# Configuration
## AgentLoopConfig
The main configuration for the agent loop:
```rust
pub struct AgentLoopConfig {
pub provider: Arc<dyn StreamProvider>,
pub model: String,
pub api_key: String,
pub thinking_level: ThinkingLevel,
pub max_tokens: Option<u32>,
pub temperature: Option<f32>,
pub model_config: Option<ModelConfig>,
pub convert_to_llm: Option<ConvertToLlmFn>,
pub transform_context: Option<TransformContextFn>,
pub get_steering_messages: Option<GetMessagesFn>,
pub get_follow_up_messages: Option<GetMessagesFn>,
pub context_config: Option<ContextConfig>,
pub compaction_strategy: Option<Arc<dyn CompactionStrategy>>,
pub execution_limits: Option<ExecutionLimits>,
pub cache_config: CacheConfig,
pub tool_execution: ToolExecutionStrategy,
pub retry_config: RetryConfig,
pub before_turn: Option<BeforeTurnFn>,
pub after_turn: Option<AfterTurnFn>,
pub on_error: Option<OnErrorFn>,
pub input_filters: Vec<Arc<dyn InputFilter>>,
pub turn_delay: Option<Duration>,
}
```
## StreamConfig
Passed to `StreamProvider::stream()`:
```rust
pub struct StreamConfig {
pub model: String,
pub system_prompt: String,
pub messages: Vec<Message>,
pub tools: Vec<ToolDefinition>,
pub thinking_level: ThinkingLevel,
pub api_key: String,
pub max_tokens: Option<u32>,
pub temperature: Option<f32>,
pub model_config: Option<ModelConfig>,
pub cache_config: CacheConfig,
}
```
## ContextConfig
Controls context window compaction:
```rust
pub struct ContextConfig {
pub max_context_tokens: usize, // Default: 100,000
pub system_prompt_tokens: usize, // Default: 4,000
pub keep_recent: usize, // Default: 10
pub keep_first: usize, // Default: 2
pub tool_output_max_lines: usize, // Default: 200
pub tool_output_max_lines_overrides: HashMap<String, usize>, // Default: {"read_file": MAX}
pub compact_target_ratio: f32, // Default: 0.7
pub compact_headroom_turns: Option<usize>, // Default: Some(30)
pub truncate_tool_output_on_append: bool, // Default: true
}
```
`compact_headroom_turns` sets the compaction target from observed growth (`target = budget − turns × growth_per_turn`), keeping the interval between compactions constant as a session lengthens; `compact_target_ratio` is the fallback and a ceiling on retention. `truncate_tool_output_on_append` caps tool output as it enters the context rather than retroactively, and `tool_output_max_lines_overrides` gives per-tool budgets so a tool that head+tail would damage (a paging reader) can opt out. All three exist to keep the provider's prefix cache intact — see [Context Management](../concepts/context-management.md#prefix-cache-stability).
When `context_config` is not explicitly set, it is automatically derived from `ModelConfig.context_window` (80% for context, 20% reserved for output). If neither is set, `ContextConfig::default()` (100K) is used.
```rust
// Derive from a model's context window:
let config = ContextConfig::from_context_window(200_000);
// config.max_context_tokens == 160_000
```
## ExecutionLimits
Prevents runaway agents:
```rust
#[non_exhaustive] // build with Default::default() + with_*
pub struct ExecutionLimits {
pub max_turns: usize, // Default: 50
pub max_total_tokens: usize, // Default: 1,000,000
pub max_duration: Duration, // Default: 600s
pub max_consecutive_identical_tool_calls: Option<usize>, // Default: Some(3)
}
```
```rust
ExecutionLimits::default()
.with_max_turns(20)
.with_max_consecutive_identical_tool_calls(None) // disable loop detection
```
## ThinkingLevel
```rust
pub enum ThinkingLevel {
Off, // No thinking (default)
Minimal, // Anthropic: effort "low" (adaptive) / 1,024-token budget (legacy)
Low, // Anthropic: effort "low" / 1,024
Medium, // Anthropic: effort "medium" / 2,048
High, // Anthropic: effort "high" / 8,192
}
```
OpenAI-family providers map these levels to `reasoning_effort` where the
compat flags enable it; the Google and Bedrock providers currently ignore
`thinking_level`.
## CostConfig
Token pricing per million:
```rust
#[non_exhaustive] // build with new() + with_*, not a literal
pub struct CostConfig {
pub input_per_million: f64,
pub output_per_million: f64,
pub cache_read_per_million: f64,
pub cache_write_per_million: f64,
pub context_tiers: Vec<ContextTier>, // empty = one flat rate at every size
}
```
Cache rates are set with builders rather than positionally. Four same-typed
`f64` arguments in a row is a transposition hazard, and no vendor publishes them
in one order — Anthropic lists input / cache-write / cache-read / output, OpenAI
lists input / cached-input / output:
```rust
CostConfig::new(5.0, 30.0) // input, output — output is always dearer
.with_cache_read(0.5)
.with_cache_write(6.25)
```
All-zero rates mean **pricing unknown**, not free. `is_configured()` reports
which, and `session_cost_usd()` returns `None` for an unpriced model rather than
$0.
### Context tiers
Some vendors charge more above a prompt-size threshold. `cost_usd` selects by
the request's **prompt** tokens (`input + cache_read + cache_write`), so a long
reply to a short prompt stays on the base rate:
```rust
CostConfig::new(5.0, 30.0)
.with_context_tier(ContextTier::new(272_000, 10.0, 45.0).with_cache_read(1.0))
```
Tiers are kept sorted, and `cost_usd` takes the last one the prompt clears, so a
multi-step schedule works. **No shipped preset sets one** — see
`ModelConfig::gpt_5_5`'s docs for why the one candidate stayed flat.
One caveat if you add a tier: prompt size is derived as
`input + cache_read + cache_write`, which holds only where the provider
subtracts cached tokens out of `input`. `bedrock.rs` populates neither cache
field, so a heavily-cached prompt reads small there.
## ModelConfig Presets
yoagent provides first-class `ModelConfig::*` constructors for Anthropic, OpenAI, Google Gemini, xAI, Groq, DeepSeek, Mistral, MiniMax, Z.ai, Qwen, Ollama, and local OpenAI-compatible servers.
See [Model Presets](../providers/model-presets.md) for the full table of constructors, default base URLs, context windows, and DeepSeek legacy alias notes.