The Tyk AI Studio Proxy is the central gateway for all Large Language Model (LLM) interactions within the platform. It acts as a secure, observable, and policy-driven entry point, managing requests from client applications to the configured backend LLM services.

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Purpose

The Proxy serves several critical functions:
  • Unified Access Point: Provides a single, consistent endpoint for applications to interact with various LLMs.
  • Security Enforcement: Handles authentication, authorization, and applies security policies.
  • Policy Management: Enforces rules related to budget limits, model access, and applies custom Filters.
  • Observability: Logs detailed analytics data for each request, feeding the Analytics & Monitoring system.
  • Vendor Abstraction: Hides the complexities of different LLM provider APIs, especially through the OpenAI-compatible endpoint.

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Core Functions

  1. Request Routing: Incoming requests include a routeId in their path (e.g., /proxy/{routeId}/... or /openai/{routeId}/...). The Proxy uses this routeId to identify the target LLM Configuration and route the request accordingly.
  2. Authentication & Authorization:
    • Validates the API key provided by the client application.
    • Identifies the associated Application and User.
    • Checks if the Application/User group has permission to access the requested LLM Configuration based on RBAC rules.
  3. Policy Enforcement: Before forwarding the request to the backend LLM, the Proxy enforces policies defined in the LLM Configuration or globally:
    • Budget Checks: Verifies if the estimated cost exceeds the configured Budgets for the App or LLM.
    • Model Access: Ensures the requested model is allowed for the specific LLM configuration.
    • Filters: Applies configured request Filters to modify the incoming request payload.
  4. Analytics Logging: After receiving the response from the backend LLM (and potentially applying response Filters), the Proxy logs detailed information about the interaction (user, app, model, tokens used, cost, latency, etc.) to the Analytics database.

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Endpoints

Tyk AI Studio typically exposes two primary types of proxy endpoints:

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1. OpenAI-Compatible Endpoint (/openai/{routeId}/v1/...)

  • Purpose: This endpoint mimics the official OpenAI API structure. It allows developers to use standard OpenAI SDKs (Python, Node.js, etc.) to interact with any LLM configured in Tyk AI Studio, regardless of the actual backend vendor (Anthropic, Google Vertex AI, etc.).
  • Translation: Tyk AI Studio includes a translation layer (using libraries like langchaingo) that converts standard OpenAI API requests into the format required by the target backend LLM (defined in the {routeId} configuration) and translates the backend LLM’s response back into the standard OpenAI format.
  • Benefits: Simplifies integration significantly, allowing developers to write code once and target multiple LLM backends managed by Tyk AI Studio. 
    # Example using OpenAI Python SDK
import openai

client = openai.OpenAI(
    base_url="https://your-ai-studio-host/openai/my-anthropic-config/v1",
    api_key="YOUR_AI_STUDIO_APP_API_KEY"
)

response = client.chat.completions.create(
    model="claude-3-opus-20240229", # Model allowed in 'my-anthropic-config'
    messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)

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2. Direct Proxy Endpoint (/proxy/{routeId}/...)

  • Purpose: Provides a more direct pass-through to the backend LLM, potentially with less translation than the OpenAI-compatible endpoint. The exact request/response format expected at this endpoint might depend more heavily on the specific backend LLM vendor configured for the {routeId}.
  • Usage: Might be used for accessing vendor-specific features not covered by the OpenAI API standard or in scenarios where the OpenAI translation layer is not desired.

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Configuration & Security

The behavior of the Proxy for a specific route is determined by the corresponding LLM Configuration, which includes details about the backend vendor, model access, budget limits, and associated filters. By centralizing LLM access through the Proxy, Tyk AI Studio provides a robust layer for security, control, and observability over AI interactions.