added company_description

Here’s the updated company_description function using an LLM to generate a short company description. This method is preferred over Wikipedia API because companies may have variations in their names (e.g., “Inc.”, “Corp.”, “Platforms”), making direct Wikipedia lookups unreliable.

app.py

@@ -10,12 +10,11 @@ from io import BytesIO
 from Gradio_UI import GradioUI
 
 @tool
-def company_logos(company_name: str, _: int) -> str:
+def company_logos(company_name: str) -> Image.Image:
     """A tool that retrieves the logo of a given company using the Clearbit Logo API.
 
     Args:
         company_name: The name of the company.
-        _: A placeholder argument (not used).
 
     Returns:
         The URL of the company's logo or an error message if retrieval fails.
@@ -38,7 +37,21 @@ def company_logos(company_name: str, _: int) -> str:
     except Exception as e:
         return f"Error fetching logo for {company_name}: {str(e)}"
 
+@tool
+def company_description(company_name: str) -> str:
+    """A tool that generates a short company description using an LLM..
+    
+    Args: 
+        company_name: The name of the company.
 
+    Returns:
+        A short description of the company
+    """
+
+    prompt = f"Write a short summary about the company {company_name}, inclding: one sentence for the company main product or service; two sentences for the company history; one sencence for the latests news about the company "
+    response = summarizer(prompt, max_length=150, do_sample=True)
+    return response[0]["generated_text"]
+    
 final_answer = FinalAnswerTool()
 
 # 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:
@@ -60,7 +73,7 @@ with open("prompts.yaml", 'r') as stream:
     
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, company_logos], ## add your tools here (don't remove final answer)
+    tools=[final_answer, company_logos, company_description], ## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,