putting it all togeather

build_videos.py

@@ -33,7 +33,7 @@ def build_chat_video():
         print(f"🚀 Transcribe: {title}")
         print("====================================================")
 
-        twitch_chat_vod.combine_twitch_vod_and_chat(f"download/videos/{id}/{id}.mp4")
+        twitch_chat_vod.combine_twitch_vod_and_chat(f"download/videos/{id}/{id}.mp4", "side-by-side", True)
 
 
 def build_transcribe():
@@ -68,7 +68,7 @@ def build_transcribe():
         print(f"🚀 Transcribe: {title}")
         print("====================================================")
         
-        transcribe_video.transcribe_to_srt(f"{target_dir}/{id}/{id}.mp4")
+        transcribe_video.transcribe_to_srt(f"{target_dir}/{id}/{id}.mp4", True)
 
 
 def build_shorts():
@@ -104,8 +104,12 @@ def build_shorts():
 
         youtube_short.fit_to_9_16_letterbox(target_dir, top_txt, f"Clipped By: {creator_name}.", True)
 
-if __name__ =="__main__":
+def main():
+    global DB
     DB = database.Database()
-    #build_shorts()
+    build_shorts()
     build_transcribe()
     build_chat_video()
+
+if __name__ == "__main__":
+    main()

database.py

@@ -91,7 +91,7 @@ class Database:
 
     def get_unuploaded_chats(self) -> list[Any]:
         """Retrieve all rows that were download but not uploaded_yt_chats"""
-        return self.__get_unuploaded("uploaded_yt_chats", "AND clips_is = 0")
+        return self.__get_unuploaded("uploaded_yt_chats", "AND clip_is = 0")
                 
     def get_unuploaded(self) -> list[Any]:
         """Retrieve all rows that were download but not uploaded_yt"""

main.py

@@ -0,0 +1,17 @@
+#!/usr/bin/env python3
+import asyncio
+
+import twitch_video_info
+import twitch_download_videos
+
+import build_videos
+
+if __name__ == "__main__":
+    # Get Twitch Video Info
+    asyncio.run(twitch_video_info.main())
+
+    # Download Twitch Videos
+    twitch_download_videos.main()
+
+    #Build
+    build_videos.main()

transcribe_video.py

@@ -1,62 +1,119 @@
 #!/usr/bin/env python3
 import os
+import sys
+import shutil
 import subprocess
-import whisper
-import linux
-from moviepy import VideoFileClip
-from whisper.utils import get_writer
 from pathlib import Path
+from faster_whisper import WhisperModel
+from faster_whisper.utils import format_timestamp
 
-model = whisper.load_model("base")
+# Prevent OpenMP thread conflicts from crashing the script
+os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
 
-def extract_audio(video_path: str):
+# 5 minutes per chunk (300 seconds) keeps RAM usage low and stable
-    # Create a temporary path for a sanitized copy of the video
+CHUNK_DURATION_SEC = 300 
-    sanitized_video_path = video_path.replace(".mp4", "_clean.mp4")
-    audio_temp_path = video_path.replace(".mp4", ".wav")
 
-    print("Sanitizing video metadata for MoviePy parser...")
+print("🔧 Initializing C++ Engine...")
-    # -map_chapters -1 removes chapter layouts that break the parser.
+model = WhisperModel(
-    # -sn strips text/subtitle streams that crash MoviePy.
+    "base", 
-    # -c copy copies video and audio instantly without quality loss.
+    device="cpu", 
-    linux.run_command(f"ffmpeg -y -i {video_path} -map_chapters -1 -sn -c copy {sanitized_video_path}")
+    compute_type="int8", 
+    cpu_threads=0, # Let CTranslate2 auto-detect safe core counts
+    num_workers=1         
+)
+print("✅ C++ Model loaded successfully.")
+
+
+def extract_audio_and_chunk(video_path: str, output_dir: Path) -> list:
+    """Extracts and splits audio into 5-minute chunks using a single FFmpeg pass."""
+    print("🚀 Extracting and chunking audio with FFmpeg...")
+    output_dir.mkdir(parents=True, exist_ok=True)
+    
+    # Segment format output: chunk_000.wav, chunk_001.wav, etc.
+    chunk_pattern = str(output_dir / "chunk_%03d.wav")
+    
+    command = [
+        "ffmpeg", "-y", "-i", video_path,
+        "-vn", "-ac", "1", "-ar", "16000",
+        "-acodec", "pcm_s16le", "-sn", "-map_chapters", "-1",
+        "-f", "segment", "-segment_time", str(CHUNK_DURATION_SEC),
+        chunk_pattern
+    ]
+    
+    result = subprocess.run(command, stdout=subprocess.DEVNULL, stderr=subprocess.PIPE, text=True)
+    if result.returncode != 0:
+        print(f"❌ FFmpeg Error Output:\n{result.stderr}")
+        raise RuntimeError("FFmpeg extraction and chunking failed.")
+        
+    # Return sorted list of generated chunk files
+    return sorted(list(output_dir.glob("chunk_*.wav")))
+
+
+def transcribe_to_srt(video_path: str, force: bool = False):
+    video_path_obj = Path(video_path)
+    srt_path = video_path_obj.with_suffix(".srt")
+    temp_dir = video_path_obj.parent / f"temp_chunks_{video_path_obj.stem}"
+
+    if srt_path.exists():
+        if not force:
+            print(f"❌ Error: Transcription file already exists: {srt_path}")
+            return
+        else:
+            srt_path.unlink()
 
-    print("Extracting uncompressed WAV audio...")
     try:
-        # Load the sanitized file instead of the raw Twitch clip
+        # Step 1: Split audio into bite-sized pieces
-        with VideoFileClip(sanitized_video_path) as video:
+        audio_chunks = extract_audio_and_chunk(str(video_path_obj), temp_dir)
-            video.audio.write_audiofile(
+        if not audio_chunks:
-                audio_temp_path, 
+            print("❌ Error: No audio chunks were generated.")
-                fps=16000,
+            return
-                codec="pcm_s16le", 
+
-                ffmpeg_params=["-ac", "1"]
+        print(f"📦 Successfully split audio into {len(audio_chunks)} chunks.")
-            )
+        print("🎙️ Starting safe chunk-by-chunk transcription...")
+
+        global_segment_index = 1
+        
+        with open(srt_path, "w", encoding="utf-8") as srt_file:
+            for chunk_idx, chunk_path in enumerate(audio_chunks):
+                # Calculate the time offset for the current chunk
+                time_offset = chunk_idx * CHUNK_DURATION_SEC
+                print(f"\n⏳ Processing chunk {chunk_idx + 1}/{len(audio_chunks)} ({chunk_path.name})...")
+                
+                segments_generator, info = model.transcribe(
+                    str(chunk_path), 
+                    beam_size=1,
+                    vad_filter=True,
+                    temperature=0.0
+                )
+                
+                # Consume chunk generator and shift timestamps instantly
+                for segment in segments_generator:
+                    # Shift timestamps relative to the original video timeline
+                    actual_start = segment.start + time_offset
+                    actual_end = segment.end + time_offset
+                    
+                    start_str = format_timestamp(actual_start, always_include_hours=True)
+                    end_str = format_timestamp(actual_end, always_include_hours=True)
+                    
+                    srt_file.write(f"{global_segment_index}\n{start_str} --> {end_str}\n{segment.text.strip()}\n\n")
+                    global_segment_index += 1
+                    
+                # Free up space as we go by deleting the processed chunk
+                chunk_path.unlink()
+
+        print(f"\n✅ All chunks combined! SRT subtitle file saved in: {srt_path}")
+
     except Exception as e:
-        print(f"❌ Error: {e}")
+        print(f"\n❌ Execution Error: {e}")
-        if os.path.exists(audio_temp_path):
-            os.remove(audio_temp_path)
     finally:
-        # Always clean up the temporary sanitized video on Windows 11
+        # Clean up the temporary folder entirely
-        if os.path.exists(sanitized_video_path):
+        if temp_dir.exists():
-            os.remove(sanitized_video_path)
+            shutil.rmtree(temp_dir)
-
-
-def transcribe_to_srt(video_path: str):
-
-    extract_audio(video_path)
-
-    transcribe_path = video_path.replace(".mp4", ".str")
-    audio_path = video_path.replace(".mp4", ".wav")
-    print("Transcribing audio...")
-    result = model.transcribe(audio_path)
-    
-    print("Creating SRT file...")
-    srt_writer = get_writer("srt", Path(transcribe_path).parent)
-    srt_writer(result, transcribe_path, {})
-    
-    print(f"SRT subtitle file saved in: {transcribe_path}")
-    if os.path.exists(audio_path):
-        os.remove(audio_path)
 
 
 if __name__ == "__main__":
-    transcribe_to_srt("download/videos/2813112936/2813112936.mp4")
+    target_video = "download/videos/2813112936/2813112936.mp4"
+    if not os.path.exists(target_video):
+        print(f"❌ System Error: Target video file does not exist at path: {target_video}")
+    else:
+        transcribe_to_srt(target_video, force=True)

twitch_chat_vod.py

@@ -7,6 +7,8 @@ def combine_twitch_vod_and_chat(vod_path: str, layout: str = "side-by-side", for
     Renders Twitch chat JSON to video and combines it with the source VOD.
     Provides real-time terminal feedback for all processing steps.
     """
+    threads = "8"
+
     video_path = vod_path
     chat_path = video_path.replace(".mp4", "_chat.json")
     temp_chat = video_path.replace(".mp4", "_temp_chat.mp4")
@@ -14,10 +16,6 @@ def combine_twitch_vod_and_chat(vod_path: str, layout: str = "side-by-side", for
     mask_path = video_path.replace(".mp4", "_temp_chat_mask.mp4")
 
     # Step 1: Pre-flight checks
-    if os.path.exists(video_chat) and force is False:
-        print(f"❌ Error: Chat video allready exists: {video_chat}")
-        return False
-    
     if not os.path.exists(video_path):
         print(f"❌ Error: Source video not found: {video_path}")
         return False
@@ -26,6 +24,17 @@ def combine_twitch_vod_and_chat(vod_path: str, layout: str = "side-by-side", for
         print(f"❌ Error: Chat file not found: {chat_path}")
         return False
     
+    if os.path.exists(video_chat):
+        if not force:
+            print(f"❌ Error: Chat video already exists: {video_chat}")
+            return False
+        else:
+            os.remove(video_chat)
+
+    if os.path.exists(temp_chat):
+        os.remove(temp_chat)
+        os.remove(mask_path)
+    
     # Step 2: Render Chat to Video
     print("====================================================")
     print("🚀 STEP 1: Rendering Chat JSON to Video Layer")
@@ -38,17 +47,19 @@ def combine_twitch_vod_and_chat(vod_path: str, layout: str = "side-by-side", for
         f"--collision Overwrite "
         f"--temp-path download/temp "
         f"--font-size 20 "           
-        f"--generate-mask "
         f"--background-color #00000000 "
-        f"-o {temp_chat} "
+        f"-o {temp_chat}"
     )
 
+    if layout == "overlay":
+        chat_cmd = (f"{chat_cmd} --generate-mask ")
+
     if not os.path.exists(temp_chat):
         chat_success = linux.run_command(chat_cmd, look_for=["[STATUS]"])
         if chat_success:
             print("✅ Success: TwitchDownloaderCLI render chat video.")
         else:
-            print(f"❌ Error: TwitchDownloaderCLI failed to render chat video. {chat_success['error']} : {chat_success['stderr']}")
+            print("❌ Error: TwitchDownloaderCLI failed to render chat video.")
             os.remove(temp_chat)
             os.remove(mask_path)
             return False
@@ -63,15 +74,16 @@ def combine_twitch_vod_and_chat(vod_path: str, layout: str = "side-by-side", for
     if layout == "side-by-side":
         ffmpeg_cmd = (
             f"ffmpeg -y -i {video_path} -i {temp_chat} "
-            f"-filter_complex '[0:v][1:v]hstack=inputs=2[v]' "
+            f"-filter_complex '[1:v]scale=-1:H[scaled_chat];[0:v][scaled_chat]hstack=inputs=2[v]' "
-            f"-map '[v]' -map 0:a? -c:a copy -preset superfast {video_chat}"
+            f"-map '[v]' -map 0:a? -c:v libx264 -crf 18 -preset slow -c:a copy "
+            f"-threads {threads} {video_chat}"
         )
     elif layout == "overlay":
         ffmpeg_cmd = (
             f"ffmpeg -y -i {video_path} -i {temp_chat} -i {mask_path} "
-            f"-filter_complex '[1:v][2:v]alphamerge[masked_chat];"
+            f"-filter_complex '[1:v][2:v]alphamerge[masked_chat];[0:v][masked_chat]overlay=x=0:y=10[v]' "
-            f"[0:v][masked_chat]overlay=x=10:y=10[v]' "
+            f"-map '[v]' -map 0:a? -c:v libx264 -crf 18 -preset slow -c:a copy "
-            f"-map '[v]' -map 0:a? -c:a copy -preset superfast {video_chat}"
+            f"-threads {threads} {video_chat}"
         )
     else:
         raise ValueError("Invalid layout choice. Choose 'side-by-side' or 'overlay'.")
@@ -97,4 +109,4 @@ def combine_twitch_vod_and_chat(vod_path: str, layout: str = "side-by-side", for
         return False
 
 if __name__ == "__main__":
-    combine_twitch_vod_and_chat("download/videos/2813112936/2813112936.mp4", "overlay")
+    combine_twitch_vod_and_chat("download/videos/2813112936/2813112936.mp4", "overlay", True)

twitch_download_videos.py

@@ -80,6 +80,10 @@ def download():
 
     print("Finished Downloading Pipeline.")
 
-if __name__ == "__main__":
+def main():
+    global DB
     DB = Database()
     download()
+
+if __name__ == "__main__":
+    main()

youtube_short.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 import os
+import json
 import linux
 import tempfile
 from pathlib import Path
@@ -10,125 +11,133 @@ from pathlib import Path
 import numpy as np
 from PIL import Image, ImageFilter
 
-def apply_gaussian_blur(frame, radius: int = 30):
+def get_video_info(input_path: Path) -> tuple:
-    """
+    """Uses ffprobe to instantly read input video dimensions and frame rate."""
-    Transforms a single NumPy array frame using PIL's true GaussianBlur filter.
+    cmd = f"ffprobe -v error -select_streams v:0 -show_entries stream=width,height,r_frame_rate -of json {input_path}"
-    """
+    # Run command and capture output (assumes linux.run_command prints or you use subprocess)
-    # Convert numpy array to PIL Image
+    import subprocess
-    image = Image.fromarray(frame)
+    result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
-    # Apply high-quality true Gaussian Blur
+    #linux.run_command(cmd)
-    blurred_image = image.filter(ImageFilter.GaussianBlur(radius=radius))
+    try:
-    # Return back as a numpy array for MoviePy
+        data = json.loads(result.stdout)
-    return np.array(blurred_image)
+        stream = data['streams'][0]
+        w = int(stream['width'])
+        h = int(stream['height'])
+        # Convert fractional FPS string (e.g. "60/1" or "30000/1001") to float
+        fps_parts = stream['r_frame_rate'].split('/')
+        fps = float(fps_parts[0]) / float(fps_parts[1]) if len(fps_parts) > 1 else float(fps_parts[0])
+        return w, h, fps
+    except Exception:
+        return 1920, 1080, 60.0  # Safe defaults if probe fails
 
 def fit_to_9_16_letterbox(input_path: str, top_text: str = "TOP TEXT", bottom_text: str = "BOTTOM TEXT", use_blur: bool = True, force: bool = False):
+    threads = "8"
     input_file = Path(input_path)
     output_suffix = "gaussian_9_16" if use_blur else "black_9_16"
     output_path = input_file.parent / f"{input_file.stem}_{output_suffix}{input_file.suffix}"
 
-    if os.path.exists(output_path) and force is False:
+    if os.path.exists(output_path):
-        print(f"❌ Error: Short video allready exists: {output_path}")
+        if not force:
-        return
+            print(f"❌ Error: Short video already exists: {output_path}")
+            return
+        else:
+            os.remove(output_path)
 
+    # 1. Probe input metadata instantly
+    orig_w, orig_h, fps = get_video_info(input_file)
+    canvas_w = 1080
+    canvas_h = 1920
 
-    print("🧼 Sanitizing video metadata streams inside an automated safe context...")
+    print("✍️ Generating text overlay graphics via MoviePy...")
-    with tempfile.NamedTemporaryFile(suffix=input_file.suffix, delete=False) as temp_file:
+    # Render static images for text instead of running a video context
-        temp_path = temp_file.name
+    title_clip = TextClip(
+        text=top_text, font_size=55, color="white", font="DejaVuSans-Bold",
+        text_align="center", size=(canvas_w - 100, 300), method="caption"
+    )
+    bottom_clip = TextClip(
+        text=bottom_text, font_size=55, color="white", font="DejaVuSans-Bold",
+        text_align="center", size=(canvas_w - 100, 300), method="caption"
+    )
 
-    bg_scaled = None
+    # Save text layers to temporary PNGs
-    bg_cropped = None
+    top_png = tempfile.NamedTemporaryFile(suffix=".png", delete=False).name
-    background_layer = None
+    bottom_png = tempfile.NamedTemporaryFile(suffix=".png", delete=False).name
+    title_clip.save_frame(top_png)
+    bottom_clip.save_frame(bottom_png)
+    
+    title_clip.close()
+    bottom_clip.close()
+
+    print("🎬 Dispatching compilation workload to FFmpeg filtergraph...")
+    
+    # 2. Build the complex FFmpeg filtergraph
+    # [0:v] is the raw input video stream
+    filter_complex = []
+
+    if use_blur:
+        # Scale height to 1920, crop center 1080x1920, apply fast boxblur (power of 3 approximates Gaussian)
+        filter_complex.append(
+            f"[0:v]scale=-1:{canvas_h},crop={canvas_w}:{canvas_h}:(iw-{canvas_w})/2:0,boxblur=luma_radius=35:luma_power=3[bg];"
+        )
+    else:
+        # Generate a pure black background canvas matching video frame specs
+        filter_complex.append(
+            f"color=c=black:s={canvas_w}x{canvas_h}:r={fps}[bg];"
+        )
+
+    # Scale the foreground video to a clean 1080 width, keeping aspect ratio
+    filter_complex.append(
+        f"[0:v]scale={canvas_w}:-1[fg];"
+    )
+
+    # Layer composition chain:
+    # Overlay 1: Put scaled foreground onto background (centered vertically)
+    filter_complex.append(
+        f"[bg][fg]overlay=0:(H-h)/2[tmp1];"
+    )
+    # Overlay 2: Drop top text asset onto position Y=180
+    filter_complex.append(
+        f"[tmp1][1:v]overlay=(W-w)/2:180[tmp2];"
+    )
+    # Overlay 3: Drop bottom text asset onto position Y=1430
+    filter_complex.append(
+        f"[tmp2][2:v]overlay=(W-w)/2:1430[finalv]"
+    )
+
+    filter_graph = "".join(filter_complex)
+
+    # 3. Execute the native assembly command
+    # -map_chapters -1 -sn: Strips unnecessary metadata chunks instantly
+    # -c:a copy: Safely pulls original digital audio directly without decompression cycles
+    # -threads 0: Forces FFmpeg to auto-consume all available processing cores
+    ffmpeg_cmd = (
+        f'ffmpeg -y -v error -i "{input_file}" -i "{top_png}" -i "{bottom_png}" '
+        f'-filter_complex "{filter_graph}" '
+        f'-map "[finalv]" -map 0:a? -c:v libx264 -crf 18 -preset slow -pix_fmt yuv420p '
+        f'-c:a copy -map_chapters -1 -sn -threads {threads} "{output_path}"'
+    )
 
     try:
-        linux.run_command(f"ffmpeg -y -i {input_file} -map_chapters -1 -sn -c copy {temp_path}")
+        linux.run_command(ffmpeg_cmd)
-        
+        print(f"🎉 High-speed processing complete! Video saved to: {output_path}")
-        # Load video
-        clip = VideoFileClip(temp_path)
-
-        # Standard vertical 9:16 canvas sizes
-        canvas_w = 1080
-        canvas_h = 1920
-
-        # Background logic
-        if use_blur:
-            print("📐 Scaling, cropping, and blurring background layer...")
-            bg_scaled = clip.resized(height=canvas_h)
-            bg_cropped = bg_scaled.cropped(width=canvas_w, x_center=bg_scaled.w / 2)
-            background_layer = bg_cropped.transform(lambda gf, t: apply_gaussian_blur(gf(t), radius=35))
-        else:
-            print("⚫ Creating solid black background canvas...")
-            background_layer = ColorClip(size=(canvas_w, canvas_h), color=(0, 0, 0), duration=clip.duration)
-
-        print("📐 Shrinking foreground video width to fit the 1080 wide canvas...")
-        foreground_clip = clip.resized(width=canvas_w)
-
-        print("✍️ Creating multi-line top title text clip...")
-        # FIXED: Added 'method="caption"' and increased vertical size to 300
-        title_clip = TextClip(
-            text=top_text,
-            font_size=55,                  # Slightly smaller to accommodate paragraphs comfortably
-            color="white",
-            font="DejaVuSans-Bold",
-            text_align="center",
-            size=(canvas_w - 100, 300),    # Subtracted 100px for safety margins on left/right edges
-            method="caption",              # Forces text to wrap cleanly onto a new line
-            duration=clip.duration
-        )
-        # Position adjusted to center the taller 300px box in the upper section
-        positioned_top_text = title_clip.with_position(("center", 180))
-
-        print("✍️ Creating multi-line bottom text clip...")
-        # FIXED: Added 'method="caption"' and increased vertical size to 300
-        bottom_clip = TextClip(
-            text=bottom_text,
-            font_size=55,                  
-            color="white",
-            font="DejaVuSans-Bold",
-            text_align="center",
-            size=(canvas_w - 100, 300),    # Left/right margins included
-            method="caption",              # Forces text to wrap cleanly onto a new line
-            duration=clip.duration
-        )
-        # Position adjusted to center the taller 300px box in the lower section
-        positioned_bottom_text = bottom_clip.with_position(("center", 1430))
-
-        # Composite layers
-        final_clip = CompositeVideoClip(
-            [
-                background_layer, 
-                foreground_clip.with_position("center"),
-                positioned_top_text,
-                positioned_bottom_text
-            ]
-        ).with_audio(clip.audio)
-
-        print("🎬 Rendering final vertical composition...")
-        final_clip.write_videofile(
-            str(output_path),
-            codec="libx264",
-            audio_codec="aac",
-            fps=clip.fps
-        )
-
-        # Clean up file locks safely
-        clip.close()
-        if bg_scaled: bg_scaled.close()
-        if bg_cropped: bg_cropped.close()
-        background_layer.close()
-        foreground_clip.close()
-        title_clip.close()
-        bottom_clip.close()
-        final_clip.close()
-
     finally:
-        temp_file_path = Path(temp_path)
+        # Clean up temporary PNG picture files safely
-        if temp_file_path.exists():
+        for path in (top_png, bottom_png):
-            temp_file_path.unlink()
+            if os.path.exists(path):
+                os.unlink(path)
 
-    print(f"🎉 Text overlay video saved to: {output_path}")
 
 if __name__ == "__main__":
+    import time
+
+    start_time = time.perf_counter()
+
     creator_name = "greenskiesbluegrass"
     top_txt = "TeamPGP Live on Twitch...\n Every Friday and Sunday @7:30 ET.\n twitch.tv/teampgp"
     bottom_txt = f"Clipped By: {creator_name}."
-    fit_to_9_16_letterbox("download/clips/AbnegateAgitatedGrassPJSalt/AbnegateAgitatedGrassPJSalt.mp4", top_txt, bottom_txt)
+    fit_to_9_16_letterbox("download/clips/AbnegateAgitatedGrassPJSalt/AbnegateAgitatedGrassPJSalt.mp4", top_txt, bottom_txt, True, True)
+
+    end_time = time.perf_counter()
+    execution_time = end_time - start_time
+
+    print(f"The function took {execution_time:.6f} seconds to complete.")