import json

from fastembed import TextEmbedding
from fastmcp import Client
from mcp.types import TextContent


async def test_call_tool(embedding_model: TextEmbedding, run_mcp: str):
    input = "Quien es el mas guapo?"
    collection = "dummy_collection"

    embedding: list[float] = list(embedding_model.embed(input))[0].tolist()

    client = Client(run_mcp)

    async with client:
        name = "semantic_search"
        body = {"embedding": embedding, "collection": collection}
        result = await client.call_tool(name, body)

    content_block = result.content[0]

    assert isinstance(content_block, TextContent)

    deserialized_result = json.loads(content_block.text)

    top_result = deserialized_result[0]

    assert top_result["chunk_id"] == "0"
    assert top_result["score"] > 0.7
    assert top_result["payload"] == {"text": "Rick es el mas guapo"}