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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}) | |
| print(messages) | |
| 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(video_path, text): | |
| video = VideoFileClip(video_path).subclip(0, min(60, VideoFileClip(video_path).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") | |
| ] | |
| with gr.Blocks(theme=gr.themes.Soft(primary_hue="red", secondary_hue="pink")) as demo: | |
| with gr.Tabs(): | |
| with gr.TabItem("Chat"): | |
| 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.", | |
| ) | |
| with gr.TabItem("Video Processing"): | |
| video_input = gr.Video(label="Upload Video") | |
| text_input = gr.Textbox(lines=5, label="Text (8 words max per line)") | |
| process_button = gr.Button("Process Video") | |
| video_output = gr.Video(label="Processed Video") | |
| process_button.click( | |
| fn=process_video, | |
| inputs=[video_input, text_input], | |
| outputs=video_output, | |
| ) | |
| demo.launch() |