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ed147e2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 | """
LLM-based note generation module.
Uses Google Gemini to generate structured study notes from transcripts.
"""
from typing import Dict, List, Optional
import google.generativeai as genai
from src.utils.logger import setup_logger
from src.utils.config import settings
logger = setup_logger(__name__)
class NoteGenerator:
"""Generates structured study notes using LLM."""
# System prompt for note generation
SYSTEM_PROMPT = """You are an expert educational note-taker. Your task is to convert video transcripts into clear, structured study notes.
Follow these guidelines:
1. Create a clear hierarchical structure with section titles
2. Use bullet points for key information
3. Highlight important concepts and definitions
4. Extract key terms and explain them
5. Be concise but comprehensive
6. Focus on educational content, skip irrelevant parts
7. Use proper Markdown formatting
Format the output as follows:
# [Main Topic/Title]
## [Section 1 Title]
- Key point 1
- Key point 2
- Sub-point if needed
- **Important term**: Definition or explanation
## [Section 2 Title]
...
## Key Concepts
- **Concept 1**: Explanation
- **Concept 2**: Explanation
"""
def __init__(self, api_key: Optional[str] = None, model_name: str = "gemini-2.5-flash"):
"""
Initialize the note generator.
Args:
api_key: Google Gemini API key (defaults to config)
model_name: Gemini model to use
"""
self.api_key = api_key or settings.google_api_key
self.model_name = model_name
# Configure Gemini
genai.configure(api_key=self.api_key)
self.model = genai.GenerativeModel(model_name)
logger.info(f"Initialized NoteGenerator with model: {model_name}")
def generate_notes_from_segment(self, segment_text: str) -> str:
"""
Generate notes from a single transcript segment.
Args:
segment_text: Text segment to process
Returns:
Generated notes in Markdown format
"""
try:
prompt = f"{self.SYSTEM_PROMPT}\n\nTranscript:\n{segment_text}\n\nGenerate structured study notes:"
logger.debug(f"Generating notes for segment ({len(segment_text)} chars)")
response = self.model.generate_content(prompt)
notes = response.text
logger.debug(f"Generated {len(notes)} characters of notes")
return notes.strip()
except Exception as e:
logger.error(f"Failed to generate notes: {e}")
return f"## Error\nFailed to generate notes for this segment: {str(e)}"
def generate_notes_from_segments(self, segments: List[Dict]) -> str:
"""
Generate notes from multiple transcript segments.
Args:
segments: List of transcript segments
Returns:
Combined notes in Markdown format
"""
all_notes = []
logger.info(f"Generating notes from {len(segments)} segments")
for i, segment in enumerate(segments, 1):
logger.info(f"Processing segment {i}/{len(segments)}")
segment_text = segment.get('text', '')
if not segment_text:
continue
# Add timestamp if available
if 'start' in segment:
timestamp = self._format_timestamp(segment['start'])
all_notes.append(f"\n---\n**Timestamp: {timestamp}**\n")
# Generate notes for this segment
notes = self.generate_notes_from_segment(segment_text)
all_notes.append(notes)
# Combine all notes
combined_notes = "\n\n".join(all_notes)
logger.info(f"Generated total of {len(combined_notes)} characters")
return combined_notes
def generate_notes_from_full_transcript(
self,
transcript_text: str,
video_title: str = "Educational Video"
) -> str:
"""
Generate notes from full transcript (for shorter videos).
Args:
transcript_text: Full transcript text
video_title: Title of the video
Returns:
Generated notes in Markdown format
"""
try:
prompt = f"""{self.SYSTEM_PROMPT}
Video Title: {video_title}
Transcript:
{transcript_text}
Generate comprehensive structured study notes:"""
logger.info(f"Generating notes from full transcript ({len(transcript_text)} chars)")
response = self.model.generate_content(prompt)
notes = response.text
# Add header with video title
final_notes = f"# {video_title}\n\n{notes.strip()}"
logger.info(f"Generated {len(final_notes)} characters of notes")
return final_notes
except Exception as e:
logger.error(f"Failed to generate notes from full transcript: {e}")
raise RuntimeError(f"Note generation failed: {str(e)}")
def generate_summary(self, notes: str) -> str:
"""
Generate a brief summary of the notes.
Args:
notes: Generated study notes
Returns:
Brief summary
"""
try:
prompt = f"""Provide a brief 2-3 sentence summary of these study notes:
{notes}
Summary:"""
response = self.model.generate_content(prompt)
summary = response.text.strip()
return summary
except Exception as e:
logger.error(f"Failed to generate summary: {e}")
return "Summary generation failed."
@staticmethod
def _format_timestamp(seconds: float) -> str:
"""Format seconds into MM:SS or HH:MM:SS."""
hours = int(seconds // 3600)
minutes = int((seconds % 3600) // 60)
secs = int(seconds % 60)
if hours > 0:
return f"{hours:02d}:{minutes:02d}:{secs:02d}"
else:
return f"{minutes:02d}:{secs:02d}"
def format_final_notes(
self,
notes: str,
video_title: str,
video_url: str,
duration: int
) -> str:
"""
Format final notes with metadata.
Args:
notes: Generated notes
video_title: Video title
video_url: Original YouTube URL
duration: Video duration in seconds
Returns:
Formatted notes with metadata header
"""
duration_str = self._format_timestamp(duration)
header = f"""# {video_title}
---
**Source:** [{video_url}]({video_url})
**Duration:** {duration_str}
**Generated:** AI Study Notes
---
"""
return header + notes
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