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import json
import os
import time
import logging
from typing import Dict, Any
from prompt.system_prompt import SYSTEM_PROMPT
from schema_script import ScriptResponse
from google import genai
from dotenv import load_dotenv
load_dotenv()
GEMINI_API_KEY = os.getenv("GEMINI_KEY")
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(message)s",
handlers=[logging.StreamHandler()]
)
logger = logging.getLogger(__name__)
def configure_gemini():
return genai.Client(api_key=GEMINI_API_KEY)
def generate_scripts(
video_path: str,
offer_details: str,
target_audience: str,
specific_hooks: str,
additional_context: str,
num_scripts: int = 3,
duration: int = 60
) -> Dict[str, Any]:
client = configure_gemini()
try:
user_prompt = f"""
Generate {num_scripts} high-converting direct response script variations,
each about {duration} seconds long.
Each variation MUST be designed for a total runtime ≤ {duration} seconds.
- Do NOT include any timestamp beyond {duration}s.
- Keep all beats within 0–{duration}s.
- Use timestamps as "M:SS" (e.g., "0:03", "0:12").
CONTEXT TO FOLLOW:
- Offer Details: {offer_details}
- Target Audience: {target_audience}
- Specific Hooks: {specific_hooks}
ADDITIONAL CONTEXT:
{additional_context}
You must reflect this additional context in:
- The script tone, CTA, visuals
- Compliance or branding constraints
- Any assumptions about audience or product
Failure to include this will be considered incomplete.
Please provide a comprehensive analysis including:
1. DETAILED VIDEO ANALYSIS with timestamp-based metrics:
- Break down the video into 5-10 second segments
- Rate each segment's effectiveness (1-10 scale)
- Identify specific elements (hook, transition, proof, CTA, etc.)
2. TIMESTAMP-BASED IMPROVEMENTS:
- Specific recommendations for each time segment
- Priority level for each improvement
- Expected impact of implementing changes
3. SCRIPT VARIATIONS:
- Create complete script variations
- Each with timestamp-by-timestamp breakdown
- Different psychological triggers and approaches
IMPORTANT: Return only valid JSON in the exact format specified in the system prompt. Analyze the video second-by-second for maximum detail."""
video_file = client.files.upload(file=video_path)
while getattr(video_file.state, "name", "") == "PROCESSING":
time.sleep(1.0)
video_file = client.files.get(name=video_file.name)
if getattr(video_file.state, "name", "") == "FAILED":
logger.error("Video processing FAILED.")
return {}
resp = client.models.generate_content(
model="gemini-2.0-flash",
contents=[SYSTEM_PROMPT, user_prompt, video_file],
config={
"response_mime_type": "application/json",
"response_schema": ScriptResponse,
},
)
parsed = getattr(resp, "parsed", None)
if parsed is None:
raw_text = getattr(resp, "text", "") or ""
if not raw_text:
parts = None
if getattr(resp, "candidates", None):
parts = getattr(resp.candidates[0].content, "parts", None)
raise RuntimeError(f"Model returned no JSON text. parts={parts}")
data = json.loads(raw_text)
return data
out = parsed.model_dump()
logger.info("Generated %d variations.", len(out.get("script_variations", [])))
return out
except Exception as e:
logger.exception("generate_scripts failed: %s", e)
return {} |