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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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import pandas as pd |
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from tools.final_answer import FinalAnswerTool |
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from Gradio_UI import GradioUI |
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@tool |
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def search_latest_ai_models(topic: str) -> str: |
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""" |
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Searches for latest AI/GenAI model announcements using DuckDuckGo and returns results in tabular format. |
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Args: |
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topic: Topic to search (e.g., 'latest Generative AI models 2025') |
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Returns: |
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Markdown table summarizing AI model, company, and purpose. |
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""" |
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search_tool = DuckDuckGoSearchTool() |
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results = search_tool(topic) |
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table_data = [] |
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for item in results[:5]: |
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title = item.get("title", "") |
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link = item.get("link", "") |
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snippet = item.get("body", "") |
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model = title.split(" ")[0] |
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company = "Unknown" |
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if "Google" in snippet or "Google" in title: |
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company = "Google" |
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elif "OpenAI" in snippet or "OpenAI" in title: |
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company = "OpenAI" |
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elif "Anthropic" in snippet or "Anthropic" in title: |
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company = "Anthropic" |
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elif "Alibaba" in snippet or "Alibaba" in title: |
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company = "Alibaba" |
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table_data.append({ |
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"Model": model, |
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"Company": company, |
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"Purpose": snippet[:100] + "..." if snippet else "N/A", |
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"Link": link |
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}) |
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markdown = "| Model | Company | Purpose | Link |\n|-------|---------|---------|------|\n" |
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for row in table_data: |
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markdown += f"| {row['Model']} | {row['Company']} | {row['Purpose']} | [Link]({row['Link']}) |\n" |
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return markdown |
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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= 'deepseek-ai/deepseek-coder-33b-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, search_latest_ai_models], |
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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() |