Fix what_can_i_do tool: convert to proper Tool class

what_can_i_do.py

@@ -0,0 +1,60 @@
+import opik
+from smolagents import Tool
+
+
+class WhatCanIDoTool(Tool):
+    name = "what_can_i_do"
+    description = """Returns a comprehensive list of available capabilities and topics in the Second Brain system.
+
+    This tool should be used when:
+    - The user explicitly asks what the system can do
+    - The user asks about available features or capabilities
+    - The user seems unsure about what questions they can ask
+    - The user wants to explore the system's knowledge areas
+
+    This tool should NOT be used when:
+    - The user asks a specific technical question
+    - The user already knows what they want to learn about
+    - The question is about a specific topic covered in the knowledge base"""
+
+    inputs = {
+        "question": {
+            "type": "string",
+            "description": "The user's query about system capabilities. While this parameter is required, the function returns a standard capability list regardless of the specific question."
+        }
+    }
+    output_type = "string"
+
+    @opik.track(name="what_can_i_do")
+    def forward(self, question: str) -> str:
+        """Returns a comprehensive list of available capabilities and topics in the Second Brain system."""
+        return """
+You can ask questions about the content in your Second Brain, such as:
+
+Architecture and Systems:
+- What is the feature/training/inference (FTI) architecture?
+- How do agentic systems work?
+- Detail how does agent memory work in agentic applications?
+
+LLM Technology:
+- What are LLMs?
+- What is BERT (Bidirectional Encoder Representations from Transformers)?
+- Detail how does RLHF (Reinforcement Learning from Human Feedback) work?
+- What are the top LLM frameworks for building applications?
+- Write me a paragraph on how can I optimize LLMs during inference?
+
+RAG and Document Processing:
+- What tools are available for processing PDFs for LLMs and RAG?
+- What's the difference between vector databases and vector indices?
+- How does document chunk overlap affect RAG performance?
+- What is chunk reranking and why is it important?
+- What are advanced RAG techniques for optimization?
+- How can RAG pipelines be evaluated?
+
+Learning Resources:
+- Can you recommend courses on LLMs and RAG?
+"""
+
+
+# Create an instance for backward compatibility
+what_can_i_do = WhatCanIDoTool()