Update app.py
Browse files
app.py
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@@ -40,30 +40,28 @@ def secret_word() -> str:
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@tool
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def on_this_day(date: str) -> str:
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"""Search for notable historical events that happened on a given date using DuckDuckGo.
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Args:
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date: A string representing the date to search for (e.g., '27 February 1924' or '27 February').
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Returns:
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A formatted string summarizing a notable event on that date, along with a source link.
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If no event is found, it states that nothing of note occurred.
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"""
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try:
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# Construct the search query
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query = f"notable events on {date} site:wikipedia.org"
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#
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search_results = DuckDuckGoSearchTool()(query)
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#
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if not search_results or len(search_results) == 0:
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return f"On the date {date}, nothing of note occurred."
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#
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first_result = search_results[0]
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#
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title = first_result.get("title", "Unknown Event")
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link = first_result.get("href", "No source available")
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@@ -73,6 +71,7 @@ def on_this_day(date: str) -> str:
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return f"Error retrieving historical data for {date}: {str(e)}"
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final_answer = FinalAnswerTool()
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# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
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@tool
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def on_this_day(date: str) -> str:
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"""Search for notable historical events that happened on a given date using DuckDuckGo."""
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try:
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# Construct the search query
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query = f"notable events on {date} site:wikipedia.org"
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# Perform the DuckDuckGo search
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search_results = DuckDuckGoSearchTool()(query)
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# 🔍 Debugging: Print the raw search results
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print(f"DEBUG: Raw search results for '{query}': {search_results}")
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# Check if results exist
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if not search_results or len(search_results) == 0:
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return f"On the date {date}, nothing of note occurred."
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# Ensure first result is a dictionary
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first_result = search_results[0]
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if not isinstance(first_result, dict):
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return f"Error: Unexpected response format for {date}: {first_result}"
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# Extract event details
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title = first_result.get("title", "Unknown Event")
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link = first_result.get("href", "No source available")
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return f"Error retrieving historical data for {date}: {str(e)}"
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final_answer = FinalAnswerTool()
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# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
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