refactor: Remove APIClients class and migrate to standalone GCS utils

- Deleted src/api_clients.py
- Moved download_from_gcs logic to src/google_src/gcs_utils.py as find_and_download_gcs_file
- Refactored all social media publishers to use gcs_utils instead of APIClients
- Removed APIClients usage from a2e_avatar.py, automation.py, and process_csv.py
- Removed cache usage from a2e_avatar.py

src/a2e_avatar.py

@@ -67,7 +67,6 @@ class TalkingVideoGenerator:
         timeout: int = 100,
         max_retries: int = 3,
         data_holder: DataHolder = None,
-        api_clients: APIClients = None
     ):
         """
         Initialize the A2E video generator
@@ -92,7 +91,6 @@ class TalkingVideoGenerator:
         self.tmp_dir = Path("/tmp")
         self.tmp_dir.mkdir(exist_ok=True)
         self.data_holder = data_holder or DataHolder()
-        self.api_clients = api_clients
         
         logger.info("TalkingVideoGenerator initialized")
     
@@ -439,22 +437,6 @@ Available Avatars with Usage Count: {available_avatar}
         os.remove(tmp_path)
         return duration
 
-    async def get_from_cache(self, method_type):
-        try:
-            with open(await self.api_clients.get_cache_url(method_type, ".txt"), 'r', encoding="utf-8") as file:
-                logger.info("Using cache a2e_tts.")
-                return file.read()
-        except: return None
-
-    async def store_in_cache(self, method_type, content):
-        try:
-            unique_id = uuid.uuid4().hex[:8]
-            file_path = f"/tmp/a2e_tts_{unique_id}.txt"
-            with open(file_path, "w", encoding="utf-8") as file:
-                file.write(content)
-            await self.api_clients.store_in_cache(file_path, method_type, ".txt")
-        except: pass
-
     def _get_voice_language_info(self, voice_id: str, voices: List[VoiceInfo]) -> Tuple[str, str]:
         """
         Get country and region from voice_id by looking up in voices list.
@@ -489,9 +471,6 @@ Available Avatars with Usage Count: {available_avatar}
             if os.getenv("TEST_AUTOMATION", "").lower() == "true":
                 return "testData/Green Screen Avatar Video3.mp3"
 
-            audio_url = await self.get_from_cache("a2e_tts")
-            if audio_url:
-                return audio_url
 
             # --- First attempt ---
             logger.info(f"Generating TTS audio (speed: {speed_rate}x)...")
@@ -540,7 +519,6 @@ Available Avatars with Usage Count: {available_avatar}
             if duration > 15 or duration < 10:
                 raise A2EAPIError(f"Audio is longer:({duration}) for the voice: {voice_id}")
 
-            await self.store_in_cache("a2e_tts", audio_url)
             logger.info(f"✓ Final TTS audio generated ({duration:.2f}s): {audio_url}")
             return audio_url
 
@@ -582,86 +560,77 @@ Available Avatars with Usage Count: {available_avatar}
                     "video_url": "testData/Green Screen Avatar Video3.mp4"
                 }
 
-            content = await self.get_from_cache("a2e_video")
-            if content:
-                return json.loads(content)
-
-            task_id = await self.get_from_cache("a2e_video_task_id")
-            if not task_id:
-                logger.info(f"Generating talking video with green screen background...")
-
-                # Calculate dimensions based on aspect ratio
-                if aspect_ratio == "9:16":
-                    if resolution == 1080:
-                        width, height = 1080, 1920
-                    else:  # 720
-                        width, height = 405, 720
-                elif aspect_ratio == "16:9":
-                    if resolution == 1080:
-                        width, height = 1920, 1080
-                    else:  # 720
-                        width, height = 1280, 720
-                else:
-                    # Default to square
-                    width = height = resolution
+            logger.info(f"Generating talking video with green screen background...")
 
-                # Convert RGB tuple to rgba() format string (alpha = 1 for fully opaque)
-                bg_color_str = f"rgba({background_color[0]},{background_color[1]},{background_color[2]},1)"
-                # {
-                #     "title": "11-09-2025 16:53:47",
-                #     "isSkipRs": true,
-                #     "isAllowReverse": true,
-                #     "resolution": 1080,
-                #     "isSubtitleEnabled": false,
-                #     "anchor_id": "67209ea6a9050edd960698c0",
-                #     "anchor_type": 0,
-                #     "msg": "Hello Ther.",
-                #     "tts_id": "66ca504f2732c24634224075",
-                #     "speech_rate": 1.2,
-                #     "audioSrc": "https://1day-tos.a2e.com.cn/tts3party_cache/stable/el/Aria/speed/a15fe669931864094b03fe17b7b2067d.wav",
-                #     "color": "rgba(0,255,0,1)",
-                #     "web_bg_width": 202.5,
-                #     "web_bg_height": 360,
-                #     "web_people_max_width": 202.5,
-                #     "web_people_max_height": 360,
-                #     "web_people_width": 600,
-                #     "web_people_height": 360,
-                #     "web_people_x": -198.75,
-                #     "web_people_y": 0
-                # }
-                payload = {
-                    "title": title,
-                    "anchor_id": avatar_id,
-                    "anchor_type": anchor_type,
-                    "audioSrc": audio_url,
-                    # "resolution": resolution,
-                    "color": bg_color_str,  # e.g. "rgba(0,255,0,1)" for green screen
-                    # "anchor_background_color": bg_color_str,  # e.g. "rgba(0,255,0,1)" for green screen
-                    # "web_bg_width": width,
-                    # "web_bg_height": height,
-                    # "web_people_width": width,
-                    # "web_people_height": height,
-                    # "web_people_x": 0,
-                    # "web_people_y": 0,
-                    "isSkipRs": True  # Fast mode
-                }
-                data = await self._make_request(
-                    "POST",
-                    "/api/v1/video/generate",
-                    json=payload
-                )
+            # Calculate dimensions based on aspect ratio
+            if aspect_ratio == "9:16":
+                if resolution == 1080:
+                    width, height = 1080, 1920
+                else:  # 720
+                    width, height = 405, 720
+            elif aspect_ratio == "16:9":
+                if resolution == 1080:
+                    width, height = 1920, 1080
+                else:  # 720
+                    width, height = 1280, 720
+            else:
+                # Default to square
+                width = height = resolution
 
-                task_id = data.get("data", {}).get("_id")
-                if not task_id:
-                    raise A2EAPIError("No task ID in response")
+            # Convert RGB tuple to rgba() format string (alpha = 1 for fully opaque)
+            bg_color_str = f"rgba({background_color[0]},{background_color[1]},{background_color[2]},1)"
+            # {
+            #     "title": "11-09-2025 16:53:47",
+            #     "isSkipRs": true,
+            #     "isAllowReverse": true,
+            #     "resolution": 1080,
+            #     "isSubtitleEnabled": false,
+            #     "anchor_id": "67209ea6a9050edd960698c0",
+            #     "anchor_type": 0,
+            #     "msg": "Hello Ther.",
+            #     "tts_id": "66ca504f2732c24634224075",
+            #     "speech_rate": 1.2,
+            #     "audioSrc": "https://1day-tos.a2e.com.cn/tts3party_cache/stable/el/Aria/speed/a15fe669931864094b03fe17b7b2067d.wav",
+            #     "color": "rgba(0,255,0,1)",
+            #     "web_bg_width": 202.5,
+            #     "web_bg_height": 360,
+            #     "web_people_max_width": 202.5,
+            #     "web_people_max_height": 360,
+            #     "web_people_width": 600,
+            #     "web_people_height": 360,
+            #     "web_people_x": -198.75,
+            #     "web_people_y": 0
+            # }
+            payload = {
+                "title": title,
+                "anchor_id": avatar_id,
+                "anchor_type": anchor_type,
+                "audioSrc": audio_url,
+                # "resolution": resolution,
+                "color": bg_color_str,  # e.g. "rgba(0,255,0,1)" for green screen
+                # "anchor_background_color": bg_color_str,  # e.g. "rgba(0,255,0,1)" for green screen
+                # "web_bg_width": width,
+                # "web_bg_height": height,
+                # "web_people_width": width,
+                # "web_people_height": height,
+                # "web_people_x": 0,
+                # "web_people_y": 0,
+                "isSkipRs": True  # Fast mode
+            }
+            data = await self._make_request(
+                "POST",
+                "/api/v1/video/generate",
+                json=payload
+            )
 
-                await self.store_in_cache("a2e_video_task_id", task_id)
+            task_id = data.get("data", {}).get("_id")
+            if not task_id:
+                raise A2EAPIError("No task ID in response")
 
             logger.info(f"✓ Video generation started. Task ID: {task_id}")
             
             # Poll for completion
             video_result = await self._poll_video_status(task_id)
-            await self.store_in_cache("a2e_video", json.dumps(video_result))
             return video_result
             
         except Exception as e:
@@ -946,7 +915,6 @@ async def create_greenscreen_video_workflow(
     preferred_language: str = "en-US",
     speed_rate: float = 1.2,
     data_holder=None,
-    api_clients=None,
     title="Green Screen Avatar Video"
 ) -> Path:
     """
@@ -967,7 +935,7 @@ async def create_greenscreen_video_workflow(
     logger.info("GREEN SCREEN TALKING VIDEO WORKFLOW")
     logger.info("=" * 60)
     
-    generator = TalkingVideoGenerator(a2e_api_key=api_key, data_holder=data_holder, api_clients=api_clients)
+    generator = TalkingVideoGenerator(a2e_api_key=api_key, data_holder=data_holder)
     
     try:
         # Step 1: Get avatars with background support

src/api_clients.py

@@ -1,195 +0,0 @@
-"""
-API clients for external services with full implementations
-"""
-
-import aiohttp
-import json
-import os
-from typing import Dict, List, Optional
-from google.cloud import storage, texttospeech
-import asyncio
-from utils import logger
-from moviepy.editor import AudioFileClip
-
-"""
-API clients for external services with full implementations
-"""
-
-import aiohttp
-import json
-import os
-from typing import Dict, List, Optional
-from google.cloud import storage, texttospeech
-import asyncio
-from utils import logger
-from data_holder import DataHolder
-from file_downloader import FileDownloader
-
-
-# --- NEW IMPORTS ---
-from google_src.gcs_utils import get_gcs_client, get_gcs_credentials, upload_file_to_gcs, list_gcs_files
-
-# --------------------
-
-import base64
-from pathlib import Path
-
-from google_src import ai_studio_sdk
-import uuid
-
-class APIClients:
-    def __init__(self, config, data_holder: DataHolder = None):
-        self.config = config
-        self.data_holder = data_holder
-
-        logger.info("Initializing GCS and TTS clients using google_src.gcs_utils...")
-
-        self.gcs_client = get_gcs_client("final_data")
-        
-        gcs_bucket_name = config.get("gcs_bucket_name")
-        print(gcs_bucket_name)
-        self.gcs_bucket = self.gcs_client.bucket(gcs_bucket_name)
-
-    async def get_from_cache(self, method_type, duration=0):
-        try:
-            with open(await self.get_cache_url(f"{method_type}_{duration}", ".txt"), 'r', encoding="utf-8") as file:
-                logger.info("Using cache aoi_client.")
-                return file.read()
-        except: return None
-
-    async def store_in_cache_file(self, method_type, content, duration=0):
-        try:
-            unique_id = uuid.uuid4().hex[:8]
-            file_path = f"/tmp/google_tts_{unique_id}.txt"
-            with open(file_path, "w", encoding="utf-8") as file:
-                file.write(content)
-            await self.store_in_cache(file_path, f"{method_type}_{duration}", ".txt")
-        except: pass
-
-
-
-
-
-
-    async def store_in_cache(self, file_path: str, method_type: str, file_ext: str = ".mp4") -> str:
-        """Store file in Google Cloud Storage and return its public URL."""
-        try:
-            if os.getenv("TEST_AUTOMATION", "").lower() == "true":
-                return None
-
-            # ✅ Ensure you're using the right attribute name ("has_tts_script" or "hash_tts_script")
-            filename = f"{self.data_holder.hash_tts_script}_{method_type}{file_ext}"
-            blob_name = f"cache_reuse/{filename}"
-            blob = self.my_temp_gcs_bucket.blob(blob_name)
-
-            # ✅ File extension to MIME mapping
-            content_types = {
-                ".mp4": "video/mp4",
-                ".mp3": "audio/mpeg",
-                ".wav": "audio/wav",
-                ".png": "image/png",
-                ".jpg": "image/jpeg",
-                ".jpeg": "image/jpeg",
-                ".json": "application/json",
-                ".txt": "text/plain",
-            }
-
-            blob.content_type = content_types.get(file_ext, "application/octet-stream")
-
-            logger.info(f"☁️ Uploading {file_path} to gs://{self.my_temp_gcs_bucket.name}/{blob_name}")
-            blob.upload_from_filename(file_path)
-
-            public_url = f"https://storage.googleapis.com/{self.my_temp_gcs_bucket.name}/{blob_name}"
-            logger.info(f"✅ File uploaded successfully: {public_url}")
-
-            return public_url
-
-        except Exception as e:
-            logger.error(f"❌ Error storing file in cache: {e}")
-            return None
-
-    async def get_cache_url(self, method_type: str, file_ext: str = ".mp4") -> str:
-        """Return public URL if cached file exists in GCS, else None."""
-        try:
-            filename = f"{self.data_holder.hash_tts_script}_{method_type}{file_ext}"
-            blob_name = f"cache_reuse/{filename}"
-            logger.info(f"Cahce file name: {blob_name}")
-            blob = self.my_temp_gcs_bucket.blob(blob_name)
-
-            if blob.exists():  # ✅ Check before returning
-                local_path = f'/tmp/{filename}'
-                blob.download_to_filename(local_path)
-                return local_path
-            else:
-                logger.warning(f"⚠️ Cache miss: {blob_name} not found in bucket.")
-                return None
-
-        except Exception as e:
-            logger.error(f"❌ Error fetching cache URL: {e}")
-            return None
-
-
-
-    async def download_from_gcs(self, tts_script: str, local_dir: str = "/tmp") -> Optional[str]:
-        """
-        Find and download a file from GCS whose name contains part of the TTS script.
-        Useful when filenames are generated dynamically based on the script text.
-
-        Args:
-            tts_script: Text content used to search for the file name in GCS
-            local_dir: Local directory to save the downloaded file
-
-        Returns:
-            Local path to downloaded file, or None on failure.
-        """
-        try:
-            if os.getenv("TEST_AUTOMATION", "").lower() == "true":
-                return f"{os.getenv('TEST_DATA_DIRECTORY')}/{uuid.uuid4().hex}.mp4"
-
-            # Prepare a safe pattern to search by
-            safe_name_10 = "".join(c for c in tts_script[:10] if c.isalnum())
-            safe_name_50 = "".join(c for c in tts_script[:50] if c.isalnum())
-
-            # Await the async list function
-            all_files = list_gcs_files()
-
-            # Try to find a matching file name
-            blob_name = next((f for f in all_files if self.data_holder.tts_script in f), None)
-            if not blob_name:
-                blob_name = next((f for f in all_files if safe_name_50 in f), None)
-            if not blob_name:
-                blob_name = next((f for f in all_files if safe_name_10 in f), None)
-
-            if not blob_name:
-                logger.error(f"❌ No matching file found in GCS for script: {tts_script[:50]}...")
-                return None
-
-            logger.info(f"☁️ Found matching file: gs://{self.gcs_bucket.name}/{blob_name}")
-
-            # Construct GCS URL
-            gs_url = f"gs://{self.gcs_bucket.name}/{blob_name}"
-            
-            # Use FileDownloader
-            downloader = FileDownloader()
-            # We can download mostly anywhere, but let's stick to the default behavior or local_dir if needed.
-            # safe_download uses temp dir by default. The original code used local_dir="/tmp/tts_downloads".
-            # FileDownloader uses its own temp dir logic.
-            # Let's see if we can pass output path. safe_download takes output_path.
-            
-            local_path = os.path.join(local_dir, os.path.basename(blob_name))
-            
-            downloaded = downloader.safe_download(gs_url, output_path=local_path)
-            
-            if downloaded:
-                file_size = os.path.getsize(downloaded)
-                logger.info(f"✅ Downloaded {blob_name} → {downloaded} ({file_size/1024:.1f} KB)")
-                return str(downloaded)
-            else:
-                 logger.error(f"❌ FileDownloader failed for {gs_url}")
-                 return None
-
-        except Exception as e:
-            logger.error(f"❌ GCS download failed: {e}")
-            return None
-
-

src/automation.py

@@ -10,7 +10,6 @@ from google_src import ai_studio_sdk
 from video_generation_process import generate_video_process
 from typing import Dict, List, Optional, Any
 from pathlib import Path
-from api_clients import APIClients
 from video_renderer import VideoRenderer
 from utils import logger
 import utils
@@ -36,11 +35,9 @@ from asset_manager import get_asset_downloader, get_audio_lib, AssetProcessor
 from file_downloader import FileDownloader
 
 class ContentAutomation:
-    def __init__(self, config: Dict[str, Any], data_holder: DataHolder = None, api_clients: 'APIClients' = None):
+    def __init__(self, config: Dict[str, Any], data_holder: DataHolder = None):
         self.config = config
         self.data_holder = data_holder or DataHolder()
-        # Reuse provided api_clients or create new one
-        self.api_clients = api_clients or APIClients(config, self.data_holder)
         
         # Initialize Google Services directly
         self.tts = GoogleTTS()
@@ -84,7 +81,6 @@ class ContentAutomation:
                     preferred_language="en-US",
                     speed_rate=1.2,
                     data_holder=self.data_holder,
-                    api_clients=self.api_clients,
                     title=self.data_holder.hash_tts_script[:30]
                 )
                 self.data_holder.visual_assets["tts_audio"] = {

src/google_src/gcs_utils.py

@@ -228,3 +228,65 @@ def create_bucket_if_not_exists(client, bucket_name: str, location: str = "us-ce
     except Exception as e:
         logger.error(f"❌ Failed to create bucket {bucket_name}: {e}")
         return False
+
+def find_and_download_gcs_file(tts_script: str, local_dir: str = "/tmp", account_name: str = "final_data") -> Optional[str]:
+    """
+    Find and download a file from GCS whose name contains part of the TTS script.
+    Useful when filenames are generated dynamically based on the script text.
+    Replaces APIClients.download_from_gcs.
+
+    Args:
+        tts_script: Text content used to search for the file name in GCS
+        local_dir: Local directory to save the downloaded file
+        account_name: GCS account to use
+
+    Returns:
+        Local path to downloaded file, or None on failure.
+    """
+    try:
+        if os.getenv("TEST_AUTOMATION", "").lower() == "true":
+            return f"{os.getenv('TEST_DATA_DIRECTORY')}/{uuid.uuid4().hex}.mp4"
+
+        # Prepare a safe pattern to search by
+        safe_name_50 = "".join(c for c in tts_script[:50] if c.isalnum())
+        safe_name_10 = "".join(c for c in tts_script[:10] if c.isalnum())
+        
+        all_files = list_gcs_files(prefix="", account_name=account_name)
+
+        # Try to find a matching file name
+        blob_name = next((f for f in all_files if tts_script in f), None)
+        if not blob_name:
+            blob_name = next((f for f in all_files if safe_name_50 in f), None)
+        if not blob_name:
+            blob_name = next((f for f in all_files if safe_name_10 in f), None)
+
+        if not blob_name:
+            logger.error(f"❌ No matching file found in GCS for script: {tts_script[:50]}...")
+            return None
+
+        client = get_gcs_client(account_name)
+        bucket_name = os.getenv("GCS_BUCKET_NAME")
+        
+        logger.info(f"☁️ Found matching file: gs://{bucket_name}/{blob_name}")
+
+        # Construct GCS URL
+        gs_url = f"gs://{bucket_name}/{blob_name}"
+        
+        from file_downloader import FileDownloader
+        downloader = FileDownloader()
+        
+        local_path = os.path.join(local_dir, os.path.basename(blob_name))
+        
+        downloaded = downloader.safe_download(gs_url, output_path=local_path, account_id=account_name)
+        
+        if downloaded:
+            file_size = os.path.getsize(downloaded)
+            logger.info(f"✅ Downloaded {blob_name} → {downloaded} ({file_size/1024:.1f} KB)")
+            return str(downloaded)
+        else:
+             logger.error(f"❌ FileDownloader failed for {gs_url}")
+             return None
+
+    except Exception as e:
+        logger.error(f"❌ GCS download failed: {e}")
+        return None

src/process_csv.py

@@ -8,7 +8,6 @@ from main import (
     run_pipeline,
 )
 from automation import ContentAutomation
-from api_clients import APIClients
 from utils import logger
 from data_holder import DataHolder
 from google_src.google_sheet import GoogleSheetReader
@@ -20,7 +19,6 @@ import setup_config
 from asset_manager import get_video_lib, get_audio_lib, get_asset_downloader, get_content_strategy_lib
 
 DATA_DIR = Path("data")
-SHARED_API_CLIENTS = None  # Shared instance to avoid redundant GCS/TTS client initialization
 
 
 def load_executed_from_gsheet(setup_type=None, job_index=None):
@@ -96,7 +94,6 @@ def log_progress_to_gsheet(tts_script: str, result: dict, job_index: int, commit
 
 async def process_row(row, config: dict):
     """Process one CSV row using the main pipeline."""
-    global SHARED_API_CLIENTS
     tts_script = row.get("TTS Script (AI Avatar)", "")
     if os.getenv("ON_SCREEN_TEXT", "false").lower() == "true":
         tts_script = row.get("On-Screen Text", "").strip()
@@ -108,14 +105,9 @@ async def process_row(row, config: dict):
     asset_downloader = get_asset_downloader()
     dataHolder.visual_assets["all_videos"] = asset_downloader.downloaded_videos
 
-    # Update shared APIClients with current dataHolder
-    if SHARED_API_CLIENTS:
-        SHARED_API_CLIENTS.data_holder = dataHolder
-
     # ContentAutomation uses asset_manager singletons directly
     automation = ContentAutomation(
-        config, dataHolder,
-        api_clients=SHARED_API_CLIENTS
+        config, dataHolder
     )
 
     content_strategy = {
@@ -138,7 +130,6 @@ async def process_row(row, config: dict):
 
 async def download_all_video(config: dict):
     """Download all library videos once using singletons."""
-    global SHARED_API_CLIENTS
 
     # Get the asset downloader singleton
     asset_downloader = get_asset_downloader()
@@ -147,12 +138,6 @@ async def download_all_video(config: dict):
     logger.info("📥 Pre-downloading all library videos...")
     videos = await asset_downloader.download_all_videos()
     
-    # Create the shared APIClients once
-    if SHARED_API_CLIENTS is None:
-        dataHolder = DataHolder()
-        dataHolder.visual_assets["all_videos"] = videos
-        SHARED_API_CLIENTS = APIClients(config, dataHolder)
-    
     logger.info(f"✓ Downloaded {len(videos)} library videos")
     return videos
 

src/social_media_publishers/instagram_publisher.py

@@ -21,8 +21,8 @@ from load_config import load_configuration
 from main import (
     load_content_strategies
 )
-from api_clients import APIClients
 import hashlib
+from google_src.gcs_utils import find_and_download_gcs_file, upload_file_to_gcs
 
 DATA_DIR = Path("data")
 
@@ -151,7 +151,6 @@ async def main():
     try:
         # Load config and initialize API client
         config = load_configuration()
-        api_client = APIClients(config)
         scheduler = InstagramPublisher()
         
         csv_files = sorted(DATA_DIR.glob("content_strategies*.csv"))
@@ -175,17 +174,21 @@ async def main():
             print("="*50)
 
             # Download from GCS via API client
-            api_client.data_holder.hash_tts_script = hashlib.sha256(tts_script.encode('utf-8')).hexdigest()
-            local_path = await api_client.download_from_gcs(tts_script)
+            # Download from GCS via GCS Utils
+            local_path = find_and_download_gcs_file(tts_script)
             
             if not local_path or not os.path.exists(local_path):
                 print(f"❌ Skipping — file not found: {tts_script}")
                 continue
             
-            # Upload to Instagram
-            # NOTE: Requires the file to be accessible by Instagram (public URL or CDN link)
-            # You can upload your video file to a temporary public bucket or use a CDN-backed URL
-            public_url = api_client.get_public_url(local_path)  # <-- implement this in APIClients
+            # Upload to temporary GCS for public URL
+            uploaded_file = upload_file_to_gcs(local_path, account_name="final_data", generate_signed_url=False, fallback_to_drive=False)
+            public_url = uploaded_file.get("public_url")
+            if not public_url:
+                print(f"❌ Failed to generate public URL for: {local_path}")
+                continue
+
+            print(f"🔗 Public URL for Instagram: {public_url}")
             result = scheduler.upload_reel(public_url, caption)
 
             # Print result

src/social_media_publishers/publisher.py

@@ -18,7 +18,7 @@ import hashlib
 
 from load_config import load_configuration
 from main import load_content_strategies
-from api_clients import APIClients
+from google_src.gcs_utils import find_and_download_gcs_file, upload_file_to_gcs
 
 # Import individual platform publishers
 from social_media_publishers.youtube_publisher import YouTubePublisher
@@ -111,7 +111,6 @@ async def run_publisher(media: str, commit=False):
     """Unified publishing pipeline with CSV read + commit tracking."""
     print(f"🚀 Starting {media.capitalize()} publishing pipeline...")
     config = load_configuration()
-    api_client = APIClients(config)
 
     # Pick platform publisher
     if media == "youtube":
@@ -155,8 +154,7 @@ async def run_publisher(media: str, commit=False):
         print("=" * 50)
 
         try:
-            api_client.data_holder.hash_tts_script = hashlib.sha256(tts_script.encode('utf-8')).hexdigest()
-            local_path = await api_client.download_from_gcs(tts_script)
+            local_path = find_and_download_gcs_file(tts_script)
             if not local_path or not os.path.exists(local_path):
                 print(f"❌ Skipping: File not found for {tts_script}")
                 continue
@@ -173,7 +171,13 @@ async def run_publisher(media: str, commit=False):
                 )
             elif media == "instagram":
                 # Instagram needs a public URL, not a local file path
-                public_url = api_client.get_public_url(local_path)
+                uploaded_file = upload_file_to_gcs(local_path, account_name="final_data", generate_signed_url=False, fallback_to_drive=False)
+                public_url = uploaded_file.get("public_url")
+                
+                if not public_url:
+                    print("❌ Failed to generate public URL for Instagram")
+                    continue
+                    
                 result = scheduler.upload_reel(public_url, caption=description)
             elif media == "tiktok":
                 result = scheduler.upload_video(

src/social_media_publishers/tiktok_publisher.py

@@ -22,8 +22,8 @@ from load_config import load_configuration
 from main import (
     load_content_strategies
 )
-from api_clients import APIClients
 import hashlib
+from google_src.gcs_utils import find_and_download_gcs_file
 
 DATA_DIR = Path("data")
 
@@ -183,7 +183,7 @@ class TikTokPublisher:
 async def main():
     try:
         config = load_configuration()
-        api_client = APIClients(config)
+        config = load_configuration()
         scheduler = TikTokPublisher()
         
         csv_files = sorted(DATA_DIR.glob("content_strategies*.csv"))
@@ -206,8 +206,7 @@ async def main():
             print("="*50)
             
             # Download from GCS
-            api_client.data_holder.hash_tts_script = hashlib.sha256(tts_script.encode('utf-8')).hexdigest()
-            local_path = await api_client.download_from_gcs(tts_script)
+            local_path = find_and_download_gcs_file(tts_script)
             if not local_path or not os.path.exists(local_path):
                 print(f"❌ File not found, skipping: {tts_script}")
                 continue

src/social_media_publishers/youtube_publisher.py

@@ -25,9 +25,9 @@ from main import (
     load_content_strategies
 )
 from pathlib import Path
-from api_clients import APIClients
 from dotenv import load_dotenv
 import hashlib
+from google_src.gcs_utils import find_and_download_gcs_file
 
 DATA_DIR = Path("data")
 
@@ -53,8 +53,8 @@ class YouTubePublisher:
         else:
             self.youtube = self._authenticate()
 
+
         config = load_configuration()
-        self.api_client = APIClients(config)
     
     def _authenticate(self):
         """Authenticate with YouTube API using environment variable (JSON string, base64, or path)."""
@@ -316,9 +316,8 @@ async def main():
 
         for idx, (csv_name, row) in enumerate(all_rows):
             tts_script = row.get("TTS Script (AI Avatar)", "").strip()
-            scheduler.api_client.data_holder.hash_tts_script = hashlib.sha256(tts_script.encode('utf-8')).hexdigest()
             description = row.get("Captions", "").strip()
-            local_path = await scheduler.api_client.download_from_gcs(tts_script)
+            local_path = find_and_download_gcs_file(tts_script)
             if local_path:
                 # Parse scheduled time if provided
                 scheduled_dt = None