Feature Services Architecture

Status

Accepted (2024-02)

Context

Common LLM tasks (translation, image analysis, embeddings) require:

• Specialized prompts and configurations

• Pre/post-processing logic

• Caching strategies

• Quality control measures

Decision

Create dedicated Feature Services for high-level operations:

• CompletionService: Text generation with format control.

• EmbeddingService: Vector operations with caching.

• VisionService: Image analysis with specialized prompts.

• TranslationService: Language translation with quality scoring.

Each service:

• Uses LlmServiceManager internally.

• Provides domain-specific methods.

• Handles caching and optimization.

• Returns typed response objects.

Consequences

Positive:

• ●● Clear separation of concerns.

• ● Reusable, tested implementations.

• ●● Consistent behavior across use cases.

• ● Built-in best practices (caching, prompts).

Negative:

• ◑ Additional classes to maintain.

• ◑ Potential duplication with manager methods.

• ◑ Learning curve for service selection.

Net Score: +6.5 (Strong positive impact - services provide high-level abstractions with best practices)