nexil 0.6.2

//! Core execution: retry/orchestration loop and LLMCore definition.

use std::collections::HashMap;
use std::sync::Arc;

use reqwest::Client;
use serde_json::Value;
use tracing::info;

use super::api_format::ApiFormat;
use super::client_registry::ClientRegistry;
use super::error_classify::AttemptDecision;
use super::errors::{ConduitError, ErrorKind};
use super::message_norm::normalize_messages_for_api;
use super::provider_runtime::ProviderRuntime;
use super::response_parser::TransportResponse;
use crate::clients::parsing::TransportKind;

/// How API keys are configured.
#[derive(Debug, Clone)]
pub enum ApiKeyConfig {
    None,
    Single(String),
    PerProvider(HashMap<String, String>),
}

/// How API bases are configured.
#[derive(Debug, Clone)]
pub enum ApiBaseConfig {
    None,
    Single(String),
    PerProvider(HashMap<String, String>),
}

/// Shared LLM execution utilities (provider resolution, retries, client cache).
pub struct LLMCore {
    provider: String,
    model: String,
    fallback_models: Vec<String>,
    max_retries: u32,
    api_key: ApiKeyConfig,
    api_base: ApiBaseConfig,
    client_registry: ClientRegistry,
    api_format: ApiFormat,
    verbose: u32,
    #[allow(clippy::type_complexity)]
    error_classifier: Option<Box<dyn Fn(&ConduitError) -> Option<ErrorKind> + Send + Sync>>,
}

fn split_model_id<'a>(
    model: &'a str,
    message: &'static str,
) -> Result<(&'a str, &'a str), ConduitError> {
    let (provider, model_id) = model
        .split_once(':')
        .ok_or_else(|| ConduitError::new(ErrorKind::InvalidInput, message))?;
    if provider.is_empty() || model_id.is_empty() {
        return Err(ConduitError::new(ErrorKind::InvalidInput, message));
    }
    Ok((provider, model_id))
}

impl LLMCore {
    /// Create a new `LLMCore` instance.
    #[allow(clippy::too_many_arguments)]
    pub fn new(
        provider: String,
        model: String,
        fallback_models: Vec<String>,
        max_retries: u32,
        api_key: ApiKeyConfig,
        api_base: ApiBaseConfig,
        api_format: impl Into<ApiFormat>,
        verbose: u32,
    ) -> Self {
        Self {
            provider,
            model,
            fallback_models,
            max_retries,
            api_key,
            api_base,
            client_registry: ClientRegistry::new(),
            api_format: api_format.into(),
            verbose,
            error_classifier: None,
        }
    }

    /// Set a custom error classifier.
    pub fn with_error_classifier(
        mut self,
        classifier: impl Fn(&ConduitError) -> Option<ErrorKind> + Send + Sync + 'static,
    ) -> Self {
        self.error_classifier = Some(Box::new(classifier));
        self
    }

    /// The primary provider name.
    pub fn provider(&self) -> &str {
        &self.provider
    }

    /// The primary model name.
    pub fn model(&self) -> &str {
        &self.model
    }

    /// The fallback model list.
    pub fn fallback_models(&self) -> &[String] {
        &self.fallback_models
    }

    /// Configured maximum retries.
    pub fn max_retries(&self) -> u32 {
        self.max_retries
    }

    /// The API key configuration.
    pub fn api_key_config(&self) -> &ApiKeyConfig {
        &self.api_key
    }

    /// The API base configuration.
    pub fn api_base_config(&self) -> &ApiBaseConfig {
        &self.api_base
    }

    /// The configured API format / transport kind.
    pub fn api_format(&self) -> ApiFormat {
        self.api_format
    }

    /// The verbosity level.
    pub fn verbose(&self) -> u32 {
        self.verbose
    }

    /// Total number of attempts = 1 + max_retries, minimum 1.
    pub fn max_attempts(&self) -> u32 {
        1u32.max(1 + self.max_retries)
    }

    fn retry_attempts(&self) -> std::ops::Range<u32> {
        0..self.max_attempts()
    }

    /// Apply the custom error classifier, if set.
    pub(crate) fn custom_classify(&self, error: &ConduitError) -> Option<ErrorKind> {
        if let Some(ref classifier) = self.error_classifier
            && let Some(kind) = classifier(error)
        {
            return Some(kind);
        }
        None
    }

    /// Resolve a `"provider:model"` string into `(provider, model)`.
    pub fn resolve_model_provider(
        model: &str,
        provider: Option<&str>,
    ) -> Result<(String, String), ConduitError> {
        if let Some(p) = provider {
            if model.contains(':') {
                return Err(ConduitError::new(
                    ErrorKind::InvalidInput,
                    "When provider is specified, model must not include a provider prefix.",
                ));
            }
            return Ok((p.to_owned(), model.to_owned()));
        }
        let (prov, mdl) = split_model_id(model, "Model must be in 'provider:model' format.")?;
        Ok((prov.to_owned(), mdl.to_owned()))
    }

    /// Resolve a fallback model string into `(provider, model)`.
    pub fn resolve_fallback(&self, model: &str) -> Result<(String, String), ConduitError> {
        if model.contains(':') {
            let (prov, mdl) =
                split_model_id(model, "Fallback models must be in 'provider:model' format.")?;
            return Ok((prov.to_owned(), mdl.to_owned()));
        }
        if !self.provider.is_empty() {
            return Ok((self.provider.clone(), model.to_owned()));
        }
        Err(ConduitError::new(
            ErrorKind::InvalidInput,
            "Fallback models must include provider or LLM must be initialized with a provider.",
        ))
    }

    /// Build the ordered list of (provider, model) candidates to try.
    pub fn model_candidates(
        &self,
        override_model: Option<&str>,
        override_provider: Option<&str>,
    ) -> Result<Vec<(String, String)>, ConduitError> {
        if let Some(om) = override_model {
            let (p, m) = Self::resolve_model_provider(om, override_provider)?;
            return Ok(vec![(p, m)]);
        }
        let mut candidates = vec![(self.provider.clone(), self.model.clone())];
        for fallback in &self.fallback_models {
            candidates.push(self.resolve_fallback(fallback)?);
        }
        Ok(candidates)
    }

    /// Resolve the API key for a given provider.
    pub fn resolve_api_key(&self, provider: &str) -> Option<String> {
        match &self.api_key {
            ApiKeyConfig::None => None,
            ApiKeyConfig::Single(key) => Some(key.clone()),
            ApiKeyConfig::PerProvider(map) => map.get(provider).cloned(),
        }
    }

    /// Resolve the API base URL for a given provider.
    pub fn resolve_api_base(&self, provider: &str) -> Option<String> {
        match &self.api_base {
            ApiBaseConfig::None => None,
            ApiBaseConfig::Single(base) => Some(base.clone()),
            ApiBaseConfig::PerProvider(map) => map.get(provider).cloned(),
        }
    }

    /// Get or create an HTTP client for the given provider.
    pub fn get_client(&mut self, provider: &str) -> Arc<Client> {
        let api_key = self.resolve_api_key(provider);
        let api_base = self.resolve_api_base(provider);
        self.client_registry
            .get_or_create(provider, api_key.as_deref(), api_base.as_deref())
    }

    /// Execute a synchronous (non-streaming) chat call with retry logic.
    ///
    /// Iterates over model candidates, retrying on transient errors.
    /// The `on_response` callback receives `(TransportResponse, provider, model, attempt)`
    /// and should return `Ok(T)` on success or `Err(None)` to signal a retry.
    #[allow(clippy::too_many_arguments)]
    pub async fn run_chat<T, F>(
        &mut self,
        messages_payload: Vec<Value>,
        tools_payload: Option<Vec<Value>>,
        model: Option<&str>,
        provider: Option<&str>,
        max_tokens: Option<u32>,
        stream: bool,
        reasoning_effort: Option<Value>,
        kwargs: serde_json::Map<String, Value>,
        on_response: F,
    ) -> Result<T, ConduitError>
    where
        F: Fn(TransportResponse, &str, &str, u32) -> Result<T, Option<ConduitError>>,
    {
        let candidates = self.model_candidates(model, provider)?;
        let mut last_error: Option<ConduitError> = None;

        for (provider_name, model_id) in &candidates {
            let client = self.get_client(provider_name);
            let api_base = self.resolve_api_base(provider_name);
            let api_key = self.resolve_api_key(provider_name);
            let runtime = ProviderRuntime::new(
                provider_name,
                model_id,
                api_key.as_deref(),
                api_base.as_deref(),
                self.api_format,
            );

            for attempt in self.retry_attempts() {
                let transport = match runtime.selected_transport(
                    tools_payload.as_deref(),
                    false, // supports_responses -- caller can override
                    None,
                ) {
                    Ok(t) => t,
                    Err(e) => {
                        last_error = Some(e);
                        break;
                    }
                };

                let resolved_api_base = runtime.resolved_api_base();

                // Normalize messages for protocol compliance
                let normalized_messages =
                    normalize_messages_for_api(messages_payload.clone(), transport);

                let request = super::request_builder::TransportCallRequest {
                    client: Arc::clone(&client),
                    provider_name: provider_name.clone(),
                    model_id: model_id.clone(),
                    api_base: Some(resolved_api_base.clone()),
                    messages_payload: normalized_messages,
                    tools_payload: tools_payload.clone(),
                    max_tokens,
                    stream,
                    reasoning_effort: reasoning_effort.clone(),
                    kwargs: kwargs.clone(),
                    is_anthropic_oauth: runtime.is_anthropic_oauth(),
                };

                let url = Self::build_request_url(&resolved_api_base, transport);
                let body = match transport {
                    TransportKind::Responses => Self::build_responses_body(&request)?,
                    TransportKind::Messages => Self::build_messages_body(&request)?,
                    TransportKind::Completion => {
                        Self::build_completion_body(&request, provider_name)?
                    }
                };

                info!(
                    target: "eli_trace",
                    provider = %provider_name,
                    model = %model_id,
                    transport = ?transport,
                    stream = body.get("stream").and_then(|v| v.as_bool()).unwrap_or(false),
                    request_body = %body,
                    "llm.request"
                );

                let http_result = client.post(&url).json(&body).send().await;

                match http_result {
                    Ok(resp) => {
                        let status = resp.status();
                        if !status.is_success() {
                            let error_body = resp.text().await.unwrap_or_default();
                            let kind = Self::classify_http_status(status.as_u16())
                                .unwrap_or(ErrorKind::Provider);
                            let error = ConduitError::new(
                                kind,
                                format!(
                                    "{}:{}: HTTP {} - {}",
                                    provider_name, model_id, status, error_body
                                ),
                            );
                            let outcome =
                                self.handle_attempt_error(error, provider_name, model_id, attempt);
                            last_error = Some(outcome.error);
                            if outcome.decision == AttemptDecision::RetrySameModel {
                                continue;
                            }
                            break;
                        }

                        // If the body forced stream=true (e.g. Codex backend)
                        // but the caller asked for non-streaming, collect SSE
                        // chunks and extract the final response.
                        let body_forced_stream = !stream
                            && body
                                .get("stream")
                                .and_then(|v| v.as_bool())
                                .unwrap_or(false);

                        let payload: Value = if body_forced_stream {
                            match Self::collect_sse_response(resp, transport).await {
                                Ok(v) => v,
                                Err(e) => {
                                    let outcome = self.handle_attempt_error(
                                        e,
                                        provider_name,
                                        model_id,
                                        attempt,
                                    );
                                    last_error = Some(outcome.error);
                                    if outcome.decision == AttemptDecision::RetrySameModel {
                                        continue;
                                    }
                                    break;
                                }
                            }
                        } else {
                            match resp.json().await {
                                Ok(v) => v,
                                Err(e) => {
                                    let error = ConduitError::new(
                                        ErrorKind::Provider,
                                        format!(
                                            "{}:{}: failed to parse response: {}",
                                            provider_name, model_id, e
                                        ),
                                    );
                                    let outcome = self.handle_attempt_error(
                                        error,
                                        provider_name,
                                        model_id,
                                        attempt,
                                    );
                                    last_error = Some(outcome.error);
                                    if outcome.decision == AttemptDecision::RetrySameModel {
                                        continue;
                                    }
                                    break;
                                }
                            }
                        };

                        info!(
                            target: "eli_trace",
                            provider = %provider_name,
                            model = %model_id,
                            transport = ?transport,
                            response_payload = %payload,
                            "llm.response"
                        );

                        let transport_response = TransportResponse { transport, payload };

                        match on_response(transport_response, provider_name, model_id, attempt) {
                            Ok(result) => return Ok(result),
                            Err(Some(e)) => {
                                last_error = Some(e);
                                break;
                            }
                            Err(None) => {
                                // Signal to retry
                                continue;
                            }
                        }
                    }
                    Err(e) => {
                        let kind = if e.is_timeout() {
                            ErrorKind::Temporary
                        } else if e.is_connect() {
                            ErrorKind::Provider
                        } else {
                            ErrorKind::Unknown
                        };
                        let error = ConduitError::new(
                            kind,
                            format!("{}:{}: {}", provider_name, model_id, e),
                        );
                        let outcome =
                            self.handle_attempt_error(error, provider_name, model_id, attempt);
                        last_error = Some(outcome.error);
                        if outcome.decision == AttemptDecision::RetrySameModel {
                            continue;
                        }
                        break;
                    }
                }
            }
        }

        Err(last_error.unwrap_or_else(|| {
            ConduitError::new(ErrorKind::Temporary, "LLM call failed after retries")
        }))
    }

    /// Execute a streaming chat call.
    ///
    /// Returns the raw `reqwest::Response` for the caller to consume as an SSE stream.
    #[allow(clippy::too_many_arguments)]
    pub async fn run_chat_stream(
        &mut self,
        messages_payload: Vec<Value>,
        tools_payload: Option<Vec<Value>>,
        model: Option<&str>,
        provider: Option<&str>,
        max_tokens: Option<u32>,
        reasoning_effort: Option<Value>,
        kwargs: serde_json::Map<String, Value>,
    ) -> Result<(reqwest::Response, TransportKind, String, String), ConduitError> {
        let candidates = self.model_candidates(model, provider)?;
        let mut last_error: Option<ConduitError> = None;

        for (provider_name, model_id) in &candidates {
            let client = self.get_client(provider_name);
            let api_base = self.resolve_api_base(provider_name);
            let api_key = self.resolve_api_key(provider_name);
            let runtime = ProviderRuntime::new(
                provider_name,
                model_id,
                api_key.as_deref(),
                api_base.as_deref(),
                self.api_format,
            );

            for attempt in self.retry_attempts() {
                let transport =
                    match runtime.selected_transport(tools_payload.as_deref(), false, None) {
                        Ok(t) => t,
                        Err(e) => {
                            last_error = Some(e);
                            break;
                        }
                    };

                let resolved_api_base = runtime.resolved_api_base();

                // Normalize messages for protocol compliance
                let normalized_messages =
                    normalize_messages_for_api(messages_payload.clone(), transport);

                let request = super::request_builder::TransportCallRequest {
                    client: Arc::clone(&client),
                    provider_name: provider_name.clone(),
                    model_id: model_id.clone(),
                    api_base: Some(resolved_api_base.clone()),
                    messages_payload: normalized_messages,
                    tools_payload: tools_payload.clone(),
                    max_tokens,
                    stream: true,
                    reasoning_effort: reasoning_effort.clone(),
                    kwargs: kwargs.clone(),
                    is_anthropic_oauth: runtime.is_anthropic_oauth(),
                };

                let url = Self::build_request_url(&resolved_api_base, transport);
                let body = match transport {
                    TransportKind::Responses => Self::build_responses_body(&request)?,
                    TransportKind::Messages => Self::build_messages_body(&request)?,
                    TransportKind::Completion => {
                        Self::build_completion_body(&request, provider_name)?
                    }
                };

                let http_result = client.post(&url).json(&body).send().await;

                match http_result {
                    Ok(resp) => {
                        let status = resp.status();
                        if !status.is_success() {
                            let error_body = resp.text().await.unwrap_or_default();
                            let kind = Self::classify_http_status(status.as_u16())
                                .unwrap_or(ErrorKind::Provider);
                            let error = ConduitError::new(
                                kind,
                                format!(
                                    "{}:{}: HTTP {} - {}",
                                    provider_name, model_id, status, error_body
                                ),
                            );
                            let outcome =
                                self.handle_attempt_error(error, provider_name, model_id, attempt);
                            last_error = Some(outcome.error);
                            if outcome.decision == AttemptDecision::RetrySameModel {
                                continue;
                            }
                            break;
                        }

                        return Ok((resp, transport, provider_name.clone(), model_id.clone()));
                    }
                    Err(e) => {
                        let kind = if e.is_timeout() {
                            ErrorKind::Temporary
                        } else if e.is_connect() {
                            ErrorKind::Provider
                        } else {
                            ErrorKind::Unknown
                        };
                        let error = ConduitError::new(
                            kind,
                            format!("{}:{}: {}", provider_name, model_id, e),
                        );
                        let outcome =
                            self.handle_attempt_error(error, provider_name, model_id, attempt);
                        last_error = Some(outcome.error);
                        if outcome.decision == AttemptDecision::RetrySameModel {
                            continue;
                        }
                        break;
                    }
                }
            }
        }

        Err(last_error.unwrap_or_else(|| {
            ConduitError::new(
                ErrorKind::Temporary,
                "LLM streaming call failed after retries",
            )
        }))
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::core::anthropic_messages;
    use crate::core::error_classify::classify_by_text_signature;
    use crate::core::message_norm::{enforce_anthropic_message_rules, prune_orphan_tool_messages};
    use serde_json::json;

    // Re-import TransportCallRequest for test use
    use super::super::request_builder::TransportCallRequest;

    #[test]
    fn test_resolve_model_provider() {
        let (p, m) = LLMCore::resolve_model_provider("openai:gpt-4", None).unwrap();
        assert_eq!(p, "openai");
        assert_eq!(m, "gpt-4");
    }

    #[test]
    fn test_resolve_model_provider_with_override() {
        let (p, m) = LLMCore::resolve_model_provider("gpt-4", Some("openai")).unwrap();
        assert_eq!(p, "openai");
        assert_eq!(m, "gpt-4");
    }

    #[test]
    fn test_resolve_model_provider_error() {
        let result = LLMCore::resolve_model_provider("gpt-4", None);
        assert!(result.is_err());
    }

    #[test]
    fn test_classify_http_status() {
        assert_eq!(LLMCore::classify_http_status(401), Some(ErrorKind::Config));
        assert_eq!(
            LLMCore::classify_http_status(429),
            Some(ErrorKind::Temporary)
        );
        assert_eq!(
            LLMCore::classify_http_status(500),
            Some(ErrorKind::Provider)
        );
        assert_eq!(LLMCore::classify_http_status(200), None);
    }

    #[test]
    fn test_split_messages_for_responses() {
        let messages = vec![
            json!({"role": "system", "content": "You are helpful."}),
            json!({"role": "user", "content": "Hello"}),
        ];
        let (instructions, items) = LLMCore::split_messages_for_responses(&messages);
        assert_eq!(instructions.unwrap(), "You are helpful.");
        assert_eq!(items.len(), 1);
        assert_eq!(items[0]["role"], "user");
    }

    #[test]
    fn test_convert_tools_for_responses() {
        let tools = vec![json!({
            "type": "function",
            "function": {
                "name": "greet",
                "description": "Say hello",
                "parameters": {"type": "object"}
            }
        })];
        let converted = LLMCore::convert_tools_for_responses(Some(&tools)).unwrap();
        assert_eq!(converted.len(), 1);
        assert_eq!(converted[0]["name"], "greet");
        assert!(converted[0].get("function").is_none());
    }

    #[test]
    fn test_normalize_anthropic_messages_keeps_multiple_tool_results() {
        let messages = vec![
            json!({
                "role": "user",
                "content": "find latest papers"
            }),
            json!({
                "role": "assistant",
                "content": [
                    {"type": "tool_use", "id": "toolu_1", "name": "bash", "input": {"cmd": "pwd"}},
                    {"type": "tool_use", "id": "toolu_2", "name": "skill", "input": {"name": "active-research"}}
                ]
            }),
            json!({
                "role": "user",
                "content": [
                    {"type": "tool_result", "tool_use_id": "toolu_1", "content": "ok-1"}
                ]
            }),
            json!({
                "role": "user",
                "content": [
                    {"type": "tool_result", "tool_use_id": "toolu_2", "content": "ok-2"}
                ]
            }),
        ];

        let normalized = anthropic_messages::normalize_messages(messages);
        assert_eq!(normalized.len(), 3);
        assert_eq!(normalized[0]["role"], "user");
        assert_eq!(normalized[1]["role"], "assistant");
        assert_eq!(normalized[2]["role"], "user");
        let content = normalized[2]["content"].as_array().unwrap();
        assert_eq!(content.len(), 2);
        assert_eq!(content[0]["tool_use_id"], "toolu_1");
        assert_eq!(content[1]["tool_use_id"], "toolu_2");
    }

    #[test]
    fn test_normalize_anthropic_messages_merges_text_with_tool_results() {
        let messages = vec![
            json!({
                "role": "user",
                "content": [
                    {"type": "tool_result", "tool_use_id": "toolu_1", "content": "ok"}
                ]
            }),
            json!({
                "role": "user",
                "content": "continue with a summary"
            }),
        ];

        let normalized = anthropic_messages::normalize_messages(messages);
        assert_eq!(normalized.len(), 1);
        let content = normalized[0]["content"].as_array().unwrap();
        assert_eq!(content.len(), 2);
        assert_eq!(content[0]["type"], "tool_result");
        assert_eq!(content[1]["type"], "text");
        assert_eq!(content[1]["text"], "continue with a summary");
    }

    #[test]
    fn test_build_messages_body_keeps_tool_results_immediately_after_tool_use() {
        let request = TransportCallRequest {
            client: Arc::new(reqwest::Client::new()),
            provider_name: "anthropic".to_owned(),
            model_id: "claude-test".to_owned(),
            api_base: None,
            messages_payload: vec![
                json!({"role": "system", "content": "system rules"}),
                json!({"role": "user", "content": "find latest papers"}),
                json!({
                    "role": "assistant",
                    "tool_calls": [
                        {"id": "toolu_1", "type": "function", "function": {"name": "bash", "arguments": "{\"cmd\":\"pwd\"}"}},
                        {"id": "toolu_2", "type": "function", "function": {"name": "skill", "arguments": "{\"name\":\"active-research\"}"}}
                    ]
                }),
                json!({"role": "tool", "tool_call_id": "toolu_1", "content": "ok-1"}),
                json!({"role": "tool", "tool_call_id": "toolu_2", "content": "ok-2"}),
                json!({"role": "user", "content": "\u{7ee7}\u{7eed}"}),
            ],
            tools_payload: None,
            max_tokens: Some(512),
            stream: false,
            reasoning_effort: None,
            kwargs: serde_json::Map::new(),
            is_anthropic_oauth: false,
        };

        let body = LLMCore::build_messages_body(&request).unwrap();
        let messages = body["messages"].as_array().unwrap();
        assert_eq!(messages.len(), 3);
        assert_eq!(messages[1]["role"], "assistant");
        assert_eq!(messages[2]["role"], "user");

        let user_blocks = messages[2]["content"].as_array().unwrap();
        assert_eq!(user_blocks[0]["type"], "tool_result");
        assert_eq!(user_blocks[0]["tool_use_id"], "toolu_1");
        assert_eq!(user_blocks[1]["type"], "tool_result");
        assert_eq!(user_blocks[1]["tool_use_id"], "toolu_2");
        assert_eq!(user_blocks[2]["type"], "text");
        assert_eq!(user_blocks[2]["text"], "\u{7ee7}\u{7eed}");
    }

    #[test]
    fn test_max_attempts() {
        let core = LLMCore::new(
            "openai".into(),
            "gpt-4".into(),
            vec![],
            2,
            ApiKeyConfig::None,
            ApiBaseConfig::None,
            TransportKind::Completion,
            0,
        );
        assert_eq!(core.max_attempts(), 3);
    }

    #[test]
    fn test_build_request_url() {
        assert_eq!(
            LLMCore::build_request_url("https://api.openai.com/v1", TransportKind::Completion),
            "https://api.openai.com/v1/chat/completions"
        );
        assert_eq!(
            LLMCore::build_request_url("https://api.openai.com/v1", TransportKind::Responses),
            "https://api.openai.com/v1/responses"
        );
        assert_eq!(
            LLMCore::build_request_url("https://api.anthropic.com/v1", TransportKind::Messages),
            "https://api.anthropic.com/v1/messages"
        );
    }

    // ----- build_error_payload -----

    #[test]
    fn test_build_error_payload_basic() {
        let core = LLMCore::new(
            "openai".into(),
            "gpt-4".into(),
            vec![],
            2,
            ApiKeyConfig::None,
            ApiBaseConfig::None,
            TransportKind::Completion,
            0,
        );
        let error = ConduitError::new(ErrorKind::Provider, "server error");
        let payload = core.build_error_payload(&error, "openai", "gpt-4", 1, None);

        assert_eq!(payload.kind, ErrorKind::Provider);
        assert_eq!(payload.message, "server error");
        let details = payload.details.unwrap();
        assert_eq!(details["provider"], "openai");
        assert_eq!(details["model"], "gpt-4");
        assert_eq!(details["attempt"], 2); // attempt + 1
        assert_eq!(details["max_attempts"], 3); // 1 + max_retries(2)
        assert!(details.get("http_status").is_none());
    }

    #[test]
    fn test_build_error_payload_with_http_status() {
        let core = LLMCore::new(
            "openai".into(),
            "gpt-4".into(),
            vec![],
            3,
            ApiKeyConfig::None,
            ApiBaseConfig::None,
            TransportKind::Completion,
            0,
        );
        let error = ConduitError::new(ErrorKind::Temporary, "rate limited");
        let payload = core.build_error_payload(&error, "openai", "gpt-4", 0, Some(429));

        assert_eq!(payload.kind, ErrorKind::Temporary);
        let details = payload.details.unwrap();
        assert_eq!(details["http_status"], 429);
        assert_eq!(details["attempt"], 1);
        assert_eq!(details["max_attempts"], 4);
    }

    #[test]
    fn test_build_error_payload_different_provider() {
        let core = LLMCore::new(
            "anthropic".into(),
            "claude-3".into(),
            vec![],
            1,
            ApiKeyConfig::None,
            ApiBaseConfig::None,
            TransportKind::Completion,
            0,
        );
        let error = ConduitError::new(ErrorKind::Config, "auth failed");
        let payload = core.build_error_payload(&error, "anthropic", "claude-3", 0, Some(401));

        assert_eq!(payload.kind, ErrorKind::Config);
        let details = payload.details.unwrap();
        assert_eq!(details["provider"], "anthropic");
        assert_eq!(details["model"], "claude-3");
        assert_eq!(details["http_status"], 401);
    }

    // ----- accessor tests -----

    #[test]
    fn test_api_key_config_accessor() {
        let core = LLMCore::new(
            "openai".into(),
            "gpt-4".into(),
            vec![],
            3,
            ApiKeyConfig::Single("my-key".into()),
            ApiBaseConfig::None,
            TransportKind::Completion,
            0,
        );
        match core.api_key_config() {
            ApiKeyConfig::Single(key) => assert_eq!(key, "my-key"),
            _ => panic!("Expected Single key config"),
        }
    }

    #[test]
    fn test_api_base_config_accessor() {
        let core = LLMCore::new(
            "openai".into(),
            "gpt-4".into(),
            vec![],
            3,
            ApiKeyConfig::None,
            ApiBaseConfig::Single("https://custom.api.com".into()),
            TransportKind::Completion,
            0,
        );
        match core.api_base_config() {
            ApiBaseConfig::Single(base) => assert_eq!(base, "https://custom.api.com"),
            _ => panic!("Expected Single base config"),
        }
    }

    #[test]
    fn test_api_format_accessor() {
        let core = LLMCore::new(
            "openai".into(),
            "gpt-4".into(),
            vec![],
            3,
            ApiKeyConfig::None,
            ApiBaseConfig::None,
            TransportKind::Responses,
            0,
        );
        assert_eq!(core.api_format(), ApiFormat::Responses);
    }

    #[test]
    fn test_verbose_accessor() {
        let core = LLMCore::new(
            "openai".into(),
            "gpt-4".into(),
            vec![],
            3,
            ApiKeyConfig::None,
            ApiBaseConfig::None,
            TransportKind::Completion,
            2,
        );
        assert_eq!(core.verbose(), 2);
    }

    // ----- classify_by_text_signature -----

    #[test]
    fn test_classify_auth_errors() {
        assert_eq!(
            classify_by_text_signature("Unauthorized request"),
            Some(ErrorKind::Config)
        );
        assert_eq!(
            classify_by_text_signature("invalid api key provided"),
            Some(ErrorKind::Config)
        );
        assert_eq!(
            classify_by_text_signature("Invalid key format"),
            Some(ErrorKind::Config)
        );
    }

    #[test]
    fn test_classify_rate_limit_errors() {
        assert_eq!(
            classify_by_text_signature("Rate limit exceeded"),
            Some(ErrorKind::Temporary)
        );
        assert_eq!(
            classify_by_text_signature("HTTP 429 Too Many Requests"),
            Some(ErrorKind::Temporary)
        );
        assert_eq!(
            classify_by_text_signature("Quota exceeded for this month"),
            Some(ErrorKind::Temporary)
        );
    }

    #[test]
    fn test_classify_not_found_errors() {
        assert_eq!(
            classify_by_text_signature("Model not found"),
            Some(ErrorKind::NotFound)
        );
        assert_eq!(
            classify_by_text_signature("HTTP 404"),
            Some(ErrorKind::NotFound)
        );
    }

    #[test]
    fn test_classify_timeout_errors() {
        assert_eq!(
            classify_by_text_signature("Request timeout"),
            Some(ErrorKind::Temporary)
        );
        assert_eq!(
            classify_by_text_signature("Connection timed out"),
            Some(ErrorKind::Temporary)
        );
    }

    #[test]
    fn test_classify_server_errors() {
        assert_eq!(
            classify_by_text_signature("Internal server error"),
            Some(ErrorKind::Temporary)
        );
        assert_eq!(
            classify_by_text_signature("HTTP 502 Bad Gateway"),
            Some(ErrorKind::Temporary)
        );
        assert_eq!(
            classify_by_text_signature("HTTP 503 Service Unavailable"),
            Some(ErrorKind::Temporary)
        );
    }

    #[test]
    fn test_classify_unknown_message() {
        assert_eq!(classify_by_text_signature("Something went wrong"), None);
        assert_eq!(classify_by_text_signature(""), None);
    }

    // ----- normalize_messages_for_api -----

    #[test]
    fn test_prune_orphan_tool_result() {
        // tool_result without matching tool_call should be removed
        let messages = vec![
            json!({"role": "user", "content": "hello"}),
            json!({"role": "tool", "tool_call_id": "call_orphan", "content": "result"}),
            json!({"role": "assistant", "content": "hi"}),
        ];
        let result = prune_orphan_tool_messages(messages);
        assert_eq!(result.len(), 2);
        assert_eq!(result[0]["role"], "user");
        assert_eq!(result[1]["role"], "assistant");
    }

    #[test]
    fn test_prune_orphan_tool_call() {
        // assistant with tool_calls but no matching tool_result should be removed
        let messages = vec![
            json!({"role": "user", "content": "hello"}),
            json!({"role": "assistant", "tool_calls": [{"id": "call_1", "type": "function", "function": {"name": "foo", "arguments": "{}"}}]}),
        ];
        let result = prune_orphan_tool_messages(messages);
        assert_eq!(result.len(), 1);
        assert_eq!(result[0]["role"], "user");
    }

    #[test]
    fn test_keep_matched_tool_pair() {
        // matched tool_call + tool_result should both be kept
        let messages = vec![
            json!({"role": "user", "content": "hello"}),
            json!({"role": "assistant", "tool_calls": [{"id": "call_1", "type": "function", "function": {"name": "foo", "arguments": "{}"}}]}),
            json!({"role": "tool", "tool_call_id": "call_1", "content": "result"}),
            json!({"role": "assistant", "content": "done"}),
        ];
        let result = prune_orphan_tool_messages(messages);
        assert_eq!(result.len(), 4);
    }

    #[test]
    fn test_anthropic_merge_consecutive_user() {
        let messages = vec![
            json!({"role": "user", "content": "first"}),
            json!({"role": "user", "content": "second"}),
            json!({"role": "assistant", "content": "reply"}),
        ];
        let result = enforce_anthropic_message_rules(messages);
        // merged_user + assistant + trailing "Continue." user
        assert_eq!(result.len(), 3);
        assert_eq!(result[0]["content"], "first\n\nsecond");
        assert_eq!(result[1]["role"], "assistant");
        assert_eq!(result[2]["role"], "user");
        assert_eq!(result[2]["content"], "Continue.");
    }

    #[test]
    fn test_anthropic_insert_user_at_start() {
        let messages = vec![json!({"role": "assistant", "content": "hi"})];
        let result = enforce_anthropic_message_rules(messages);
        assert_eq!(result.len(), 3); // synthetic user + assistant + trailing user
        assert_eq!(result[0]["role"], "user");
        assert_eq!(result[0]["content"], "Continue.");
        assert_eq!(result[1]["role"], "assistant");
        assert_eq!(result[2]["role"], "user");
    }

    #[test]
    fn test_anthropic_append_user_at_end() {
        let messages = vec![
            json!({"role": "user", "content": "hello"}),
            json!({"role": "assistant", "content": "reply"}),
        ];
        let result = enforce_anthropic_message_rules(messages);
        assert_eq!(result.len(), 3);
        assert_eq!(result[2]["role"], "user");
        assert_eq!(result[2]["content"], "Continue.");
    }

    #[test]
    fn test_anthropic_no_append_when_user_last() {
        let messages = vec![
            json!({"role": "user", "content": "hello"}),
            json!({"role": "assistant", "content": "reply"}),
            json!({"role": "user", "content": "more"}),
        ];
        let result = enforce_anthropic_message_rules(messages);
        assert_eq!(result.len(), 3);
        assert_eq!(result[2]["content"], "more");
    }

    #[test]
    fn test_anthropic_system_preserved() {
        let messages = vec![
            json!({"role": "system", "content": "system prompt"}),
            json!({"role": "user", "content": "hello"}),
        ];
        let result = enforce_anthropic_message_rules(messages);
        assert_eq!(result.len(), 2);
        assert_eq!(result[0]["role"], "system");
        assert_eq!(result[1]["role"], "user");
    }

    #[test]
    fn test_normalize_empty() {
        let result = normalize_messages_for_api(vec![], TransportKind::Messages);
        assert!(result.is_empty());
    }

    #[test]
    fn test_normalize_completion_skips_anthropic_rules() {
        // For completion transport, consecutive same-role should NOT be merged
        let messages = vec![
            json!({"role": "user", "content": "first"}),
            json!({"role": "user", "content": "second"}),
        ];
        let result = normalize_messages_for_api(messages, TransportKind::Completion);
        assert_eq!(result.len(), 2);
    }

    #[test]
    fn test_normalize_messages_keeps_multiple_tool_results_for_messages_transport() {
        let messages = vec![
            json!({"role": "user", "content": "hello"}),
            json!({
                "role": "assistant",
                "tool_calls": [
                    {"id": "call_1", "type": "function", "function": {"name": "bash", "arguments": "{}"}},
                    {"id": "call_2", "type": "function", "function": {"name": "skill", "arguments": "{}"}}
                ]
            }),
            json!({"role": "tool", "tool_call_id": "call_1", "content": "result-1"}),
            json!({"role": "tool", "tool_call_id": "call_2", "content": "result-2"}),
        ];

        let result = normalize_messages_for_api(messages, TransportKind::Messages);
        assert_eq!(result.len(), 4);
        assert_eq!(result[2]["tool_call_id"], "call_1");
        assert_eq!(result[3]["tool_call_id"], "call_2");
    }

    #[test]
    fn test_normalize_messages_canonicalizes_responses_style_tool_calls() {
        let messages = vec![
            json!({"role": "user", "content": "hello"}),
            json!({
                "role": "assistant",
                "tool_calls": [{
                    "type": "function_call",
                    "call_id": "call_123",
                    "name": "tape_info",
                    "arguments": "{}"
                }]
            }),
            json!({"role": "tool", "tool_call_id": "call_123", "content": "ok"}),
        ];

        let result = normalize_messages_for_api(messages, TransportKind::Messages);

        assert_eq!(result.len(), 3);
        assert_eq!(result[1]["tool_calls"][0]["id"], "call_123");
        assert_eq!(result[1]["tool_calls"][0]["function"]["name"], "tape_info");
    }
}