feat: Add intelligent auto-router and enhanced integrations
- Add intelligent-router.sh hook for automatic agent routing - Add AUTO-TRIGGER-SUMMARY.md documentation - Add FINAL-INTEGRATION-SUMMARY.md documentation - Complete Prometheus integration (6 commands + 4 tools) - Complete Dexto integration (12 commands + 5 tools) - Enhanced Ralph with access to all agents - Fix /clawd command (removed disable-model-invocation) - Update hooks.json to v5 with intelligent routing - 291 total skills now available - All 21 commands with automatic routing 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
admin
180
prometheus/docs/Multi-Agent-Architecture.md
Normal file
180
prometheus/docs/Multi-Agent-Architecture.md
Normal file
@@ -0,0 +1,180 @@
|
||||
# Multi-Agent Architecture
|
||||
|
||||
Prometheus uses a multi-agent system powered by LangGraph to intelligently process and resolve GitHub issues. Each agent is specialized for a specific task in the issue resolution pipeline.
|
||||
|
||||
## Agent Overview
|
||||
|
||||
### 1. Issue Classification Agent
|
||||
|
||||
**Purpose**: Automatically classifies GitHub issues into categories (bug, question, feature, documentation).
|
||||
|
||||
**Location**: `prometheus/lang_graph/subgraphs/issue_classification_subgraph.py`
|
||||
|
||||
**Workflow**:
|
||||
- Retrieves relevant code context from the knowledge graph
|
||||
- Uses LLM to analyze issue content and classify type
|
||||
- Returns issue type for routing to appropriate handler
|
||||
|
||||
**When Used**: When `issue_type == "auto"` in the issue request
|
||||
|
||||
---
|
||||
|
||||
### 2. Environment Build Agent
|
||||
|
||||
**Status**: In Progress
|
||||
|
||||
**Purpose**: Automatically sets up and configures the development environment for testing and building.
|
||||
|
||||
**Planned Features**:
|
||||
- Auto-detect project type (Python, Node.js, Java, etc.)
|
||||
- Install dependencies
|
||||
- Configure build tools
|
||||
- Validate environment setup
|
||||
|
||||
---
|
||||
|
||||
### 3. Bug Reproduction Agent
|
||||
|
||||
**Purpose**: Attempts to reproduce reported bugs by writing and executing reproduction tests.
|
||||
|
||||
**Location**: `prometheus/lang_graph/subgraphs/bug_reproduction_subgraph.py`
|
||||
|
||||
**Workflow**:
|
||||
1. Retrieves bug-related code context from knowledge graph
|
||||
2. Generates reproduction test code using LLM
|
||||
3. Edits necessary files to create the test
|
||||
4. Executes the test in a Docker container
|
||||
5. Evaluates whether the bug was successfully reproduced
|
||||
6. Retries with feedback if reproduction fails
|
||||
|
||||
**Output**:
|
||||
- `reproduced_bug`: Boolean indicating success
|
||||
- `reproduced_bug_file`: Path to reproduction test
|
||||
- `reproduced_bug_commands`: Commands to reproduce
|
||||
- `reproduced_bug_patch`: Git patch with changes
|
||||
|
||||
**Key Features**:
|
||||
- Iterative refinement with retry loops
|
||||
- Docker-isolated execution
|
||||
- Feedback-driven improvement
|
||||
|
||||
---
|
||||
|
||||
### 4. Context Retrieval Agent
|
||||
|
||||
**Purpose**: Retrieves relevant code and documentation context from the Neo4j knowledge graph.
|
||||
|
||||
**Location**: `prometheus/lang_graph/subgraphs/context_retrieval_subgraph.py`
|
||||
|
||||
**Workflow**:
|
||||
1. Converts natural language query to knowledge graph query
|
||||
2. Uses LLM with graph traversal tools to find relevant context
|
||||
3. Selects and extracts useful code snippets
|
||||
4. Optionally refines query and retries if context is insufficient
|
||||
5. Returns structured context (code, AST nodes, documentation)
|
||||
|
||||
**Key Features**:
|
||||
- Iterative query refinement (2-4 loops)
|
||||
- Tool-augmented LLM with Neo4j access
|
||||
- Traverses file hierarchy, AST structure, and text chunks
|
||||
|
||||
**Used By**: All other agents for context gathering
|
||||
|
||||
---
|
||||
|
||||
### 5. Issue Resolution Agent
|
||||
|
||||
**Purpose**: Generates and validates bug fix patches for verified bugs.
|
||||
|
||||
**Location**: `prometheus/lang_graph/subgraphs/issue_verified_bug_subgraph.py`
|
||||
|
||||
**Workflow**:
|
||||
1. Retrieves fix-relevant code context
|
||||
2. Analyzes bug root cause using LLM
|
||||
3. Generates code patch to fix the bug
|
||||
4. Applies patch and creates git diff
|
||||
5. Validates patch against:
|
||||
- Reproduction test (must pass)
|
||||
- Regression tests (optional)
|
||||
- Existing test suite (optional)
|
||||
6. Generates multiple candidate patches
|
||||
7. Selects best patch based on test results
|
||||
8. Retries with error feedback if tests fail
|
||||
|
||||
**Output**:
|
||||
- `edit_patch`: Final selected fix patch
|
||||
- Test pass/fail results
|
||||
|
||||
**Key Features**:
|
||||
- Multi-candidate patch generation
|
||||
- Multi-level validation (reproduction, regression, existing tests)
|
||||
- Feedback-driven iteration
|
||||
- Best patch selection using LLM
|
||||
|
||||
---
|
||||
|
||||
## Agent Coordination
|
||||
|
||||
### Main Issue Processing Flow
|
||||
|
||||
```
|
||||
User Issue -> Issue Classification Agent
|
||||
|
|
||||
[Route by issue type]
|
||||
|
|
||||
+-----+-----+
|
||||
| |
|
||||
BUG QUESTION
|
||||
| |
|
||||
v v
|
||||
Bug Pipeline Question Pipeline
|
||||
```
|
||||
|
||||
### Bug Resolution Pipeline
|
||||
|
||||
```
|
||||
Bug Issue -> Context Retrieval Agent (select regression tests)
|
||||
-> Bug Reproduction Agent (verify bug exists)
|
||||
-> [If reproduced] -> Issue Resolution Agent (generate fix)
|
||||
-> [If not reproduced] -> Direct resolution without reproduction
|
||||
-> Response Generation
|
||||
```
|
||||
|
||||
### Question Answering Pipeline
|
||||
|
||||
```
|
||||
Question -> Context Retrieval Agent (gather relevant code/docs)
|
||||
-> Question Analysis Agent (LLM with tools)
|
||||
-> Response Generation
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Agent Communication
|
||||
|
||||
Agents communicate through **shared state** managed by LangGraph:
|
||||
|
||||
- Each subgraph has a typed state dictionary
|
||||
- State flows through nodes and is updated progressively
|
||||
- Parent states are inherited by child subgraphs
|
||||
- Results are passed back through state returns
|
||||
|
||||
---
|
||||
|
||||
## Technology Stack
|
||||
|
||||
- **LangGraph**: State machine orchestration
|
||||
- **LangChain**: LLM integration and tool calling
|
||||
- **Neo4j**: Knowledge graph storage and retrieval
|
||||
- **Docker**: Isolated test execution environment
|
||||
- **Tree-sitter**: Code parsing and AST generation
|
||||
- **Git**: Patch management and version control
|
||||
|
||||
---
|
||||
|
||||
## Future Enhancements
|
||||
|
||||
- **Environment Build Agent**: Complete implementation for automatic setup
|
||||
- **Pull Request Review Agent**: Automated code review
|
||||
- **Feature Implementation Agent**: Handle feature requests
|
||||
- **Documentation Generation Agent**: Auto-generate docs from code
|
||||
Reference in New Issue
Block a user