from __future__ import annotations

from dataclasses import dataclass
from typing import Any, Dict, Optional

from openai import OpenAI


# ----------------------------
# Low-level (pass-through)
# ----------------------------

def agent_call_req(client: OpenAI, req: Dict[str, Any]) -> Any:
    """
    Lowest-level call: forwards the request dict to the OpenAI Responses API.

    Use this when your code already builds `req` with fields like:
      - model, input, max_output_tokens
      - text.format (json_schema / json_object)
      - reasoning / temperature, etc.
    """
    return client.responses.create(**req)


# ----------------------------
# High-level convenience (optional)
# ----------------------------

@dataclass
class AgentCallResult:
    text: str
    used_structured_output: bool


def agent_call(
    client: OpenAI,
    model: str,
    prompt: str,
    max_output_tokens: int,
    schema: Optional[dict] = None,
) -> AgentCallResult:
    """
    Convenience wrapper for simple calls.

    IMPORTANT:
    This uses `response_format=...` which is a different request shape than
    the `text: {format: ...}` style you use in main/main.py.

    For your current pipeline (where you build `req` with text.format),
    prefer `agent_call_req(client, req)`.
    """
    if schema:
        resp = client.responses.create(
            model=model,
            input=prompt,
            max_output_tokens=max_output_tokens,
            response_format={
                "type": "json_schema",
                "json_schema": schema,
            },
        )
        return AgentCallResult(text=resp.output_text, used_structured_output=True)

    resp = client.responses.create(
        model=model,
        input=prompt,
        max_output_tokens=max_output_tokens,
    )
    return AgentCallResult(text=resp.output_text, used_structured_output=False)