from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool import datetime import requests import pytz import yaml from tools.final_answer import FinalAnswerTool from tools.web_search import DuckDuckGoSearchTool from tools.visit_webpage import VisitWebpageTool from Gradio_UI import GradioUI from kokoro import KPipeline import soundfile as sf import os import numpy as np # Initialize the Kokoro pipeline pipeline = KPipeline(lang_code='a') # 'a' stands for American English @tool def text_to_speech_kokoro(text: str, voice: str = 'af_heart', speed: float = 1.0) -> str: """Convert text to speech using the Kokoro-82M model. Args: text: The text to be converted to speech. voice: The voice to use for speech synthesis (default is 'af_heart'). speed: The speed of the speech (default is 1.0). Returns: An AgentAudio object with the relative URL to the generated audio file. """ try: # Generate speech audio generator = pipeline(text, voice=voice, speed=speed, split_pattern=r'\n+') audio_segments = [] for _, _, audio in generator: audio_segments.append(audio) if not audio_segments: raise ValueError("No audio generated.") # Concatenate segments into one audio array full_audio = np.concatenate(audio_segments) sample_rate = 24000 # Kokoro outputs at 24 kHz # Ensure the static folder exists and save the file there os.makedirs("tools", exist_ok=True) filename = os.path.join("tools", "output.wav") sf.write(filename, full_audio, sample_rate) # Return an AgentAudio object pointing to the relative URL of the audio file from smolagents.agent_types import AgentAudio return AgentAudio(f"tools/output.wav") except Exception as e: return f"Error generating speech: {str(e)}" @tool def search_dad_jokes(term: str) -> str: """A tool that searches for dad jokes containing a specific term. Args: term: The keyword to search for in dad jokes. """ try: headers = { "Accept": "application/json", "User-Agent": "YourAppName (https://yourappurl.com)" } response = requests.get(f"https://icanhazdadjoke.com/search?term={term}", headers=headers) data = response.json() if data['results']: jokes = [joke['joke'] for joke in data['results']] return f"Found {len(jokes)} jokes:\n" + "\n\n".join(jokes) else: return f"No jokes found for the term '{term}'." except Exception as e: return f"Error searching for jokes: {str(e)}" final_answer = FinalAnswerTool() web_search_tool = DuckDuckGoSearchTool() visit_webpage_tool = VisitWebpageTool() # If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder: # model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' model = HfApiModel( max_tokens=2096, temperature=0.5, model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded custom_role_conversions=None, ) # Import tool from Hub image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True) with open("prompts.yaml", 'r') as stream: prompt_templates = yaml.safe_load(stream) agent = CodeAgent( model=model, tools=[visit_webpage_tool, web_search_tool, final_answer, image_generation_tool, get_current_time_in_timezone, get_random_cocktail, search_dad_jokes, text_to_speech_kokoro], ## add your tools here (don't remove final answer) max_steps=6, verbosity_level=1, grammar=None, planning_interval=None, name=None, description=None, prompt_templates=prompt_templates ) GradioUI(agent).launch()