chat2graph

chat2graph copied to clipboard

feat(agent): implement agentic text-to-GQL system with multi-stage wo…

1

…rkflow https://github.com/TuGraph-family/chat2graph/issues/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...

SeasonPilot

feat(dal): implement persistence for Agent instances in database (#40…

3

…) #232 ## Summary Implement database persistence for Agent instances (both Leader and Expert) to resolve issue #40. ## Changes ### New Files - `app/core/dal/do/agent_do.py`: Agent configuration data model with...

SeasonPilot

feat(workflow): support pre-defined workflow agent

1

qishipengqsp

## Background Implementing a logging system for Multi-Agent LLM interactions to ensure observability and debugging capabilities. ## Key Requirements 1. Agent Communication Logging - Track inter-agent message exchanges - Log...

Appointat

# Description Currently, agent instances (both leader and experts) are not persisted in the database. As noted in the TODO comment in agent.py, we need to implement proper persistence for...

Appointat

**Context:** Google Cloud recently announced the Agent2Agent (A2A) protocol on April 9, 2025. As described in their announcement ([link](https://developers.googleblog.com/en/a2a-a-new-era-of-agent-interoperability/)), A2A is a new, open protocol designed to allow AI agents...

Appointat

qishipengqsp

benchmark oriented

qishipengqsp

qishipengqsp

As a accuracy-orientted task, it can be implemented with an automated workflow or a pre-defined workflow.

qishipengqsp