Wrapper that adds reliability features to any LLMClient.
Provides:
- Retry with configurable policies (exponential backoff, linear, fixed)
- Circuit breaker to fail fast when service is down
- Deadline enforcement to prevent hanging operations
- Metrics tracking for retry attempts and circuit breaker state
Thread-safety: Uses AtomicInteger/AtomicReference for circuit breaker state management to ensure correct behavior under concurrent access.
Value parameters
- collector
-
Optional metrics collector for observability
- config
-
Reliability configuration
- providerName
-
Explicit provider name for stable metrics labels
- underlying
-
The client to wrap
Attributes
- Companion
- object
- Graph
-
- Supertypes
Members list
Value members
Concrete methods
Releases resources and closes connections to the LLM provider.
Releases resources and closes connections to the LLM provider.
Call when the client is no longer needed. After calling close(), the client should not be used. Default implementation is a no-op; override if managing resources like connections or thread pools.
Attributes
- Definition Classes
-
LLMClient -> AutoCloseable
Executes a blocking completion request and returns the full response.
Executes a blocking completion request and returns the full response.
Sends the conversation to the LLM and waits for the complete response. Use when you need the entire response at once or when streaming is not required.
Value parameters
- conversation
-
conversation history including system, user, assistant, and tool messages
- options
-
configuration including temperature, max tokens, tools, etc. (default: CompletionOptions())
Attributes
- Returns
-
Right(Completion) with the model's response, or Left(LLMError) on failure
- Definition Classes
Get current circuit breaker state (for testing/monitoring).
Get current circuit breaker state (for testing/monitoring).
Attributes
Returns the maximum context window size supported by this model in tokens.
Returns the maximum context window size supported by this model in tokens.
The context window is the total tokens (prompt + completion) the model can process in a single request, including all conversation messages and the generated response.
Attributes
- Returns
-
total context window size in tokens (e.g., 4096, 8192, 128000)
- Definition Classes
Returns the number of tokens reserved for the model's completion response.
Returns the number of tokens reserved for the model's completion response.
This value is subtracted from the context window when calculating available tokens for prompts. Corresponds to the max_tokens or completion token limit configured for the model.
Attributes
- Returns
-
number of tokens reserved for completion
- Definition Classes
Reset circuit breaker state (for testing).
Reset circuit breaker state (for testing).
Attributes
Executes a streaming completion request, invoking a callback for each chunk as it arrives.
Executes a streaming completion request, invoking a callback for each chunk as it arrives.
Streams the response incrementally, calling onChunk for each token/chunk received. Enables real-time display of responses. Returns the final accumulated completion on success.
Value parameters
- conversation
-
conversation history including system, user, assistant, and tool messages
- onChunk
-
callback invoked for each chunk; called synchronously, avoid blocking operations
- options
-
configuration including temperature, max tokens, tools, etc. (default: CompletionOptions())
Attributes
- Returns
-
Right(Completion) with the complete accumulated response, or Left(LLMError) on failure
- Definition Classes
Validates client configuration and connectivity to the LLM provider.
Validates client configuration and connectivity to the LLM provider.
May perform checks such as verifying API credentials, testing connectivity, and validating configuration. Default implementation returns success; override for provider-specific validation.
Attributes
- Returns
-
Right(()) if validation succeeds, Left(LLMError) with details on failure
- Definition Classes
Inherited methods
Calculates available token budget for prompts after accounting for completion reserve and headroom.
Calculates available token budget for prompts after accounting for completion reserve and headroom.
Formula: (contextWindow - reserveCompletion) * (1 - headroom)
Headroom provides a safety margin for tokenization variations and message formatting overhead.
Value parameters
- headroom
-
safety margin as percentage of prompt budget (default: HeadroomPercent.Standard ~10%)
Attributes
- Returns
-
maximum tokens available for prompt content
- Inherited from:
- LLMClient