const ants = new AgenticAnts({ apiKey: process.env.AGENTICANTS_API_KEY }) const llm = new ChatOpenAI({ callbacks: [new AgenticAntsCallbackHandler(ants)] }) // All LLM calls automatically traced! const response = await llm.call([ { role: 'user', content: 'What is AI?' } ])

Python with AutoGen

python

from agenticants import AgenticAnts from agenticants.integrations import autogen ants = AgenticAnts(api_key=os.getenv('AGENTICANTS_API_KEY')) autogen.instrument(ants) # All AutoGen agents automatically traced! agent = ag.AssistantAgent( name="assistant", llm_config={"model": "gpt-4"} )

Java with Spring Boot

java

@Service public class AgentService { private final AntsPlatformClient client; public AgentService() { this.client = AntsPlatformClient.builder() .url("https://api.agenticants.ai") .credentials( System.getenv("ANTS_PLATFORM_PUBLIC_KEY"), System.getenv("ANTS_PLATFORM_SECRET_KEY") ) .build(); } // All agent operations automatically traced! public String processQuery(String query) { // Your agent logic here } }

No-Code with Flowise

yaml

# In Flowise, add AgenticAnts node: 1. Drag "AgenticAnts" node to canvas 2. Connect to your flow 3. Configure API key 4. All flows automatically monitored!

Integration Benefits

Automatic Instrumentation

Most integrations provide zero-code instrumentation:

python

# Just enable the integration from agenticants.integrations import langchain langchain.auto_instrument() # Now all LangChain calls are automatically traced! from langchain import OpenAI llm = OpenAI() llm("Hello") # Automatically traced

Comprehensive Coverage

Track everything:

LLM calls - Model, tokens, cost, latency
Vector searches - Queries, results, embeddings
Tool usage - Function calls and outputs
Agent decisions - Reasoning and actions
Multi-agent interactions - Collaboration flows

Rich Context

Integrations capture framework-specific data:

typescript

// LangChain callback provides: { chain_type: 'ConversationalRetrievalChain', retriever_docs: 5, prompt_template: '...', llm_output: {...}, memory_messages: [...] } // AutoGen integration provides: { agent_name: 'coder', message_type: 'code_execution', conversation_history: [...], code_executed: '...', execution_result: '...' }

Choosing an Integration

Start with SDKs

For full control and customization:

JavaScript/TypeScript SDK - Web apps, Node.js services
Python SDK - Data science, ML pipelines
Java SDK - Enterprise applications, Spring Boot services
OpenTelemetry - Multi-language, standardized

Use Framework Integrations

For quick setup with existing code:

LangChain - Most popular LLM framework
LlamaIndex - RAG and data apps
AutoGen - Multi-agent systems

Try No-Code Tools

For rapid prototyping:

Flowise - Visual flow builder
Langflow - Drag-and-drop interfaces
Dify.AI - Complete platform

Migration Paths

From OpenAI to AgenticAnts

typescript

// Before const openai = new OpenAI() const response = await openai.chat.completions.create({...}) // After - Add AgenticAnts with one line const ants = new AgenticAnts({ apiKey: process.env.AGENTICANTS_API_KEY }) const openai = ants.wrap(new OpenAI()) // Automatically traced! const response = await openai.chat.completions.create({...})

From LangSmith to AgenticAnts

python

# Before - LangSmith from langsmith import Client client = Client() # After - AgenticAnts (drop-in replacement) from agenticants import AgenticAnts from agenticants.integrations import langchain ants = AgenticAnts(api_key=os.getenv('AGENTICANTS_API_KEY')) langchain.auto_instrument() # Same API, better insights!

Integration Support

Community Support

Discord: Join our Discord
GitHub: Report issues
Documentation: Comprehensive guides for each integration

Enterprise Support

Dedicated support team
Custom integrations built for you
Migration assistance from other platforms
Training and onboarding

Request an Integration

Don't see your tool? Let us know!

bash

# Via CLI ants integrations request --tool "YourTool" --priority high # Via API curl -X POST https://api.agenticants.ai/v1/integrations/requests \ -H "Authorization: Bearer $API_KEY" \ -d '{"tool": "YourTool", "use_case": "..."}'

Next Steps

Choose your integration and get started:

Start with LangChain →

Use Python SDK →