// SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
// SPDX-License-Identifier: Apache-2.0

use dynamo_async_openai::types::ChatCompletionMessageContent;
use dynamo_llm::protocols::{
    ContentProvider, DataStream,
    codec::{Message, SseCodecError, create_message_stream},
    openai::{
        ParsingOptions,
        chat_completions::{NvCreateChatCompletionResponse, aggregator::ChatCompletionAggregator},
        completions::NvCreateCompletionResponse,
    },
};
use futures::StreamExt;

fn get_text(content: &ChatCompletionMessageContent) -> &str {
    match content {
        ChatCompletionMessageContent::Text(text) => text.as_str(),
        ChatCompletionMessageContent::Parts(_) => "",
    }
}

const CMPL_ROOT_PATH: &str = "tests/data/replays/meta/llama-3.1-8b-instruct/completions";
const CHAT_ROOT_PATH: &str = "tests/data/replays/meta/llama-3.1-8b-instruct/chat_completions";

fn create_stream(root_path: &str, file_name: &str) -> DataStream<Result<Message, SseCodecError>> {
    let data = std::fs::read_to_string(format!("{}/{}", root_path, file_name)).unwrap();
    create_message_stream(&data)
}

#[tokio::test]
async fn test_openai_chat_stream() {
    let data = std::fs::read_to_string("tests/data/replays/meta/llama-3.1-8b-instruct/chat_completions/chat-completion.streaming.1").unwrap();

    // note: we are only taking the first 16 messages to keep the size of the response small
    let stream = create_message_stream(&data).take(16);
    let result = NvCreateChatCompletionResponse::from_sse_stream(
        Box::pin(stream),
        ParsingOptions::default(),
    )
    .await
    .unwrap();

    // todo: provide a cleaner way to extract the content from choices
    assert_eq!(
        get_text(
            result
                .choices
                .first()
                .unwrap()
                .message
                .content
                .as_ref()
                .expect("there to be content")
        ),
        "Deep learning is a subfield of machine learning that involves the use of artificial"
    );
}

#[tokio::test]
async fn test_openai_chat_edge_case_multi_line_data() {
    let stream = create_stream(CHAT_ROOT_PATH, "edge_cases/valid-multi-line-data");
    let result = NvCreateChatCompletionResponse::from_sse_stream(
        Box::pin(stream),
        ParsingOptions::default(),
    )
    .await
    .unwrap();

    assert_eq!(
        get_text(
            result
                .choices
                .first()
                .unwrap()
                .message
                .content
                .as_ref()
                .expect("there to be content")
        ),
        "Deep learning"
    );
}

#[tokio::test]
async fn test_openai_chat_edge_case_comments_per_response() {
    let stream = create_stream(CHAT_ROOT_PATH, "edge_cases/valid-comments_per_response");
    let result = NvCreateChatCompletionResponse::from_sse_stream(
        Box::pin(stream),
        ParsingOptions::default(),
    )
    .await
    .unwrap();

    assert_eq!(
        get_text(
            result
                .choices
                .first()
                .unwrap()
                .message
                .content
                .as_ref()
                .expect("there to be content")
        ),
        "Deep learning"
    );
}

#[tokio::test]
async fn test_openai_chat_edge_case_invalid_deserialize_error() {
    let stream = create_stream(CHAT_ROOT_PATH, "edge_cases/invalid-deserialize_error");
    let result = NvCreateChatCompletionResponse::from_sse_stream(
        Box::pin(stream),
        ParsingOptions::default(),
    )
    .await;

    assert!(result.is_err());
    // insta::assert_debug_snapshot!(result);
}

// =============================
// Completions (/v1/completions)
// =============================

#[tokio::test]
async fn test_openai_cmpl_stream() {
    let stream = create_stream(CMPL_ROOT_PATH, "completion.streaming.1").take(16);
    let result =
        NvCreateCompletionResponse::from_sse_stream(Box::pin(stream), ParsingOptions::default())
            .await
            .unwrap();

    // todo: provide a cleaner way to extract the content from choices
    assert_eq!(
        result.inner.choices.first().unwrap().content(),
        " This is a question that is often asked by those outside of AI research and development"
    );
}
