feat(agent): implement agentic Text2GQL system with multi-stage workflow

[SeasonPilot]

Summary

#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.

[SeasonPilot]

#231

[qishipengqsp]

Remove the Chinese comments and file headers, aligning to the project

[Copilot]

Pull request overview

This pull request implements a comprehensive agentic text-to-GQL (Graph Query Language) system with multi-stage workflow capabilities. The implementation includes a complete testing suite covering both unit and integration tests for the DAL layer, service layer, operators, and workflow orchestration.

Changes:

• Added comprehensive test coverage for QueryContextService with session, context, and history management tests (707 lines)
• Added unit tests for context management tools (ContextRetriever, PreferenceLearner, QuerySuggester) with 648 lines
• Added extensive DAL layer tests covering 4 DAO classes with full CRUD operations and edge cases
• Added integration tests for operators (QueryValidation, QueryDesign, QueryComplexityAnalysis) and workflow orchestration
• Added workflow integration tests for simple queries, error recovery, complex queries, and tool collaboration
• Created conftest.py with shared fixtures for integration tests

Reviewed changes

Copilot reviewed 38 out of 44 changed files in this pull request and generated 71 comments.

Show a summary per file

File	Description
test/unit/core/service/test_query_context_service.py	Comprehensive unit tests for QueryContextService covering session management, context operations, and statistics
test/unit/core/service/test_context_tools.py	Unit tests for context tools (ContextRetriever, PreferenceLearner, QuerySuggester) with mocked service
test/unit/core/dal/test_query_session_dao.py	Unit tests for QuerySessionDao CRUD operations and edge cases
test/unit/core/dal/test_query_pattern_dao.py	Unit tests for QueryPatternDao with pattern matching and statistics
test/unit/core/dal/test_query_history_dao.py	Unit tests for QueryHistoryDao with query tracking and statistics
test/unit/core/dal/test_query_feedback_dao.py	Unit tests for QueryFeedbackDao with feedback aggregation
test/integration/workflow/*.py	Integration tests for simple queries, error recovery, and complex workflows
test/integration/orchestration/*.py	Integration tests for tool and operator collaboration patterns
test/integration/operator/*.py	Integration tests for validation, design, and complexity analysis operators
test/integration/conftest.py	Shared pytest configuration and fixtures for integration tests
app/plugin/tugraph/operator/init.py	Module initialization for TuGraph operators

---

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.