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Files changed (1) hide show
  1. app.py +57 -60
app.py CHANGED
@@ -7,82 +7,79 @@ from fastapi.responses import HTMLResponse
7
  from gradio_client import Client
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  import uvicorn
9
 
10
-
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  app = FastAPI(title="Meeting Summarizer API")
12
 
13
-
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  # Replace this with your actual deployed HF space/model if needed
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  HF_MODEL_SPACE = "Ravishankarsharma/voice2text-summarizer"
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17
-
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  # Public demo audio (replace if you want your own)
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  DEM0_AUDIO_URL = "https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/0001.flac"
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-
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  # Initialize HF client
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  try:
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- client = Client(HF_MODEL_SPACE)
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  except Exception as e:
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- print("⚠️ Client initialization failed:", e)
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- client = None
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-
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-
30
 
31
 
32
  @app.get("/", response_class=HTMLResponse)
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  async def home():
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- return """
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- <html><body>
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- <h2>Meeting Summarizer API</h2>
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- <p>➡️ Call <a href='/summarize'>/summarize</a> to get meeting summary</p>
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- <p>➡️ Swagger docs: <a href='/docs'>/docs</a></p>
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- </body></html>
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- """
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-
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-
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  @app.get("/summarize")
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  async def summarize_meeting():
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- if not client:
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- raise HTTPException(status_code=500, detail="❌ Hugging Face client not initialized")
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-
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-
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- try:
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- meeting_url = DEM0_AUDIO_URL
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-
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-
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- # Download audio
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- response = requests.get(meeting_url, stream=True, timeout=30)
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- if response.status_code != 200:
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- raise HTTPException(status_code=400, detail=f"Failed to fetch meeting audio (status {response.status_code})")
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-
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-
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- suffix = ".flac" if meeting_url.endswith('.flac') else os.path.splitext(meeting_url)[1] or ".wav"
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-
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-
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- with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
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- for chunk in response.iter_content(chunk_size=8192):
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- if chunk:
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- tmp.write(chunk)
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- tmp_path = tmp.name
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-
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-
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- # Call your HF model. The predict input depends on how your space expects input.
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- # If your space expects a file, use handle_file(tmp_path) instead. Here we try both common ways.
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- try:
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- # First try: send file path (many gradio-based spaces accept this)
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- result = client.predict(tmp_path, api_name="/predict")
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- except Exception:
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- # Fallback: send the raw bytes
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- with open(tmp_path, "rb") as fd:
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- data = fd.read()
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- result = client.predict(data, api_name="/predict")
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-
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-
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- # Clean up
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- try:
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- os.remove(tmp_path)
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- except Exception:
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- pass
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- uvicorn.run("app:app", host="0.0.0.0", port=8000, reload=True)
 
 
 
 
 
 
7
  from gradio_client import Client
8
  import uvicorn
9
 
 
10
  app = FastAPI(title="Meeting Summarizer API")
11
 
 
12
  # Replace this with your actual deployed HF space/model if needed
13
  HF_MODEL_SPACE = "Ravishankarsharma/voice2text-summarizer"
14
 
 
15
  # Public demo audio (replace if you want your own)
16
  DEM0_AUDIO_URL = "https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/0001.flac"
17
 
 
18
  # Initialize HF client
19
  try:
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+ client = Client(HF_MODEL_SPACE)
21
  except Exception as e:
22
+ print("⚠️ Client initialization failed:", e)
23
+ client = None
 
 
24
 
25
 
26
  @app.get("/", response_class=HTMLResponse)
27
  async def home():
28
+ return """
29
+ <html><body>
30
+ <h2>Meeting Summarizer API</h2>
31
+ <p>➡️ Call <a href='/summarize'>/summarize</a> to get meeting summary</p>
32
+ <p>➡️ Swagger docs: <a href='/docs'>/docs</a></p>
33
+ </body></html>
34
+ """
 
 
35
 
36
 
37
  @app.get("/summarize")
38
  async def summarize_meeting():
39
+ if not client:
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+ raise HTTPException(status_code=500, detail="❌ Hugging Face client not initialized")
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+
42
+ try:
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+ meeting_url = DEM0_AUDIO_URL
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+
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+ # Download audio
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+ response = requests.get(meeting_url, stream=True, timeout=30)
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+ if response.status_code != 200:
48
+ raise HTTPException(
49
+ status_code=400,
50
+ detail=f"Failed to fetch meeting audio (status {response.status_code})"
51
+ )
52
+
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+ suffix = ".flac" if meeting_url.endswith('.flac') else os.path.splitext(meeting_url)[1] or ".wav"
54
+
55
+ with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
56
+ for chunk in response.iter_content(chunk_size=8192):
57
+ if chunk:
58
+ tmp.write(chunk)
59
+ tmp_path = tmp.name
60
+
61
+ # Call your HF model. The predict input depends on how your space expects input.
62
+ # If your space expects a file, use handle_file(tmp_path) instead. Here we try both common ways.
63
+ try:
64
+ # First try: send file path (many gradio-based spaces accept this)
65
+ result = client.predict(tmp_path, api_name="/predict")
66
+ except Exception:
67
+ # Fallback: send the raw bytes
68
+ with open(tmp_path, "rb") as fd:
69
+ data = fd.read()
70
+ result = client.predict(data, api_name="/predict")
71
+
72
+ # Clean up
73
+ try:
74
+ os.remove(tmp_path)
75
+ except Exception:
76
+ pass
77
+
78
+ return result
79
+
80
+ except Exception as e:
81
+ raise HTTPException(status_code=500, detail=f"❌ Error summarizing meeting: {e}")
82
+
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+
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+ if __name__ == "__main__":
85
+ uvicorn.run("app:app", host="0.0.0.0", port=8000, reload=True)