Universal API Integration
Costa Code provides an OpenAI-compatible API that works with virtually any AI agent, custom application, or automation tool. This allows you to integrate enterprise-grade AI capabilities into your existing workflows while maintaining the highest security standards.API Configuration
Base Configuration
Copy
Ask AI
export COSTA_API_KEY="REPLACE_WITH_YOUR_COSTA_API_KEY"
export COSTA_BASE_URL="https://ai.costa.app/api/v1"
export COSTA_MODEL="costa/auto"
Integration Examples
Python SDK Integration
Copy
Ask AI
import openai
# Configure Costa Code as OpenAI provider
client = openai.OpenAI(
api_key="costa_ent_your_key_here",
base_url="https://ai.costa.app/api/v1"
)
# Basic chat completion
response = client.chat.completions.create(
model="costa/enterprise-coder-v1",
messages=[
{"role": "user", "content": "Write a secure Python function for user authentication"}
],
max_tokens=1000,
temperature=0.7
)
print(response.choices[0].message.content)
# With enterprise security headers
response = client.chat.completions.create(
model="costa/secure-claude-3-5-sonnet",
messages=[
{"role": "user", "content": "Review this code for security vulnerabilities"}
],
extra_headers={
"Costa-Security-Level": "maximum",
"Costa-Data-Residency": "us-east",
"Costa-Audit-Enabled": "true",
"Costa-Zero-Retention": "true"
}
)
JavaScript/Node.js Integration
Copy
Ask AI
import OpenAI from 'openai';
// Configure Costa Code client
const openai = new OpenAI({
apiKey: 'costa_ent_your_key_here',
baseURL: 'https://ai.costa.app/api/v1'
});
// Basic completion
async function generateCode(prompt) {
const completion = await openai.chat.completions.create({
model: 'costa/enterprise-coder-v1',
messages: [{ role: 'user', content: prompt }],
max_tokens: 1000,
temperature: 0.7
});
return completion.choices[0].message.content;
}
// Enterprise security completion
async function secureGeneration(prompt, securityLevel = 'high') {
const completion = await openai.chat.completions.create({
model: 'costa/secure-claude-3-5-sonnet',
messages: [{ role: 'user', content: prompt }],
max_tokens: 1500,
extra_headers: {
'Costa-Security-Level': securityLevel,
'Costa-Audit-Enabled': 'true',
'Costa-Data-Residency': 'us-east'
}
});
return completion.choices[0].message.content;
}
// Usage
const code = await generateCode('Create a REST API for user management');
const secureCode = await secureGeneration('Review this payment processing code', 'maximum');
cURL Examples
Copy
Ask AI
curl -X POST "https://ai.costa.app/api/v1/chat/completions" \
-H "Authorization: Bearer costa_ent_your_key_here" \
-H "Content-Type: application/json" \
-d '{
"model": "costa/enterprise-coder-v1",
"messages": [
{
"role": "user",
"content": "Write a secure authentication middleware for Express.js"
}
],
"max_tokens": 1000,
"temperature": 0.7
}'
Popular AI Agent Integrations
AutoGPT Integration
Copy
Ask AI
ai_provider: custom
api_base: https://ai.costa.app/api/v1
api_key: costa_ent_your_key_here
models:
fast_llm: costa/enterprise-coder-v1
smart_llm: costa/secure-claude-3-5-sonnet
security:
audit_enabled: true
data_residency: us-east
security_level: high
headers:
Costa-Security-Level: high
Costa-Audit-Enabled: "true"
Costa-Data-Residency: us-east
LangChain Integration
Copy
Ask AI
from langchain.llms import OpenAI
from langchain.chat_models import ChatOpenAI
from langchain.schema import HumanMessage
# Configure Costa Code as LangChain provider
costa_llm = ChatOpenAI(
openai_api_key="costa_ent_your_key_here",
openai_api_base="https://ai.costa.app/api/v1",
model_name="costa/enterprise-coder-v1",
temperature=0.7
)
# Use with LangChain chains
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
prompt = PromptTemplate(
input_variables=["task"],
template="Write secure, enterprise-grade code for: {task}"
)
chain = LLMChain(llm=costa_llm, prompt=prompt)
result = chain.run(task="user authentication system with MFA")
# Enterprise security configuration
costa_secure = ChatOpenAI(
openai_api_key="costa_ent_your_key_here",
openai_api_base="https://ai.costa.app/api/v1",
model_name="costa/secure-claude-3-5-sonnet",
model_kwargs={
"extra_headers": {
"Costa-Security-Level": "maximum",
"Costa-Audit-Enabled": "true"
}
}
)
Custom AI Agent Template
Copy
Ask AI
import requests
import json
from typing import Dict, List, Optional
class EnterpriseAIAgent:
def __init__(self, api_key: str, default_model: str = "costa/enterprise-coder-v1"):
self.api_key = api_key
self.base_url = "https://ai.costa.app/api/v1"
self.default_model = default_model
self.session = requests.Session()
self.session.headers.update({
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
})
def execute_task(
self,
task: str,
model: Optional[str] = None,
security_level: str = "high",
compliance_frameworks: List[str] = None,
**kwargs
) -> Dict:
"""Execute AI task with enterprise security"""
headers = {
"Costa-Security-Level": security_level,
"Costa-Audit-Enabled": "true",
"Costa-Data-Residency": kwargs.get("region", "us-east")
}
if kwargs.get("zero_retention", False):
headers["Costa-Zero-Retention"] = "true"
if compliance_frameworks:
headers["Costa-Compliance-Frameworks"] = ",".join(compliance_frameworks)
payload = {
"model": model or self.default_model,
"messages": [{"role": "user", "content": task}],
"max_tokens": kwargs.get("max_tokens", 1000),
"temperature": kwargs.get("temperature", 0.7)
}
response = self.session.post(
f"{self.base_url}/chat/completions",
headers=headers,
json=payload
)
response.raise_for_status()
return response.json()
def code_review(self, code: str, framework: str = "general") -> Dict:
"""Perform security-focused code review"""
model_map = {
"hipaa": "costa/compliance-assistant",
"sox": "costa/compliance-assistant",
"pci": "costa/compliance-assistant",
"general": "costa/secure-claude-3-5-sonnet"
}
task = f"Perform a comprehensive security review of this code for {framework} compliance:\n\n{code}"
return self.execute_task(
task=task,
model=model_map.get(framework, "costa/secure-claude-3-5-sonnet"),
security_level="maximum",
compliance_frameworks=[framework] if framework != "general" else [],
zero_retention=True
)
def generate_code(self, requirements: str, language: str = "python") -> Dict:
"""Generate enterprise-grade code"""
task = f"Generate secure, enterprise-grade {language} code for: {requirements}"
return self.execute_task(
task=task,
model="costa/enterprise-coder-v1",
security_level="high",
max_tokens=2000
)
# Usage example
agent = EnterpriseAIAgent("costa_ent_your_key_here")
# Generate secure code
code_result = agent.generate_code(
"User authentication system with JWT and rate limiting",
language="python"
)
# Review code for compliance
review_result = agent.code_review(
code="def process_payment(card_data): ...",
framework="pci"
)
print("Generated code:", code_result["choices"][0]["message"]["content"])
print("Security review:", review_result["choices"][0]["message"]["content"])
Enterprise Headers Reference
Security Level Control
Security Level Control
Header:
Costa-Security-LevelValues:standard- Default security measureshigh- Enhanced security protocolsmaximum- Highest security, compliance mode
Copy
Ask AI
-H "Costa-Security-Level: maximum"
Data Residency
Data Residency
Header:
Costa-Data-ResidencyValues:us-east- US East Coastus-west- US West Coasteu-west- European Unionasia-pacific- Asia Pacific
Copy
Ask AI
-H "Costa-Data-Residency: eu-west"
Audit Logging
Audit Logging
Header:
Costa-Audit-EnabledValues: true, falseUsage:Copy
Ask AI
-H "Costa-Audit-Enabled: true"
Zero Retention
Zero Retention
Header:
Costa-Zero-RetentionValues: true, falseDescription: Enable zero data retention modeUsage:Copy
Ask AI
-H "Costa-Zero-Retention: true"
Compliance Frameworks
Compliance Frameworks
Header:
Costa-Compliance-FrameworksValues: Comma-separated list of hipaa, sox, pci-dss, gdprUsage:Copy
Ask AI
-H "Costa-Compliance-Frameworks: hipaa,sox"
Error Handling
Copy
Ask AI
import requests
from requests.exceptions import RequestException
def safe_costa_request(api_key, model, messages, **kwargs):
"""Make a safe request to Costa Code API with error handling"""
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
"Costa-Security-Level": kwargs.get("security_level", "high"),
"Costa-Audit-Enabled": "true"
}
payload = {
"model": model,
"messages": messages,
"max_tokens": kwargs.get("max_tokens", 1000),
"temperature": kwargs.get("temperature", 0.7)
}
try:
response = requests.post(
"https://ai.costa.app/api/v1/chat/completions",
headers=headers,
json=payload,
timeout=30
)
# Handle HTTP errors
if response.status_code == 401:
raise Exception("Invalid API key or authentication failed")
elif response.status_code == 403:
raise Exception("Access denied - check model permissions")
elif response.status_code == 429:
raise Exception("Rate limit exceeded - please retry later")
elif response.status_code >= 500:
raise Exception("Costa Code service error - please retry")
response.raise_for_status()
return response.json()
except RequestException as e:
raise Exception(f"Network error: {str(e)}")
except Exception as e:
raise Exception(f"API request failed: {str(e)}")
# Usage with error handling
try:
result = safe_costa_request(
api_key="costa_ent_your_key_here",
model="costa/enterprise-coder-v1",
messages=[{"role": "user", "content": "Generate secure code"}],
security_level="high"
)
print("Success:", result["choices"][0]["message"]["content"])
except Exception as e:
print("Error:", str(e))
Testing & Validation
Copy
Ask AI
import unittest
import requests
class CostaCodeAPITest(unittest.TestCase):
def setUp(self):
self.api_key = "costa_ent_your_test_key_here"
self.base_url = "https://ai.costa.app/api/v1"
self.headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json"
}
def test_basic_completion(self):
"""Test basic chat completion"""
payload = {
"model": "costa/enterprise-coder-v1",
"messages": [{"role": "user", "content": "Hello, world!"}],
"max_tokens": 50
}
response = requests.post(
f"{self.base_url}/chat/completions",
headers=self.headers,
json=payload
)
self.assertEqual(response.status_code, 200)
data = response.json()
self.assertIn("choices", data)
self.assertGreater(len(data["choices"]), 0)
def test_security_headers(self):
"""Test enterprise security headers"""
headers = {
**self.headers,
"Costa-Security-Level": "maximum",
"Costa-Audit-Enabled": "true"
}
payload = {
"model": "costa/secure-claude-3-5-sonnet",
"messages": [{"role": "user", "content": "Test security"}],
"max_tokens": 50
}
response = requests.post(
f"{self.base_url}/chat/completions",
headers=headers,
json=payload
)
self.assertEqual(response.status_code, 200)
data = response.json()
self.assertIn("security", data)
def test_model_availability(self):
"""Test available models"""
response = requests.get(
f"{self.base_url}/models",
headers=self.headers
)
self.assertEqual(response.status_code, 200)
data = response.json()
model_ids = [model["id"] for model in data["data"]]
self.assertIn("costa/enterprise-coder-v1", model_ids)
if __name__ == "__main__":
unittest.main()
Best Practices
1
Authentication Security
- Store API keys securely using environment variables
- Rotate API keys regularly
- Use different keys for development and production
2
Error Handling
- Implement comprehensive error handling
- Add retry logic for transient failures
- Log errors for debugging and monitoring
3
Security Configuration
- Use appropriate security levels for your use case
- Enable audit logging for compliance requirements
- Configure data residency based on regulations
4
Performance Optimization
- Use streaming for real-time applications
- Cache responses when appropriate
- Monitor usage and optimize model selection
Enterprise Integration: When integrating Costa Code with AI agents, ensure proper security measures are implemented including secure API key storage, appropriate security levels, and compliance configuration for your industry requirements.