Overview

The AI Agent Stack Builder is an intelligent recommendation engine designed to help development teams select the optimal technology stack for building AI agents. By analyzing project requirements—including type, expected user load, budget constraints, latency requirements, deployment preferences, and team expertise—the system provides curated recommendations for frameworks, large language models (LLMs), and supporting technologies.

This tool addresses a critical pain point in modern AI development: the overwhelming number of choices when building agent-based systems. Whether you're developing a customer service chatbot, autonomous research agent, or data analysis tool, the Stack Builder evaluates your unique constraints and generates a prioritized set of recommendations tailored to your situation.

The API is ideal for development teams, AI architects, technical leads, and organizations evaluating AI agent solutions who need objective, data-driven guidance on technology selection aligned with their specific operational and business constraints.

Usage

Sample Request:

{
  "formData": {
    "projectType": "customer_service_chatbot",
    "userLoad": "high",
    "budget": "medium",
    "latency": "low",
    "deployment": "cloud",
    "expertise": "intermediate",
    "capabilities": ["natural_language_understanding", "context_retention", "multi_turn_conversation"],
    "security": ["data_encryption", "role_based_access_control"],
    "additionalNotes": "Need HIPAA compliance for healthcare customer service"
  },
  "sessionId": "sess_abc123def456",
  "userId": 12345,
  "timestamp": "2024-01-15T14:30:00Z"
}

Sample Response:

{
  "recommendation": {
    "frameworks": [
      {
        "name": "LangChain",
        "priority": 1,
        "reasoning": "Excellent for multi-turn conversations with memory management and integrations",
        "suitability_score": 0.95
      },
      {
        "name": "LlamaIndex",
        "priority": 2,
        "reasoning": "Strong context retention and retrieval capabilities",
        "suitability_score": 0.88
      }
    ],
    "llms": [
      {
        "name": "GPT-4",
        "provider": "OpenAI",
        "priority": 1,
        "reasoning": "Superior NLU and context understanding for customer interactions",
        "cost_per_1m_tokens": 0.03,
        "latency_ms": 200
      },
      {
        "name": "Claude 3 Sonnet",
        "provider": "Anthropic",
        "priority": 2,
        "reasoning": "Strong privacy stance and cost-effective alternative",
        "cost_per_1m_tokens": 0.003,
        "latency_ms": 250
      }
    ],
    "supporting_technologies": [
      {
        "category": "vector_database",
        "recommendation": "Pinecone",
        "reasoning": "Managed solution suitable for cloud deployment with high availability"
      },
      {
        "category": "monitoring",
        "recommendation": "Datadog",
        "reasoning": "Comprehensive monitoring for latency-sensitive applications"
      }
    ],
    "compliance_notes": "Verify LLM provider's HIPAA BAA requirements; consider on-premise deployment for sensitive data handling",
    "estimated_monthly_cost": 1500,
    "implementation_timeline_weeks": 4
  }
}

Endpoints

GET /

Root / Health Check

Returns a health status of the API service.

Response: 200 OK

{
  "status": "healthy",
  "version": "1.0.0"
}

POST /api/agent/stack

Generate Stack Recommendation

Generates an AI agent technology stack recommendation based on project requirements and constraints.

Response: 200 OK

{
  "recommendation": {
    "frameworks": [...],
    "llms": [...],
    "supporting_technologies": [...],
    "compliance_notes": "string",
    "estimated_monthly_cost": 0,
    "implementation_timeline_weeks": 0
  }
}

Error Response: 422 Unprocessable Entity

{
  "detail": [
    {
      "loc": ["body", "formData", "projectType"],
      "msg": "field required",
      "type": "value_error.missing"
    }
  ]
}

GET /api/frameworks

Get Available Frameworks

Retrieves the list of available AI agent frameworks that the system can recommend.

Response: 200 OK

{
  "frameworks": [
    {
      "name": "LangChain",
      "version": "0.1.0",
      "category": "orchestration",
      "description": "Framework for building applications with LLMs",
      "maturity": "production"
    },
    {
      "name": "LlamaIndex",
      "version": "0.10.0",
      "category": "retrieval",
      "description": "Data framework for LLM applications",
      "maturity": "production"
    }
  ]
}

GET /api/llms

Get Available LLMs

Retrieves the list of available large language models that the system can recommend.

Response: 200 OK

{
  "llms": [
    {
      "name": "GPT-4",
      "provider": "OpenAI",
      "type": "closed_source",
      "context_window": 128000,
      "cost_per_1m_tokens": 0.03,
      "latency_ms": 200
    },
    {
      "name": "Claude 3 Opus",
      "provider": "Anthropic",
      "type": "closed_source",
      "context_window": 200000,
      "cost_per_1m_tokens": 0.015,
      "latency_ms": 300
    }
  ]
}

Pricing

About

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References

• Kong Route: https://api.mkkpro.com/creative/ai-agent-stack-builder
• API Docs: https://api.mkkpro.com:8162/docs