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Models

The Models page in the PinionAI Studio interface is dedicated to defining and managing the Large Language Models (LLMs) available to your agents. This allows for fine-grained control over model versions, providers, local hosting configurations, cost tracking, and rate limits.

Prerequisites

Before you can manage Models, ensure the following conditions are met:

  1. You must be logged into the application.
  2. Your user role must have the necessary permissions (owner, admin, editor, or models).
  3. You must have an Account selected from the sidebar.

Page Overview

The Models page is divided into two main sections:

  1. Add Model: An expandable form for creating new model configurations.
  2. Models List: A list of existing models associated with the selected account and agent, providing details on status, provider, and capabilities.

Creating a New Model

To create a new model:

  1. Navigate to the Models page.
  2. Expand the "New Model" section.
  3. Fill out the configuration fields described below.
  4. Click Create Model.

Configuration Fields

Basic Information

  • Name: A unique name for the model configuration (e.g., Gemini 2.0 Pro - Production).
  • Model Value: The specific identifier required by the provider (e.g., gemini-2.0-pro-exp-02-05, gpt-4o).
  • Status: Toggle to enable or disable the model.
  • Agent(s): Associate this model configuration with specific agents. Select "All" to make it globally available within the account.
  • Provider: The model service provider (e.g., google, openAI, anthropic, deepseek, meta, selected_agent_name,mistral).
  • Model Type: Defines the hosting environment (cloud, local, ip, huggingface, custom).

Connection & Security

  • Connector: Select a Connector that provides the necessary API keys or Service Account credentials for this model.
  • Endpoint: The URL or path for local or IP-based models (e.g., http://localhost:11434 for Ollama).
  • Port: The port number for IP-based models.
  • Protocol: The communication protocol (http, https, grpc websocket).
  • SSL Verify: Toggle whether to verify SSL certificates for custom endpoints.
  • Version: Optional release or version string of the model.

Capabilities

  • Capabilities: Multi-select of features supported by the model (text, vision, audio, file, function-calling, reasoning).
  • Supports Vision/Audio/File: Explicit toggles for multimodal capabilities.
  • Supports Function Calling: Enable if the model supports tool use.
  • Supports Reasoning: Enable for models with dedicated reasoning chains (e.g., "Thinking" models).
  • Supports Streaming: Enable if the model endpoint supports real-time token streaming.
  • Supports JSON Mode: Enable if the model can be forced into strict JSON output mode.

Performance & Limits

  • Max Tokens: Maximum context window supported by the model.
  • Max Input/Output Tokens: Specific limits for prompt and response lengths.
  • Rate Limits:
  • RPS: Requests Per Second.
  • RPM: Requests Per Minute.
  • Daily: Maximum requests allowed in a 24-hour period.
  • Timeout: Seconds to wait for a model response before failing.
  • Retry Logic: Configure Retry Attempts and Backoff (ms) for handling transient errors.

Cost Tracking

  • Input/Output Cost/Token: Decimal values representing the cost per token (e.g., 0.0000025).
  • Cache Creation/Read Cost: Costs associated with context caching if supported.

Advanced Configuration

  • Custom Headers (JSON): Additional HTTP headers required for custom API endpoints.
  • Model Config JSON: Flexible storage for provider-specific configurations.
  • Model Params JSON: Additional model parameters (e.g., default top_p, top_k, repetition_penalty).

Listing and Managing Models

The Models List section displays all models associated with the selected criteria:

  • Filtering: The list respects the agent selection in the sidebar.
  • Details: Expanding a model entry reveals its full configuration, including connection details, costs, and limits.
  • Edit: Click the edit icon to modify any aspect of the model configuration.
  • Delete: Remove a model configuration from the account.

Usage Examples

Example 1: Google Gemini 3.1 Flash lite (Cloud)

Used for quick conversational agents and classification leveraging Google's infrastructure.

  • Type: cloud
  • Provider: google
  • Model Value: gemini-3.1-flash-lite
  • Connector: My Google Cloud Connector

Example 2: Local Gemma4 3 via Ollama

Ideal for private processing on local hardware.

  • Type: local
  • Protocol: ollama
  • Endpoint: http://localhost:11434
  • Model Value: gemma4:12b

Example 3: Reasoning Model (GPT-o1)

Used for complex problem solving requiring deep thought chains.

  • Provider: openAI
  • Model Value: o1-preview
  • Supports Reasoning: True
  • Capabilities: text, reasoning