use std::sync::Arc;

use hermesllm::apis::openai::{ChatCompletionsRequest, Message, MessageContent, Role};
use hyper::header::HeaderMap;

use crate::handlers::agent_selector::{AgentSelectionError, AgentSelector};
use crate::handlers::pipeline_processor::PipelineProcessor;
use crate::router::plano_orchestrator::OrchestratorService;
use common::errors::BrightStaffError;
use http_body_util::BodyExt;
use hyper::StatusCode;
/// Integration test that demonstrates the modular agent chat flow
/// This test shows how the three main components work together:
/// 1. AgentSelector - selects the appropriate agents based on orchestration
/// 2. PipelineProcessor - executes the agent pipeline
/// 3. ResponseHandler - handles response streaming
#[cfg(test)]
mod tests {
    use super::*;
    use common::configuration::{Agent, AgentFilterChain, Listener};

    fn create_test_orchestrator_service() -> Arc<OrchestratorService> {
        Arc::new(OrchestratorService::new(
            "http://localhost:8080".to_string(),
            "test-model".to_string(),
        ))
    }

    fn create_test_message(role: Role, content: &str) -> Message {
        Message {
            role,
            content: Some(MessageContent::Text(content.to_string())),
            name: None,
            tool_calls: None,
            tool_call_id: None,
        }
    }

    #[tokio::test]
    async fn test_modular_agent_chat_flow() {
        // Setup services
        let orchestrator_service = create_test_orchestrator_service();
        let agent_selector = AgentSelector::new(orchestrator_service);
        let mut pipeline_processor = PipelineProcessor::default();

        // Create test data
        let agents = vec![
            Agent {
                id: "filter-agent".to_string(),
                agent_type: Some("filter".to_string()),
                url: "http://localhost:8081".to_string(),
                tool: None,
                transport: None,
            },
            Agent {
                id: "terminal-agent".to_string(),
                agent_type: Some("terminal".to_string()),
                url: "http://localhost:8082".to_string(),
                tool: None,
                transport: None,
            },
        ];

        let agent_pipeline = AgentFilterChain {
            id: "terminal-agent".to_string(),
            filter_chain: Some(vec![
                "filter-agent".to_string(),
                "terminal-agent".to_string(),
            ]),
            description: Some("Test pipeline".to_string()),
            default: Some(true),
        };

        let listener = Listener {
            name: "test-listener".to_string(),
            agents: Some(vec![agent_pipeline.clone()]),
            port: 8080,
            router: None,
        };

        let listeners = vec![listener];
        let messages = vec![create_test_message(Role::User, "Hello world!")];

        // Test 1: Agent Selection
        let selected_listener = agent_selector
            .find_listener(Some("test-listener"), &listeners)
            .await;

        assert!(selected_listener.is_ok());
        let listener = selected_listener.unwrap();
        assert_eq!(listener.name, "test-listener");

        // Test 2: Agent Map Creation
        let agent_map = agent_selector.create_agent_map(&agents);
        assert_eq!(agent_map.len(), 2);
        assert!(agent_map.contains_key("filter-agent"));
        assert!(agent_map.contains_key("terminal-agent"));

        // Test 3: Pipeline Processing (empty filter chain for testing)
        let request = ChatCompletionsRequest {
            messages: messages.clone(),
            model: "test-model".to_string(),
            ..Default::default()
        };

        // Create a pipeline with empty filter chain to avoid network calls
        let test_pipeline = AgentFilterChain {
            id: "terminal-agent".to_string(),
            filter_chain: Some(vec![]), // Empty filter chain - no network calls needed
            description: None,
            default: None,
        };

        let headers = HeaderMap::new();
        let result = pipeline_processor
            .process_filter_chain(&request.messages, &test_pipeline, &agent_map, &headers)
            .await;

        println!("Pipeline processing result: {:?}", result);

        assert!(result.is_ok());
        let processed_messages = result.unwrap();
        // With empty filter chain, should return the original messages unchanged
        assert_eq!(processed_messages.len(), 1);
        if let Some(MessageContent::Text(content)) = &processed_messages[0].content {
            assert_eq!(content, "Hello world!");
        } else {
            panic!("Expected text content");
        }

        // Test 4: Error Response Creation
        let err = BrightStaffError::ModelNotFound("gpt-5-secret".to_string());
        let response = err.into_response();

        assert_eq!(response.status(), StatusCode::NOT_FOUND);

        // Helper to extract body as JSON
        let body_bytes = response.into_body().collect().await.unwrap().to_bytes();
        let body: serde_json::Value = serde_json::from_slice(&body_bytes).unwrap();

        assert_eq!(body["error"]["code"], "ModelNotFound");
        assert_eq!(
            body["error"]["details"]["rejected_model_id"],
            "gpt-5-secret"
        );
        assert!(body["error"]["message"]
            .as_str()
            .unwrap()
            .contains("gpt-5-secret"));

        println!("✅ All modular components working correctly!");
    }

    #[tokio::test]
    async fn test_error_handling_flow() {
        let router_service = create_test_orchestrator_service();
        let agent_selector = AgentSelector::new(router_service);

        // Test listener not found
        let result = agent_selector.find_listener(Some("nonexistent"), &[]).await;

        assert!(result.is_err());
        assert!(matches!(
            result.unwrap_err(),
            AgentSelectionError::ListenerNotFound(_)
        ));

        let technical_reason = "Database connection timed out";
        let err = BrightStaffError::InternalServerError(technical_reason.to_string());

        let response = err.into_response();

        // --- 1. EXTRACT BYTES ---
        let body_bytes = response.into_body().collect().await.unwrap().to_bytes();

        // --- 2. DECLARE body_json HERE ---
        let body_json: serde_json::Value =
            serde_json::from_slice(&body_bytes).expect("Failed to parse JSON body");

        // --- 3. USE body_json ---
        assert_eq!(body_json["error"]["code"], "InternalServerError");
        assert_eq!(body_json["error"]["details"]["reason"], technical_reason);

        println!("✅ Error handling working correctly!");
    }
}