looprs 0.4.0

use serde_json::{Value, json};
use std::time::Duration;

use crate::api::ContentBlock;
use crate::errors::ProviderError;

use super::{InferenceRequest, InferenceResponse, LLMProvider, Usage};
use crate::types::ModelId;

const OLLAMA_TIMEOUT_SECS: u64 = 120;
const HEALTH_CHECK_TIMEOUT_SECS: u64 = 5;

pub struct LocalProvider {
    client: reqwest::Client,
    host: String,
    model: ModelId,
}

impl LocalProvider {
    pub fn new() -> Result<Self, ProviderError> {
        let model = std::env::var("MODEL")
            .or_else(|_| std::env::var("OLLAMA_MODEL"))
            .ok()
            .map(ModelId::new);
        Self::new_with_model(model)
    }

    pub fn new_with_model(model: Option<ModelId>) -> Result<Self, ProviderError> {
        let client = reqwest::Client::builder()
            .timeout(Duration::from_secs(OLLAMA_TIMEOUT_SECS))
            .build()?;

        let host =
            std::env::var("OLLAMA_HOST").unwrap_or_else(|_| "http://localhost:11434".to_string());
        let model = match model {
            Some(model) => model,
            None => {
                let env_model = std::env::var("OLLAMA_MODEL")
                    .ok()
                    .or_else(|| std::env::var("MODEL").ok())
                    .map(ModelId::new);
                env_model.ok_or_else(|| {
                    ProviderError::Config(
                        "No local model configured. Set MODEL or OLLAMA_MODEL, or configure .looprs/provider.json"
                            .to_string(),
                    )
                })?
            }
        };

        Ok(Self {
            client,
            host,
            model,
        })
    }

    pub async fn is_available() -> bool {
        let host =
            std::env::var("OLLAMA_HOST").unwrap_or_else(|_| "http://localhost:11434".to_string());
        let client = match reqwest::Client::builder()
            .timeout(Duration::from_secs(HEALTH_CHECK_TIMEOUT_SECS))
            .build()
        {
            Ok(c) => c,
            Err(_) => return false,
        };

        match client.get(format!("{host}/api/tags")).send().await {
            Ok(res) => res.status().is_success(),
            Err(_) => false,
        }
    }

    fn convert_to_ollama_message(msg: &crate::api::Message) -> Value {
        let mut content = String::new();

        for block in &msg.content {
            match block {
                ContentBlock::Text { text } => {
                    content.push_str(text);
                }
                ContentBlock::ToolUse { id, name, input } => {
                    content.push_str(&format!("\n[TOOL_USE id={id} name={name}]\n{input}"));
                }
                ContentBlock::ToolResult {
                    tool_use_id,
                    content: result_content,
                } => {
                    content.push_str(&format!(
                        "\n[TOOL_RESULT id={tool_use_id}]\n{result_content}"
                    ));
                }
            }
        }

        json!({
            "role": msg.role,
            "content": content
        })
    }
}

#[async_trait::async_trait]
impl LLMProvider for LocalProvider {
    async fn infer(
        &self,
        req: &InferenceRequest,
    ) -> Result<InferenceResponse, Box<dyn std::error::Error + Send + Sync>> {
        let mut messages = vec![json!({
            "role": "system",
            "content": req.system
        })];

        messages.extend(req.messages.iter().map(Self::convert_to_ollama_message));

        let mut body = json!({
            "model": req.model.as_str(),
            "messages": messages,
            "stream": false,
        });
        if let Some(temp) = req.temperature {
            body["options"] = json!({ "temperature": temp });
        }

        let res = self
            .client
            .post(format!("{}/api/chat", self.host))
            .header("Content-Type", "application/json")
            .json(&body)
            .send()
            .await?;

        if !res.status().is_success() {
            let status = res.status();
            let err_text = res.text().await?;
            return Err(
                ProviderError::ApiError(format!("Ollama API Error {status}: {err_text}")).into(),
            );
        }

        let response_json: Value = res.json().await?;

        let content_str = response_json
            .get("message")
            .and_then(|m| m.get("content"))
            .and_then(|c| c.as_str())
            .ok_or_else(|| {
                ProviderError::InvalidResponse("No message content in response".to_string())
            })?;

        // Simple parsing for tool markers since local models don't support structured tools well
        let mut blocks = Vec::new();
        let mut current_text = String::new();

        for line in content_str.lines() {
            if line.starts_with("[TOOL_USE") {
                if !current_text.is_empty() {
                    blocks.push(ContentBlock::Text {
                        text: current_text.trim().to_string(),
                    });
                    current_text.clear();
                }
                // Try to parse tool use marker
                if let Some(end) = line.find(']') {
                    let marker = &line[..=end];
                    if marker.contains("id=") && marker.contains("name=") {
                        // Simplified parsing - local models don't always follow strict format
                        blocks.push(ContentBlock::Text {
                            text: marker.to_string(),
                        });
                    }
                }
            } else {
                current_text.push_str(line);
                current_text.push('\n');
            }
        }

        if !current_text.is_empty() {
            blocks.push(ContentBlock::Text {
                text: current_text.trim().to_string(),
            });
        }

        let usage = if let Some(usage_obj) = response_json.get("eval_count") {
            Usage {
                input_tokens: response_json
                    .get("prompt_eval_count")
                    .and_then(|v| v.as_u64())
                    .unwrap_or(0) as u32,
                output_tokens: usage_obj.as_u64().unwrap_or(0) as u32,
            }
        } else {
            Usage {
                input_tokens: 0,
                output_tokens: 0,
            }
        };

        Ok(InferenceResponse {
            content: blocks,
            stop_reason: "stop".to_string(),
            usage,
        })
    }

    fn name(&self) -> &str {
        "local"
    }

    fn model(&self) -> &ModelId {
        &self.model
    }

    fn validate_config(&self) -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
        if self.host.is_empty() {
            return Err(ProviderError::Config("Ollama host is empty".to_string()).into());
        }
        Ok(())
    }

    fn supports_tool_use(&self) -> bool {
        false
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use looprs_core::ports::test_contracts::assert_inference_provider_contract;

    #[test]
    fn local_provider_satisfies_inference_provider_contract() {
        let p = LocalProvider::new_with_model(Some(ModelId::new("llama3")))
            .expect("LocalProvider::new_with_model must succeed in test");
        assert_inference_provider_contract(&p);
    }
}