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Update app.py
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app.py
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@@ -33,6 +33,27 @@ def get_square_root_tool(input_number:int)-> int: #it's import to specify the re
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except Exception as e:
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return f"Error fetching Square root of '{input_number}': {str(e)}"
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@tool
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def get_current_time_in_timezone(timezone: str) -> str:
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"""A tool that fetches the current local time in a specified timezone.
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@@ -70,7 +91,7 @@ with open("prompts.yaml", 'r') as stream:
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agent = CodeAgent(
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model=model,
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tools=[final_answer,image_generation_tool,get_square_root_tool], ## add your tools here (don't remove final answer)
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max_steps=6,
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verbosity_level=1,
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grammar=None,
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except Exception as e:
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return f"Error fetching Square root of '{input_number}': {str(e)}"
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@tool
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def classify_educational_article(text: str) -> int:
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"""
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Classifier for judging the educational value of web pages.
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Args:
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article_text: The content of the news article to be classified.
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Returns:
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str: This function will output a dictionary with the input text, the predicted score, and an integer score between 0 and 5
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"""
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from transformers import pipeline
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# Perform classification
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model_name = "HuggingFaceTB/fineweb-edu-classifier"
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classifier = pipeline("text-classification", model=model_name)
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inputs = tokenizer(text, return_tensors="pt", padding="longest", truncation=True)
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outputs = classifier(**inputs)
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logits = outputs.logits.squeeze(-1).float().detach().numpy()
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score = logits.item()
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return score
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@tool
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def get_current_time_in_timezone(timezone: str) -> str:
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"""A tool that fetches the current local time in a specified timezone.
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agent = CodeAgent(
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model=model,
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tools=[final_answer,image_generation_tool,get_square_root_tool,classify_educational_article], ## add your tools here (don't remove final answer)
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max_steps=6,
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verbosity_level=1,
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grammar=None,
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