File size: 4,583 Bytes
9551276
3be135a
5e72808
 
95edb23
5e72808
c93e6a7
 
 
 
 
 
 
2bcefc7
c93e6a7
2bcefc7
95edb23
c93e6a7
 
 
 
14f07e7
 
 
 
2bcefc7
c93e6a7
3be135a
14f07e7
 
5e72808
3be135a
 
95edb23
5e72808
2bcefc7
110c323
 
 
 
bb25d5e
5e72808
 
 
 
 
 
e42b84a
5d31a12
 
 
5e72808
 
 
c93e6a7
70e2653
 
 
 
 
 
 
 
c93e6a7
70e2653
 
95edb23
c93e6a7
 
 
70e2653
c93e6a7
95edb23
70e2653
95edb23
70e2653
95edb23
 
70e2653
95edb23
 
c93e6a7
5d135b7
 
 
 
 
 
 
 
c93e6a7
 
5d135b7
 
 
 
 
c93e6a7
5d135b7
c93e6a7
5d135b7
 
 
 
 
 
 
 
 
bc69648
5d135b7
 
5b1af87
c93e6a7
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
108
109
110
111
112
113
114
115
import os
import random
import gradio as gr
from groq import Groq
from moviepy.editor import VideoFileClip, TextClip, CompositeVideoClip

```python
import gradio as gr
import os
import random
from moviepy.editor import VideoFileClip, TextClip, CompositeVideoClip

# Initialize client with API key
client = Groq(
    api_key=os.getenv("Groq_Api_Key")
)

if client.api_key is None:
    raise EnvironmentError("Groq_Api_Key environment variable is not set.")

# Helper to create messages from history
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

# Generate response function
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

# Process video function
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()
    formatted_text = "
".join([" ".join(text_lines[i:i + 8]) for i in range(0, len(text_lines), 8)])

    text_clip = TextClip(formatted_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 for the chat interface
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")
]

# Gradio interface with blocks and tabs
with gr.Blocks(theme=gr.themes.Soft(primary_hue="red", secondary_hue="pink")) as demo:
    with gr.Tabs():
        with gr.TabItem("Chat"):
            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.",
            )
        with gr.TabItem("Video Processing"):
            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=text_input,
                outputs=video_output,
            )

# Launch the Gradio demo
demo.launch()