chore: Add Dockerfile and FastAPI implementation

Dockerfile

@@ -0,0 +1,20 @@
+# Use the official Python image from the Docker Hub
+FROM python:3.9
+
+# Create a user to run the application
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+# Set the working directory
+WORKDIR /app
+
+# Copy the requirements.txt and install dependencies
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+# Copy the application code
+COPY --chown=user . /app
+
+# Command to run the FastAPI application with uvicorn
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

main_glitch.py → app.py

@@ -23,6 +23,8 @@ from google.auth.transport.requests import Request
 import nltk
 from tts import synthesiser, speaker_embedding 
 import soundfile as sf
+from fastapi import FastAPI
+import uuid
 
 # from tortoise_tts import TextToSpeech
 
@@ -499,28 +501,71 @@ def combine_audio_files(audio_files, output_file):
 api_key = 'VhLwkCKi3iu5Pf37LXfz-Lp7hTW69EV8uw_hkLAPkiA'  # Replace with your Unsplash API key
 background_image = fetch_random_nature_image(api_key)
 
-if background_image:
-    fetch_reddit_data('Glitch_in_the_Matrix')
-    reddit_data = read_json('top_post.json')
-    title = reddit_data.get('title')
-    selftext = reddit_data.get('selftext')
+app = FastAPI()
+
+@app.get("/generate-video")
+def generate_video():
+    try:
+        api_key = 'VhLwkCKi3iu5Pf37LXfz-Lp7hTW69EV8uw_hkLAPkiA'  # Replace with your Unsplash API key
+        background_image = fetch_random_nature_image(api_key)
+
+        if background_image:
+            fetch_reddit_data('Glitch_in_the_Matrix')
+            reddit_data = read_json('top_post.json')
+            title = reddit_data.get('title')
+            selftext = reddit_data.get('selftext')
+
+            # Split title into sentences
+            sentences = nltk.sent_tokenize(selftext)
+            
+            # Generate audio for each sentence and get durations
+            audio_files, audio_durations = tts_per_sentence(sentences, 'audio')
+
+            # Create and save the video
+            video_filename = "reddit_post_video_cv2.mp4"
+            create_video_from_title(title, sentences, background_image, video_filename, audio_durations)
+
+            # Combine all audio files into one (if needed)
+            combined_audio_file = combine_audio_files(audio_files, 'combined_voiceover.mp3')  # Implement this function
+
+            final_filename = "video_" + str(uuid.uuid4())
+
+            # Combine the final video and audio
+            combine_audio_video(video_filename, combined_audio_file, final_filename + '.mp4')
 
-    # Split title into sentences
-    sentences = nltk.sent_tokenize(selftext)
+            return {"status": "success", "filename": final_filename + '.mp4'}
+        else:
+            return {"status": "failed", "message": "Failed to fetch background image"}
+    except Exception as e:
+        return {"status": "error", "message": str(e)}
+
+# Run the application using Uvicorn
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)
+
+# if background_image:
+#     fetch_reddit_data('Glitch_in_the_Matrix')
+#     reddit_data = read_json('top_post.json')
+#     title = reddit_data.get('title')
+#     selftext = reddit_data.get('selftext')
+
+#     # Split title into sentences
+#     sentences = nltk.sent_tokenize(selftext)
     
-    # Generate audio for each sentence and get durations
-    audio_files, audio_durations = tts_per_sentence(sentences, 'audio')
+#     # Generate audio for each sentence and get durations
+#     audio_files, audio_durations = tts_per_sentence(sentences, 'audio')
 
-    # Create and save the video
-    create_video_from_title(title, sentences, background_image, "reddit_post_video_cv2.mp4", audio_durations)
+#     # Create and save the video
+#     create_video_from_title(title, sentences, background_image, "reddit_post_video_cv2.mp4", audio_durations)
 
-    # Combine all audio files into one (if needed)
-    combined_audio_file = combine_audio_files(audio_files, 'combined_voiceover.mp3')  # Implement this function
+#     # Combine all audio files into one (if needed)
+#     combined_audio_file = combine_audio_files(audio_files, 'combined_voiceover.mp3')  # Implement this function
 
-    filename = "video_" + str(uuid.uuid4())
+#     filename = "video_" + str(uuid.uuid4())
 
-    # Combine the final video and audio
-    combine_audio_video('reddit_post_video_cv2.mp4', combined_audio_file, filename + '.mp4')
+#     # Combine the final video and audio
+#     combine_audio_video('reddit_post_video_cv2.mp4', combined_audio_file, filename + '.mp4')
 
 # if background_image:
 #     # Example usage

requirements.txt

@@ -13,4 +13,6 @@ nltk
 gradio
 soundfile
 transformers
-datasets[audio]
+datasets[audio]
+fastapi
+uvicorn[standard]