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| from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool | |
| import datetime | |
| import requests | |
| import pytz | |
| import yaml | |
| from tools.final_answer import FinalAnswerTool | |
| from smolagents import LiteLLMModel | |
| from Gradio_UI import GradioUI | |
| #S&P500 Sentiment StoryTeller | |
| def market_sentiment_story(index: str) -> str: | |
| """Fetches market data for a stock index and returns a prompt for generating a story. | |
| Args: | |
| index: One of 'sp500', 'dowjones', or 'nasdaq'. | |
| """ | |
| # 1. Map user input to Yahoo Finance symbols (Can create another tool down the line) | |
| symbols = { | |
| "sp500": "^GSPC", | |
| "dowjones": "^DJI", | |
| "nasdaq": "^IXIC" | |
| } | |
| # 2. Get the correct symbol for the requested index | |
| symbol = symbols.get(index.lower()) | |
| try: | |
| # 3. Fetch data from Yahoo Finance | |
| url = f"https://query1.finance.yahoo.com/v8/finance/chart/{symbol}" | |
| data = requests.get(url).json() | |
| # 4. Extract current and previous prices | |
| result = data["chart"]["result"][0]["meta"] | |
| current = result["regularMarketPrice"] | |
| previous = result["chartPreviousClose"] | |
| change = current - previous | |
| percent = (change / previous) * 100 | |
| # 5. Return a prompt for the LLM to generate a story | |
| return ( | |
| f"The {index.upper()} is currently at {current:.2f}, " | |
| f"which is a change of {percent:.2f}% from the previous close. " | |
| f"Write a short, realistic story that explains why it moved in this direction." | |
| ) | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| def get_current_time_in_timezone(timezone: str) -> str: | |
| """A tool that fetches the current local time in a specified timezone. | |
| Args: | |
| timezone: A string representing a valid timezone (e.g., 'America/New_York'). | |
| """ | |
| try: | |
| # Create timezone object | |
| tz = pytz.timezone(timezone) | |
| # Get current time in that timezone | |
| local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S") | |
| return f"The current local time in {timezone} is: {local_time}" | |
| except Exception as e: | |
| return f"Error fetching time for timezone '{timezone}': {str(e)}" | |
| final_answer = FinalAnswerTool() | |
| # 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 = LiteLLMModel( | |
| model_id="qwen2:7b", | |
| api_base="http://localhost:11434", # Or 127.0.0.1 | |
| model_provider="ollama", # 👈 THIS is the key fix! | |
| num_ctx=8192, | |
| ) | |
| # 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=[final_answer, market_sentiment_story], ## 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() |