ShortsAutomator / app.py
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import os
import random
import gradio as gr
from groq import Groq
from moviepy.editor import VideoFileClip, TextClip, CompositeVideoClip
client = Groq(
api_key=os.environ.get("Groq_Api_Key")
)
def create_history_messages(history):
history_messages = [{"role": "user", "content": m[0]} for m in history]
history_messages.extend([{"role": "assistant", "content": m[1]} for m in history])
return history_messages
def generate_response(prompt, history, model, temperature, max_tokens, top_p, seed):
messages = create_history_messages(history)
messages.append({"role": "user", "content": prompt})
if seed == 0:
seed = random.randint(1, 100000)
stream = client.chat.completions.create(
messages=messages,
model=model,
temperature=temperature,
max_tokens=max_tokens,
top_p=top_p,
seed=seed,
stop=None,
stream=True,
)
response = ""
for chunk in stream:
delta_content = chunk.choices[0].delta.content
if delta_content is not None:
response += delta_content
yield response
return response
def process_video(text):
video_folder = "videos"
video_files = [os.path.join(video_folder, f) for f in os.listdir(video_folder) if f.endswith(('mp4', 'mov', 'avi', 'mkv'))]
if not video_files:
raise FileNotFoundError("No video files found in the specified directory.")
selected_video = random.choice(video_files)
video = VideoFileClip(selected_video)
start_time = random.uniform(0, max(0, video.duration - 60))
video = video.subclip(start_time, min(start_time + 60, video.duration))
video = video.resize(height=1920).crop(x1=video.w // 2 - 540, x2=video.w // 2 + 540)
text_lines = text.split()
text = "\n".join([" ".join(text_lines[i:i+8]) for i in range(0, len(text_lines), 8)])
text_clip = TextClip(text, fontsize=70, color='white', size=video.size, method='caption')
text_clip = text_clip.set_position('center').set_duration(video.duration)
final = CompositeVideoClip([video, text_clip])
output_path = "output.mp4"
final.write_videofile(output_path, codec="libx264")
return output_path
additional_inputs = [
gr.Dropdown(choices=["llama3-70b-8192", "llama3-8b-8192", "mixtral-8x7b-32768", "gemma-7b-it"], value="llama3-70b-8192", label="Model"),
gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.5, label="Temperature", info="Controls diversity of the generated text. Lower is more deterministic, higher is more creative."),
gr.Slider(minimum=1, maximum=32192, step=1, value=4096, label="Max Tokens", info="The maximum number of tokens that the model can process in a single response.<br>Maximums: 8k for gemma 7b, llama 7b & 70b, 32k for mixtral 8x7b."),
gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.5, label="Top P", info="A method of text generation where a model will only consider the most probable next tokens that make up the probability p."),
gr.Number(precision=0, value=42, label="Seed", info="A starting point to initiate generation, use 0 for random")
]
chat_interface = gr.ChatInterface(
fn=generate_response,
chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
additional_inputs=additional_inputs,
title="YTSHorts Maker",
description="Powered by GROQ, MoviePy, and other tools.",
)
def process_video_interface():
text_input = gr.Textbox(lines=5, label="Text (8 words max per line)")
video_output = gr.Video(label="Processed Video")
def process_video_callback(text):
output_path = process_video(text)
video_output.value = output_path
return gr.Interface(
fn=process_video_callback,
inputs=text_input,
outputs=video_output,
title="Video Processing",
description="Select a video file from 'videos' folder, add text, and process.",
)
demo = gr.Interface(
[chat_interface, process_video_interface()],
title="YTSHorts Maker",
description="Powered by GROQ, MoviePy, and other tools.",
theme="soft",
)
demo.launch()