llm_service.rs — Multi-Provider Inference & Routing

The llm_service.rs module powers Oxyde’s dynamic routing across multiple LLMs. It supports OpenAI, Groq, Anthropic, xAI, Perplexity, and more — with a uniform trait interface.

🌐 Core Trait

trait LLMProvider {
    fn generate(&self, prompt: &str, stream: bool) -> Result<String>;
    fn name(&self) -> &'static str;
}

Each provider implements this trait with their own:

• HTTP client

• Token limits

• Streaming options

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🧭 Provider Selection Logic

Oxyde includes a router that picks a provider based on:

Factor	Notes
Prompt length	Short prompts → low-latency models (Groq)
Emotion state	Aggressive tone → model with higher creativity
API availability	Fall back if 429 errors occur
Config weights	You can hard-prefer OpenAI, etc.

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🔁 Routing Example

let model = router.select_provider(&agent.emotion, &prompt);
let result = model.generate(&prompt, stream = false)?;

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🔒 Rate Limiting & Failover

If a provider returns:

• HTTP 429 → retry with exponential backoff

• HTTP 5xx → fallback to next preferred model

You can also implement caching or queueing middleware here.

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🔊 Streaming Support

If stream = true, providers return output token-by-token:

"Y... You shouldn't have come here..."

This is handled via futures::Stream in async Rust.

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🧩 Adding a New Provider

Just implement the LLMProvider trait:

pub struct MyCustomLLM { /* ... */ }

impl LLMProvider for MyCustomLLM {
    fn generate(&self, prompt: &str, stream: bool) -> Result<String> {
        // call your API here
    }
    fn name(&self) -> &'static str { "MyLLM" }
}

Then add to the router map in llm_service.rs.