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@SeasonPilot SeasonPilot commented Nov 26, 2025

…rkflow

#231

Implement comprehensive agentic text-to-graph query language system with context awareness, multi-stage validation, and self-optimization capabilities.

Core Components:

  • DAL Layer: Query session, history, pattern, and feedback management (8 files)
  • Service Layer: Context tools and query context service (2 files)
  • Operators: 6 specialized operators for query lifecycle management
    • Query intention analysis and validation
    • Complexity analysis with index recommendations
    • Path pattern recognition (multi-hop, temporal, spatial)
    • Comprehensive query validation (schema, semantic, performance, security)
    • Context enhancement with user preference learning
    • Query design with optimization strategies
  • Resources: Multi-hop reasoning, query planning, and validation (3 files)
  • Workflow: Complete agentic text2gql configuration with 7-stage pipeline
  • Testing: Comprehensive test suite (22 files: unit + integration)
    • Unit tests for DAOs and services
    • Integration tests for operator collaboration and workflows

Key Features:

  • Multi-stage workflow: understand → analyze → enhance → design → validate → execute
  • Context-aware query optimization with historical pattern learning
  • Real-time validation (schema, semantic, performance, security)
  • Support for complex patterns: multi-hop, temporal, spatial queries
  • Self-validating agentic workflow with feedback loops

Title

Type

  • feat: (new feature)
  • fix: (bug fix)
  • docs: (doc update)
  • style: (update format)
  • refactor: (refactor code)
  • test: (test code)
  • chore: (other updates)

Scope

  • app: (Application Layer)
    • web: (web front-end module)
    • server: (web server module)
    • dal: (data access layer)
    • sdk: (sdk module)
  • agent: (Agent Layer)
    • reasoner: (reasoner module)
    • planner: (planner module)
    • workflow: (workflow module)
    • memory: (memory module)
    • knowledge: (knowledge module)
    • env: (env module)
    • toolkit: (toolkit module)
  • system: (System Layer)
    • plugin: (plugin module)
    • tracer: (tracer module)
    • resource: (resource module)
  • none: (N/A)

Description

Issue: #

Checklist

  • I have prepared the pull request title according to the requirements.
  • I have successfully run all unit tests and integration tests.
  • I have followed the code style guidelines of this project.
  • I have already rebased the latest master branch.
  • I have commented my code, particularly in hard-to-understand areas.
  • I have made corresponding changes to the documentation.

…rkflow

Implement comprehensive agentic text-to-graph query language system with
context awareness, multi-stage validation, and self-optimization capabilities.

Core Components:
- DAL Layer: Query session, history, pattern, and feedback management (8 files)
- Service Layer: Context tools and query context service (2 files)
- Operators: 6 specialized operators for query lifecycle management
  * Query intention analysis and validation
  * Complexity analysis with index recommendations
  * Path pattern recognition (multi-hop, temporal, spatial)
  * Comprehensive query validation (schema, semantic, performance, security)
  * Context enhancement with user preference learning
  * Query design with optimization strategies
- Resources: Multi-hop reasoning, query planning, and validation (3 files)
- Workflow: Complete agentic text2gql configuration with 7-stage pipeline
- Testing: Comprehensive test suite (22 files: unit + integration)
  * Unit tests for DAOs and services
  * Integration tests for operator collaboration and workflows

Key Features:
- Multi-stage workflow: understand → analyze → enhance → design → validate → execute
- Context-aware query optimization with historical pattern learning
- Real-time validation (schema, semantic, performance, security)
- Support for complex patterns: multi-hop, temporal, spatial queries
- Self-validating agentic workflow with feedback loops
@SeasonPilot
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#231

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