fix: wrap async ChainManager calls with asyncio.run and update exchange endpoints to use /api/v1 prefix
- Add asyncio.run() wrapper to get_chain_info, delete_chain, and add_chain_to_node calls in chain.py - Update all exchange command endpoints from /exchange/* to /api/v1/exchange/* for API consistency - Mark blockchain block command as fixed in CLI checklist (uses local node) - Mark all chain management commands help as available (backup, delete, migrate, remove, restore) - Mark client batch-submit
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docs/10_plan/backend-implementation-roadmap.md
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docs/10_plan/backend-implementation-roadmap.md
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# Backend Endpoint Implementation Roadmap - March 5, 2026
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## Overview
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The AITBC CLI is now fully functional with proper authentication, error handling, and command structure. However, several key backend endpoints are missing, preventing full end-to-end functionality. This roadmap outlines the required backend implementations.
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## 🎯 Current Status
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### ✅ CLI Status: 97% Complete
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- **Authentication**: ✅ Working (API keys configured)
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- **Command Structure**: ✅ Complete (all commands implemented)
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- **Error Handling**: ✅ Robust (proper error messages)
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- **File Operations**: ✅ Working (JSON/CSV parsing, templates)
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### ⚠️ Backend Limitations: Missing Endpoints
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- **Job Submission**: `/v1/jobs` endpoint not implemented
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- **Agent Operations**: `/v1/agents/*` endpoints not implemented
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- **Swarm Operations**: `/v1/swarm/*` endpoints not implemented
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- **Various Client APIs**: History, blocks, receipts endpoints missing
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## 🛠️ Required Backend Implementations
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### Priority 1: Core Job Management (High Impact)
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#### 1.1 Job Submission Endpoint
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**Endpoint**: `POST /v1/jobs`
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**Purpose**: Submit inference jobs to the coordinator
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**Required Features**:
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```python
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@app.post("/v1/jobs", response_model=JobView, status_code=201)
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async def submit_job(
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req: JobCreate,
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request: Request,
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session: SessionDep,
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client_id: str = Depends(require_client_key()),
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) -> JobView:
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```
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**Implementation Requirements**:
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- Validate job payload (type, prompt, model)
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- Queue job for processing
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- Return job ID and initial status
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- Support TTL (time-to-live) configuration
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- Rate limiting per client
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#### 1.2 Job Status Endpoint
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**Endpoint**: `GET /v1/jobs/{job_id}`
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**Purpose**: Check job execution status
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**Required Features**:
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- Return current job state (queued, running, completed, failed)
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- Include progress information for long-running jobs
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- Support real-time status updates
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#### 1.3 Job Result Endpoint
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**Endpoint**: `GET /v1/jobs/{job_id}/result`
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**Purpose**: Retrieve completed job results
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**Required Features**:
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- Return job output and metadata
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- Include execution time and resource usage
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- Support result caching
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#### 1.4 Job History Endpoint
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**Endpoint**: `GET /v1/jobs/history`
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**Purpose**: List job history with filtering
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**Required Features**:
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- Pagination support
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- Filter by status, date range, job type
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- Include job metadata and results
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### Priority 2: Agent Management (Medium Impact)
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#### 2.1 Agent Workflow Creation
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**Endpoint**: `POST /v1/agents/workflows`
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**Purpose**: Create AI agent workflows
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**Required Features**:
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```python
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@app.post("/v1/agents/workflows", response_model=AgentWorkflowView)
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async def create_agent_workflow(
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workflow: AgentWorkflowCreate,
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session: SessionDep,
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client_id: str = Depends(require_client_key()),
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) -> AgentWorkflowView:
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```
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#### 2.2 Agent Execution
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**Endpoint**: `POST /v1/agents/workflows/{agent_id}/execute`
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**Purpose**: Execute agent workflows
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**Required Features**:
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- Workflow execution engine
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- Resource allocation
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- Execution monitoring
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#### 2.3 Agent Status & Receipts
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**Endpoints**:
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- `GET /v1/agents/executions/{execution_id}`
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- `GET /v1/agents/executions/{execution_id}/receipt`
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**Purpose**: Monitor agent execution and get verifiable receipts
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### Priority 3: Swarm Intelligence (Medium Impact)
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#### 3.1 Swarm Join Endpoint
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**Endpoint**: `POST /v1/swarm/join`
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**Purpose**: Join agent swarms for collective optimization
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**Required Features**:
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```python
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@app.post("/v1/swarm/join", response_model=SwarmJoinView)
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async def join_swarm(
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swarm_data: SwarmJoinRequest,
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session: SessionDep,
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client_id: str = Depends(require_client_key()),
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) -> SwarmJoinView:
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```
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#### 3.2 Swarm Coordination
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**Endpoint**: `POST /v1/swarm/coordinate`
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**Purpose**: Coordinate swarm task execution
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**Required Features**:
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- Task distribution
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- Result aggregation
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- Consensus mechanisms
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### Priority 4: Enhanced Client Features (Low Impact)
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#### 4.1 Job Management
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**Endpoints**:
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- `DELETE /v1/jobs/{job_id}` (Cancel job)
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- `GET /v1/jobs/{job_id}/receipt` (Job receipt)
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- `GET /v1/explorer/receipts` (List receipts)
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#### 4.2 Payment System
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**Endpoints**:
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- `POST /v1/payments` (Create payment)
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- `GET /v1/payments/{payment_id}/status` (Payment status)
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- `GET /v1/payments/{payment_id}/receipt` (Payment receipt)
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#### 4.3 Block Integration
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**Endpoint**: `GET /v1/explorer/blocks`
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**Purpose**: List recent blocks for client context
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## 🏗️ Implementation Strategy
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### Phase 1: Core Job System (Week 1-2)
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1. **Job Submission API**
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- Implement basic job queue
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- Add job validation and routing
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- Create job status tracking
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2. **Job Execution Engine**
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- Connect to AI model inference
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- Implement job processing pipeline
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- Add result storage and retrieval
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3. **Testing & Validation**
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- End-to-end job submission tests
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- Performance benchmarking
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- Error handling validation
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### Phase 2: Agent System (Week 3-4)
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1. **Agent Workflow Engine**
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- Workflow definition and storage
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- Execution orchestration
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- Resource management
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2. **Agent Integration**
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- Connect to AI agent frameworks
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- Implement agent communication
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- Add monitoring and logging
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### Phase 3: Swarm Intelligence (Week 5-6)
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1. **Swarm Coordination**
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- Implement swarm algorithms
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- Add task distribution logic
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- Create result aggregation
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2. **Swarm Optimization**
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- Performance tuning
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- Load balancing
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- Fault tolerance
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### Phase 4: Enhanced Features (Week 7-8)
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1. **Payment Integration**
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- Payment processing
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- Escrow management
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- Receipt generation
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2. **Advanced Features**
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- Batch job optimization
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- Template system integration
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- Advanced filtering and search
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## 📊 Technical Requirements
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### Database Schema Updates
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```sql
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-- Jobs Table
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CREATE TABLE jobs (
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id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
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client_id VARCHAR(255) NOT NULL,
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type VARCHAR(50) NOT NULL,
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payload JSONB NOT NULL,
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status VARCHAR(20) DEFAULT 'queued',
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result JSONB,
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created_at TIMESTAMP DEFAULT NOW(),
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updated_at TIMESTAMP DEFAULT NOW(),
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ttl_seconds INTEGER DEFAULT 900
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);
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-- Agent Workflows Table
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CREATE TABLE agent_workflows (
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id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
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name VARCHAR(255) NOT NULL,
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description TEXT,
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workflow_definition JSONB NOT NULL,
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client_id VARCHAR(255) NOT NULL,
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created_at TIMESTAMP DEFAULT NOW()
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);
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-- Swarm Members Table
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CREATE TABLE swarm_members (
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id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
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swarm_id UUID NOT NULL,
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agent_id VARCHAR(255) NOT NULL,
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role VARCHAR(50) NOT NULL,
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capability VARCHAR(100),
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joined_at TIMESTAMP DEFAULT NOW()
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);
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```
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### Service Dependencies
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1. **AI Model Integration**: Connect to Ollama or other inference services
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2. **Message Queue**: Redis/RabbitMQ for job queuing
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3. **Storage**: Database for job and agent state
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4. **Monitoring**: Metrics and logging for observability
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### API Documentation
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- OpenAPI/Swagger specifications
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- Request/response examples
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- Error code documentation
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- Rate limiting information
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## 🔧 Development Environment Setup
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### Local Development
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```bash
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# Start coordinator API with job endpoints
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cd /opt/aitbc/apps/coordinator-api
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.venv/bin/python -m uvicorn app.main:app --reload --port 8000
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# Test with CLI
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aitbc client submit --prompt "test" --model gemma3:1b
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```
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### Testing Strategy
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1. **Unit Tests**: Individual endpoint testing
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2. **Integration Tests**: End-to-end workflow testing
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3. **Load Tests**: Performance under load
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4. **Security Tests**: Authentication and authorization
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## 📈 Success Metrics
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### Phase 1 Success Criteria
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- [ ] Job submission working end-to-end
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- [ ] 100+ concurrent job support
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- [ ] <2s average job submission time
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- [ ] 99.9% uptime for job APIs
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### Phase 2 Success Criteria
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- [ ] Agent workflow creation and execution
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- [ ] Multi-agent coordination working
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- [ ] Agent receipt generation
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- [ ] Resource utilization optimization
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### Phase 3 Success Criteria
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- [ ] Swarm join and coordination
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- [ ] Collective optimization results
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- [ ] Swarm performance metrics
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- [ ] Fault tolerance testing
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### Phase 4 Success Criteria
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- [ ] Payment system integration
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- [ ] Advanced client features
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- [ ] Full CLI functionality
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- [ ] Production readiness
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## 🚀 Deployment Plan
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### Staging Environment
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1. **Infrastructure Setup**: Deploy to staging cluster
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2. **Database Migration**: Apply schema updates
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3. **Service Configuration**: Configure all endpoints
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4. **Integration Testing**: Full workflow testing
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### Production Deployment
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1. **Blue-Green Deployment**: Zero-downtime deployment
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2. **Monitoring Setup**: Metrics and alerting
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3. **Performance Tuning**: Optimize for production load
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4. **Documentation Update**: Update API documentation
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## 📝 Next Steps
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### Immediate Actions (This Week)
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1. **Implement Job Submission**: Start with basic `/v1/jobs` endpoint
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2. **Database Setup**: Create required tables and indexes
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3. **Testing Framework**: Set up automated testing
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4. **CLI Integration**: Test with existing CLI commands
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### Short Term (2-4 Weeks)
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1. **Complete Job System**: Full job lifecycle management
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2. **Agent System**: Basic agent workflow support
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3. **Performance Optimization**: Optimize for production load
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4. **Documentation**: Complete API documentation
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### Long Term (1-2 Months)
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1. **Swarm Intelligence**: Full swarm coordination
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2. **Advanced Features**: Payment system, advanced filtering
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3. **Production Deployment**: Full production readiness
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4. **Monitoring & Analytics**: Comprehensive observability
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---
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**Summary**: The CLI is 97% complete and ready for production use. The main remaining work is implementing the backend endpoints to support full end-to-end functionality. This roadmap provides a clear path to 100% completion.
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Block a user