VectorDBCrypto Research Agent
Input
Output
Agent
Crypto Research Agent
Input fields
Average Time
This agent transforms input queries into structured vector representations for efficient retrieval in a Vector Database. It processes data through sequential stages: Embedding Generation → Semantic Summarization → Relevance Filtering Each stage refines the query to ensure accurate vector searches, enhancing retrieval quality.
Best Use Cases
Ideal for routing queries to specialized agents based on their type and context
Inputs
Content to Process
Example: What is the current price of Bitcoin?
Output
Structured vector representation