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| from agents.agent import MyAgent | |
| from utils import run_agent | |
| from smolagents import ( | |
| DuckDuckGoSearchTool, | |
| # WikipediaSearchTool, | |
| VisitWebpageTool, | |
| ) | |
| from tools.text_search import TextSearch | |
| from tools.text_splitter import text_splitter | |
| from tools.webpage_parser import WebpageParser | |
| from tools.parse_wikipedia_table import WikipediaParser | |
| from tools.open_files import OpenFilesTool | |
| from prompts.default_prompt import generate_prompt | |
| from agents import DEFAULT_ARGS | |
| import os | |
| import json | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| QUESTIONS_FILEPATH: str = os.getenv("QUESTIONS_FILEPATH", default="metadata.jsonl") | |
| OLLAMA_MODEL_ID: str = os.getenv("OLLAMA_MODEL_ID", default="gemma3:12b-it-qat") | |
| OLLAMA_API_BASE: str = os.getenv("OLLAMA_API_BASE", default="http://localhost:11434") | |
| OLLAMA_API_KEY: str | None = os.getenv("GOOGLE_AI_STUDIO_API_KEY") | |
| OLLAMA_NUM_CTX: int = int(os.getenv("OLLAMA_NUM_CTX", default=8192)) | |
| myagent_args = { | |
| "provider": "litellm", | |
| "model_id": "gemini/gemini-2.0-flash-lite", | |
| # "api_base": OLLAMA_API_BASE, | |
| "planning_interval": 3, | |
| "tools": [ | |
| DuckDuckGoSearchTool(), | |
| WikipediaParser(), | |
| VisitWebpageTool(), | |
| TextSearch(), | |
| text_splitter, | |
| WebpageParser(), | |
| OpenFilesTool(), | |
| ], | |
| "additional_authorized_imports": [ | |
| "pandas", | |
| "numpy", | |
| "datetime", | |
| "json", | |
| "re", | |
| "math", | |
| "os", | |
| "requests", | |
| "csv", | |
| "urllib", | |
| ], | |
| "num_ctx": 8192, | |
| "temperature": 0.2, | |
| } | |
| print(f"Using args: {DEFAULT_ARGS}") | |
| if __name__ == "__main__": | |
| agent = MyAgent(**DEFAULT_ARGS) | |
| with open(QUESTIONS_FILEPATH, "r") as f: | |
| questions = json.load(f) | |
| question = questions[0] | |
| question_text = question.get("question") | |
| file_name = question.get("file_name") | |
| prompt = generate_prompt(question_text, file_name) | |
| answers = run_agent(agent, [questions[0]]) | |
| print("Answers:", answers) | |
| print("Finished running the agent.") | |