use anyhow::Result;
use async_trait::async_trait;
use futures::stream::BoxStream;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use uuid::Uuid;

use super::{ProviderResponse, ProviderStreamChunk};
use crate::{
    config::AppConfig,
    errors::AppError,
    models::{ContentPart, FunctionCall, FunctionCallDelta, ToolCall, ToolCallDelta, UnifiedMessage, UnifiedRequest},
};

// ========== Gemini Request Structs ==========

#[derive(Debug, Serialize)]
#[serde(rename_all = "camelCase")]
struct GeminiRequest {
    contents: Vec<GeminiContent>,
    #[serde(skip_serializing_if = "Option::is_none")]
    generation_config: Option<GeminiGenerationConfig>,
    #[serde(skip_serializing_if = "Option::is_none")]
    tools: Option<Vec<GeminiTool>>,
    #[serde(skip_serializing_if = "Option::is_none")]
    tool_config: Option<GeminiToolConfig>,
}

#[derive(Debug, Serialize, Deserialize)]
struct GeminiContent {
    parts: Vec<GeminiPart>,
    role: String,
}

#[derive(Debug, Serialize, Deserialize)]
#[serde(rename_all = "camelCase")]
struct GeminiPart {
    #[serde(skip_serializing_if = "Option::is_none")]
    text: Option<String>,
    #[serde(skip_serializing_if = "Option::is_none")]
    inline_data: Option<GeminiInlineData>,
    #[serde(skip_serializing_if = "Option::is_none")]
    function_call: Option<GeminiFunctionCall>,
    #[serde(skip_serializing_if = "Option::is_none")]
    function_response: Option<GeminiFunctionResponse>,
}

#[derive(Debug, Serialize, Deserialize)]
struct GeminiInlineData {
    mime_type: String,
    data: String,
}

#[derive(Debug, Serialize, Deserialize)]
struct GeminiFunctionCall {
    name: String,
    args: Value,
}

#[derive(Debug, Serialize, Deserialize)]
struct GeminiFunctionResponse {
    name: String,
    response: Value,
}

#[derive(Debug, Serialize)]
#[serde(rename_all = "camelCase")]
struct GeminiGenerationConfig {
    temperature: Option<f64>,
    max_output_tokens: Option<u32>,
}

// ========== Gemini Tool Structs ==========

#[derive(Debug, Serialize)]
#[serde(rename_all = "camelCase")]
struct GeminiTool {
    function_declarations: Vec<GeminiFunctionDeclaration>,
}

#[derive(Debug, Serialize)]
struct GeminiFunctionDeclaration {
    name: String,
    #[serde(skip_serializing_if = "Option::is_none")]
    description: Option<String>,
    #[serde(skip_serializing_if = "Option::is_none")]
    parameters: Option<Value>,
}

#[derive(Debug, Serialize)]
#[serde(rename_all = "camelCase")]
struct GeminiToolConfig {
    function_calling_config: GeminiFunctionCallingConfig,
}

#[derive(Debug, Serialize)]
struct GeminiFunctionCallingConfig {
    mode: String,
    #[serde(skip_serializing_if = "Option::is_none", rename = "allowedFunctionNames")]
    allowed_function_names: Option<Vec<String>>,
}

// ========== Gemini Response Structs ==========

#[derive(Debug, Deserialize)]
#[serde(rename_all = "camelCase")]
struct GeminiCandidate {
    content: GeminiContent,
    #[serde(default)]
    finish_reason: Option<String>,
}

#[derive(Debug, Deserialize)]
#[serde(rename_all = "camelCase")]
struct GeminiUsageMetadata {
    #[serde(default)]
    prompt_token_count: u32,
    #[serde(default)]
    candidates_token_count: u32,
    #[serde(default)]
    total_token_count: u32,
}

#[derive(Debug, Deserialize)]
#[serde(rename_all = "camelCase")]
struct GeminiResponse {
    candidates: Vec<GeminiCandidate>,
    usage_metadata: Option<GeminiUsageMetadata>,
}

// ========== Provider Implementation ==========

pub struct GeminiProvider {
    client: reqwest::Client,
    config: crate::config::GeminiConfig,
    api_key: String,
    pricing: Vec<crate::config::ModelPricing>,
}

impl GeminiProvider {
    pub fn new(config: &crate::config::GeminiConfig, app_config: &AppConfig) -> Result<Self> {
        let api_key = app_config.get_api_key("gemini")?;
        Self::new_with_key(config, app_config, api_key)
    }

    pub fn new_with_key(config: &crate::config::GeminiConfig, app_config: &AppConfig, api_key: String) -> Result<Self> {
        let client = reqwest::Client::builder()
            .timeout(std::time::Duration::from_secs(30))
            .build()?;

        Ok(Self {
            client,
            config: config.clone(),
            api_key,
            pricing: app_config.pricing.gemini.clone(),
        })
    }

    /// Convert unified messages to Gemini content format.
    /// Handles text, images, tool calls (assistant), and tool results.
    async fn convert_messages(messages: Vec<UnifiedMessage>) -> Result<Vec<GeminiContent>, AppError> {
        let mut contents = Vec::with_capacity(messages.len());

        for msg in messages {
            // Tool-result messages → functionResponse parts under role "user"
            if msg.role == "tool" {
                let text_content = msg
                    .content
                    .first()
                    .map(|p| match p {
                        ContentPart::Text { text } => text.clone(),
                        ContentPart::Image(_) => "[Image]".to_string(),
                    })
                    .unwrap_or_default();

                let name = msg.name.unwrap_or_default();

                // Parse the content as JSON if possible, otherwise wrap as string
                let response_value = serde_json::from_str::<Value>(&text_content)
                    .unwrap_or_else(|_| serde_json::json!({ "result": text_content }));

                contents.push(GeminiContent {
                    parts: vec![GeminiPart {
                        text: None,
                        inline_data: None,
                        function_call: None,
                        function_response: Some(GeminiFunctionResponse {
                            name,
                            response: response_value,
                        }),
                    }],
                    role: "user".to_string(),
                });
                continue;
            }

            // Assistant messages with tool_calls → functionCall parts
            if msg.role == "assistant" {
                if let Some(tool_calls) = &msg.tool_calls {
                    let mut parts = Vec::new();

                    // Include text content if present
                    for p in &msg.content {
                        if let ContentPart::Text { text } = p {
                            if !text.is_empty() {
                                parts.push(GeminiPart {
                                    text: Some(text.clone()),
                                    inline_data: None,
                                    function_call: None,
                                    function_response: None,
                                });
                            }
                        }
                    }

                    // Convert each tool call to a functionCall part
                    for tc in tool_calls {
                        let args = serde_json::from_str::<Value>(&tc.function.arguments)
                            .unwrap_or_else(|_| serde_json::json!({}));
                        parts.push(GeminiPart {
                            text: None,
                            inline_data: None,
                            function_call: Some(GeminiFunctionCall {
                                name: tc.function.name.clone(),
                                args,
                            }),
                            function_response: None,
                        });
                    }

                    contents.push(GeminiContent {
                        parts,
                        role: "model".to_string(),
                    });
                    continue;
                }
            }

            // Regular text/image messages
            let mut parts = Vec::with_capacity(msg.content.len());
            for part in msg.content {
                match part {
                    ContentPart::Text { text } => {
                        parts.push(GeminiPart {
                            text: Some(text),
                            inline_data: None,
                            function_call: None,
                            function_response: None,
                        });
                    }
                    ContentPart::Image(image_input) => {
                        let (base64_data, mime_type) = image_input
                            .to_base64()
                            .await
                            .map_err(|e| AppError::ProviderError(format!("Failed to convert image: {}", e)))?;

                        parts.push(GeminiPart {
                            text: None,
                            inline_data: Some(GeminiInlineData {
                                mime_type,
                                data: base64_data,
                            }),
                            function_call: None,
                            function_response: None,
                        });
                    }
                }
            }

            let role = match msg.role.as_str() {
                "assistant" => "model".to_string(),
                _ => "user".to_string(),
            };

            contents.push(GeminiContent { parts, role });
        }

        Ok(contents)
    }

    /// Convert OpenAI tools to Gemini function declarations.
    fn convert_tools(request: &UnifiedRequest) -> Option<Vec<GeminiTool>> {
        request.tools.as_ref().map(|tools| {
            let declarations: Vec<GeminiFunctionDeclaration> = tools
                .iter()
                .map(|t| GeminiFunctionDeclaration {
                    name: t.function.name.clone(),
                    description: t.function.description.clone(),
                    parameters: t.function.parameters.clone(),
                })
                .collect();
            vec![GeminiTool {
                function_declarations: declarations,
            }]
        })
    }

    /// Convert OpenAI tool_choice to Gemini tool_config.
    fn convert_tool_config(request: &UnifiedRequest) -> Option<GeminiToolConfig> {
        request.tool_choice.as_ref().map(|tc| {
            let (mode, allowed_names) = match tc {
                crate::models::ToolChoice::Mode(mode) => {
                    let gemini_mode = match mode.as_str() {
                        "auto" => "AUTO",
                        "none" => "NONE",
                        "required" => "ANY",
                        _ => "AUTO",
                    };
                    (gemini_mode.to_string(), None)
                }
                crate::models::ToolChoice::Specific(specific) => {
                    ("ANY".to_string(), Some(vec![specific.function.name.clone()]))
                }
            };
            GeminiToolConfig {
                function_calling_config: GeminiFunctionCallingConfig {
                    mode,
                    allowed_function_names: allowed_names,
                },
            }
        })
    }

    /// Extract tool calls from Gemini response parts into OpenAI-format ToolCalls.
    fn extract_tool_calls(parts: &[GeminiPart]) -> Option<Vec<ToolCall>> {
        let calls: Vec<ToolCall> = parts
            .iter()
            .filter_map(|p| p.function_call.as_ref())
            .map(|fc| ToolCall {
                id: format!("call_{}", Uuid::new_v4().simple()),
                call_type: "function".to_string(),
                function: FunctionCall {
                    name: fc.name.clone(),
                    arguments: serde_json::to_string(&fc.args).unwrap_or_else(|_| "{}".to_string()),
                },
            })
            .collect();

        if calls.is_empty() { None } else { Some(calls) }
    }

    /// Extract tool call deltas from Gemini response parts for streaming.
    fn extract_tool_call_deltas(parts: &[GeminiPart]) -> Option<Vec<ToolCallDelta>> {
        let deltas: Vec<ToolCallDelta> = parts
            .iter()
            .filter_map(|p| p.function_call.as_ref())
            .enumerate()
            .map(|(i, fc)| ToolCallDelta {
                index: i as u32,
                id: Some(format!("call_{}", Uuid::new_v4().simple())),
                call_type: Some("function".to_string()),
                function: Some(FunctionCallDelta {
                    name: Some(fc.name.clone()),
                    arguments: Some(serde_json::to_string(&fc.args).unwrap_or_else(|_| "{}".to_string())),
                }),
            })
            .collect();

        if deltas.is_empty() { None } else { Some(deltas) }
    }
}

#[async_trait]
impl super::Provider for GeminiProvider {
    fn name(&self) -> &str {
        "gemini"
    }

    fn supports_model(&self, model: &str) -> bool {
        model.starts_with("gemini-")
    }

    fn supports_multimodal(&self) -> bool {
        true // Gemini supports vision
    }

    async fn chat_completion(&self, request: UnifiedRequest) -> Result<ProviderResponse, AppError> {
        let model = request.model.clone();
        let tools = Self::convert_tools(&request);
        let tool_config = Self::convert_tool_config(&request);
        let contents = Self::convert_messages(request.messages).await?;

        if contents.is_empty() {
            return Err(AppError::ProviderError("No valid messages to send".to_string()));
        }

        let generation_config = if request.temperature.is_some() || request.max_tokens.is_some() {
            Some(GeminiGenerationConfig {
                temperature: request.temperature,
                max_output_tokens: request.max_tokens,
            })
        } else {
            None
        };

        let gemini_request = GeminiRequest {
            contents,
            generation_config,
            tools,
            tool_config,
        };

        let url = format!("{}/models/{}:generateContent", self.config.base_url, model);

        let response = self
            .client
            .post(&url)
            .header("x-goog-api-key", &self.api_key)
            .json(&gemini_request)
            .send()
            .await
            .map_err(|e| AppError::ProviderError(format!("HTTP request failed: {}", e)))?;

        let status = response.status();
        if !status.is_success() {
            let error_text = response.text().await.unwrap_or_default();
            return Err(AppError::ProviderError(format!(
                "Gemini API error ({}): {}",
                status, error_text
            )));
        }

        let gemini_response: GeminiResponse = response
            .json()
            .await
            .map_err(|e| AppError::ProviderError(format!("Failed to parse response: {}", e)))?;

        let candidate = gemini_response.candidates.first();

        // Extract text content (may be absent if only function calls)
        let content = candidate
            .and_then(|c| c.content.parts.iter().find_map(|p| p.text.clone()))
            .unwrap_or_default();

        // Extract function calls → OpenAI tool_calls
        let tool_calls = candidate.and_then(|c| Self::extract_tool_calls(&c.content.parts));

        let prompt_tokens = gemini_response
            .usage_metadata
            .as_ref()
            .map(|u| u.prompt_token_count)
            .unwrap_or(0);
        let completion_tokens = gemini_response
            .usage_metadata
            .as_ref()
            .map(|u| u.candidates_token_count)
            .unwrap_or(0);
        let total_tokens = gemini_response
            .usage_metadata
            .as_ref()
            .map(|u| u.total_token_count)
            .unwrap_or(0);

        Ok(ProviderResponse {
            content,
            reasoning_content: None,
            tool_calls,
            prompt_tokens,
            completion_tokens,
            total_tokens,
            model,
        })
    }

    fn estimate_tokens(&self, request: &UnifiedRequest) -> Result<u32> {
        Ok(crate::utils::tokens::estimate_request_tokens(&request.model, request))
    }

    fn calculate_cost(
        &self,
        model: &str,
        prompt_tokens: u32,
        completion_tokens: u32,
        registry: &crate::models::registry::ModelRegistry,
    ) -> f64 {
        super::helpers::calculate_cost_with_registry(
            model,
            prompt_tokens,
            completion_tokens,
            registry,
            &self.pricing,
            0.075,
            0.30,
        )
    }

    async fn chat_completion_stream(
        &self,
        request: UnifiedRequest,
    ) -> Result<BoxStream<'static, Result<ProviderStreamChunk, AppError>>, AppError> {
        let model = request.model.clone();
        let tools = Self::convert_tools(&request);
        let tool_config = Self::convert_tool_config(&request);
        let contents = Self::convert_messages(request.messages).await?;

        let generation_config = if request.temperature.is_some() || request.max_tokens.is_some() {
            Some(GeminiGenerationConfig {
                temperature: request.temperature,
                max_output_tokens: request.max_tokens,
            })
        } else {
            None
        };

        let gemini_request = GeminiRequest {
            contents,
            generation_config,
            tools,
            tool_config,
        };

        let url = format!(
            "{}/models/{}:streamGenerateContent?alt=sse",
            self.config.base_url, model,
        );

        use futures::StreamExt;
        use reqwest_eventsource::{Event, EventSource};

        let es = EventSource::new(
            self.client
                .post(&url)
                .header("x-goog-api-key", &self.api_key)
                .json(&gemini_request),
        )
        .map_err(|e| AppError::ProviderError(format!("Failed to create EventSource: {}", e)))?;

        let stream = async_stream::try_stream! {
            let mut es = es;
            while let Some(event) = es.next().await {
                match event {
                    Ok(Event::Message(msg)) => {
                        let gemini_response: GeminiResponse = serde_json::from_str(&msg.data)
                            .map_err(|e| AppError::ProviderError(format!("Failed to parse stream chunk: {}", e)))?;

                        if let Some(candidate) = gemini_response.candidates.first() {
                            let content = candidate
                                .content
                                .parts
                                .iter()
                                .find_map(|p| p.text.clone())
                                .unwrap_or_default();

                            let tool_calls = Self::extract_tool_call_deltas(&candidate.content.parts);

                            // Determine finish_reason
                            let finish_reason = candidate.finish_reason.as_ref().map(|fr| {
                                match fr.as_str() {
                                    "STOP" => "stop".to_string(),
                                    _ => fr.to_lowercase(),
                                }
                            });

                            yield ProviderStreamChunk {
                                content,
                                reasoning_content: None,
                                finish_reason,
                                tool_calls,
                                model: model.clone(),
                            };
                        }
                    }
                    Ok(_) => continue,
                    Err(e) => {
                        Err(AppError::ProviderError(format!("Stream error: {}", e)))?;
                    }
                }
            }
        };

        Ok(Box::pin(stream))
    }
}