Spaces:
Runtime error
Runtime error
show ffmpg command in case of error
#6
by
Aivo
- opened
- app.py +42 -86
- requirements.txt +1 -1
app.py
CHANGED
@@ -12,24 +12,13 @@ import tempfile
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import shlex
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import shutil
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-
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"base_url": "https://api.deepseek.com/v1",
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"env_key": "DEEPSEEK_API_KEY",
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},
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}
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# Initialize client with first available model
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client = OpenAI(
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base_url=next(iter(MODELS.values()))["base_url"],
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api_key=os.environ[next(iter(MODELS.values()))["env_key"]],
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)
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allowed_medias = [
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".png",
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".jpg",
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".webp",
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".jpeg",
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".tiff",
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".bmp",
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@@ -95,7 +84,7 @@ def get_files_infos(files):
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return results
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def get_completion(prompt, files_info, top_p, temperature
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# Create table header
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files_info_string = "| Type | Name | Dimensions | Duration | Audio Channels |\n"
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files_info_string += "|------|------|------------|-----------|--------|\n"
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@@ -128,7 +117,6 @@ You are given:
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Your objective is to generate the SIMPLEST POSSIBLE single ffmpeg command to create the requested video.
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Key requirements:
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- First, think step-by-step about what the user is asking for and reformulate it into a clear technical specification
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- Use the absolute minimum number of ffmpeg options needed
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- Avoid complex filter chains or filter_complex if possible
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- Prefer simple concatenation, scaling, and basic filters
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@@ -144,19 +132,15 @@ Remember: Simpler is better. Only use advanced ffmpeg features if absolutely nec
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},
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{
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"role": "user",
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"content": f"""Always output the media as video/mp4 and output file with "output.mp4".
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The current assets and objective follow.
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AVAILABLE ASSETS LIST:
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{files_info_string}
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OBJECTIVE: {prompt} and output at "output.mp4"
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First, think step-by-step about what I'm asking for and reformulate it into a clear technical specification.
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Then provide the FFMPEG command that will accomplish this task.
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YOUR RESPONSE:
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""",
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},
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]
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@@ -168,16 +152,8 @@ YOUR RESPONSE:
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print(msg["content"])
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print("=====================\n")
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if model_choice not in MODELS:
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raise ValueError(f"Model {model_choice} is not supported")
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model_config = MODELS[model_choice]
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client.base_url = model_config["base_url"]
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client.api_key = os.environ[model_config["env_key"]]
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model = "deepseek-chat" if "deepseek" in model_choice.lower() else model_choice
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completion = client.chat.completions.create(
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model=
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messages=messages,
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temperature=temperature,
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top_p=top_p,
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@@ -189,23 +165,13 @@ YOUR RESPONSE:
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# Find content between ```sh or ```bash and the next ```
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import re
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-
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if
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command =
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else:
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# Try to find a line that starts with ffmpeg
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ffmpeg_lines = [line.strip() for line in content.split('\n') if line.strip().startswith('ffmpeg')]
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if ffmpeg_lines:
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command = ffmpeg_lines[0]
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else:
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command = content.replace("\n", "")
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else:
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# Try to find a line that starts with ffmpeg
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ffmpeg_lines = [line.strip() for line in content.split('\n') if line.strip().startswith('ffmpeg')]
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if ffmpeg_lines:
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command = ffmpeg_lines[0]
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else:
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command = content.replace("\n", "")
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# remove output.mp4 with the actual output file path
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command = command.replace("output.mp4", "")
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@@ -215,13 +181,7 @@ YOUR RESPONSE:
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raise Exception("API Error")
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def update(
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files,
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prompt,
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top_p=1,
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temperature=1,
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model_choice="deepseek-ai/DeepSeek-V3",
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):
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if prompt == "":
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raise gr.Error("Please enter a prompt.")
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@@ -233,16 +193,14 @@ def update(
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raise gr.Error(
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"Please make sure all videos are less than 2 minute long."
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)
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if file_info["size"] >
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raise gr.Error("Please make sure all files are less than
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attempts = 0
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while attempts < 2:
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print("ATTEMPT", attempts)
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try:
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command_string = get_completion(
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prompt, files_info, top_p, temperature, model_choice
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)
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print(
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f"""///PROMTP {prompt} \n\n/// START OF COMMAND ///:\n\n{command_string}\n\n/// END OF COMMAND ///\n\n"""
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)
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@@ -281,9 +239,7 @@ def update(
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f"\n=== EXECUTING FFMPEG COMMAND ===\nffmpeg {' '.join(final_command[1:])}\n"
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)
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subprocess.run(final_command, cwd=temp_dir)
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command_for_display = f"ffmpeg {' '.join(args[1:])} -y output.mp4"
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generated_command = f"### Generated Command\n```bash\n{command_for_display}\n```"
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return output_file_path, gr.update(value=generated_command)
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except Exception as e:
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attempts += 1
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@@ -296,7 +252,7 @@ with gr.Blocks() as demo:
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gr.Markdown(
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"""
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# π AI Video Composer
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Compose new videos from your assets using natural language. Add video, image and audio assets and let [Qwen2.5-Coder](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct)
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""",
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elem_id="header",
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)
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file_types=allowed_medias,
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)
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user_prompt = gr.Textbox(
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placeholder="
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label="Instructions",
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)
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btn = gr.Button("Run")
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with gr.Accordion("Parameters", open=False):
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model_choice = gr.Radio(
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choices=list(MODELS.keys()),
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value=list(MODELS.keys())[0],
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label="Model",
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)
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top_p = gr.Slider(
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minimum=-0,
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maximum=1.0,
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@@ -342,7 +293,7 @@ with gr.Blocks() as demo:
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btn.click(
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fn=update,
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inputs=[user_files, user_prompt, top_p, temperature
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outputs=[generated_video, generated_command],
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)
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with gr.Row():
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examples=[
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[
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["./examples/ai_talk.wav", "./examples/bg-image.png"],
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-
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0.7,
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0.1,
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list(MODELS.keys())[0],
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],
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[
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["./examples/ai_talk.wav", "./examples/bg-image.png"],
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"Use the image as the background with a waveform visualization for the audio positioned in center of the video. Make sure the waveform has a max height of 250 pixels.",
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0.7,
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0.1,
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list(MODELS.keys())[0],
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],
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[
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[
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"./examples/cat1.jpeg",
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"./examples/cat2.jpeg",
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"./examples/cat3.jpeg",
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"./examples/cat4.jpeg",
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"./examples/cat5.jpeg",
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"./examples/cat6.jpeg",
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"./examples/heat-wave.mp3",
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],
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outputs=[generated_video, generated_command],
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fn=update,
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run_on_click=True,
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import shlex
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import shutil
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HF_API_KEY = os.environ["HF_TOKEN"]
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client = OpenAI(base_url="https://api-inference.huggingface.co/v1/", api_key=HF_API_KEY)
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allowed_medias = [
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".png",
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".jpg",
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".jpeg",
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".tiff",
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".bmp",
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return results
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+
def get_completion(prompt, files_info, top_p, temperature):
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# Create table header
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files_info_string = "| Type | Name | Dimensions | Duration | Audio Channels |\n"
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files_info_string += "|------|------|------------|-----------|--------|\n"
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Your objective is to generate the SIMPLEST POSSIBLE single ffmpeg command to create the requested video.
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Key requirements:
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- Use the absolute minimum number of ffmpeg options needed
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- Avoid complex filter chains or filter_complex if possible
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- Prefer simple concatenation, scaling, and basic filters
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},
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{
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"role": "user",
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"content": f"""Always output the media as video/mp4 and output file with "output.mp4". Provide only the shell command without any explanations.
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The current assets and objective follow. Reply with the FFMPEG command:
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AVAILABLE ASSETS LIST:
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{files_info_string}
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OBJECTIVE: {prompt} and output at "output.mp4"
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YOUR FFMPEG COMMAND:
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""",
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},
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]
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print(msg["content"])
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print("=====================\n")
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completion = client.chat.completions.create(
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model="Qwen/Qwen2.5-Coder-32B-Instruct",
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messages=messages,
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temperature=temperature,
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top_p=top_p,
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# Find content between ```sh or ```bash and the next ```
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import re
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command = re.search(r"```(?:sh|bash)?\n(.*?)\n```", content, re.DOTALL)
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if command:
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command = command.group(1).strip()
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else:
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command = content.replace("\n", "")
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else:
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command = content.replace("\n", "")
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# remove output.mp4 with the actual output file path
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command = command.replace("output.mp4", "")
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raise Exception("API Error")
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def update(files, prompt, top_p=1, temperature=1):
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if prompt == "":
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raise gr.Error("Please enter a prompt.")
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raise gr.Error(
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"Please make sure all videos are less than 2 minute long."
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)
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if file_info["size"] > 10000000:
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raise gr.Error("Please make sure all files are less than 10MB in size.")
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attempts = 0
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while attempts < 2:
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print("ATTEMPT", attempts)
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try:
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command_string = get_completion(prompt, files_info, top_p, temperature)
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print(
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f"""///PROMTP {prompt} \n\n/// START OF COMMAND ///:\n\n{command_string}\n\n/// END OF COMMAND ///\n\n"""
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)
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f"\n=== EXECUTING FFMPEG COMMAND ===\nffmpeg {' '.join(final_command[1:])}\n"
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)
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subprocess.run(final_command, cwd=temp_dir)
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generated_command = f"### Generated Command\n```bash\nffmpeg {' '.join(args[1:])} -y output.mp4\n```"
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return output_file_path, gr.update(value=generated_command)
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except Exception as e:
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attempts += 1
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gr.Markdown(
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"""
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# π AI Video Composer
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+
Compose new videos from your assets using natural language. Add video, image and audio assets and let [Qwen2.5-Coder](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct) generate a new video for you (using FFMPEG).
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""",
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elem_id="header",
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)
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file_types=allowed_medias,
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)
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user_prompt = gr.Textbox(
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+
placeholder="I want to convert to a gif under 15mb",
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label="Instructions",
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)
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btn = gr.Button("Run")
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with gr.Accordion("Parameters", open=False):
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top_p = gr.Slider(
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minimum=-0,
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maximum=1.0,
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btn.click(
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fn=update,
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inputs=[user_files, user_prompt, top_p, temperature],
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outputs=[generated_video, generated_command],
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)
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with gr.Row():
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examples=[
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[
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["./examples/ai_talk.wav", "./examples/bg-image.png"],
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+
"Use the image as the background with a waveform visualization for the audio positioned in center of the video.",
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0.7,
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0.1,
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],
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[
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[
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+
"./examples/cat8.jpeg",
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"./examples/cat1.jpeg",
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"./examples/cat2.jpeg",
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"./examples/cat3.jpeg",
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"./examples/cat4.jpeg",
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"./examples/cat5.jpeg",
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"./examples/cat6.jpeg",
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"./examples/cat7.jpeg",
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"./examples/heat-wave.mp3",
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],
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"Generate an MP4 slideshow where each photo appears for 2 seconds, using the provided audio as soundtrack.",
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0.7,
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0.1,
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],
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[
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["./examples/waterfall-overlay.png", "./examples/waterfall.mp4"],
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"Add the overlay to the video.",
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0.7,
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0.1,
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],
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[
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["./examples/example.mp4"],
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"Make this video 10 times faster",
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0.7,
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0.1,
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],
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],
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inputs=[user_files, user_prompt, top_p, temperature],
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outputs=[generated_video, generated_command],
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fn=update,
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run_on_click=True,
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requirements.txt
CHANGED
@@ -1,3 +1,3 @@
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openai>=1.55.0
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-
gradio==5.
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moviepy==1
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openai>=1.55.0
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gradio==5.6.0
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moviepy==1
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