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Changelog

All notable changes to the pgEdge RAG Server will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[1.0.0-alpha5] - 2025-12-03

Fixed

  • Fixed filter parameter indexing bug where API filters would cause "operator does not exist: text = vector" errors. The filter clause was generating SQL placeholders starting at $1, but VectorSearch already uses $1 for the vector and $2 for LIMIT.

[1.0.0-alpha4] - 2025-12-03

Breaking Changes

  • Security Fix: API filter parameters now require structured filter format to eliminate SQL injection vulnerabilities. API filters must use conditions, operators, and values (parameterized queries prevent injection).

  • Config Rename: The column_pairs field in pipeline configuration has been renamed to tables for clarity. The internal type ColumnPair is now TableSource.

Changed

  • Filter system now uses parameterized queries for API request filters
  • API filter parameter changed from string to structured object
  • Config filter field now accepts either raw SQL strings (for complex queries like subqueries) or structured filter objects

Added

  • Config filters support raw SQL strings for complex expressions (subqueries, JOINs, functions) that cannot be expressed with structured format. Since config files are admin-controlled, raw SQL is safe here.

Migration Guide

API filters (JSON) - must use structured format:

Old (removed):

{"filter": "product = 'pgAdmin'"}

New:

{
  "filter": {
    "conditions": [
      {"column": "product", "operator": "=", "value": "pgAdmin"}
    ]
  }
}

Config filters (YAML) - both formats supported:

Raw SQL (for complex queries):

filter: "source_id IN (SELECT id FROM sources WHERE product='pgEdge')"

Structured:

filter:
  conditions:
    - column: "product"
      operator: "="
      value: "pgAdmin"
    - column: "status"
      operator: "="
      value: "published"
  logic: "AND"

Supported operators (for structured filters): =, !=, <, >, <=, >=, LIKE, ILIKE, IN, NOT IN, IS NULL, IS NOT NULL

Config field rename:

Old:

column_pairs:
  - table: "documents"
    text_column: "content"
    vector_column: "embedding"

New:

tables:
  - table: "documents"
    text_column: "content"
    vector_column: "embedding"

[1.0.0-alpha3] - 2025-12-01

Added

  • GitHub Actions workflow to generate builds when repository is tagged, producing binaries for multiple platforms (linux/amd64, linux/arm64, darwin/amd64, darwin/arm64).

[1.0.0-alpha2] - 2025-12-01

Added

  • Per-pipeline LLM configuration: Pipelines can override embedding_llm and rag_llm settings, allowing different pipelines to use different providers or models.

  • Per-pipeline API keys: API keys can be configured at three levels with cascade priority (pipeline > defaults > global), enabling different pipelines to use separate API keys or accounts.

  • SQL filter support: Tables can include a filter field with a SQL WHERE clause fragment applied to all queries. Filters can also be specified per-request via the API.

  • Extended defaults section: The defaults configuration now supports embedding_llm, rag_llm, and api_keys in addition to token_budget and top_n.

[1.0.0-alpha1] - 2025-11-28

Added

  • Initial RAG server implementation with REST API
  • Multiple pipeline support for different data sources
  • Hybrid search combining vector similarity (pgvector) and BM25 text matching
  • Reciprocal Rank Fusion (RRF) for combining search results

  • Support for multiple LLM providers:

    • OpenAI (embeddings and completions)
    • Anthropic (completions)
    • Voyage AI (embeddings)
    • Ollama (embeddings and completions)

  • Token budget management to control LLM costs

  • Streaming responses via Server-Sent Events (SSE)
  • TLS/HTTPS support for production deployments
  • OpenAPI v3 specification with RFC 8631 Link headers
  • Flexible API key configuration (files, environment variables, defaults)
  • Comprehensive test coverage for core modules