Dotando a IAs con: V1 Enrich Legal (ETL-D API)
CONTENT: The Hallucination Problem: Large Language Models (LLMs) often face the challenge of 'hallucination,' where they generate plausible-sounding but incorrect or nonsensical answers. This is ma...
Source: DEV Community
CONTENT: The Hallucination Problem: Large Language Models (LLMs) often face the challenge of 'hallucination,' where they generate plausible-sounding but incorrect or nonsensical answers. This is mainly due to their probabilistic nature, which can lead to guessing when precise data validation is needed. The given ETL-D endpoint /v1/enrich/legal serves as a crucial tool for LLMs in domains requiring exact validation, such as legal or financial data processing. By integrating this endpoint, the LLM can deterministically validate Tax Identification Numbers and IBANs, preventing the generation of incorrect information and ensuring compliance with financial regulations. Agent Tool Architecture: In an LLM Agent setup, the endpoint acts as a deterministic middleware, allowing the agent to offload specific validation tasks to a robust external service. This separation ensures the agent uses verified data for decision-making processes. The architecture involves the LLM acting as an orchestrator
