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| import yaml | |
| from smolagents import CodeAgent, HfApiModel | |
| from smolagents.tools import Tool | |
| from tools.resumescraper import ResumeScraperTool | |
| from huggingface_hub import InferenceClient | |
| class FinalAnswerTool(Tool): | |
| name = "final_answer" | |
| description = "Use this tool to provide your final roast" | |
| inputs = { | |
| "answer": { | |
| "type": "string", | |
| "description": "The final roast for the resume" | |
| } | |
| } | |
| output_type = "string" | |
| def forward(self, answer: str) -> str: | |
| return answer | |
| def create_agent(): | |
| final_answer = FinalAnswerTool() | |
| resume_scraper = ResumeScraperTool() | |
| # Instantiate HfApiModel using Qwen/Qwen2.5-Coder-32B-Instruct for roasting. | |
| model = HfApiModel( | |
| max_tokens=2096, | |
| temperature=0.7, | |
| model_id='Qwen/Qwen2.5-Coder-32B-Instruct', | |
| custom_role_conversions=None, | |
| ) | |
| # Create a dedicated InferenceClient using your public endpoint | |
| client = InferenceClient("https://jc26mwg228mkj8dw.us-east-1.aws.endpoints.huggingface.cloud") | |
| # Override the model's client with our dedicated client | |
| model.client = client | |
| with open("prompts.yaml", 'r') as stream: | |
| prompt_templates = yaml.safe_load(stream) | |
| agent = CodeAgent( | |
| model=model, | |
| tools=[resume_scraper, final_answer], | |
| max_steps=1, | |
| verbosity_level=1, | |
| prompt_templates=prompt_templates | |
| ) | |
| return agent |