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| import os | |
| from smolagents import ( | |
| CodeAgent, | |
| DuckDuckGoSearchTool, | |
| VisitWebpageTool, | |
| PythonInterpreterTool, | |
| InferenceClientModel, | |
| # HfApiModel, # import bug from smolagents after adding duckduckgo-search in requirements | |
| tool | |
| ) | |
| from typing import List, Dict, Any, Optional | |
| class QAgent: | |
| def __init__( | |
| self, | |
| model_type: str = "InferenceClientModel", | |
| model_id: Optional[str] = None, | |
| api_key: Optional[str] = None, | |
| provider: Optional[str] = None, # for InferenceClientModel | |
| timeout: Optional[int] = None, # for InferenceClientModel | |
| system_prompt: Optional[str] = None, | |
| verbose: bool = False # Verbose logging or not | |
| ): | |
| """ | |
| QAgent description | |
| """ | |
| self.verbose = verbose | |
| self.system_prompt = system_prompt | |
| # if model_type == "HfApiModel": | |
| # if api_key is None: | |
| # api_key = os.getenv("SP_HF_TOK") | |
| # if not api_key: | |
| # raise ValueError("No API Key found for HuggingFace. Please set SP_HF_TOK or pass api_key.") | |
| # | |
| # if self.verbose: | |
| # print(f"Using Hugging Face token: {api_key[:5]}... (HfApiModel mode)") | |
| # | |
| # self.model = HfApiModel( | |
| # model_id=model_id or "Qwen/Qwen2.5-Coder-32B-Instruct", # précédemment : or "meta-llama/Llama-3-70B-Instruct", | |
| # token=api_key | |
| # # temperature=temperature | |
| # ) | |
| # el | |
| if model_type == "InferenceClientModel": | |
| if api_key is None: | |
| api_key = os.getenv("Q_NEB_TOK") | |
| if not api_key: | |
| raise ValueError("No API Key found for HuggingFace. Please set SP_HF_TOK or pass api_key.") | |
| if self.verbose: | |
| print(f"Using Hugging Face token: {api_key[:5]}... (InferenceClientModel mode)") | |
| self.model = InferenceClientModel( | |
| model_id=model_id or "Qwen/Qwen2.5-Coder-32B-Instruct", # précédemment : or "meta-llama/Llama-3-70B-Instruct", | |
| provider=provider or "nebius", # or "hf-inference", | |
| token=api_key, | |
| timeout=timeout or 120 | |
| # temperature=temperature | |
| ) | |
| else: | |
| raise ValueError(f"Unknown model type: {model_type}") | |
| if self.verbose: | |
| print(f"Model initialized: {model_type} - {self.model.model_id} - prov: {self.model.provider}") | |
| # Initialize tools | |
| self.tools = [ | |
| DuckDuckGoSearchTool(), | |
| PythonInterpreterTool(), | |
| # save_and_read_file, | |
| # download_file_from_url, | |
| # analyze_csv_file, | |
| # analyze_excel_file | |
| ] | |
| # Setup imports | |
| self.imports = ["pandas", "numpy", "datetime", "json", "re", "math", "os", "requests", "csv", "urllib"] | |
| # Create CodeAgent | |
| self.agent = CodeAgent( | |
| tools=self.tools, | |
| model=self.model, | |
| # additional_authorized_imports=self.imports, | |
| # executor_type=executor_type, | |
| # executor_kwargs=executor_kwargs, | |
| verbosity_level=2 if self.verbose else 0 | |
| ) | |
| if self.verbose: | |
| print("CodeAgent initialized") | |
| def invoke(self, prompt: str) -> str: | |
| print(f"Agent invoked with prompt: {prompt[:80]}...") | |
| result = self.agent.run(prompt) | |
| print(result) | |
| return result | |