brad/LLM_Engineering_OLD
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Bootcamp Week 2: Add Meeting Minutes Creator with transcription and generation features

Browse Source
This commit is contained in:
Mohamed Salah
2025-10-27 12:55:06 +03:00
parent 8faff0283b
commit e8cfa78499
3 changed files with 346 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

301
week3/community-contributions/salah/meeting_minutes_v2.py Normal file
View File

@@ -0,0 +1,301 @@
#!/usr/bin/env python3
import os
import torch
import requests
import json
import librosa
import numpy as np
from pathlib import Path
from datetime import datetime
from transformers import pipeline
import gradio as gr
# Basic config
TRANSCRIPTION_MODEL = "openai/whisper-tiny.en"
OLLAMA_MODEL = "llama3.2:latest"
OLLAMA_URL = "http://localhost:11434"
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
OUTPUT_DIR = Path("./output")
# ============================
# MODEL LOADING
# ============================
def check_ollama():
try:
response = requests.get(f"{OLLAMA_URL}/api/tags", timeout=5)
if response.status_code == 200:
models = response.json().get('models', [])
model_names = [model['name'] for model in models]
return OLLAMA_MODEL in model_names
return False
except:
return False
def call_ollama(prompt):
payload = {
"model": OLLAMA_MODEL,
"prompt": prompt,
"stream": False,
"options": {
"temperature": 0.7,
"num_predict": 1000
}
}
try:
response = requests.post(f"{OLLAMA_URL}/api/generate", json=payload, timeout=120)
if response.status_code == 200:
return response.json().get('response', '').strip()
return "Error: Ollama request failed"
except:
return "Error: Could not connect to Ollama"
def load_models():
print("Loading models...")
if not check_ollama():
print("Ollama not available")
return None, False
try:
transcription_pipe = pipeline(
"automatic-speech-recognition",
model=TRANSCRIPTION_MODEL,
torch_dtype=torch.float16 if DEVICE == "cuda" else torch.float32,
device=0 if DEVICE == "cuda" else -1,
return_timestamps=True
)
print("Models loaded successfully")
return transcription_pipe, True
except Exception as e:
print(f"Failed to load models: {e}")
return None, False
# ============================
# PROCESSING FUNCTIONS
# ============================
def transcribe_audio(audio_file_path, transcription_pipe):
if not os.path.exists(audio_file_path):
return "Error: Audio file not found"
try:
# Load audio with librosa
audio, sr = librosa.load(audio_file_path, sr=16000)
if not isinstance(audio, np.ndarray):
audio = np.array(audio)
result = transcription_pipe(audio)
# Extract text from result
if isinstance(result, dict):
if "text" in result:
transcription = result["text"].strip()
elif "chunks" in result:
transcription = " ".join([chunk["text"] for chunk in result["chunks"]]).strip()
else:
transcription = str(result).strip()
else:
transcription = str(result).strip()
return transcription
except Exception as e:
return f"Error: {str(e)}"
def generate_minutes(transcription):
prompt = f"""Create meeting minutes from this transcript:
{transcription[:2000]}
Include:
- Summary with attendees and topics
- Key discussion points
- Important decisions
- Action items
Meeting Minutes:"""
result = call_ollama(prompt)
return result
def save_results(transcription, minutes, meeting_type="meeting"):
try:
OUTPUT_DIR.mkdir(exist_ok=True)
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
filename = f"{meeting_type}_minutes_{timestamp}.md"
filepath = OUTPUT_DIR / filename
content = f"""# Meeting Minutes
**Generated:** {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}
## Meeting Minutes
{minutes}
## Full Transcription
{transcription}
"""
with open(filepath, 'w', encoding='utf-8') as f:
f.write(content)
return str(filepath)
except Exception as e:
return f"Error saving: {str(e)}"
# ============================
# GRADIO INTERFACE
# ============================
def process_audio_file(audio_file, meeting_type, progress=gr.Progress()):
progress(0.0, desc="Starting...")
if not hasattr(process_audio_file, 'models') or not process_audio_file.models[0]:
return "", "", "Models not loaded"
transcription_pipe, ollama_ready = process_audio_file.models
if not ollama_ready:
return "", "", "Ollama not available"
try:
audio_path = audio_file.name if hasattr(audio_file, 'name') else str(audio_file)
if not audio_path:
return "", "", "No audio file provided"
progress(0.2, desc="Transcribing...")
transcription = transcribe_audio(audio_path, transcription_pipe)
if transcription.startswith("Error:"):
return transcription, "", "Transcription failed"
progress(0.6, desc="Generating minutes...")
minutes = generate_minutes(transcription)
if minutes.startswith("Error:"):
return transcription, minutes, "Minutes generation failed"
progress(0.9, desc="Saving...")
save_path = save_results(transcription, minutes, meeting_type)
progress(1.0, desc="Complete!")
status = f"""Processing completed!
Transcription: {len(transcription)} characters
Minutes: {len(minutes)} characters
Saved to: {save_path}
Models used:
- Transcription: {TRANSCRIPTION_MODEL}
- LLM: {OLLAMA_MODEL}
- Device: {DEVICE}
"""
return transcription, minutes, status
except Exception as e:
progress(1.0, desc="Failed")
return "", "", f"Processing failed: {str(e)}"
def create_interface():
with gr.Blocks(title="Meeting Minutes Creator") as interface:
gr.HTML("<h1>Meeting Minutes Creator</h1><p>HuggingFace Whisper + Ollama</p>")
with gr.Row():
with gr.Column():
gr.Markdown("### Audio Input")
audio_input = gr.Audio(
label="Upload or Record Audio",
type="filepath",
sources=["upload", "microphone"]
)
meeting_type = gr.Dropdown(
choices=["meeting", "standup", "interview", "call"],
value="meeting",
label="Meeting Type"
)
process_btn = gr.Button("Generate Minutes", variant="primary")
gr.HTML(f"""
<div>
<h4>Configuration</h4>
<ul>
<li>Transcription: {TRANSCRIPTION_MODEL}</li>
<li>LLM: {OLLAMA_MODEL}</li>
<li>Device: {DEVICE}</li>
</ul>
</div>
""")
with gr.Column():
gr.Markdown("### Results")
status_output = gr.Markdown("Ready to process audio")
with gr.Tabs():
with gr.Tab("Meeting Minutes"):
minutes_output = gr.Markdown("Minutes will appear here")
with gr.Tab("Transcription"):
transcription_output = gr.Textbox(
"Transcription will appear here",
lines=15,
show_copy_button=True
)
process_btn.click(
fn=process_audio_file,
inputs=[audio_input, meeting_type],
outputs=[transcription_output, minutes_output, status_output],
show_progress=True
)
return interface
# ============================
# MAIN APPLICATION
# ============================
def main():
print("Meeting Minutes Creator - HuggingFace + Ollama")
print("Loading models...")
transcription_pipe, ollama_ready = load_models()
if not transcription_pipe or not ollama_ready:
print("Failed to load models or connect to Ollama")
print("Make sure Ollama is running and has the model available")
return
process_audio_file.models = (transcription_pipe, ollama_ready)
print("Models loaded successfully!")
print("Starting web interface...")
print("Access at: http://localhost:7860")
interface = create_interface()
try:
interface.launch(
server_name="localhost",
server_port=7860,
debug=False
)
except KeyboardInterrupt:
print("Shutting down...")
except Exception as e:
print(f"Failed to launch: {e}")
if __name__ == "__main__":
main()

36
week3/community-contributions/salah/output/meeting_minutes_20251024_062609.md Normal file
View File

@@ -0,0 +1,36 @@
# Meeting Minutes
**Generated:** 2025-10-24 06:26:09
## Meeting Minutes
Here are the meeting minutes based on the transcript:
**Dilistanda Meeting Minutes - October 24**
**Attendees:**
* Jean (Project Manager)
* [Unknown speaker] ( attendee, name not provided)
**Summary:**
This meeting was held to discuss ongoing project updates and tasks for Dilistanda. The attendees reviewed the progress made by Jean on the user authentication module and discussed other ongoing work.
**Key Discussion Points:**
* Jean shared his update on completing the user authentication module and fixing three bugs on the login system.
* [Unknown speaker] mentioned they finished a database migration script and reviewed SORAP or request, but did not provide further details.
**Important Decisions:**
None
**Action Items:**
1. **Jean:** Continue working on the dashboard to components without any blockers.
2. [Unknown speaker]: Focus on API points for mobile app development.
Note: Unfortunately, some information was missing from the transcript (e.g., the identity of the second attendee), which made it challenging to create a comprehensive set of meeting minutes.
## Full Transcription
Good morning everyone, this is our Dilistanda meeting for October 24. I am sorrow as a project manager. Jean, can you give us your update? Yeah, Jean here yesterday I completed the user authentication module and I fixed three bugs on the login system. Today I will be working on the dashboard to components, no blocker. Okay, so I'm going to make your turn. How is this mic? I finished the database migration script and I reviewed SORAP or request. Today I will focus on the API points for mobile app.

9
week3/community-contributions/salah/requirements.txt Normal file
View File

@@ -0,0 +1,9 @@
# Meeting Minutes Creator V2 - HuggingFace + Ollama Implementation
# Requirements for Week 3 Day 5 Exercise
torch>=2.0.0
transformers>=4.35.0
gradio>=4.0.0
librosa>=0.10.0
soundfile>=0.12.0
requests>=2.31.0