DataLens Master Implementation Plan

The plan outlines Epics for DS-STAR intelligence, Text-to-SQL, Document RAG, and DataLens Skill, detailing components like extraction, GPU infrastructure, and AI models such as Qwen2.5-Coder-14B-AWQ, with integration of Qdrant, DuckDB, and LlamaIndex, for autonomous data analysis and system orchestration. The DataLens DS-STAR Implementation Plan includes the Planner component for creating extraction plans. The plan includes Extractor Agents to extract and structure various data types. The plan includes a Verifier agent to check data quality after extraction. Router agent manages fixes and extensions to the extraction plan. The implementation uses DuckDB as a unified database for storing extracted data. After SQL execution, results are visualized as part of the pipeline. RAGAgent optionally searches unstructured text in the data analysis process. The plan uses vLLM for large language model inference on elin GPU. The implementation requires Python environment setup with all dependencies.