Spaces:
Running
Running
File size: 4,171 Bytes
9551276 3be135a 5e72808 95edb23 5e72808 2bcefc7 95edb23 2bcefc7 95edb23 14f07e7 2bcefc7 3be135a 14f07e7 5e72808 3be135a 95edb23 5e72808 2bcefc7 110c323 bb25d5e 5e72808 e42b84a 5d31a12 5e72808 70e2653 95edb23 70e2653 95edb23 70e2653 95edb23 70e2653 95edb23 70e2653 95edb23 110c323 415dd0a 2bcefc7 415dd0a 3be135a 110c323 5e72808 6a80409 04f0cbd 5a9b61d 04f0cbd 5a9b61d 04f0cbd 5b1af87 95edb23 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 |
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() |