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bd91486 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 | # COGENBAI Integration Guide
## Component Integration Map
### 1. Core Components
```
cogenbai/core/
├── model.py # Main AI model (CogenBAI class)
└── config.py # Configuration management
```
- `model.py` is the central component that integrates with all other modules
- `config.py` provides configuration management used across all components
### 2. API Layer Integration
```
cogenbai/api/
├── server.py # FastAPI server
└── middleware.py # Request logging and auth
```
- `server.py` exposes core functionality via REST API
- Connects to core model, language generator, and collaboration features
### 3. Language Support Integration
```
cogenbai/languages/
└── generator.py # Language-specific code generation
```
- Used by core model for language-specific code generation
- Integrates with templates and modern frameworks
### 4. Collaboration Features
```
cogenbai/collaboration/
├── session.py # Session management
└── websocket.py # Real-time collaboration
```
- WebSocket server handles real-time code synchronization
- Session manager tracks active collaboration sessions
### 5. Development Tools
```
cogenbai/
├── debug/ # Code analysis
├── review/ # Code review
└── testing/ # Test generation
```
- All tools integrate with core model via API endpoints
- Share common configuration and language support
## Integration Flow
1. **Startup Sequence**
```python
from cogenbai import CogenBAI, CogenConfig
# Load configuration
config = CogenConfig.load('config.yaml')
# Initialize core model
model = CogenBAI(config)
# Start API server
from cogenbai.api.server import app
import uvicorn
uvicorn.run(app)
```
2. **Code Generation Flow**
```python
# 1. Request comes through API
@app.post("/generate")
async def generate_code(request: CodeRequest):
# 2. Core model handles request
code = model.generate_code(
prompt=request.prompt,
language=request.language
)
# 3. Language generator processes code
from cogenbai.languages.generator import LanguageGenerator
lang_generator = LanguageGenerator()
formatted_code = lang_generator.format(code, request.language)
return {"code": formatted_code}
```
3. **Collaboration Flow**
```python
# 1. WebSocket connection established
@app.websocket("/ws/{session_id}")
async def websocket_endpoint(websocket: WebSocket, session_id: str):
# 2. Session manager handles connection
await session_manager.connect(session_id, websocket)
# 3. Real-time updates broadcast to all participants
await collaboration_manager.broadcast(
session_id,
{"type": "update", "data": code_update}
)
```
## File Paths and Dependencies
All components are installed under the main package:
```
/c:/Users/shahrear/Downloads/cogenbai/
├── cogenbai/ # Main package directory
├── tests/ # Test files
├── Modelfile # Ollama model definition
├── BUILD.md # Build instructions
└── INTEGRATION.md # This file
```
## Configuration Integration
The `config.py` file integrates all components through shared settings:
```yaml
model:
name: codegen-16B-multi
device: cuda
languages:
default: python
supported: [python, javascript, ...]
collaboration:
max_sessions: 100
timeout: 3600
api:
host: 0.0.0.0
port: 8000
```
## Testing Integration
Run integrated tests:
```bash
pytest tests/integration/
```
## Monitoring Integration
All components emit metrics:
```python
from cogenbai.monitoring import metrics
# Track model performance
metrics.track_generation_time(duration)
# Monitor API requests
metrics.track_api_request(endpoint, status)
# Log collaboration events
metrics.track_collaboration_session(session_id)
```
## Security Integration
Components share common security features:
- API authentication
- Session validation
- Rate limiting
- Input sanitization
## Production Integration Steps
1. Build the model:
```bash
ollama create cogenbai -f Modelfile
```
2. Start all components:
```bash
# Start API server
uvicorn cogenbai.api.server:app
# Start collaboration server
python -m cogenbai.collaboration.server
# Start monitoring
docker-compose up -d prometheus grafana
```
3. Verify integration:
```bash
curl http://localhost:8000/health
```
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