vtcode-llm 0.181.2

//! Request building for Anthropic Claude API.

mod hardening;
mod messages;
mod system;
mod thinking;
pub(crate) mod tools;

use crate::provider::{
    AnthropicOptionalStringOverride, AnthropicOptionalU32Override, AnthropicThinkingConfig, LLMError, LLMRequest,
};
use crate::providers::anthropic_types::{
    AnthropicAdvisorCaching, AnthropicAdvisorTool, AnthropicFallbackParam, AnthropicFallbacksKeyword,
    AnthropicFallbacksParam, AnthropicOutputConfig, AnthropicOutputFormat, AnthropicRequest, AnthropicTaskBudget,
    AnthropicTool, CacheControl, ThinkingConfig, ThinkingDisplay,
};
use serde_json::{Value, json};
use vtcode_config::constants::reasoning;
use vtcode_config::core::{
    AdvisorConfig, AnthropicConfig, AnthropicFallbackMode, AnthropicFallbacks, AnthropicPromptCacheSettings,
};
use vtcode_config::types::ReasoningEffortLevel;

use super::capabilities::{
    default_effort_for_model, default_max_tokens_for_model, effort_allowed_for_model, preserves_thinking_across_turns,
    rejects_forced_tool_choice, resolve_model_name, supports_assistant_prefill, supports_effort,
    supports_mid_conversation_system_messages, supports_server_side_fallback, supports_task_budget, thinking_is_on,
};
use super::prompt_cache::{get_tools_cache_ttl, messages_cache_ttl_for_profile};
use messages::{build_messages, hoist_largest_user_message};
use system::{HistorySystemPlacement, SystemPromptBuildResult, build_system_prompt};
use thinking::build_thinking_config;
pub(crate) use thinking::rewrite_thinking_for_model;
use tools::{build_tool_choice, build_tools};

#[cfg(test)]
pub(crate) use messages::tool_result_blocks;

pub(crate) struct RequestBuilderContext<'a> {
    pub(crate) prompt_cache_enabled: bool,
    pub(crate) prompt_cache_settings: &'a AnthropicPromptCacheSettings,
    pub(crate) anthropic_config: &'a AnthropicConfig,
    pub(crate) model: &'a str,
    /// Whether the endpoint accepts server-side refusal fallbacks. Only the
    /// first-party Claude API does; Bedrock, Vertex, Foundry and
    /// Anthropic-compatible third-party endpoints reject or ignore them, so
    /// the configured `provider.anthropic.fallbacks` is applied only when set.
    pub(crate) server_side_fallbacks_available: bool,
}

fn resolve_messages_ttl(request: &LLMRequest, ctx: &RequestBuilderContext<'_>) -> &'static str {
    if !ctx.prompt_cache_enabled {
        return "5m";
    }

    messages_cache_ttl_for_profile(ctx.prompt_cache_settings, request.prompt_cache_profile)
}

pub(crate) fn convert_to_anthropic_format(
    request: &LLMRequest,
    ctx: &RequestBuilderContext,
) -> Result<Value, LLMError> {
    let resolved_model = resolve_model_name(&request.model, ctx.model);
    let tools_ttl = if ctx.prompt_cache_enabled {
        get_tools_cache_ttl(ctx.prompt_cache_settings)
    } else {
        "5m"
    };

    let messages_ttl = resolve_messages_ttl(request, ctx);

    let tools_cache_control = if ctx.prompt_cache_enabled && ctx.prompt_cache_settings.cache_tool_definitions {
        Some(CacheControl {
            control_type: "ephemeral".into(),
            ttl: Some(tools_ttl.into()),
        })
    } else {
        None
    };

    let system_cache_control = if ctx.prompt_cache_enabled && ctx.prompt_cache_settings.cache_system_messages {
        Some(CacheControl {
            control_type: "ephemeral".into(),
            ttl: Some(tools_ttl.into()),
        })
    } else {
        None
    };

    let max_breakpoints = if ctx.prompt_cache_enabled {
        ctx.prompt_cache_settings.max_breakpoints as usize
    } else {
        0
    };
    let mut breakpoints_remaining = max_breakpoints;

    let tools_breakpoints_before = breakpoints_remaining;
    let mut tools = build_tools(request, tools_cache_control.as_ref(), &mut breakpoints_remaining)?;
    let tools_breakpoints_used = tools_breakpoints_before.saturating_sub(breakpoints_remaining);

    // Inject the Anthropic server-side advisor tool when enabled and the executor
    // model forms a valid pair with the configured advisor model.
    let advisor_injected =
        if let Some(advisor_tool) = resolve_advisor_tool(resolved_model, &ctx.anthropic_config.advisor) {
            let mut built = tools.unwrap_or_default();
            built.push(advisor_tool);
            tools = Some(built);
            true
        } else {
            false
        };

    let allow_mid_conversation_system = supports_mid_conversation_system_messages(resolved_model, ctx.model);
    let history_system_placement = HistorySystemPlacement::for_route(allow_mid_conversation_system);

    let SystemPromptBuildResult {
        mut system_value,
        breakpoints_used,
        has_uncached_runtime_context,
    } = build_system_prompt(request, system_cache_control.as_ref(), breakpoints_remaining, history_system_placement);
    breakpoints_remaining = breakpoints_remaining.saturating_sub(breakpoints_used);

    // When the advisor tool is active, append a system-prompt block guiding the
    // executor model on when to invoke it (per Anthropic's recommended prompt
    // for coding tasks).
    if advisor_injected {
        let advisor_guidance = concat!(
            "You have access to an advisor tool that pairs a faster executor model with a ",
            "higher-intelligence advisor model for strategic guidance mid-generation. ",
            "Use the advisor tool when you:\n",
            "- Need a second opinion on a complex architectural decision\n",
            "- Are unsure about the best approach to a multi-step problem\n",
            "- Want to validate your plan before executing many tool calls\n",
            "- Hit a blocker you cannot resolve alone\n",
            "When the advisor returns guidance, incorporate it into your response. ",
            "If the advisor suggests a different approach, weigh it against your own reasoning.",
        );
        let guidance_block = json!({
            "type": "text",
            "text": advisor_guidance,
        });
        match &mut system_value {
            Some(Value::Array(blocks)) => {
                blocks.push(guidance_block);
            }
            Some(Value::String(text)) => {
                let existing = std::mem::take(text);
                system_value = Some(Value::Array(vec![json!({ "type": "text", "text": existing }), guidance_block]));
            }
            // build_system_prompt only produces String, Array, or None —
            // this arm is defensive for forward-compatibility.
            _ => {
                system_value = Some(Value::Array(vec![guidance_block]));
            }
        }
    }

    let messages_cache_control = if ctx.prompt_cache_enabled && ctx.prompt_cache_settings.cache_user_messages {
        Some(CacheControl {
            control_type: "ephemeral".into(),
            ttl: Some(messages_ttl.into()),
        })
    } else {
        None
    };

    // Leading system messages already live in the top-level system prompt
    // (see `HistorySystemPlacement`); skip them here so each history system
    // message is rendered exactly once.
    let conversation_messages = &request.messages[history_system_placement.leading_folded_count(&request.messages)..];

    // Hoisting moves the largest user message to the front, which reorders
    // earlier turns. On preserved-thinking models that invalidates every
    // replayed thinking block (their signatures bind the exact prior prefix),
    // so the optimization is skipped there and history stays append-only.
    let needs_hoisting = request
        .coding_agent_settings
        .as_ref()
        .is_some_and(|s| s.long_context_optimization)
        && conversation_messages.len() > 1
        && !preserves_thinking_across_turns(resolved_model, ctx.model);

    // Only clone the message vector when hoisting will actually mutate it.
    // In the common case (no long-context optimization or single message),
    // borrow the original slice and skip the deep copy.
    let mut hoisted_messages: Vec<crate::provider::Message>;
    let messages_to_process: &[crate::provider::Message] = if needs_hoisting {
        hoisted_messages = conversation_messages.to_vec();
        hoist_largest_user_message(&mut hoisted_messages);
        &hoisted_messages
    } else {
        conversation_messages
    };

    let messages_breakpoints_before = breakpoints_remaining;
    let messages = build_messages(
        request,
        messages_to_process,
        messages_cache_control.as_ref(),
        ctx.prompt_cache_settings,
        &mut breakpoints_remaining,
        ctx.model,
    )?;
    let messages_breakpoints_used = messages_breakpoints_before.saturating_sub(breakpoints_remaining);
    let explicit_breakpoints_used = max_breakpoints.saturating_sub(breakpoints_remaining);

    let (thinking_val, reasoning_val) = build_thinking_config(request, ctx.anthropic_config, ctx.model)?;

    let anthropic_overrides = request.anthropic_request_overrides.as_ref();
    let thinking_is_adaptive = matches!(thinking_val, Some(ThinkingConfig::Adaptive { .. }));

    let adaptive_effort = if thinking_is_adaptive && request.effort.is_none() {
        request
            .reasoning_effort
            .map(|effort| effort_from_reasoning_for_adaptive(effort).to_string())
    } else {
        None
    };
    let effort_value = if supports_effort(resolved_model, ctx.model) && thinking_is_adaptive {
        match anthropic_overrides.map(|overrides| &overrides.effort) {
            Some(AnthropicOptionalStringOverride::Explicit(effort)) => Some(effort.to_ascii_lowercase()),
            Some(AnthropicOptionalStringOverride::Omit) => None,
            _ => request
                .effort
                .as_ref()
                .map(|effort| effort.to_ascii_lowercase())
                .or_else(|| adaptive_effort.as_ref().map(|effort| effort.to_ascii_lowercase()))
                .or_else(|| {
                    // Only an explicitly configured effort overrides the
                    // model's own default (for example `medium` on Opus 5.5).
                    thinking_val.as_ref().and_then(|_| {
                        ctx.anthropic_config
                            .effort
                            .map(|effort| effort.as_str())
                            .filter(|effort| effort_allowed_for_model(resolved_model, ctx.model, effort))
                            .or_else(|| default_effort_for_model(resolved_model, ctx.model))
                            .map(str::to_string)
                    })
                }),
        }
    } else {
        None
    };
    let task_budget = if supports_task_budget(resolved_model, ctx.model) {
        match anthropic_overrides.map(|overrides| &overrides.task_budget_tokens) {
            Some(AnthropicOptionalU32Override::Explicit(total)) => {
                Some(AnthropicTaskBudget { budget_type: "tokens".to_string(), total: *total })
            }
            Some(AnthropicOptionalU32Override::Omit) => None,
            _ => ctx
                .anthropic_config
                .task_budget_tokens
                .map(|total| AnthropicTaskBudget { budget_type: "tokens".to_string(), total }),
        }
    } else {
        None
    };
    let fallbacks = build_fallbacks(request, ctx, resolved_model, thinking_val.as_ref(), effort_value.as_deref());
    // Forced tool use (`any`/`tool`) is rejected when thinking is on and, on
    // some models, unconditionally. Fallback entries inherit the top-level
    // `tool_choice`, so every fallback model must accept it as well.
    let forced_tool_choice_allowed = !thinking_is_on(thinking_val.as_ref(), resolved_model, ctx.model)
        && !rejects_forced_tool_choice(resolved_model, ctx.model)
        && fallbacks.as_ref().is_none_or(|fallbacks| {
            fallbacks.models().iter().all(|fb| {
                let fallback_thinking = fb.thinking.as_ref().or(thinking_val.as_ref());
                !thinking_is_on(fallback_thinking, &fb.model, ctx.model)
                    && !rejects_forced_tool_choice(&fb.model, ctx.model)
            })
        });
    let final_tool_choice = build_tool_choice(request, forced_tool_choice_allowed);
    let output_format = request
        .output_format
        .as_ref()
        .map(|schema| AnthropicOutputFormat::JsonSchema { schema: schema.clone() });
    let output_config = if effort_value.is_some() || task_budget.is_some() || output_format.is_some() {
        Some(AnthropicOutputConfig {
            effort: effort_value,
            task_budget,
            format: output_format,
        })
    } else {
        None
    };

    let top_level_cache_control =
        if ctx.prompt_cache_enabled && explicit_breakpoints_used < max_breakpoints && !has_uncached_runtime_context {
            let ttl = if messages_breakpoints_used > 0 {
                messages_ttl
            } else if breakpoints_used > 0 || tools_breakpoints_used > 0 {
                tools_ttl
            } else {
                messages_ttl
            };

            Some(CacheControl {
                control_type: "ephemeral".into(),
                ttl: Some(ttl.into()),
            })
        } else {
            None
        };

    let mut anthropic_request = AnthropicRequest {
        model: resolved_model.to_string(),
        max_tokens: request
            .max_tokens
            .unwrap_or_else(|| default_max_tokens_for_model(resolved_model, ctx.model, thinking_val.is_some())),
        cache_control: top_level_cache_control,
        messages,
        system: system_value,
        tools,
        tool_choice: final_tool_choice,
        thinking: thinking_val,
        reasoning: reasoning_val,
        output_config: output_config.map(Into::into),
        context_management: request.context_management.clone(),
        fallbacks,
        fallback_credit_token: request.fallback_credit_token.clone(),
        stream: request.stream,
    };

    hardening::strip_globally_orphaned_tool_blocks(&mut anthropic_request.messages);
    hardening::enforce_tool_use_result_adjacency(&mut anthropic_request.messages);
    hardening::hoist_tool_results_to_front(&mut anthropic_request.messages);
    hardening::guard_trailing_assistant_message(
        &mut anthropic_request.messages,
        supports_assistant_prefill(resolved_model, ctx.model),
    );

    serde_json::to_value(anthropic_request).map_err(|e| LLMError::Provider {
        message: format!("Serialization error: {e}"),
        metadata: None,
    })
}

/// Builds the server-side `fallbacks` parameter.
///
/// Fallbacks are only sent on the first-party API, for models whose profile
/// supports server-side fallbacks, and never on a credit-token retry. Within
/// those gates, request-level `fallbacks` win over `provider.anthropic.fallbacks`:
/// an empty request list sends nothing, and an invalid one (too long, blank or
/// repeated models, zero `max_tokens`) is dropped with a warning. Otherwise
/// `"default"` sends the keyword form, an explicit list sends entries, and
/// `"off"` (or an invalid list, which config validation reports) sends nothing.
fn build_fallbacks(
    request: &LLMRequest,
    ctx: &RequestBuilderContext<'_>,
    resolved_model: &str,
    primary_thinking: Option<&ThinkingConfig>,
    effort: Option<&str>,
) -> Option<AnthropicFallbacksParam> {
    // A credit-token retry already targets the fallback model; asking for
    // further fallbacks would change the prompt-shaping fields the token was
    // issued for.
    if request.fallback_credit_token.is_some()
        || !ctx.server_side_fallbacks_available
        || !supports_server_side_fallback(resolved_model, ctx.model)
    {
        return None;
    }

    if let Some(fallbacks) = request.fallbacks.as_ref() {
        if fallbacks.is_empty() {
            return None;
        }
        if let Some(reason) = AnthropicFallbacks::entries_validation_error(
            "fallbacks",
            fallbacks.iter().map(|fb| (fb.model.as_str(), fb.max_tokens)),
        ) {
            tracing::warn!(%reason, "request-level fallbacks dropped: invalid entries");
            return None;
        }
        let entries = fallbacks
            .iter()
            .map(|fb| (fb.model.trim(), fb.max_tokens, fb.thinking.as_ref().map(fallback_thinking_config)));
        return Some(AnthropicFallbacksParam::Models(sanitize_fallback_entries(
            entries,
            primary_thinking,
            effort,
            ctx.model,
        )));
    }

    match &ctx.anthropic_config.fallbacks {
        AnthropicFallbacks::Mode(AnthropicFallbackMode::Default) => {
            Some(AnthropicFallbacksParam::Mode(AnthropicFallbacksKeyword::Default))
        }
        AnthropicFallbacks::Mode(AnthropicFallbackMode::Off) => None,
        configured @ AnthropicFallbacks::Models(targets) => {
            if configured.validation_error("provider.anthropic.fallbacks").is_some() {
                return None;
            }
            let entries = targets.iter().map(|target| (target.model.trim(), target.max_tokens, None));
            Some(AnthropicFallbacksParam::Models(sanitize_fallback_entries(
                entries,
                primary_thinking,
                effort,
                ctx.model,
            )))
        }
    }
}

/// Makes explicit `fallbacks` entries valid for their own models.
///
/// The API merges each entry into the primary request, and the merged request
/// must be valid as a direct request to the entry's model. An explicit thinking
/// override is rewritten for its model; without one, the entry inherits the
/// primary thinking config, so an explicit valid override is added whenever
/// the fallback model would reject the inherited config.
fn sanitize_fallback_entries<'m>(
    entries: impl Iterator<Item = (&'m str, Option<u32>, Option<ThinkingConfig>)>,
    primary_thinking: Option<&ThinkingConfig>,
    effort: Option<&str>,
    default_model: &str,
) -> Vec<AnthropicFallbackParam> {
    entries
        .map(|(model, max_tokens, explicit_thinking)| {
            let thinking = match explicit_thinking {
                Some(explicit) => {
                    Some(rewrite_thinking_for_model(&explicit, model, default_model, effort).unwrap_or(explicit))
                }
                None => primary_thinking
                    .and_then(|inherited| rewrite_thinking_for_model(inherited, model, default_model, effort)),
            };
            AnthropicFallbackParam { model: model.to_string(), max_tokens, thinking }
        })
        .collect()
}

fn fallback_thinking_config(thinking: &AnthropicThinkingConfig) -> ThinkingConfig {
    match thinking {
        AnthropicThinkingConfig::Disabled => ThinkingConfig::Disabled,
        AnthropicThinkingConfig::Enabled { budget_tokens, display } => ThinkingConfig::Enabled {
            budget_tokens: *budget_tokens,
            display: parse_thinking_display(display.as_deref()),
        },
        AnthropicThinkingConfig::Adaptive { display } => ThinkingConfig::Adaptive {
            display: parse_thinking_display(display.as_deref()),
        },
    }
}

fn parse_thinking_display(display: Option<&str>) -> Option<ThinkingDisplay> {
    match display? {
        "summarized" => Some(ThinkingDisplay::Summarized),
        "omitted" => Some(ThinkingDisplay::Omitted),
        "updates" => Some(ThinkingDisplay::Updates),
        _ => None,
    }
}

fn effort_from_reasoning_for_adaptive(effort: ReasoningEffortLevel) -> &'static str {
    match effort {
        ReasoningEffortLevel::None | ReasoningEffortLevel::Minimal | ReasoningEffortLevel::Low => reasoning::LOW,
        _ => effort.as_str(),
    }
}

/// Whether the given model is an Anthropic model eligible to act as an advisor
/// executor. Server-side advisor tooling is only available on Anthropic models.
///
/// Model ids may carry a `-YYYYMMDD` version pin; this strips the single known
/// dated suffix before checking against the supported set. Keep this in lockstep
/// with `vtcode_config::constants::models::anthropic::normalize_model_id` so the
/// executor check and the advisor-pair validation agree on normalization.
fn is_anthropic_executor_model(model: &str) -> bool {
    use vtcode_config::constants::models::anthropic::{SUPPORTED_MODELS, normalize_model_id};
    let normalized = normalize_model_id(model);
    SUPPORTED_MODELS.contains(&normalized)
}

/// Single source of truth for the Anthropic server-side advisor tool.
///
/// Resolves and builds the `advisor_20260301` tool, or returns `None` when the
/// advisor is disabled, the executor is not an eligible Anthropic model, or the
/// executor/advisor model pair fails `validate_advisor_pair`. Both the request
/// builder (tool injection) and the provider (beta-header gating) call this so
/// the two can never disagree.
pub(crate) fn resolve_advisor_tool(executor: &str, advisor: &AdvisorConfig) -> Option<AnthropicTool> {
    if !advisor.enabled {
        return None;
    }

    if !is_anthropic_executor_model(executor) {
        return None;
    }

    let advisor_model = if advisor.model.is_empty() {
        vtcode_config::constants::models::anthropic::default_advisor_model(executor).to_string()
    } else {
        advisor.model.clone()
    };

    if let Err(reason) = vtcode_config::constants::models::anthropic::validate_advisor_pair(executor, &advisor_model) {
        tracing::warn!(%reason, "advisor tool disabled: invalid model pair");
        return None;
    }

    // Validate max_tokens if specified (API minimum is 1024).
    if let Some(max_tokens) = advisor.max_tokens
        && max_tokens < 1024
    {
        tracing::warn!(max_tokens, "advisor tool disabled: max_tokens must be >= 1024");
        return None;
    }

    let caching = advisor.caching.and_then(|c| {
        c.enabled.then_some(AnthropicAdvisorCaching {
            cache_type: "ephemeral".to_string(),
            ttl: c.ttl.as_str().to_string(),
        })
    });

    Some(AnthropicTool::Advisor(AnthropicAdvisorTool {
        tool_type: "advisor_20260301".to_string(),
        name: "advisor".to_string(),
        model: advisor_model,
        max_uses: advisor.max_uses,
        max_tokens: advisor.max_tokens,
        caching,
    }))
}

#[cfg(test)]
mod tests;