# from flask import Flask, request, jsonify
# from flask_cors import CORS
# import requests
# import json
# from datetime import datetime
# from google.oauth2 import service_account
# from googleapiclient.discovery import build

# app = Flask(__name__)
# CORS(app)

# # ========================
# # CONFIGURATION
# # ========================

# import os
# from dotenv import load_dotenv

# load_dotenv()

# GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
# GOOGLE_CREDENTIALS_FILE = os.getenv("GOOGLE_CREDENTIALS_FILE")
# SPREADSHEET_ID = os.getenv("SPREADSHEET_ID")

# # ========================
# # GOOGLE SHEETS
# # ========================

# def get_sheets_service():
#     SCOPES = ['https://www.googleapis.com/auth/spreadsheets']
#     creds = service_account.Credentials.from_service_account_file(
#         GOOGLE_CREDENTIALS_FILE, scopes=SCOPES)
#     service = build('sheets', 'v4', credentials=creds)
#     return service

# def save_to_sheet(topic, caption, hashtags, reel_script, metadata):
#     try:
#         service = get_sheets_service()
#         sheet = service.spreadsheets()
        
#         timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
        
#         values = [[
#             timestamp, 
#             topic, 
#             metadata.get('duration', 'N/A'),
#             metadata.get('level', 'N/A'),
#             metadata.get('tone', 'N/A'),
#             metadata.get('language', 'N/A'),
#             metadata.get('series_info', 'Single'),
#             caption, 
#             hashtags, 
#             reel_script
#         ]]
        
#         body = {'values': values}
        
#         sheet.values().append(
#             spreadsheetId=SPREADSHEET_ID,
#             range='Sheet1!A:J',
#             valueInputOption='RAW',
#             body=body
#         ).execute()
        
#         return True
#     except Exception as e:
#         print(f"Sheet Error: {e}")
#         return False

# # ========================
# # GEMINI AI
# # ========================

# def call_gemini_api(prompt, retry_count=0, max_retries=3):
#     import time
    
#     url = f"https://generativelanguage.googleapis.com/v1/models/gemini-2.5-flash:generateContent?key={GEMINI_API_KEY}"
    
#     headers = {"Content-Type": "application/json"}
#     data = {
#         "contents": [{
#             "parts": [{"text": prompt}]
#         }]
#     }
    
#     # Progressive delay: 3s, 10s, 30s
#     delays = [3, 10, 30]
#     if retry_count > 0:
#         wait_time = delays[min(retry_count - 1, 2)]
#         print(f"⏳ Rate limit hit. Waiting {wait_time}s before retry {retry_count}/{max_retries}...")
#         time.sleep(wait_time)
#     else:
#         time.sleep(3)  # Base delay between requests
    
#     response = requests.post(url, headers=headers, json=data)
    
#     if response.status_code == 200:
#         result = response.json()
#         return result['candidates'][0]['content']['parts'][0]['text'].strip()
#     elif response.status_code == 429:
#         if retry_count < max_retries:
#             return call_gemini_api(prompt, retry_count + 1, max_retries)
#         else:
#             raise Exception("Rate limit exceeded after retries. Please wait 1-2 minutes and try again!")
#     else:
#         raise Exception(f"API Error: {response.status_code}")

# def generate_instagram_content(topic, duration, level, tone, language, series_config):
#     import time
    
#     # Tone descriptions
#     tone_styles = {
#         'professional': 'professional and corporate tone',
#         'funny': 'humorous, witty, and entertaining tone with jokes',
#         'inspiring': 'motivational, uplifting, and inspiring tone',
#         'serious': 'serious, educational, and informative tone',
#         'casual': 'casual, friendly, and conversational tone',
#         'storytelling': 'narrative storytelling style with engaging flow'
#     }
    
#     # Language instructions
#     language_styles = {
#         'hinglish': 'Mix of Hindi and English (Hinglish). Use both languages naturally',
#         'hindi': 'Pure Hindi language only. No English words',
#         'english': 'Pure English language only. No Hindi words'
#     }
    
#     # Content level descriptions
#     level_descriptions = {
#         'basic': 'simple, easy-to-understand for beginners',
#         'intermediate': 'moderate depth with some technical terms',
#         'advanced': 'in-depth, expert-level with advanced concepts'
#     }
    
#     tone_desc = tone_styles.get(tone, 'inspiring tone')
#     lang_desc = language_styles.get(language, 'Hinglish')
#     level_desc = level_descriptions.get(level, 'intermediate')
    
#     # Calculate scenes
#     scenes = calculate_scenes(duration)
    
#     # Series context
#     series_context = ""
#     if series_config['enabled']:
#         current = series_config['currentPart']
#         total = series_config['totalParts']
#         previous = series_config.get('previousContent', '')
        
#         if current == 1:
#             series_context = f"\n\nSERIES INFO: This is PART 1/{total} of a series. End with a hook/cliffhanger for next part!"
#         elif current == total:
#             series_context = f"\n\nSERIES INFO: FINAL PART {current}/{total}. Provide conclusion referencing previous parts.\nPrevious: {previous[:400]}"
#         else:
#             series_context = f"\n\nSERIES INFO: PART {current}/{total}. Continue from previous part.\nPrevious: {previous[:400]}"
    
#     # CAPTION
#     caption_prompt = f"""Create Instagram caption for: {topic}

# REQUIREMENTS:
# - Tone: {tone_desc}
# - Language: {lang_desc}
# - Level: {level_desc}
# - 2-3 lines, engaging
# - Use emojis
# - Call-to-action
# {f'- Mention Part {series_config["currentPart"]}/{series_config["totalParts"]}' if series_config['enabled'] else ''}

# ONLY return caption, nothing else."""
    
#     print(f"Generating caption: {topic}")
#     caption = call_gemini_api(caption_prompt)
    
#     # HASHTAGS
#     hashtags_prompt = f"""Generate 12-15 Instagram hashtags for: {topic}

# Style: {tone}
# Language: {language}
# Level: {level}

# Return ONLY hashtags with # in one line."""
    
#     print("Generating hashtags...")
#     hashtags = call_gemini_api(hashtags_prompt)
    
#     # REEL SCRIPT
#     reel_prompt = f"""Create {duration}-second Instagram Reel script for: {topic}

# STYLE:
# - Tone: {tone_desc}
# - Language: {lang_desc}
# - Level: {level_desc}

# STRUCTURE ({scenes['total_duration']} seconds total):
# [Hook] - Opening (2-3s)
# {chr(10).join([f'[Scene {i+1}] - Description ({scenes["scene_duration"]}s)' for i in range(scenes["num_scenes"])])}
# [CTA] - Call to action (3-5s)

# {series_context}

# FORMAT EXACTLY as shown above. Make it viral!"""
    
#     print("Generating reel script...")
#     reel_script = call_gemini_api(reel_prompt)
    
#     return caption, hashtags, reel_script

# def calculate_scenes(duration):
#     available_time = duration - 8
    
#     if duration <= 20:
#         num_scenes = 2
#     elif duration <= 45:
#         num_scenes = 3
#     elif duration <= 75:
#         num_scenes = 4
#     elif duration <= 120:
#         num_scenes = 5
#     else:
#         num_scenes = 6
    
#     scene_duration = available_time // num_scenes
    
#     return {
#         'num_scenes': num_scenes,
#         'scene_duration': scene_duration,
#         'total_duration': duration
#     }

# # ========================
# # API ROUTES
# # ========================

# @app.route('/')
# def home():
#     return """
#     🎨 Instagram AI Content Generator ULTIMATE
    
#     ⚡ Powered by Sai Tech
    
#     Features:
#     - Bulk content generation
#     - Custom tone, language, level
#     - Multi-part series
#     - PDF/ZIP export
    
#     Status: Running ✅
#     """

# @app.route('/generate', methods=['POST'])
# def generate():
#     try:
#         data = request.json
#         topic = data.get('topic', '').strip()
#         duration = data.get('duration', 30)
#         level = data.get('level', 'intermediate')
#         tone = data.get('tone', 'inspiring')
#         language = data.get('language', 'hinglish')
#         series_config = data.get('series', {'enabled': False})
        
#         if not topic:
#             return jsonify({
#                 'success': False,
#                 'error': 'Topic required!'
#             }), 400
        
#         print(f"\n{'='*60}")
#         print(f"⚡ SAI TECH - Processing Request")
#         print(f"{'='*60}")
#         print(f"  Topic: {topic}")
#         print(f"  Duration: {duration}s")
#         print(f"  Level: {level}")
#         print(f"  Tone: {tone}")
#         print(f"  Language: {language}")
#         if series_config['enabled']:
#             print(f"  Series: Part {series_config['currentPart']}/{series_config['totalParts']}")
#         print(f"{'='*60}\n")
        
#         # Generate content
#         caption, hashtags, reel_script = generate_instagram_content(
#             topic, duration, level, tone, language, series_config
#         )
        
#         # Metadata
#         metadata = {
#             'duration': f"{duration}s",
#             'level': level,
#             'tone': tone,
#             'language': language,
#             'series_info': f"Part {series_config['currentPart']}/{series_config['totalParts']}" if series_config['enabled'] else "Single"
#         }
        
#         # Save to sheets
#         save_to_sheet(topic, caption, hashtags, reel_script, metadata)
        
#         print("✅ Content generated successfully!\n")
        
#         return jsonify({
#             'success': True,
#             'topic': topic,
#             'caption': caption,
#             'hashtags': hashtags,
#             'reel_script': reel_script,
#             'metadata': metadata
#         })
        
#     except Exception as e:
#         print(f"\n❌ Error: {str(e)}\n")
#         return jsonify({
#             'success': False,
#             'error': str(e)
#         }), 500

# if __name__ == '__main__':
#     print("=" * 70)
#     print("⚡ SAI TECH - Instagram AI Content Generator ULTIMATE")
#     print("=" * 70)
#     print("📍 Server: http://localhost:5000")
#     print("🌐 Open index.html in browser")
#     print("=" * 70)
#     print("\n🔥 ULTIMATE Features:")
#     print("  ✅ Bulk topic generation")
#     print("  ✅ Custom tone (Professional/Funny/Inspiring/etc)")
#     print("  ✅ Language selection (Hindi/English/Hinglish)")
#     print("  ✅ Content levels (Basic/Intermediate/Advanced)")
#     print("  ✅ Multi-part series with auto-continuation")
#     print("  ✅ PDF/ZIP download with Sai Tech watermark")
#     print("  ✅ Auto Google Sheets backup")
#     print("=" * 70)
#     print("\n💡 Example Bulk Topics:")
#     print("  motivation, fitness, cooking, travel, photography")
#     print("=" * 70)
#     app.run(debug=True, port=5000)

# from flask import Flask, request, jsonify
# from flask_cors import CORS
# import requests
# import json
# import time
# import os
# from datetime import datetime
# from dotenv import load_dotenv
# from google.oauth2 import service_account
# from googleapiclient.discovery import build

# app = Flask(__name__)
# CORS(app)

# load_dotenv()

# GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
# GOOGLE_CREDENTIALS_FILE = os.getenv("GOOGLE_CREDENTIALS_FILE")
# SPREADSHEET_ID = os.getenv("SPREADSHEET_ID")

# CACHE = {}
# LAST_CALL_TIME = 0
# MIN_INTERVAL = 2


# def get_sheets_service():
#     SCOPES = ['https://www.googleapis.com/auth/spreadsheets']
#     creds = service_account.Credentials.from_service_account_file(
#         GOOGLE_CREDENTIALS_FILE, scopes=SCOPES
#     )
#     return build('sheets', 'v4', credentials=creds)


# def save_to_sheet(topic, caption, hashtags, reel_script, metadata):
#     try:
#         service = get_sheets_service()
#         sheet = service.spreadsheets()

#         timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")

#         values = [[
#             timestamp, topic,
#             metadata.get("duration"),
#             metadata.get("level"),
#             metadata.get("tone"),
#             metadata.get("language"),
#             metadata.get("series_info"),
#             caption, hashtags, reel_script
#         ]]

#         sheet.values().append(
#             spreadsheetId=SPREADSHEET_ID,
#             range="Sheet1!A:J",
#             valueInputOption="RAW",
#             body={"values": values}
#         ).execute()

#         return True
#     except Exception as e:
#         print("Sheet Error:", e)
#         return False


# def call_gemini_api(prompt, retry=0):
#     global LAST_CALL_TIME

#     if prompt in CACHE:
#         return CACHE[prompt]

#     now = time.time()
#     wait = MIN_INTERVAL - (now - LAST_CALL_TIME)
#     if wait > 0:
#         time.sleep(wait)

#     url = f"https://generativelanguage.googleapis.com/v1/models/gemini-2.5-flash:generateContent?key={GEMINI_API_KEY}"

#     headers = {"Content-Type": "application/json"}
#     data = {"contents": [{"parts": [{"text": prompt}]}]}

#     response = requests.post(url, headers=headers, json=data)
#     LAST_CALL_TIME = time.time()

#     if response.status_code == 200:
#         text = response.json()["candidates"][0]["content"]["parts"][0]["text"].strip()
#         CACHE[prompt] = text
#         return text

#     if response.status_code == 429 and retry < 3:
#         time.sleep(5 * (retry + 1))
#         return call_gemini_api(prompt, retry + 1)

#     raise Exception(f"Gemini API Error: {response.status_code}")


# def generate_instagram_content(topic, duration, level, tone, language, series):

#     series_context = ""
#     if series.get("enabled"):
#         current = series.get("currentPart", 1)
#         total = series.get("totalParts", 1)
#         prev = series.get("previousContent", "")[:300]

#         if current == 1:
#             series_context = f"PART 1/{total}. End with hook."
#         elif current == total:
#             series_context = f"FINAL PART {current}/{total}. Previous: {prev}"
#         else:
#             series_context = f"PART {current}/{total}. Continue. Previous: {prev}"

#     prompt = f'''
# Create Instagram content for topic: {topic}

# Return ONLY valid JSON:
# {{
#  "caption": "...",
#  "hashtags": "...",
#  "reel_script": "..."
# }}

# Tone: {tone}
# Language: {language}
# Level: {level}
# Duration: {duration}s
# {series_context}
# '''

#     response = call_gemini_api(prompt)

#     try:
#         data = json.loads(response)
#         return data["caption"], data["hashtags"], data["reel_script"]
#     except Exception:
#         raise Exception("Invalid JSON from AI")


# @app.route("/")
# def home():
#     return "Sai Tech AI Generator Running 🚀"


# @app.route("/generate", methods=["POST"])
# def generate():
#     try:
#         data = request.json

#         topic = data.get("topic", "").strip()
#         duration = data.get("duration", 30)
#         level = data.get("level", "intermediate")
#         tone = data.get("tone", "inspiring")
#         language = data.get("language", "hinglish")
#         series = data.get("series", {"enabled": False})

#         if not topic:
#             return jsonify({"success": False, "error": "Topic required"}), 400

#         caption, hashtags, reel_script = generate_instagram_content(
#             topic, duration, level, tone, language, series
#         )

#         metadata = {
#             "duration": f"{duration}s",
#             "level": level,
#             "tone": tone,
#             "language": language,
#             "series_info": f"Part {series.get('currentPart',1)}/{series.get('totalParts',1)}"
#         }

#         save_to_sheet(topic, caption, hashtags, reel_script, metadata)

#         return jsonify({
#             "success": True,
#             "caption": caption,
#             "hashtags": hashtags,
#             "reel_script": reel_script
#         })

#     except Exception as e:
#         return jsonify({"success": False, "error": str(e)}), 500


# if __name__ == "__main__":
#     app.run(debug=True, port=5000)
import os
import time
import requests
import gradio as gr
from datetime import datetime
from google.oauth2 import service_account
from googleapiclient.discovery import build

# ========================
# ENV VARIABLES
# ========================

GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
GOOGLE_CREDENTIALS_FILE = os.getenv("GOOGLE_CREDENTIALS_FILE")
SPREADSHEET_ID = os.getenv("SPREADSHEET_ID")

# ========================
# GOOGLE SHEETS
# ========================

def get_sheets_service():
    SCOPES = ['https://www.googleapis.com/auth/spreadsheets']
    creds = service_account.Credentials.from_service_account_file(
        GOOGLE_CREDENTIALS_FILE, scopes=SCOPES)
    return build('sheets', 'v4', credentials=creds)


def save_to_sheet(topic, caption, hashtags, reel_script, metadata):
    try:
        service = get_sheets_service()
        sheet = service.spreadsheets()

        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")

        values = [[
            timestamp,
            topic,
            metadata.get('duration'),
            metadata.get('level'),
            metadata.get('tone'),
            metadata.get('language'),
            metadata.get('series_info'),
            caption,
            hashtags,
            reel_script
        ]]

        sheet.values().append(
            spreadsheetId=SPREADSHEET_ID,
            range='Sheet1!A:J',
            valueInputOption='RAW',
            body={'values': values}
        ).execute()

    except Exception as e:
        print("Sheet Error:", e)


# ========================
# GEMINI CALL
# ========================

def call_gemini(prompt):
    url = f"https://generativelanguage.googleapis.com/v1/models/gemini-2.5-flash:generateContent?key={GEMINI_API_KEY}"

    data = {
        "contents": [{"parts": [{"text": prompt}]}]
    }

    time.sleep(2)
    res = requests.post(url, json=data)

    if res.status_code != 200:
        raise Exception(f"Gemini Error: {res.status_code}")

    return res.json()['candidates'][0]['content']['parts'][0]['text'].strip()


# ========================
# MAIN GENERATOR
# ========================

def generate_content(topic, duration, level, tone, language):

    caption = call_gemini(f"Write short Instagram caption about {topic} in {language} with {tone} tone.")
    hashtags = call_gemini(f"Give 15 hashtags for {topic}.")
    reel = call_gemini(f"Write {duration} sec Instagram reel script about {topic}.")

    metadata = {
        "duration": f"{duration}s",
        "level": level,
        "tone": tone,
        "language": language,
        "series_info": "Single"
    }

    save_to_sheet(topic, caption, hashtags, reel, metadata)

    return caption, hashtags, reel


# ========================
# GRADIO UI
# ========================

with gr.Blocks(title="Instagram AI Generator") as app:

    gr.Markdown("# 🚀 Instagram AI Content Generator")
    gr.Markdown("Generate captions, hashtags & reel scripts using AI")

    topic = gr.Textbox(label="Topic")
    duration = gr.Slider(10, 120, value=30, step=5, label="Reel Duration (sec)")
    level = gr.Dropdown(["basic", "intermediate", "advanced"], value="intermediate", label="Level")
    tone = gr.Dropdown(["professional", "funny", "inspiring", "casual"], value="inspiring", label="Tone")
    language = gr.Dropdown(["english", "hindi", "hinglish"], value="hinglish", label="Language")

    btn = gr.Button("Generate")

    caption_out = gr.Textbox(label="Caption")
    hashtag_out = gr.Textbox(label="Hashtags")
    reel_out = gr.Textbox(label="Reel Script", lines=8)

    btn.click(
        generate_content,
        inputs=[topic, duration, level, tone, language],
        outputs=[caption_out, hashtag_out, reel_out]
    )

app.launch()