openai-protocol 1.0.0

use std::collections::HashMap;

use serde::{Deserialize, Serialize};
use serde_json::{Map, Value};

use super::common::*;

// ============================================================================
// Completions API (v1/completions) - DEPRECATED but still supported
// ============================================================================

#[derive(Debug, Clone, Deserialize, Serialize)]
pub struct CompletionRequest {
    /// ID of the model to use (required for OpenAI, optional for some implementations, such as SGLang)
    pub model: String,

    /// The prompt(s) to generate completions for
    pub prompt: StringOrArray,

    /// The suffix that comes after a completion of inserted text
    #[serde(skip_serializing_if = "Option::is_none")]
    pub suffix: Option<String>,

    /// The maximum number of tokens to generate
    #[serde(skip_serializing_if = "Option::is_none")]
    pub max_tokens: Option<u32>,

    /// What sampling temperature to use, between 0 and 2
    #[serde(skip_serializing_if = "Option::is_none")]
    pub temperature: Option<f32>,

    /// An alternative to sampling with temperature (nucleus sampling)
    #[serde(skip_serializing_if = "Option::is_none")]
    pub top_p: Option<f32>,

    /// How many completions to generate for each prompt
    #[serde(skip_serializing_if = "Option::is_none")]
    pub n: Option<u32>,

    /// Whether to stream back partial progress
    #[serde(default)]
    pub stream: bool,

    /// Options for streaming response
    #[serde(skip_serializing_if = "Option::is_none")]
    pub stream_options: Option<StreamOptions>,

    /// Include the log probabilities on the logprobs most likely tokens
    #[serde(skip_serializing_if = "Option::is_none")]
    pub logprobs: Option<u32>,

    /// Echo back the prompt in addition to the completion
    #[serde(default)]
    pub echo: bool,

    /// Up to 4 sequences where the API will stop generating further tokens
    #[serde(skip_serializing_if = "Option::is_none")]
    pub stop: Option<StringOrArray>,

    /// Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far
    #[serde(skip_serializing_if = "Option::is_none")]
    pub presence_penalty: Option<f32>,

    /// Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far
    #[serde(skip_serializing_if = "Option::is_none")]
    pub frequency_penalty: Option<f32>,

    /// Generates best_of completions server-side and returns the "best"
    #[serde(skip_serializing_if = "Option::is_none")]
    pub best_of: Option<u32>,

    /// Modify the likelihood of specified tokens appearing in the completion
    #[serde(skip_serializing_if = "Option::is_none")]
    pub logit_bias: Option<HashMap<String, f32>>,

    /// A unique identifier representing your end-user
    #[serde(skip_serializing_if = "Option::is_none")]
    pub user: Option<String>,

    /// If specified, our system will make a best effort to sample deterministically
    #[serde(skip_serializing_if = "Option::is_none")]
    pub seed: Option<i64>,

    // -------- Engine Specific Sampling Parameters --------
    /// Top-k sampling parameter (-1 to disable)
    #[serde(skip_serializing_if = "Option::is_none")]
    pub top_k: Option<i32>,

    /// Min-p nucleus sampling parameter
    #[serde(skip_serializing_if = "Option::is_none")]
    pub min_p: Option<f32>,

    /// Minimum number of tokens to generate
    #[serde(skip_serializing_if = "Option::is_none")]
    pub min_tokens: Option<u32>,

    /// Repetition penalty for reducing repetitive text
    #[serde(skip_serializing_if = "Option::is_none")]
    pub repetition_penalty: Option<f32>,

    /// Regex constraint for output generation
    #[serde(skip_serializing_if = "Option::is_none")]
    pub regex: Option<String>,

    /// EBNF grammar constraint for structured output
    #[serde(skip_serializing_if = "Option::is_none")]
    pub ebnf: Option<String>,

    /// JSON schema constraint for structured output
    #[serde(skip_serializing_if = "Option::is_none")]
    pub json_schema: Option<String>,

    /// Specific token IDs to use as stop conditions
    #[serde(skip_serializing_if = "Option::is_none")]
    pub stop_token_ids: Option<Vec<u32>>,

    /// Skip trimming stop tokens from output
    #[serde(default)]
    pub no_stop_trim: bool,

    /// Ignore end-of-sequence tokens during generation
    #[serde(default)]
    pub ignore_eos: bool,

    /// Skip special tokens during detokenization
    #[serde(default = "default_true")]
    pub skip_special_tokens: bool,

    /// Path to LoRA adapter(s) for model customization
    #[serde(skip_serializing_if = "Option::is_none")]
    pub lora_path: Option<String>,

    /// Session parameters for continual prompting
    #[serde(skip_serializing_if = "Option::is_none")]
    pub session_params: Option<HashMap<String, Value>>,

    /// Return model hidden states
    #[serde(default)]
    pub return_hidden_states: bool,

    /// Sampling seed for deterministic outputs
    #[serde(skip_serializing_if = "Option::is_none")]
    pub sampling_seed: Option<u64>,

    /// Additional fields including bootstrap info for PD routing
    #[serde(flatten)]
    pub other: Map<String, Value>,
}

impl GenerationRequest for CompletionRequest {
    fn is_stream(&self) -> bool {
        self.stream
    }

    fn get_model(&self) -> Option<&str> {
        Some(&self.model)
    }

    fn extract_text_for_routing(&self) -> String {
        match &self.prompt {
            StringOrArray::String(s) => s.clone(),
            StringOrArray::Array(v) => v.join(" "),
        }
    }
}

// ============================================================================
// Response Types
// ============================================================================

#[derive(Debug, Clone, Deserialize, Serialize)]
pub struct CompletionResponse {
    pub id: String,
    pub object: String, // "text_completion"
    pub created: u64,
    pub model: String,
    pub choices: Vec<CompletionChoice>,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub usage: Option<Usage>,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub system_fingerprint: Option<String>,
}

#[derive(Debug, Clone, Deserialize, Serialize)]
pub struct CompletionChoice {
    pub text: String,
    pub index: u32,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub logprobs: Option<LogProbs>,
    pub finish_reason: Option<String>, // "stop", "length", "content_filter", etc.
    /// Information about which stop condition was matched
    #[serde(skip_serializing_if = "Option::is_none")]
    pub matched_stop: Option<Value>, // Can be string or integer
}

#[derive(Debug, Clone, Deserialize, Serialize)]
pub struct CompletionStreamResponse {
    pub id: String,
    pub object: String, // "text_completion"
    pub created: u64,
    pub choices: Vec<CompletionStreamChoice>,
    pub model: String,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub system_fingerprint: Option<String>,
}

#[derive(Debug, Clone, Deserialize, Serialize)]
pub struct CompletionStreamChoice {
    pub text: String,
    pub index: u32,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub logprobs: Option<LogProbs>,
    pub finish_reason: Option<String>,
}