Cloning Cognigy.AI Bot Flow Definitions via REST APIs with Python

What You Will Build

• A Python module that clones bot flow definitions using the Cognigy.AI REST API, remaps node references, validates graph constraints, detects circular dependencies, verifies variable scopes, and executes atomic creation requests.
• Uses Cognigy.AI v1 REST API endpoints for flow retrieval, validation, and provisioning.
• Covers Python 3.9+ with requests, httpx, and standard library modules for metrics tracking, audit logging, and webhook synchronization.

Prerequisites

• OAuth client credentials configured in Cognigy.AI with flow:read and flow:write scopes
• Cognigy.AI v1 API access enabled for your tenant
• Python 3.9 or higher
• External dependencies: pip install requests httpx pydantic

Authentication Setup

Cognigy.AI uses OAuth 2.0 client credentials grant for programmatic access. The following implementation caches the access token and handles expiration gracefully.

import requests
import time
import threading
from typing import Optional

class CognigyAuth:
    def __init__(self, tenant: str, client_id: str, client_secret: str):
        self.base_url = f"https://{tenant}.cognigy.ai/api/v1"
        self.client_id = client_id
        self.client_secret = client_secret
        self.token: Optional[str] = None
        self.expires_at: float = 0.0
        self.lock = threading.Lock()

    def _fetch_token(self) -> str:
        payload = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret
        }
        response = requests.post(f"{self.base_url}/oauth/token", json=payload)
        response.raise_for_status()
        data = response.json()
        return data["access_token"], data.get("expires_in", 3600)

    def get_token(self) -> str:
        with self.lock:
            if self.token and time.time() < self.expires_at:
                return self.token
            token, expires_in = self._fetch_token()
            self.token = token
            self.expires_at = time.time() + expires_in - 60
            return self.token

    def get_headers(self) -> dict:
        return {
            "Authorization": f"Bearer {self.get_token()}",
            "Content-Type": "application/json"
        }

Implementation

Step 1: Fetch Source Flow and Construct Clone Payload

The cloning process begins by retrieving the source flow definition. You must remap all internal identifiers to prevent UUID collisions in the target environment. The payload requires a complete node matrix, remapped edge references, and a duplicateDirective marker for audit tracking.

import uuid
import copy
import requests
from typing import Dict, Any

class FlowCloner:
    def __init__(self, auth: CognigyAuth):
        self.auth = auth
        self.base_url = auth.base_url

    def fetch_flow(self, flow_id: str) -> Dict[str, Any]:
        response = requests.get(
            f"{self.base_url}/flows/{flow_id}",
            headers=self.auth.get_headers()
        )
        response.raise_for_status()
        return response.json()

    def construct_clone_payload(self, source_flow: Dict[str, Any], new_name: str) -> Dict[str, Any]:
        # Deep copy to avoid mutating the source reference
        payload = copy.deepcopy(source_flow)
        payload["id"] = str(uuid.uuid4())
        payload["name"] = new_name
        payload["version"] = 0
        payload["duplicateDirective"] = "cloned_via_api"

        # Remap node and edge identifiers
        id_mapping = {}
        for node in payload.get("nodes", []):
            old_id = node["id"]
            new_id = str(uuid.uuid4())
            id_mapping[old_id] = new_id
            node["id"] = new_id

        for edge in payload.get("edges", []):
            if edge.get("from") in id_mapping:
                edge["from"] = id_mapping[edge["from"]]
            if edge.get("to") in id_mapping:
                edge["to"] = id_mapping[edge["to"]]

        return payload

Step 2: Validate Schema and Graph Constraints

Before submission, you must validate the payload against Cognigy.AI graph engine constraints. This includes enforcing maximum node counts, detecting circular dependencies via depth-first search, and verifying variable scope definitions against node configurations.

from collections import defaultdict
from typing import List, Tuple

class FlowValidator:
    MAX_NODE_COUNT = 500

    @staticmethod
    def validate_node_count(payload: Dict[str, Any]) -> bool:
        node_count = len(payload.get("nodes", []))
        if node_count > FlowValidator.MAX_NODE_COUNT:
            raise ValueError(f"Node count {node_count} exceeds maximum limit of {FlowValidator.MAX_NODE_COUNT}")
        return True

    @staticmethod
    def detect_circular_dependencies(payload: Dict[str, Any]) -> bool:
        graph = defaultdict(list)
        nodes = {n["id"] for n in payload.get("nodes", [])}
        for edge in payload.get("edges", []):
            if edge.get("from") in nodes and edge.get("to") in nodes:
                graph[edge["from"]].append(edge["to"])

        visited = set()
        rec_stack = set()

        def dfs(node: str) -> bool:
            visited.add(node)
            rec_stack.add(node)
            for neighbor in graph[node]:
                if neighbor not in visited:
                    if dfs(neighbor):
                        return True
                elif neighbor in rec_stack:
                    return True
            rec_stack.discard(node)
            return False

        for node in nodes:
            if node not in visited:
                if dfs(node):
                    raise ValueError("Circular dependency detected in flow graph")
        return True

    @staticmethod
    def verify_variable_scope(payload: Dict[str, Any]) -> bool:
        defined_vars = {v["name"] for v in payload.get("variables", [])}
        for node in payload.get("nodes", []):
            config = node.get("config", {})
            # Cognigy nodes reference variables via ${variableName} or direct config keys
            if "variable" in config and config["variable"] not in defined_vars:
                raise ValueError(f"Undefined variable reference: {config['variable']} in node {node['id']}")
        return True

Step 3: Execute Atomic Clone POST and Handle Reference Resolution

Cognigy.AI requires the complete flow definition in a single atomic POST operation. The following implementation includes exponential backoff for 429 rate limits, format verification, and automatic retry logic.

import httpx
import time
from typing import Dict, Any

class FlowDeployer:
    def __init__(self, auth: CognigyAuth):
        self.auth = auth
        self.base_url = auth.base_url
        self.client = httpx.Client(timeout=30.0)

    def deploy_clone(self, payload: Dict[str, Any], max_retries: int = 3) -> Dict[str, Any]:
        url = f"{self.base_url}/flows"
        headers = self.auth.get_headers()

        for attempt in range(max_retries):
            response = self.client.post(url, json=payload, headers=headers)

            if response.status_code == 200 or response.status_code == 201:
                return response.json()
            elif response.status_code == 429:
                retry_after = int(response.headers.get("Retry-After", 2 ** attempt))
                time.sleep(retry_after)
                continue
            elif response.status_code == 400:
                raise ValueError(f"Payload validation failed: {response.text}")
            elif response.status_code == 409:
                raise ConflictError(f"Flow conflict: {response.text}")
            else:
                response.raise_for_status()

        raise RuntimeError("Maximum retry attempts exceeded for 429 rate limiting")

class ConflictError(Exception):
    pass

Step 4: Verify Clone and Synchronize with External Version Control

After successful deployment, you must trigger external version control webhooks, calculate cloning latency, update success metrics, and generate structured audit logs for governance compliance.

import json
import time
import logging
from datetime import datetime, timezone

class CloneOrchestrator:
    def __init__(self, auth: CognigyAuth, webhook_url: str):
        self.auth = auth
        self.webhook_url = webhook_url
        self.cloner = FlowCloner(auth)
        self.validator = FlowValidator()
        self.deployer = FlowDeployer(auth)
        self.success_count = 0
        self.total_attempts = 0
        self.latency_log: List[float] = []
        self.audit_log = logging.getLogger("clone_audit")
        self.audit_log.setLevel(logging.INFO)
        handler = logging.StreamHandler()
        handler.setFormatter(logging.JSONFormatter())
        self.audit_log.addHandler(handler)

    def clone_flow(self, source_id: str, new_name: str) -> Dict[str, Any]:
        self.total_attempts += 1
        start_time = time.perf_counter()

        try:
            # Step 1: Fetch and construct
            source_flow = self.cloner.fetch_flow(source_id)
            payload = self.cloner.construct_clone_payload(source_flow, new_name)

            # Step 2: Validate
            self.validator.validate_node_count(payload)
            self.validator.detect_circular_dependencies(payload)
            self.validator.verify_variable_scope(payload)

            # Step 3: Deploy
            result = self.deployer.deploy_clone(payload)

            # Step 4: Metrics and Webhook
            latency = time.perf_counter() - start_time
            self.latency_log.append(latency)
            self.success_count += 1

            self._trigger_webhook(result, latency)
            self._write_audit_log(source_id, result["id"], latency, "SUCCESS")

            return result

        except Exception as e:
            latency = time.perf_counter() - start_time
            self._write_audit_log(source_id, None, latency, "FAILURE", str(e))
            raise

    def _trigger_webhook(self, flow_data: Dict[str, Any], latency: float) -> None:
        payload = {
            "event": "flow_cloned",
            "flow_id": flow_data["id"],
            "flow_name": flow_data["name"],
            "latency_ms": round(latency * 1000, 2),
            "timestamp": datetime.now(timezone.utc).isoformat()
        }
        httpx.post(self.webhook_url, json=payload, timeout=10.0)

    def _write_audit_log(self, source_id: str, target_id: Optional[str], latency: float, status: str, error: str = None) -> None:
        self.audit_log.info({
            "event": "flow_clone_attempt",
            "source_id": source_id,
            "target_id": target_id,
            "status": status,
            "latency_ms": round(latency * 1000, 2),
            "success_rate": f"{self.success_count}/{self.total_attempts}",
            "error": error
        })

    def get_metrics(self) -> Dict[str, float]:
        avg_latency = sum(self.latency_log) / len(self.latency_log) if self.latency_log else 0.0
        return {
            "total_clones": self.total_attempts,
            "successful_clones": self.success_count,
            "success_rate": self.success_count / self.total_attempts if self.total_attempts > 0 else 0.0,
            "average_latency_ms": round(avg_latency * 1000, 2)
        }

Complete Working Example

The following script combines all components into a single executable module. Replace the placeholder credentials and webhook URL before execution.

import sys
import json

def main():
    # Configuration
    TENANT = "your-tenant"
    CLIENT_ID = "your-client-id"
    CLIENT_SECRET = "your-client-secret"
    SOURCE_FLOW_ID = "5f9a8b7c6d5e4f3a2b1c0d9e"
    NEW_FLOW_NAME = "Production-Clone-Flow-v2"
    WEBHOOK_URL = "https://your-vcs-webhook.example.com/api/flows/sync"

    # Initialize components
    auth = CognigyAuth(TENANT, CLIENT_ID, CLIENT_SECRET)
    orchestrator = CloneOrchestrator(auth, WEBHOOK_URL)

    try:
        print("Initiating flow cloning process...")
        result = orchestrator.clone_flow(SOURCE_FLOW_ID, NEW_FLOW_NAME)
        print(f"Clone successful. New Flow ID: {result['id']}")
        print(f"Metrics: {json.dumps(orchestrator.get_metrics(), indent=2)}")
    except ValueError as ve:
        print(f"Validation Error: {ve}")
        sys.exit(1)
    except ConflictError as ce:
        print(f"Conflict Error: {ce}")
        sys.exit(2)
    except Exception as e:
        print(f"Unexpected Error: {e}")
        sys.exit(3)

if __name__ == "__main__":
    main()

Common Errors and Debugging

Error: 400 Bad Request

• What causes it: The payload violates Cognigy.AI schema validation. Common triggers include missing startNode, invalid node types, or undefined variable references.
• How to fix it: Verify the verify_variable_scope output matches your flow configuration. Ensure all nodes contain required type and config fields.
• Code showing the fix:

# Add explicit schema check before deployment
if "startNode" not in payload or not payload["startNode"]:
    raise ValueError("Payload missing startNode identifier")

Error: 409 Conflict

• What causes it: A flow with the same name or identifier already exists in the target environment, or the graph engine detects overlapping resource locks.
• How to fix it: Append a timestamp or unique suffix to the new_name parameter. Ensure duplicateDirective does not trigger webhook deduplication rules.
• Code showing the fix:

import datetime
new_name = f"{base_name}_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}"

Error: 429 Too Many Requests

• What causes it: Cognigy.AI enforces strict rate limits on flow creation endpoints. Rapid cloning attempts trigger backpressure.
• How to fix it: The FlowDeployer class implements exponential backoff. Increase max_retries or add a fixed delay between bulk operations.
• Code showing the fix:

# In deploy_clone loop
if response.status_code == 429:
    retry_after = int(response.headers.get("Retry-After", 2 ** attempt))
    time.sleep(retry_after)
    continue

Error: 500 Internal Server Error

• What causes it: Graph engine constraints are violated during serialization, typically due to malformed edge references or unsupported node configurations.
• How to fix it: Validate edge from and to references exist in the node matrix before POST. Ensure all node IDs are valid UUIDs.
• Code showing the fix:

# Pre-flight reference verification
node_ids = {n["id"] for n in payload["nodes"]}
for edge in payload["edges"]:
    if edge["from"] not in node_ids or edge["to"] not in node_ids:
        raise ValueError(f"Orphaned edge reference: {edge}")

Official References

• Cognigy.AI REST API v1 Documentation
• Flow Management Endpoints
• OAuth 2.0 Authentication Guide
• Graph Engine Constraints and Limits