Index NICE Cognigy.AI LLM Gateway Token Usage via REST APIs with Python

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Index NICE Cognigy.AI LLM Gateway Token Usage via REST APIs with Python

What You Will Build

This script indexes LLM gateway token consumption by submitting structured usage payloads to the Cognigy.AI metering engine. It uses the Cognigy.AI REST API v1 with Python and the requests library. The implementation covers atomic POST operations, quota validation, overage alerting, webhook synchronization, and audit logging.

Prerequisites

  • OAuth 2.0 Client Credentials grant with scopes ai:token:read, metering:index:write, quota:manage, webhook:trigger
  • Cognigy.AI API v1.0 or later
  • Python 3.9+
  • pip install requests pydantic python-dotenv

Authentication Setup

Cognigy.AI uses a standard OAuth 2.0 Client Credentials flow. The token endpoint issues short-lived access tokens that require caching and automatic refresh. The following code establishes a secure token manager with TTL tracking and 401 recovery.

import os
import time
import requests
from typing import Optional

class CognigyAuthManager:
    def __init__(self, client_id: str, client_secret: str, base_url: str):
        self.client_id = client_id
        self.client_secret = client_secret
        self.token_url = f"{base_url}/api/v1/system/oauth/token"
        self._token: Optional[str] = None
        self._expires_at: float = 0.0

    def get_token(self) -> str:
        if self._token and time.time() < self._expires_at - 30:
            return self._token
        
        payload = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": "ai:token:read metering:index:write quota:manage webhook:trigger"
        }
        
        headers = {"Content-Type": "application/json"}
        response = requests.post(self.token_url, json=payload, headers=headers, timeout=10)
        response.raise_for_status()
        
        data = response.json()
        self._token = data["access_token"]
        self._expires_at = time.time() + data["expires_in"]
        return self._token

OAuth scope requirement for this endpoint: system:oauth:manage (implicit in client credentials). The token manager caches the credential and refreshes automatically when the TTL approaches expiration.

Implementation

Step 1: Construct Index Payload and Validate Against Metering Constraints

The metering engine rejects payloads that exceed billing cycle limits or violate model tier quotas. You must validate the index schema before submission. The payload requires a usageReference, quotaMatrix, and tallyDirective. Pydantic enforces structural compliance.

from pydantic import BaseModel, Field, field_validator
from datetime import datetime
from typing import Dict, List

class QuotaMatrix(BaseModel):
    model_tier: str = Field(..., pattern="^(standard|premium|enterprise)$")
    input_tokens: int = Field(..., ge=0)
    output_tokens: int = Field(..., ge=0)
    context_window_limit: int = Field(..., ge=1, le=128000)

class TallyDirective(BaseModel):
    aggregation_type: str = Field(..., pattern="^(atomic|batch|streaming)$")
    billing_cycle_id: str
    max_cycle_limit: int = Field(..., ge=1)
    overage_alert_enabled: bool = True

class IndexPayload(BaseModel):
    usage_reference: str = Field(..., pattern="^[A-Z]{2}-[0-9]{4}-[A-Z0-9]{8}$")
    timestamp: str = Field(default_factory=lambda: datetime.utcnow().isoformat() + "Z")
    quota_matrix: QuotaMatrix
    tally_directive: TallyDirective
    rate_limit_compliance: bool = True

    @field_validator("quota_matrix")
    @classmethod
    def validate_metering_constraints(cls, v: QuotaMatrix) -> QuotaMatrix:
        if v.model_tier == "standard" and (v.input_tokens + v.output_tokens) > 50000:
            raise ValueError("Standard tier exceeds per-request token cap of 50000")
        if v.context_window_limit > 128000:
            raise ValueError("Context window limit exceeds metering engine maximum")
        return v

The schema validation prevents indexing failures caused by invalid tier assignments or context window violations. The usage_reference follows Cognigy.AI gateway routing conventions.

Step 2: Atomic POST Submission with Rate Limit Compliance

The metering engine processes index submissions atomically. You must handle HTTP 429 responses with exponential backoff and verify format compliance on the response payload. The following function executes the POST request with retry logic.

import json
import logging
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry

logger = logging.getLogger("cognigy_indexer")

class CognigyMeteringClient:
    def __init__(self, base_url: str, auth: CognigyAuthManager):
        self.base_url = base_url
        self.auth = auth
        self.index_endpoint = f"{base_url}/api/v1/ai/token-usage/index"
        self.session = requests.Session()
        
        retry_strategy = Retry(
            total=3,
            backoff_factor=0.5,
            status_forcelist=[429, 500, 502, 503, 504],
            allowed_methods=["POST"]
        )
        adapter = HTTPAdapter(max_retries=retry_strategy)
        self.session.mount("https://", adapter)
        self.session.mount("http://", adapter)

    def submit_index(self, payload: IndexPayload) -> dict:
        token = self.auth.get_token()
        headers = {
            "Authorization": f"Bearer {token}",
            "Content-Type": "application/json",
            "X-Request-Id": f"idx-{payload.usage_reference}-{int(time.time())}"
        }
        
        request_body = payload.model_dump(mode="json")
        
        logger.info("Submitting index payload: %s", json.dumps(request_body))
        
        response = self.session.post(
            self.index_endpoint,
            json=request_body,
            headers=headers,
            timeout=15
        )
        
        if response.status_code == 401:
            self.auth._token = None
            return self.submit_index(payload)
            
        if response.status_code == 429:
            retry_after = int(response.headers.get("Retry-After", 2))
            logger.warning("Rate limited. Retrying in %d seconds", retry_after)
            time.sleep(retry_after)
            return self.submit_index(payload)
            
        response.raise_for_status()
        return response.json()

OAuth scope requirement for this endpoint: metering:index:write. The retry strategy handles transient 429 and 5xx errors. The 401 handler forces token rotation. The X-Request-Id header enables traceability in Cognigy.AI gateway logs.

Step 3: Quota Validation Pipeline and Overage Alert Triggering

Before indexing, you must verify that the submission does not breach the billing cycle limit. The quota validation endpoint returns the current cycle consumption and remaining capacity. The indexer blocks submission when the limit is reached and triggers an overage alert.

class QuotaValidator:
    def __init__(self, base_url: str, auth: CognigyAuthManager):
        self.base_url = base_url
        self.auth = auth
        self.quota_endpoint = f"{base_url}/api/v1/ai/quotas/validate"

    def check_and_alert(self, payload: IndexPayload) -> bool:
        token = self.auth.get_token()
        headers = {
            "Authorization": f"Bearer {token}",
            "Content-Type": "application/json"
        }
        
        validation_request = {
            "billing_cycle_id": payload.tally_directive.billing_cycle_id,
            "model_tier": payload.quota_matrix.model_tier,
            "projected_tokens": payload.quota_matrix.input_tokens + payload.quota_matrix.output_tokens
        }
        
        response = requests.post(
            self.quota_endpoint,
            json=validation_request,
            headers=headers,
            timeout=10
        )
        response.raise_for_status()
        
        quota_status = response.json()
        remaining = quota_status.get("remaining_cycle_tokens", 0)
        projected = validation_request["projected_tokens"]
        
        if projected > remaining:
            logger.error("Budget overrun detected. Projected %d exceeds remaining %d", projected, remaining)
            self._trigger_overage_alert(payload, remaining)
            return False
            
        return True

    def _trigger_overage_alert(self, payload: IndexPayload, remaining: int) -> None:
        alert_payload = {
            "alert_type": "QUOTA_OVERAGE",
            "usage_reference": payload.usage_reference,
            "billing_cycle_id": payload.tally_directive.billing_cycle_id,
            "remaining_tokens": remaining,
            "timestamp": datetime.utcnow().isoformat() + "Z"
        }
        
        webhook_url = os.getenv("COGNIGY_OVERAGE_WEBHOOK_URL")
        if webhook_url:
            requests.post(webhook_url, json=alert_payload, timeout=5)
            logger.info("Overage alert dispatched to FinOps dashboard")

OAuth scope requirement for quota validation: quota:manage. The validator compares projected consumption against the metering engine’s remaining cycle allowance. When the limit is breached, the system blocks indexing and posts an alert to the configured webhook URL.

Step 4: Webhook Synchronization, Latency Tracking, and Audit Logging

Production indexers must synchronize with external FinOps dashboards, track submission latency, and maintain audit trails. The following class wraps the submission pipeline with telemetry and audit generation.

class QuotaIndexer:
    def __init__(self, base_url: str, auth: CognigyAuthManager):
        self.client = CognigyMeteringClient(base_url, auth)
        self.validator = QuotaValidator(base_url, auth)
        self.success_count = 0
        self.failure_count = 0
        self.total_latency_ms = 0.0
        self.audit_log: List[dict] = []

    def index(self, payload: IndexPayload) -> dict:
        start_time = time.perf_counter()
        
        if not self.validator.check_and_alert(payload):
            self.failure_count += 1
            raise RuntimeError("Indexing blocked due to quota validation failure")
        
        result = self.client.submit_index(payload)
        
        latency_ms = (time.perf_counter() - start_time) * 1000
        self.total_latency_ms += latency_ms
        self.success_count += 1
        
        audit_entry = {
            "event": "INDEX_SUBMITTED",
            "usage_reference": payload.usage_reference,
            "status": "SUCCESS",
            "latency_ms": round(latency_ms, 2),
            "tokens_indexed": payload.quota_matrix.input_tokens + payload.quota_matrix.output_tokens,
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "response_id": result.get("indexId", "unknown")
        }
        self.audit_log.append(audit_entry)
        
        self._sync_finops_dashboard(audit_entry)
        return result

    def _sync_finops_dashboard(self, audit_entry: dict) -> None:
        webhook_url = os.getenv("COGNIGY_FINOPS_WEBHOOK_URL")
        if not webhook_url:
            return
            
        sync_payload = {
            "source": "cognigy_ai_metering",
            "type": "usage_index_sync",
            "data": audit_entry
        }
        
        try:
            requests.post(webhook_url, json=sync_payload, timeout=5)
        except requests.RequestException as e:
            logger.warning("FinOps webhook sync failed: %s", e)

    def get_metrics(self) -> dict:
        total = self.success_count + self.failure_count
        success_rate = (self.success_count / total * 100) if total > 0 else 0.0
        avg_latency = (self.total_latency_ms / self.success_count) if self.success_count > 0 else 0.0
        
        return {
            "total_submissions": total,
            "success_rate_percent": round(success_rate, 2),
            "average_latency_ms": round(avg_latency, 2),
            "audit_log_size": len(self.audit_log)
        }

The QuotaIndexer class exposes a single index() method that handles validation, submission, latency measurement, success tracking, audit logging, and webhook synchronization. OAuth scope requirement for webhook triggers: webhook:trigger. The telemetry pipeline enables cost predictability and financial governance compliance.

Complete Working Example

The following script combines all components into a runnable module. Replace the environment variables with your Cognigy.AI tenant credentials.

import os
import time
import logging
import requests
from datetime import datetime
from typing import List, Optional
from pydantic import BaseModel, Field, field_validator
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry

logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
logger = logging.getLogger("cognigy_indexer")

class CognigyAuthManager:
    def __init__(self, client_id: str, client_secret: str, base_url: str):
        self.client_id = client_id
        self.client_secret = client_secret
        self.token_url = f"{base_url}/api/v1/system/oauth/token"
        self._token: Optional[str] = None
        self._expires_at: float = 0.0

    def get_token(self) -> str:
        if self._token and time.time() < self._expires_at - 30:
            return self._token
        
        payload = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": "ai:token:read metering:index:write quota:manage webhook:trigger"
        }
        
        headers = {"Content-Type": "application/json"}
        response = requests.post(self.token_url, json=payload, headers=headers, timeout=10)
        response.raise_for_status()
        
        data = response.json()
        self._token = data["access_token"]
        self._expires_at = time.time() + data["expires_in"]
        return self._token

class QuotaMatrix(BaseModel):
    model_tier: str = Field(..., pattern="^(standard|premium|enterprise)$")
    input_tokens: int = Field(..., ge=0)
    output_tokens: int = Field(..., ge=0)
    context_window_limit: int = Field(..., ge=1, le=128000)

class TallyDirective(BaseModel):
    aggregation_type: str = Field(..., pattern="^(atomic|batch|streaming)$")
    billing_cycle_id: str
    max_cycle_limit: int = Field(..., ge=1)
    overage_alert_enabled: bool = True

class IndexPayload(BaseModel):
    usage_reference: str = Field(..., pattern="^[A-Z]{2}-[0-9]{4}-[A-Z0-9]{8}$")
    timestamp: str = Field(default_factory=lambda: datetime.utcnow().isoformat() + "Z")
    quota_matrix: QuotaMatrix
    tally_directive: TallyDirective
    rate_limit_compliance: bool = True

    @field_validator("quota_matrix")
    @classmethod
    def validate_metering_constraints(cls, v: QuotaMatrix) -> QuotaMatrix:
        if v.model_tier == "standard" and (v.input_tokens + v.output_tokens) > 50000:
            raise ValueError("Standard tier exceeds per-request token cap of 50000")
        if v.context_window_limit > 128000:
            raise ValueError("Context window limit exceeds metering engine maximum")
        return v

class CognigyMeteringClient:
    def __init__(self, base_url: str, auth: CognigyAuthManager):
        self.base_url = base_url
        self.auth = auth
        self.index_endpoint = f"{base_url}/api/v1/ai/token-usage/index"
        self.session = requests.Session()
        
        retry_strategy = Retry(
            total=3,
            backoff_factor=0.5,
            status_forcelist=[429, 500, 502, 503, 504],
            allowed_methods=["POST"]
        )
        adapter = HTTPAdapter(max_retries=retry_strategy)
        self.session.mount("https://", adapter)
        self.session.mount("http://", adapter)

    def submit_index(self, payload: IndexPayload) -> dict:
        token = self.auth.get_token()
        headers = {
            "Authorization": f"Bearer {token}",
            "Content-Type": "application/json",
            "X-Request-Id": f"idx-{payload.usage_reference}-{int(time.time())}"
        }
        
        request_body = payload.model_dump(mode="json")
        logger.info("Submitting index payload: %s", str(request_body))
        
        response = self.session.post(
            self.index_endpoint,
            json=request_body,
            headers=headers,
            timeout=15
        )
        
        if response.status_code == 401:
            self.auth._token = None
            return self.submit_index(payload)
            
        if response.status_code == 429:
            retry_after = int(response.headers.get("Retry-After", 2))
            logger.warning("Rate limited. Retrying in %d seconds", retry_after)
            time.sleep(retry_after)
            return self.submit_index(payload)
            
        response.raise_for_status()
        return response.json()

class QuotaValidator:
    def __init__(self, base_url: str, auth: CognigyAuthManager):
        self.base_url = base_url
        self.auth = auth
        self.quota_endpoint = f"{base_url}/api/v1/ai/quotas/validate"

    def check_and_alert(self, payload: IndexPayload) -> bool:
        token = self.auth.get_token()
        headers = {
            "Authorization": f"Bearer {token}",
            "Content-Type": "application/json"
        }
        
        validation_request = {
            "billing_cycle_id": payload.tally_directive.billing_cycle_id,
            "model_tier": payload.quota_matrix.model_tier,
            "projected_tokens": payload.quota_matrix.input_tokens + payload.quota_matrix.output_tokens
        }
        
        response = requests.post(
            self.quota_endpoint,
            json=validation_request,
            headers=headers,
            timeout=10
        )
        response.raise_for_status()
        
        quota_status = response.json()
        remaining = quota_status.get("remaining_cycle_tokens", 0)
        projected = validation_request["projected_tokens"]
        
        if projected > remaining:
            logger.error("Budget overrun detected. Projected %d exceeds remaining %d", projected, remaining)
            self._trigger_overage_alert(payload, remaining)
            return False
            
        return True

    def _trigger_overage_alert(self, payload: IndexPayload, remaining: int) -> None:
        alert_payload = {
            "alert_type": "QUOTA_OVERAGE",
            "usage_reference": payload.usage_reference,
            "billing_cycle_id": payload.tally_directive.billing_cycle_id,
            "remaining_tokens": remaining,
            "timestamp": datetime.utcnow().isoformat() + "Z"
        }
        
        webhook_url = os.getenv("COGNIGY_OVERAGE_WEBHOOK_URL")
        if webhook_url:
            requests.post(webhook_url, json=alert_payload, timeout=5)
            logger.info("Overage alert dispatched to FinOps dashboard")

class QuotaIndexer:
    def __init__(self, base_url: str, auth: CognigyAuthManager):
        self.client = CognigyMeteringClient(base_url, auth)
        self.validator = QuotaValidator(base_url, auth)
        self.success_count = 0
        self.failure_count = 0
        self.total_latency_ms = 0.0
        self.audit_log: List[dict] = []

    def index(self, payload: IndexPayload) -> dict:
        start_time = time.perf_counter()
        
        if not self.validator.check_and_alert(payload):
            self.failure_count += 1
            raise RuntimeError("Indexing blocked due to quota validation failure")
        
        result = self.client.submit_index(payload)
        
        latency_ms = (time.perf_counter() - start_time) * 1000
        self.total_latency_ms += latency_ms
        self.success_count += 1
        
        audit_entry = {
            "event": "INDEX_SUBMITTED",
            "usage_reference": payload.usage_reference,
            "status": "SUCCESS",
            "latency_ms": round(latency_ms, 2),
            "tokens_indexed": payload.quota_matrix.input_tokens + payload.quota_matrix.output_tokens,
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "response_id": result.get("indexId", "unknown")
        }
        self.audit_log.append(audit_entry)
        
        self._sync_finops_dashboard(audit_entry)
        return result

    def _sync_finops_dashboard(self, audit_entry: dict) -> None:
        webhook_url = os.getenv("COGNIGY_FINOPS_WEBHOOK_URL")
        if not webhook_url:
            return
            
        sync_payload = {
            "source": "cognigy_ai_metering",
            "type": "usage_index_sync",
            "data": audit_entry
        }
        
        try:
            requests.post(webhook_url, json=sync_payload, timeout=5)
        except requests.RequestException as e:
            logger.warning("FinOps webhook sync failed: %s", e)

    def get_metrics(self) -> dict:
        total = self.success_count + self.failure_count
        success_rate = (self.success_count / total * 100) if total > 0 else 0.0
        avg_latency = (self.total_latency_ms / self.success_count) if self.success_count > 0 else 0.0
        
        return {
            "total_submissions": total,
            "success_rate_percent": round(success_rate, 2),
            "average_latency_ms": round(avg_latency, 2),
            "audit_log_size": len(self.audit_log)
        }

if __name__ == "__main__":
    BASE_URL = os.getenv("COGNIGY_BASE_URL", "https://api.cognigy.ai")
    CLIENT_ID = os.getenv("COGNIGY_CLIENT_ID")
    CLIENT_SECRET = os.getenv("COGNIGY_CLIENT_SECRET")
    
    if not CLIENT_ID or not CLIENT_SECRET:
        raise ValueError("COGNIGY_CLIENT_ID and COGNIGY_CLIENT_SECRET must be set")
        
    auth = CognigyAuthManager(CLIENT_ID, CLIENT_SECRET, BASE_URL)
    indexer = QuotaIndexer(BASE_URL, auth)
    
    sample_payload = IndexPayload(
        usage_reference="US-2024-AB12CD34",
        quota_matrix=QuotaMatrix(
            model_tier="premium",
            input_tokens=1200,
            output_tokens=3400,
            context_window_limit=8192
        ),
        tally_directive=TallyDirective(
            aggregation_type="atomic",
            billing_cycle_id="CYC-2024-Q4-001",
            max_cycle_limit=500000,
            overage_alert_enabled=True
        )
    )
    
    try:
        result = indexer.index(sample_payload)
        print("Index submission successful:", result)
        print("Metrics:", indexer.get_metrics())
    except Exception as e:
        logger.error("Indexing pipeline failed: %s", e)

Common Errors & Debugging

Error: HTTP 400 Bad Request

  • Cause: The index payload violates metering engine constraints. Common triggers include invalid model_tier values, context_window_limit exceeding 128000, or malformed usage_reference patterns.
  • Fix: Verify the Pydantic validation output before submission. Ensure the usage_reference matches the regex ^[A-Z]{2}-[0-9]{4}-[A-Z0-9]{8}$. Adjust context_window_limit to stay within the 128000 maximum.
  • Code showing the fix: The validate_metering_constraints method in IndexPayload catches these violations and raises a descriptive ValueError before the HTTP call executes.

Error: HTTP 403 Forbidden

  • Cause: The OAuth token lacks the required scopes for the targeted endpoint. The metering index endpoint requires metering:index:write. The quota validation endpoint requires quota:manage.
  • Fix: Update the scope parameter in the token request payload. Regenerate the token and retry the operation.
  • Code showing the fix: The CognigyAuthManager.get_token() method requests the combined scope string ai:token:read metering:index:write quota:manage webhook:trigger. If your tenant restricts scope granularity, split the request into separate client credentials flows.

Error: HTTP 429 Too Many Requests

  • Cause: The indexer exceeds the Cognigy.AI gateway rate limit. Token indexing endpoints typically enforce 50 requests per minute per tenant.
  • Fix: The CognigyMeteringClient applies a Retry strategy with exponential backoff. The code reads the Retry-After header and sleeps accordingly. If the limit persists, reduce the batch frequency or implement a token bucket algorithm locally.
  • Code showing the fix: The urllib3.util.retry.Retry configuration in CognigyMeteringClient.__init__ handles automatic 429 recovery. The manual 429 block in submit_index provides fallback handling when the adapter exhausts retries.

Error: HTTP 409 Conflict

  • Cause: The billing cycle limit is exhausted. The quotaMatrix projection exceeds remaining_cycle_tokens returned by the validation endpoint.
  • Fix: The QuotaValidator blocks submission and triggers an overage alert. Rotate the billing_cycle_id to the next cycle or request a quota increase from your NICE CXone account manager.
  • Code showing the fix: The check_and_alert method compares projected_tokens against remaining. When projected > remaining, the method returns False and dispatches the webhook alert.

Official References