data/knowledge_base.txt

### AI and Agent Concepts
- An agent is an autonomous entity that observes and acts upon an environment using sensors and actuators, usually to achieve specific goals.
- GAIA (General AI Assistant) is a framework for creating and evaluating AI assistants that can perform a wide range of tasks.
- The agent loop consists of perception, reasoning, and action.
- RAG (Retrieval-Augmented Generation) combines retrieval of relevant information with generation capabilities of language models.
- An LLM (Large Language Model) is a neural network trained on vast amounts of text data to understand and generate human language.

### Agent Capabilities
- Tool use refers to an agent's ability to employ external tools like search engines, APIs, or specialized algorithms.
- An effective agent should be able to decompose complex problems into manageable parts.
- Chain-of-thought reasoning allows agents to break down problem-solving steps to improve accuracy.
- Agents should apply appropriate reasoning strategies based on the type of question (factual, analytical, etc.)
- Self-reflection helps agents identify and correct errors in their reasoning.

### Evaluation Criteria
- Agent responses should be accurate, relevant, and factually correct.
- Effective agents provide concise yet comprehensive answers.
- Agents should acknowledge limitations and uncertainties when appropriate.
- Good agents can follow multi-step instructions and fulfill all requirements.
- Reasoning transparency helps users understand how the agent arrived at its conclusions.