69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
"""
|
|
Script generation module using Google Gemini Pro
|
|
|
|
This module generates natural Japanese narration scripts based on:
|
|
- Extracted PDF data
|
|
- Video transcription
|
|
- Template constraints
|
|
"""
|
|
|
|
import os
|
|
from typing import Dict, Any, List, Optional
|
|
|
|
|
|
class ScriptGenerator:
|
|
"""Generate narration scripts using Gemini Pro"""
|
|
|
|
def __init__(self, api_key: Optional[str] = None):
|
|
self.api_key = api_key or os.getenv("GEMINI_API_KEY")
|
|
if not self.api_key:
|
|
raise ValueError("GEMINI_API_KEY not found in environment")
|
|
|
|
def generate(
|
|
self,
|
|
pdf_data: Dict[str, Any],
|
|
video_data: Optional[Dict[str, Any]] = None,
|
|
style: str = "friendly"
|
|
) -> Dict[str, Any]:
|
|
"""
|
|
Generate narration script
|
|
|
|
Args:
|
|
pdf_data: Structured data from PDF extraction
|
|
video_data: Optional video transcription data
|
|
style: Narration style ('friendly', 'professional', 'casual')
|
|
|
|
Returns:
|
|
Dictionary containing:
|
|
- segments: List of narration segments
|
|
- total_duration: Estimated total duration in seconds
|
|
- sync_points: Recommended chart/video sync points
|
|
"""
|
|
# TODO: Implement script generation
|
|
# 1. Build prompt with PDF data and constraints
|
|
# 2. Call Gemini Pro API
|
|
# 3. Parse and structure the response
|
|
# 4. Estimate timing for each segment
|
|
|
|
raise NotImplementedError("Script generation not yet implemented")
|
|
|
|
def _build_prompt(self, pdf_data: Dict, style: str) -> str:
|
|
"""Build the prompt for Gemini Pro"""
|
|
# TODO: Implement prompt engineering
|
|
# Should include:
|
|
# - PDF data summary
|
|
# - Style guidelines (natural Japanese, friendly tone)
|
|
# - Output format requirements (JSON with segments)
|
|
# - Length constraints (target 3-5 minutes)
|
|
|
|
return ""
|
|
|
|
|
|
def generate_script(
|
|
pdf_data: Dict[str, Any],
|
|
video_data: Optional[Dict[str, Any]] = None
|
|
) -> Dict[str, Any]:
|
|
"""Convenience function for script generation"""
|
|
generator = ScriptGenerator()
|
|
return generator.generate(pdf_data, video_data)
|