sql-rl-gen
The SQL-RL-GEN is an algorithm based on a Reinforcement Learning approach with a reward function generated by a LLM to guide the agent's training process in solving the specific text2SQL generation task.
Large Language Models (LLMs) have revolutionized text and code generation tasks, but the text-to-SQL (text2SQL) problem still remains challenging. Current state-of-the-art models require extensive preprocessing steps to achieve accurate SQL query generation, which can be data-hungry and time-consuming. We introduce a Reinforcement Learning-based approach that improves text2SQL generation while minimizing resources and maximizing flexibility.
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Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/ibm-sql-rl-gen — read its card at https://meshkore.com/agent/ibm-sql-rl-gen/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/ibm-sql-rl-genFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/ibm-sql-rl-gen/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
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