Allow runtime model capability declaration via DSN syntax

[OskarStark]

Problem

When AI models gain new capabilities that are already supported by our platform, users cannot use them without a library release. Example: Platform supports tool-calling, model initially doesn't. When model gains tool-calling support, users must wait for a library update to use it.

Proposed Solution

Allow users to declare model capabilities at runtime using DSN syntax:

model-name@capability1,capability2,capability3

As a bonus we could get rid of all the model classes.

Examples

Scenario

Platform supports: input-image, tool-calling, output-streaming
Model GPT-4 initially supports: input-image
Model GPT-4 later adds: tool-calling (no library release needed!)

// Before: Limited to hardcoded capabilities in library
$model = 'gpt-4';  // Only uses capabilities defined in library code

// After: User can declare newly supported capabilities
$model = 'gpt-4@tool-calling';  // Uses tool-calling without library update

Usage Examples

// Enable single capability
'gpt-4@tool-calling'
// Enable multiple capabilities  
'claude-3@tool-calling,output-streaming'
// Enable multiple capabilities
'gpt-4o@input-image,tool-calling,output-streaming'
// No additional capabilities (default behavior)
'gpt-4'

Available Capabilities (from Capability enum)

• input-audio, input-image, input-messages, input-multiple, input-pdf, input-text
• output-audio, output-image, output-streaming, output-structured, output-text
• tool-calling
• text-to-speech, speech-to-text

Benefits

• Zero-day capability adoption: Use new model capabilities immediately when API supports them
• No library releases needed for capability updates
• Forward compatible: Platform already knows the capability, just needs model declaration
• Backward compatible: Models without @ work as before

Bundle

In the bundle it could look like:

ai:
    agent:
        my_agent:
            platform: 'ai.platform.openai'
-            model:
-                class: 'Symfony\AI\Platform\Bridge\OpenAi\Gpt'
-                name: 'gpt-4.1-mini'
+            model: 'gpt-4.1-mini@tool-calling'

Note

• API validates if model supports requested capabilities and returns meaningful errors if not supported.
• You cannot forbid certain capabilities or limit the model to some specific capabilitites as those are implemented on platform level.

---

EDIT:

Updated Proposal: Extended Configuration Support

Based on community feedback, the proposal has been extended to include configuration parameters alongside capabilities. The DSN syntax now supports:

1. Capabilities Declaration (original proposal): Use @ followed by comma-separated capabilities
   • Example: gpt-4@tool-calling,streaming
2. Configuration Parameters (new addition): Use ? followed by query-string style parameters
   • Example: gpt-4?temperature=0.5&max_tokens=1000
3. Combined Usage: Both capabilities and parameters can be used together
   • Example: gpt-4@tool-calling?temperature=0.5
     This enhancement allows for complete runtime configuration of AI models, including both feature capabilities and operational parameters, all within a single, familiar DSN-like string format. The syntax follows established conventions (similar to database DSNs) making it intuitive for developers while providing maximum flexibility for model configuration.

[chr-hertel]

Yes please, let's ease configuration here

What do you think about adding simple options here as well, like temperature=0.5

[OskarStark]

What do you think about adding simple options here as well, like temperature=0.5

Yes, like gpt-4.1-mini@tool-calling?temperature=0.5 👍

[OskarStark]

Issue body updated ✅

[chr-hertel]

Another item we could tackle instead is to connect to model source/catalogs like this one provided by LiteLLM:

• https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json
• https://models.litellm.ai/

so we would offload the work and make it more universal

(credits for this idea go to James Abrahams of Drupal AI initiative)

[alexfinnarn]

I'm trying to follow this project from using Ruby LLM to make a ChatGPT-like clone in Ruby on Rails. Even though my background is in PHP, I have gotten decently far and generally like how Ruby LLM sets things up.

They have a Model Registry: https://rubyllm.com/models/ and a task to rebuild it devs can call to refresh the registry. Uses an API from "Parsera", I guess.

Just wanted to provide another example for you to look at. Keep up the good work!