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from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool |
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import datetime |
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import requests |
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import pytz |
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import yaml |
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from tools.final_answer import FinalAnswerTool |
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from diffusers import DiffusionPipeline |
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from Gradio_UI import GradioUI |
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@tool |
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def my_custom_tool(arg1:str, arg2:int)-> str: |
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"""A tool that does nothing yet |
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Args: |
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arg1: the first argument |
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arg2: the second argument |
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""" |
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return "What magic will you build ?" |
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@tool |
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def video_generation( |
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prompt: str |
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) -> str: |
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"""Generate a video from text. Returns path to saved video file. |
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Args: |
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prompt (str): Text description of the desired video content |
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# num_frames (int): Number of frames in output video (16-32 recommended) |
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# num_inference_steps (int): Denoising steps (25-75, higher=better quality) |
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# guidance_scale (float): Prompt adherence (7.0-10.0 recommended) |
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Returns: |
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str: Path to generated video file |
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""" |
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pipe = DiffusionPipeline.from_pretrained("vdo/text-to-video-ms-1.7b") |
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video_frames = pipe( |
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prompt, |
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24, |
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50, |
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9.0, |
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generator=torch.Generator().manual_seed(42) |
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).frames[0] |
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output_path = "MohanaPrasad2002/First_agent_template/generated_video.mp4" |
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video_frames[0].save( |
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output_path, |
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save_all=True, |
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append_images=video_frames[1:], |
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duration=1000, |
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loop=0 |
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) |
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return f"the video saved at {output_path}" |
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@tool |
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def get_current_time_in_timezone(timezone: str) -> str: |
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"""A tool that fetches the current local time in a specified timezone. |
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Args: |
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timezone: A string representing a valid timezone (e.g., 'America/New_York'). |
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""" |
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try: |
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tz = pytz.timezone(timezone) |
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local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S") |
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return f"The current local time in {timezone} is: {local_time}" |
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except Exception as e: |
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return f"Error fetching time for timezone '{timezone}': {str(e)}" |
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final_answer = FinalAnswerTool() |
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model = HfApiModel( |
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max_tokens=2096, |
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temperature=0.5, |
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model_id='Qwen/Qwen2.5-Coder-32B-Instruct', |
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custom_role_conversions=None, |
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) |
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image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True) |
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with open("prompts.yaml", 'r') as stream: |
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prompt_templates = yaml.safe_load(stream) |
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agent = CodeAgent( |
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model=model, |
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tools=[final_answer,image_generation_tool,video_generation], |
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max_steps=6, |
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verbosity_level=1, |
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grammar=None, |
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planning_interval=None, |
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name=None, |
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description=None, |
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prompt_templates=prompt_templates |
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) |
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GradioUI(agent).launch() |