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Module provider

vtcode_core::llm

Module provider 

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Universal LLM provider abstraction with API-specific role handling

This module provides a unified interface for different LLM providers (OpenAI, Anthropic, Gemini) while properly handling their specific requirements for message roles and tool calling.

§Message Role Mapping

Different LLM providers have varying support for message roles, especially for tool calling:

§OpenAI API

  • Full Support: system, user, assistant, tool
  • Tool Messages: Must include tool_call_id to reference the original tool call
  • Tool Calls: Only assistant messages can contain tool_calls

§Anthropic API

  • Standard Roles: user, assistant
  • System Messages: Can be hoisted to system parameter or treated as user messages
  • Tool Responses: Converted to user messages (no separate tool role)
  • Tool Choice: Supports auto, any, tool, none modes

§Gemini API

  • Conversation Roles: Only user and model (not assistant)
  • System Messages: Handled separately as systemInstruction parameter
  • Tool Responses: Converted to user messages with functionResponse format
  • Function Calls: Uses functionCall in model messages

§Best Practices

  1. Always use MessageRole::tool_response() constructor for tool responses
  2. Validate messages using validate_for_provider() before sending
  3. Use appropriate role mapping methods for each provider
  4. Handle provider-specific constraints (e.g., Gemini’s system instruction requirement)

§Example Usage

use vtcode_core::llm::provider::{Message, MessageRole};

// Create a proper tool response message
let tool_response = Message::tool_response(
    "call_123".to_string(),
    "Tool execution completed successfully".to_string()
);

// Validate for specific provider
tool_response.validate_for_provider("openai").unwrap();

Structs§

AnthropicRequestOverrides
CodingAgentSettings
Settings to refine model behavior for coding agent tasks
FunctionCall
Function call within a tool call
FunctionDefinition
Function definition within a tool
GrammarDefinition
Grammar definition for GPT-5 context-free grammar (CFG) constraints
LLMErrorMetadata
LLMRequest
Universal LLM request structure
LLMResponse
Universal LLM response structure
Message
Universal message structure supporting both text and image content
ParallelToolConfig
Configuration for parallel tool use behavior Based on Anthropic’s parallel tool use guidelines
PreparedResponsesRequest
ProviderCapabilities
Cached provider capabilities to reduce repeated trait method calls
ResponsesCompactionOptions
Optional overrides for standalone Responses compaction requests.
ResponsesContinuationState
ShellToolDefinition
Shell tool definition for GPT-5.1 shell tool type Allows controlled command-line interface interactions
SpecificFunctionChoice
Specific function choice details
SpecificToolChoice
Specific tool choice for forcing a particular function call
ToolCall
Universal tool call that matches OpenAI/Anthropic/Gemini specifications
ToolDefinition
Universal tool definition that matches OpenAI/Anthropic/Gemini specifications Based on official API documentation from Context7
Usage

Enums§

AnthropicOptionalStringOverride
AnthropicOptionalU32Override
AnthropicThinkingDisplayOverride
AnthropicThinkingModeOverride
AssistantPhase
Phase metadata for assistant messages in multi-step Responses-style workflows.
ContentPart
Content type for messages that can include both text and images
FinishReason
LLMError
LLM error types with optional provider metadata
LLMStreamEvent
MessageContent
MessageRole
NormalizedStreamEvent
PromptCacheProfile
ToolChoice
Tool choice configuration that works across different providers Based on OpenAI, Anthropic, and Gemini API specifications Follows Anthropic’s tool use best practices for optimal performance
ToolSearchAlgorithm
Tool search algorithm for Anthropic’s advanced-tool-use beta

Traits§

LLMProvider
Universal LLM provider trait

Functions§

get_cached_capabilities
Extract and cache provider capabilities for a given provider and model
prepare_openai_responses_request
prepare_responses_continuation_request
responses_continuation_key
supports_responses_chaining
uses_incremental_responses_history

Type Aliases§

BorrowedLLMStream
LLMNormalizedStream
LLMStream