// Responses API response types

use crate::protocols::openai::responses::request::ResponsesRequest;
use crate::protocols::openai::responses::types::*;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;

fn generate_response_id() -> String {
    format!("resp_{}", uuid::Uuid::new_v4().simple())
}

fn current_timestamp() -> i64 {
    std::time::SystemTime::now()
        .duration_since(std::time::UNIX_EPOCH)
        .unwrap_or_else(|_| std::time::Duration::from_secs(0))
        .as_secs() as i64
}

#[derive(Debug, Clone, Deserialize, Serialize)]
pub struct ResponsesResponse {
    /// Response ID
    #[serde(default = "generate_response_id")]
    pub id: String,

    /// Object type
    #[serde(default = "default_object_type")]
    pub object: String,

    /// Creation timestamp
    #[serde(default = "current_timestamp")]
    pub created_at: i64,

    /// Model name
    pub model: String,

    /// Output items
    #[serde(default)]
    pub output: Vec<ResponseOutputItem>,

    /// Response status
    pub status: ResponseStatus,

    /// Usage information
    #[serde(skip_serializing_if = "Option::is_none")]
    pub usage: Option<UsageInfo>,

    /// Whether parallel tool calls are enabled
    #[serde(default = "default_true")]
    pub parallel_tool_calls: bool,

    /// Tool choice setting
    #[serde(default = "default_tool_choice")]
    pub tool_choice: String,

    /// Available tools
    #[serde(default)]
    pub tools: Vec<ResponseTool>,
}

fn default_object_type() -> String {
    "response".to_string()
}

fn default_true() -> bool {
    true
}

fn default_tool_choice() -> String {
    "auto".to_string()
}

impl ResponsesResponse {
    /// Create a response from a request
    #[allow(clippy::too_many_arguments)]
    pub fn from_request(
        request: &ResponsesRequest,
        _sampling_params: &HashMap<String, serde_json::Value>,
        model_name: String,
        created_time: i64,
        output: Vec<ResponseOutputItem>,
        status: ResponseStatus,
        usage: Option<UsageInfo>,
    ) -> Self {
        Self {
            id: request.request_id.clone(),
            object: "response".to_string(),
            created_at: created_time,
            model: model_name,
            output,
            status,
            usage,
            parallel_tool_calls: request.parallel_tool_calls,
            tool_choice: match request.tool_choice {
                ToolChoice::Auto => "auto".to_string(),
                ToolChoice::Required => "required".to_string(),
                ToolChoice::None => "none".to_string(),
            },
            tools: request.tools.clone(),
        }
    }

    /// Create a new response with default values
    pub fn new(request_id: String, model: String, status: ResponseStatus) -> Self {
        Self {
            id: request_id,
            object: "response".to_string(),
            created_at: current_timestamp(),
            model,
            output: Vec::new(),
            status,
            usage: None,
            parallel_tool_calls: true,
            tool_choice: "auto".to_string(),
            tools: Vec::new(),
        }
    }

    /// Add an output item to the response
    pub fn add_output(&mut self, item: ResponseOutputItem) {
        self.output.push(item);
    }

    /// Set the usage information
    pub fn set_usage(&mut self, usage: UsageInfo) {
        self.usage = Some(usage);
    }

    /// Update the status
    pub fn set_status(&mut self, status: ResponseStatus) {
        self.status = status;
    }

    /// Check if the response is complete
    pub fn is_complete(&self) -> bool {
        matches!(self.status, ResponseStatus::Completed)
    }

    /// Check if the response is in progress
    pub fn is_in_progress(&self) -> bool {
        matches!(self.status, ResponseStatus::InProgress)
    }

    /// Check if the response failed
    pub fn is_failed(&self) -> bool {
        matches!(self.status, ResponseStatus::Failed)
    }

    /// Check if the response was cancelled
    pub fn is_cancelled(&self) -> bool {
        matches!(self.status, ResponseStatus::Cancelled)
    }

    /// Check if the response is queued
    pub fn is_queued(&self) -> bool {
        matches!(self.status, ResponseStatus::Queued)
    }

    /// Convert usage to OpenAI Responses API format
    pub fn usage_in_response_format(
        &self,
    ) -> Option<crate::protocols::openai::responses::types::ResponseUsage> {
        self.usage.as_ref().map(|usage| usage.to_response_usage())
    }

    /// Get the response as a JSON value with usage in response format
    pub fn to_response_format(&self) -> serde_json::Value {
        let mut response = serde_json::to_value(self).unwrap_or(serde_json::Value::Null);

        // Convert usage to response format if present
        if let Some(usage) = &self.usage {
            if let Ok(usage_value) = serde_json::to_value(usage.to_response_usage()) {
                response["usage"] = usage_value;
            }
        }

        response
    }
}

// ============= Helper Functions =============

impl ResponseOutputItem {
    /// Create a new message output item
    pub fn new_message(
        id: String,
        role: String,
        content: Vec<ResponseContentPart>,
        status: String,
    ) -> Self {
        Self::Message {
            id,
            role,
            content,
            status,
        }
    }

    /// Create a new reasoning output item
    pub fn new_reasoning(
        id: String,
        summary: Vec<String>,
        content: Vec<ResponseReasoningContent>,
        status: Option<String>,
    ) -> Self {
        Self::Reasoning {
            id,
            summary,
            content,
            status,
        }
    }

    /// Create a new function tool call output item
    pub fn new_function_tool_call(
        id: String,
        name: String,
        arguments: String,
        output: Option<String>,
        status: String,
    ) -> Self {
        Self::FunctionToolCall {
            id,
            name,
            arguments,
            output,
            status,
        }
    }
}

impl ResponseContentPart {
    /// Create a new text content part
    pub fn new_text(
        text: String,
        annotations: Vec<String>,
        logprobs: Option<crate::protocols::openai::common::ChatLogProbs>,
    ) -> Self {
        Self::OutputText {
            text,
            annotations,
            logprobs,
        }
    }
}

impl ResponseReasoningContent {
    /// Create a new reasoning text content
    pub fn new_reasoning_text(text: String) -> Self {
        Self::ReasoningText { text }
    }
}

impl UsageInfo {
    /// Create a new usage info with token counts
    pub fn new(prompt_tokens: u32, completion_tokens: u32, reasoning_tokens: Option<u32>) -> Self {
        Self {
            prompt_tokens,
            completion_tokens,
            total_tokens: prompt_tokens + completion_tokens,
            reasoning_tokens,
            prompt_tokens_details: None,
        }
    }

    /// Create usage info with cached token details
    pub fn new_with_cached(
        prompt_tokens: u32,
        completion_tokens: u32,
        reasoning_tokens: Option<u32>,
        cached_tokens: u32,
    ) -> Self {
        Self {
            prompt_tokens,
            completion_tokens,
            total_tokens: prompt_tokens + completion_tokens,
            reasoning_tokens,
            prompt_tokens_details: Some(PromptTokenUsageInfo { cached_tokens }),
        }
    }
}