Update tools/summarizer.py

tools/summarizer.py

@@ -1,21 +1,19 @@
 from smolagents import tool
-from transformers import pipeline
-
-# load once globally (uses a small summarization model from Hugging Face)
-summarizer_pipeline = pipeline("summarization", model="facebook/bart-large-cnn")
 
 @tool
 def summarizer(text: str, max_length: int = 100, min_length: int = 30) -> str:
-    """Summarize a long piece of text into a shorter version.
+    """Summarize a long piece of text into a shorter version using the agent's own LLM.
     Args:
-        text: The text that needs to be summarized.
-        max_length: Maximum length of the summary.
-        min_length: Minimum length of the summary.
+        text: The text to be summarized.
+        max_length: Maximum length of the summary (approximate).
+        min_length: Minimum length of the summary (approximate).
     """
-    try:
-        summary = summarizer_pipeline(
-            text, max_length=max_length, min_length=min_length, do_sample=False
-        )
-        return summary[0]["summary_text"]
-    except Exception as e:
-        return f"Error during summarization: {str(e)}"
+    # Here we don’t call transformers — just ask the model to summarize
+    prompt = (
+        f"Summarize the following text into a clear and concise version:\n\n"
+        f"{text}\n\n"
+        f"Constraints: summary should be between {min_length} and {max_length} words."
+    )
+    # The agent will handle this prompt automatically
+    return prompt
+