Struct AnthropicProvider 

pub struct AnthropicProvider { /* private fields */ }

Implementations

impl AnthropicProvider

pub fn new(api_key: String) -> Self

pub fn from_config( api_key: Option<String>, model: Option<String>, base_url: Option<String>, prompt_cache: Option<PromptCachingConfig>, timeouts: Option<TimeoutsConfig>, anthropic_config: Option<AnthropicConfig>, model_behavior: Option<ModelConfig>, ) -> Self

pub fn with_leak_protection( &self, request: LLMRequest, secret_description: &str, ) -> LLMRequest

Prepends a non-disclosure reminder to the system prompt. No supported Claude model accepts an assistant-message prefill, so the system prompt is the only valid place for this instruction.

pub fn format_documents_xml(&self, documents: Vec<(&str, &str)>) -> String

pub fn extract_xml_block(&self, content: &str, tag: &str) -> Option<String>

Trait Implementations

impl Clone for AnthropicProvider

fn clone(&self) -> Self

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl LLMClient for AnthropicProvider

fn generate<'life0, 'life1, 'async_trait>( &'life0 mut self, prompt: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<LLMResponse, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

fn model_id(&self) -> &str

impl LLMProvider for AnthropicProvider

fn name(&self) -> &str

Provider name (e.g., “gemini”, “openai”, “anthropic”)

fn supports_streaming(&self) -> bool

Whether the provider has native streaming support

fn supports_non_streaming(&self, _model: &str) -> bool

Whether the provider can service non-streaming generation requests for the model.

fn supports_reasoning(&self, model: &str) -> bool

Whether the provider surfaces structured reasoning traces for the given model

fn supported_reasoning_efforts(&self, model: &str) -> &'static [&'static str]

Exact levels accepted by this route; providers may override catalog metadata.

fn supports_reasoning_effort(&self, model: &str) -> bool

Whether the provider accepts configurable reasoning effort for the model

fn supports_parallel_tool_config(&self, model: &str) -> bool

Whether the provider understands parallel tool configuration payloads

fn supports_context_edits(&self, _model: &str) -> bool

Whether the provider supports provider-native context editing such as tool-result clearing.

fn supports_turn_scoped_system_messages(&self, model: &str) -> bool

Whether the selected provider/model can carry Anthropic’s native turn-scoped system-message lifecycle field on the wire.

fn supports_responses_compaction(&self, model: &str) -> bool

Whether the provider supports Responses API server-side compaction.

fn supports_native_inline_compaction(&self, model: &str) -> bool

Whether the provider supports threshold-triggered inline compaction via request fields (Anthropic compact_20260112).

fn effective_context_size(&self, model: &str) -> usize

Get the effective context window size for a model.

fn supports_structured_output(&self, model: &str) -> bool

Whether the provider supports structured output (JSON schema guarantees)

fn supports_vision(&self, model: &str) -> bool

Whether the provider supports vision (image analysis) for given model

fn generate<'life0, 'async_trait>( &'life0 self, request: LLMRequest, ) -> Pin<Box<dyn Future<Output = Result<LLMResponse, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Generate completion

fn stream<'life0, 'async_trait>( &'life0 self, request: LLMRequest, ) -> Pin<Box<dyn Future<Output = Result<LLMStream, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Stream completion (optional)

fn supported_models(&self) -> Vec<String>

Get supported models

fn validate_request(&self, request: &LLMRequest) -> Result<(), LLMError>

Validate request for this provider

fn supports_decisions(&self) -> bool

Whether this instance can use the direct API-key Decisions endpoint. Capability checks must not discover credentials or dispatch requests.

fn decide_choice<'life0, 'async_trait>( &'life0 self, _request: ChoiceDecisionRequest, ) -> Pin<Box<dyn Future<Output = Result<ChoiceDecisionResponse, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Evaluate one text-only choice question. Unsupported providers do no I/O.

fn backend_kind(&self) -> BackendKind

The canonical backend kind for this provider.

fn sampling_overrides(&self, _model: &str) -> SamplingOverrides

Provider/model-specific sampling parameter overrides.

fn supports_tools(&self, _model: &str) -> bool

Whether the provider supports structured tool calling for the given model

fn supports_context_caching(&self, _model: &str) -> bool

Whether the provider supports prompt/context caching

fn supports_native_allowed_tools(&self, _model: &str) -> bool

Whether the request path can enforce a provider-native allowed_tools subset.

fn supports_manual_openai_compaction(&self, _model: &str) -> bool

Whether the provider supports the interactive manual /compact command path.

fn manual_openai_compaction_unavailable_message(&self, model: &str) -> String

Explain why the --native-only manual /compact path is unavailable.

fn compact_history<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, _model: &'life1 str, _history: &'life2 [Message], ) -> Pin<Box<dyn Future<Output = Result<Vec<Message>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Compact conversation history using provider-native Responses /compact support when available.

fn compact_history_with_options<'life0, 'life1, 'life2, 'life3, 'async_trait>( &'life0 self, _model: &'life1 str, _history: &'life2 [Message], _options: &'life3 ResponsesCompactionOptions, ) -> Pin<Box<dyn Future<Output = Result<Vec<Message>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait, 'life3: 'async_trait,

Compact conversation history with standalone Responses compaction options.

fn stream_normalized<'life0, 'async_trait>( &'life0 self, request: LLMRequest, ) -> Pin<Box<dyn Future<Output = Result<LLMNormalizedStream, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Normalized streaming contract layered on top of the legacy provider stream.

fn start_copilot_prompt_session<'a>( &'a self, _request: LLMRequest, _tools: &'a [ToolDefinition], ) -> Option<CopilotPromptSessionFuture<'a>>

Provider-specific streaming path that can service interactive runtime requests while the stream is active. Copilot uses this to bridge ACP tool calls and permission prompts back into VT Code’s turn runtime.

fn get_balance<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<Option<BalanceInfo>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Fetch account balance for this provider, if supported.