use async_trait::async_trait;
use futures::StreamExt;
use log::{info, trace};
use serde_json::Value;
use tokio::sync::mpsc;

pub mod cache;
pub mod episodic_memory;
pub mod llm_models;
pub mod local;
pub mod observability;

pub use llm_models::get_handler;

#[async_trait]
pub trait LLMProvider: Send + Sync {
    async fn generate(
        &self,
        prompt: &str,
        config: &Value,
        model: &str,
        key: &str,
    ) -> Result<String, Box<dyn std::error::Error + Send + Sync>>;

    async fn generate_stream(
        &self,
        prompt: &str,
        config: &Value,
        tx: mpsc::Sender<String>,
        model: &str,
        key: &str,
    ) -> Result<(), Box<dyn std::error::Error + Send + Sync>>;

    async fn cancel_job(
        &self,
        session_id: &str,
    ) -> Result<(), Box<dyn std::error::Error + Send + Sync>>;
}

#[derive(Debug)]
pub struct OpenAIClient {
    client: reqwest::Client,
    base_url: String,
}

impl OpenAIClient {
    pub fn new(_api_key: String, base_url: Option<String>) -> Self {
        Self {
            client: reqwest::Client::new(),
            base_url: base_url.unwrap_or_else(|| "https://api.openai.com".to_string()),
        }
    }

    pub fn build_messages(
        system_prompt: &str,
        context_data: &str,
        history: &[(String, String)],
    ) -> Value {
        let mut messages = Vec::new();
        if !system_prompt.is_empty() {
            messages.push(serde_json::json!({
                "role": "system",
                "content": system_prompt
            }));
        }
        if !context_data.is_empty() {
            messages.push(serde_json::json!({
                "role": "system",
                "content": context_data
            }));
        }
        for (role, content) in history {
            messages.push(serde_json::json!({
                "role": role,
                "content": content
            }));
        }
        serde_json::Value::Array(messages)
    }
}

#[async_trait]
impl LLMProvider for OpenAIClient {
    async fn generate(
        &self,
        prompt: &str,
        messages: &Value,
        model: &str,
        key: &str,
    ) -> Result<String, Box<dyn std::error::Error + Send + Sync>> {
        let default_messages = serde_json::json!([{"role": "user", "content": prompt}]);
        let response = self
            .client
            .post(&format!("{}/v1/chat/completions", self.base_url))
            .header("Authorization", format!("Bearer {}", key))
            .json(&serde_json::json!({
                "model": model,
                "messages": if messages.is_array() && !messages.as_array().unwrap().is_empty() {
                    messages
                } else {
                    &default_messages
                }
            }))
            .send()
            .await?;

        let result: Value = response.json().await?;
        let raw_content = result["choices"][0]["message"]["content"]
            .as_str()
            .unwrap_or("");

        let handler = get_handler(model);
        let content = handler.process_content(raw_content);

        Ok(content)
    }

    async fn generate_stream(
        &self,
        prompt: &str,
        messages: &Value,
        tx: mpsc::Sender<String>,
        model: &str,
        key: &str,
    ) -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
        let default_messages = serde_json::json!([{"role": "user", "content": prompt}]);
        let response = self
            .client
            .post(&format!("{}/v1/chat/completions", self.base_url))
            .header("Authorization", format!("Bearer {}", key))
            .json(&serde_json::json!({
                "model": model,
                "messages": if messages.is_array() && !messages.as_array().unwrap().is_empty() {
                    info!("Using provided messages: {:?}", messages);
                    messages
                } else {
                    &default_messages
                },
                "stream": true
            }))
            .send()
            .await?;

        let status = response.status();
        if status != reqwest::StatusCode::OK {
            let error_text = response.text().await.unwrap_or_default();
            trace!("LLM generate_stream error: {}", error_text);
            return Err(format!("LLM request failed with status: {}", status).into());
        }

        let handler = get_handler(model);
        let mut stream = response.bytes_stream();
        let mut buffer = String::new();

        while let Some(chunk) = stream.next().await {
            let chunk = chunk?;
            let chunk_str = String::from_utf8_lossy(&chunk);
            for line in chunk_str.lines() {
                if line.starts_with("data: ") && !line.contains("[DONE]") {
                    if let Ok(data) = serde_json::from_str::<Value>(&line[6..]) {
                        if let Some(content) = data["choices"][0]["delta"]["content"].as_str() {
                            buffer.push_str(content);
                            let processed = handler.process_content(content);
                            if !processed.is_empty() {
                                let _ = tx.send(processed).await;
                            }
                        }
                    }
                }
            }
        }

        Ok(())
    }

    async fn cancel_job(
        &self,
        _session_id: &str,
    ) -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
        Ok(())
    }
}

pub fn start_llm_services(state: &std::sync::Arc<crate::shared::state::AppState>) {
    episodic_memory::start_episodic_memory_scheduler(std::sync::Arc::clone(state));
    info!("LLM services started (episodic memory scheduler)");
}