feat(rag_platform): U1 — RAG platform skeleton + LlamaIndex integration
Create src/agentkit/rag_platform/ module with:
- models.py: Pydantic domain models (KB, Document, Chunk, QueryResult)
- indexing.py: PGVectorStore wrapper with explicit table name
(rag_platform_kb_chunks) for schema isolation from episodic_memory
- pipeline.py: RAGPipeline wrapping LlamaIndex IngestionPipeline
(SentenceSplitter + embedding + vector store)
Add dependencies: llama-index-core, llama-index-vector-stores-postgres,
llama-index-embeddings-openai, pgvector, jieba.
Tests: 14 unit tests covering models, indexing (URL conversion, table
name isolation, embed_dim), and pipeline (ingest, query, chunk params).
27d0184392