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| from smolagents import OpenAIServerModel | |
| from dotenv import load_dotenv | |
| from huggingface_hub import HfApi | |
| import os | |
| load_dotenv() | |
| OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY") | |
| repo_id = "zaradana/temp_files" | |
| api = HfApi() | |
| def check_asnwer_format(final_answer, agent_memory): | |
| multimodal_model = OpenAIServerModel("gpt-4o", max_tokens=8096, api_key=OPENAI_API_KEY) | |
| prompt = ( | |
| f"Here is a user-given task and the agent steps: {agent_memory.get_succinct_steps()}. " | |
| f"Here is the final answer: {final_answer}. " | |
| "Please check that the answer is in the requested format. " | |
| "First list reasons why yes/no, then write your final decision: PASS in caps lock if it is satisfactory, FAIL if it is not." | |
| ) | |
| messages = [ | |
| { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": prompt, | |
| } | |
| ], | |
| } | |
| ] | |
| output = multimodal_model(messages).content | |
| print("Feedback: ", output) | |
| if "FAIL" in output: | |
| raise Exception(output) | |
| return True | |
| def upload_file(file_local_path: str) -> str: | |
| """ | |
| Upload a file to the Hugging Face Hub and return the URL | |
| Args: | |
| file_local_path: The local path to the file | |
| Returns: | |
| The URL of the uploaded file | |
| """ | |
| file_name = file_local_path.split("/")[-1] | |
| api.upload_file( | |
| path_or_fileobj=file_local_path, | |
| path_in_repo=file_name, | |
| repo_id=repo_id, | |
| repo_type="dataset" | |
| ) | |
| file_url = f"https://huggingface.co/datasets/{repo_id}/resolve/main/{file_name}" | |
| return file_url | |