"""GPT Researcher MCP — deep web research as fallback for any industry.

This is the universal fallback: when structured data sources don't have
data for a niche/cold industry, deep web research fills the gap.

Requires GPT Researcher MCP server to be running (already configured in ~/.claude.json).
For direct API use, we call the MCP tools via the subprocess approach.
"""

from __future__ import annotations

import asyncio
import json
import logging
import subprocess
from typing import Any

from .base import DataSource, DataResult

logger = logging.getLogger(__name__)


class GPTResearcherSource(DataSource):
    name = "gpt_researcher"
    description = "Deep web research — universal fallback for any industry/topic"

    def supports(self, data_type: str, country: str | None = None) -> bool:
        # Supports everything — this is the universal fallback
        return True

    async def fetch(
        self, query: str, *, data_type: str = "general", country: str | None = None, **kwargs,
    ) -> DataResult:
        mode = kwargs.get("mode", "quick")  # "quick" or "deep"

        # GPT Researcher is available as MCP tools in Claude Code.
        # For standalone use, we need to call it via its API.
        # The MCP server runs at a local port — check if available.

        # For now, provide a structured placeholder that agents can use
        # to request deep research. The actual MCP call happens at the
        # agent level when integrated into the pipeline.
        return DataResult(
            source=self.name,
            data={
                "query": query,
                "mode": mode,
                "status": "ready",
                "note": (
                    "GPT Researcher MCP is available for deep web research. "
                    "Call via MCP tools: deep_research() or quick_search(). "
                    "This source returns research-ready queries for MCP integration."
                ),
            },
            metadata={
                "type": "mcp_research_request",
                "mode": mode,
                "data_type": data_type,
                "country": country,
            },
        )