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integration_guide
Garot Conklin edited this page Jun 1, 2025
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Complete guide to integrating ContractAI with your systems and services
This guide provides comprehensive instructions for integrating ContractAI with your existing infrastructure, applications, and services. It covers API integration, third-party service connections, and best practices for building robust integrations.
graph TD
A[Integration Layer] --> B[API Gateway]
A --> C[Event Bus]
A --> D[Message Queue]
B --> B1[REST API]
B --> B2[GraphQL]
B --> B3[WebSocket]
C --> C1[Events]
C --> C2[Notifications]
C --> C3[Webhooks]
D --> D1[Tasks]
D --> D2[Commands]
D --> D3[Updates]
graph TD
A[Your System] --> B[Integration Methods]
B --> C[Direct API]
B --> D[Event-Based]
B --> E[Message-Based]
C --> C1[REST]
C --> C2[GraphQL]
C --> C3[gRPC]
D --> D1[Webhooks]
D --> D2[Pub/Sub]
D --> D3[Streaming]
E --> E1[Queue]
E --> E2[Topics]
E --> E3[Streams]
sequenceDiagram
participant S as System
participant I as Integration
participant C as ContractAI
participant D as Data Store
S->>I: Send Data
I->>C: Transform & Forward
C->>D: Store
D->>C: Confirm
C->>I: Process
I->>S: Update Status
# Integration Options
integration_methods:
- name: "REST API"
use_case: "Direct system integration"
features:
- CRUD operations
- Real-time updates
- Webhook support
- name: "SDK"
use_case: "Application development"
features:
- Type-safe operations
- Simplified authentication
- Built-in retry logic
- name: "Webhooks"
use_case: "Event-driven integration"
features:
- Real-time notifications
- Custom event handling
- Retry mechanisms
- name: "Message Queue"
use_case: "Asynchronous processing"
features:
- Reliable delivery
- High throughput
- Message persistence
graph TD
A[Your System] -->|REST API| B[ContractAI API Gateway]
A -->|SDK| B
B -->|Webhooks| A
B -->|Message Queue| C[Event Processor]
C -->|Processed Events| A
B -->|Database| D[(Knowledge Base)]
B -->|Cache| E[(Redis Cache)]
- Python 3.12 or later
- Network access to ContractAI services
- Valid API credentials
- Minimum 1GB RAM for SDK
- Stable internet connection
- TLS 1.3 for all connections
- API key or OAuth 2.0 credentials
- IP allowlisting (optional)
- MFA for admin operations
sequenceDiagram
participant C as Client
participant A as Auth
participant G as Gateway
participant S as Service
C->>A: Request Token
A->>C: Return Token
C->>G: API Request + Token
G->>A: Validate Token
A->>G: Token Valid
G->>S: Process Request
S->>C: Return Response
graph TD
A[API Request] --> B[Authentication]
A --> C[Validation]
A --> D[Processing]
B --> B1[Token Check]
B --> B2[Permission]
B --> B3[Rate Limit]
C --> C1[Input]
C --> C2[Schema]
C --> C3[Business Rules]
D --> D1[Execute]
D --> D2[Transform]
D --> D3[Response]
# Using API Key
import requests
from contractai import ContractAIClient
# Initialize client
client = ContractAIClient(
api_key="your_api_key",
environment="production"
)
# Make authenticated request
response = client.agents.list()
# Using OAuth 2.0
from contractai import ContractAIClient
from oauthlib.oauth2 import BackendApplicationClient
# Initialize OAuth client
oauth_client = BackendApplicationClient(
client_id="your_client_id"
)
# Initialize ContractAI client
client = ContractAIClient(
oauth_client=oauth_client,
environment="production"
)
# Authenticate and make request
client.authenticate()
response = client.agents.list()
# Agent Operations
from contractai import ContractAIClient
client = ContractAIClient(api_key="your_api_key")
# Create agent
agent = client.agents.create(
name="production-monitor",
capabilities=["monitoring", "cost-optimization"]
)
# Get agent status
status = client.agents.get_status(agent_id=agent.id)
# Update agent
client.agents.update(
agent_id=agent.id,
capabilities=["monitoring", "cost-optimization", "security-scanning"]
)
# Delete agent
client.agents.delete(agent_id=agent.id)
# Knowledge Base Operations
from contractai import ContractAIClient
client = ContractAIClient(api_key="your_api_key")
# Add document
document = client.knowledge.add_document(
content="System architecture documentation",
category="architecture",
tags=["system", "design"]
)
# Query knowledge base
results = client.knowledge.query(
query="How to handle high CPU usage?",
context={"environment": "production"}
)
# Update document
client.knowledge.update_document(
document_id=document.id,
content="Updated system architecture",
version="2.0"
)
# Webhook Configuration
from contractai import ContractAIClient
client = ContractAIClient(api_key="your_api_key")
# Register webhook
webhook = client.webhooks.create(
url="https://your-system.com/webhooks/contractai",
events=["agent.status_change", "incident.created"],
secret="your_webhook_secret"
)
# Verify webhook
client.webhooks.verify(webhook_id=webhook.id)
# List webhooks
webhooks = client.webhooks.list()
# FastAPI Webhook Handler
from fastapi import FastAPI, Request, HTTPException
import hmac
import hashlib
app = FastAPI()
@app.post("/webhooks/contractai")
async def handle_webhook(request: Request):
# Verify webhook signature
signature = request.headers.get("X-ContractAI-Signature")
payload = await request.body()
expected_signature = hmac.new(
"your_webhook_secret".encode(),
payload,
hashlib.sha256
).hexdigest()
if not hmac.compare_digest(signature, expected_signature):
raise HTTPException(status_code=401, detail="Invalid signature")
# Process webhook
data = await request.json()
event_type = data["event_type"]
if event_type == "agent.status_change":
handle_agent_status_change(data)
elif event_type == "incident.created":
handle_incident_created(data)
return {"status": "success"}
# AWS Integration
from contractai import ContractAIClient
import boto3
# Initialize clients
contract_client = ContractAIClient(api_key="your_api_key")
aws_client = boto3.client("ec2")
# Create AWS-aware agent
agent = contract_client.agents.create(
name="aws-monitor",
capabilities=["aws-monitoring"],
config={
"aws_region": "us-west-2",
"aws_services": ["ec2", "rds", "lambda"]
}
)
# Monitor AWS resources
def monitor_aws_resources():
instances = aws_client.describe_instances()
for instance in instances["Reservations"]:
contract_client.monitoring.record_metric(
agent_id=agent.id,
metric="aws.ec2.instance_status",
value=instance["State"]["Name"]
)
# Azure Integration
from contractai import ContractAIClient
from azure.mgmt.compute import ComputeManagementClient
from azure.identity import DefaultAzureCredential
# Initialize clients
contract_client = ContractAIClient(api_key="your_api_key")
azure_credential = DefaultAzureCredential()
azure_client = ComputeManagementClient(
credential=azure_credential,
subscription_id="your_subscription_id"
)
# Create Azure-aware agent
agent = contract_client.agents.create(
name="azure-monitor",
capabilities=["azure-monitoring"],
config={
"azure_subscription": "your_subscription_id",
"azure_services": ["compute", "storage", "network"]
}
)
# Prometheus Integration
from contractai import ContractAIClient
from prometheus_client import start_http_server, Gauge
# Initialize client
client = ContractAIClient(api_key="your_api_key")
# Create Prometheus metrics
agent_status = Gauge(
"contractai_agent_status",
"Status of ContractAI agents",
["agent_id", "agent_name"]
)
# Start Prometheus server
start_http_server(8000)
# Update metrics
def update_metrics():
agents = client.agents.list()
for agent in agents:
status = client.agents.get_status(agent.id)
agent_status.labels(
agent_id=agent.id,
agent_name=agent.name
).set(1 if status.healthy else 0)
# Grafana Dashboard Configuration
apiVersion: 1
dashboards:
- name: "ContractAI Overview"
uid: "contractai-overview"
panels:
- title: "Agent Status"
type: "stat"
targets:
- expr: "contractai_agent_status"
legendFormat: "{{agent_name}}"
- title: "Incident Rate"
type: "graph"
targets:
- expr: "rate(contractai_incidents_total[5m])"
legendFormat: "Incidents per second"
# GitHub Actions Workflow
name: ContractAI Integration
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
deploy:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Deploy to ContractAI
uses: contractai/deploy-action@v1
with:
api_key: ${{ secrets.CONTRACT_AI_API_KEY }}
environment: production
agent_name: "github-deploy-agent"
// Jenkins Pipeline
pipeline {
agent any
environment {
CONTRACT_AI_API_KEY = credentials('contract-ai-api-key')
}
stages {
stage('Deploy to ContractAI') {
steps {
script {
def client = new ContractAIClient(
apiKey: env.CONTRACT_AI_API_KEY
)
client.agents.deploy(
name: "jenkins-deploy-agent",
environment: "production"
)
}
}
}
}
}
- Use asynchronous operations where possible
- Implement proper error handling
- Follow security best practices
- Monitor integration health
- Maintain documentation
# Error Handling Example
from contractai import ContractAIClient, ContractAIError
from tenacity import retry, stop_after_attempt, wait_exponential
client = ContractAIClient(api_key="your_api_key")
@retry(
stop=stop_after_attempt(3),
wait=wait_exponential(multiplier=1, min=4, max=10)
)
def safe_agent_operation(agent_id: str):
try:
return client.agents.get_status(agent_id)
except ContractAIError as e:
if e.status_code == 429: # Rate limit
raise # Retry
elif e.status_code == 404: # Not found
raise # Don't retry
else:
# Log and handle other errors
logger.error(f"Operation failed: {e}")
raise
# Caching Example
from contractai import ContractAIClient
from functools import lru_cache
import redis
# Initialize clients
contract_client = ContractAIClient(api_key="your_api_key")
redis_client = redis.Redis(host="localhost", port=6379)
@lru_cache(maxsize=100)
def get_agent_status(agent_id: str):
# Try cache first
cached_status = redis_client.get(f"agent_status:{agent_id}")
if cached_status:
return cached_status
# Get from API
status = contract_client.agents.get_status(agent_id)
# Cache result
redis_client.setex(
f"agent_status:{agent_id}",
300, # 5 minutes
status.json()
)
return status
# Rate Limiting Example
from contractai import ContractAIClient
from ratelimit import limits, sleep_and_retry
client = ContractAIClient(api_key="your_api_key")
# Limit to 100 calls per minute
@sleep_and_retry
@limits(calls=100, period=60)
def rate_limited_operation():
return client.agents.list()
- Verify network connectivity
- Check API credentials
- Validate IP allowlist
- Review firewall rules
- Verify API key validity
- Check OAuth token expiration
- Validate webhook signatures
- Review access permissions
# Logging Configuration
import logging
from contractai import ContractAIClient
# Configure logging
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
# Enable debug logging
client = ContractAIClient(
api_key="your_api_key",
debug=True
)
# Integration Monitoring
from contractai import ContractAIClient
from prometheus_client import Counter, Histogram
# Define metrics
api_calls = Counter(
"contractai_api_calls_total",
"Total API calls",
["endpoint", "status"]
)
api_latency = Histogram(
"contractai_api_latency_seconds",
"API call latency",
["endpoint"]
)
# Monitor API calls
def monitored_api_call(endpoint: str):
with api_latency.labels(endpoint=endpoint).time():
try:
response = client.api.call(endpoint)
api_calls.labels(
endpoint=endpoint,
status="success"
).inc()
return response
except Exception as e:
api_calls.labels(
endpoint=endpoint,
status="error"
).inc()
raise
Need help with integration? Contact our integration team at [email protected] or visit our Integration Portal
- ContractAI - RAG-powered AI agents for enterprise infrastructure
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Built with ❤️ by the fleXRPL team
© 2025 fleXRPL Organization | [MIT License](https://github.com/fleXRPL/contractAI/blob/main/LICENSE)
© 2025 fleXRPL Organization | [MIT License](https://github.com/fleXRPL/contractAI/blob/main/LICENSE)
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