"""
Robust tool-call parser for small language models.

Extracts structured tool calls from free-form model output using
regex-based parsing with multiple fallback strategies. Designed for
models that cannot reliably produce valid JSON (e.g. Qwen3-0.6B).

The expected model output format::

    Thought: I need to search the documents for information about X.
    <tool>retrieve_documents</tool>
    <param name="query">information about X</param>

Or for a final answer::

    Thought: I have enough information to answer.
    <answer>The answer is Y.</answer>

If parsing fails entirely, the raw output is treated as a direct answer.
"""

from __future__ import annotations

import re

from src.agents.schemas import ToolCall

# ---------------------------------------------------------------------------
# Regex patterns
# ---------------------------------------------------------------------------

_TOOL_RE = re.compile(r"<tool>\s*(\w+)\s*</tool[!.]?>", re.IGNORECASE)
_PARAM_RE = re.compile(
    r'<param\s+name=["\'](\w+)["\']>(.*?)</param[!.]?>',
    re.IGNORECASE | re.DOTALL,
)
_ANSWER_RE = re.compile(r"<answer>(.*?)</answer[!.]?>", re.IGNORECASE | re.DOTALL)
_THOUGHT_RE = re.compile(
    r"(?:Thought|Reasoning|Think):\s*(.+?)(?=<tool>|<answer>|$)",
    re.IGNORECASE | re.DOTALL,
)
# Fallback: model uses <tool_name>key: value\n...</tool_name> instead of
# the canonical <tool>/<param> format. Common with small models.
_ALT_TOOL_RE = re.compile(
    r"<(\w+)>\s*(.*?)\s*</\1>",
    re.IGNORECASE | re.DOTALL,
)
_ALT_PARAM_RE = re.compile(r"(\w+)\s*:\s*(.+)", re.MULTILINE)


# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------


def parse_tool_call(text: str) -> tuple[str, ToolCall | None, str | None]:
    """Parse model output into *(thought, tool_call_or_none, final_answer_or_none)*.

    Exactly one of *tool_call* or *final_answer* will be non-``None``.
    If neither is parseable the raw text is returned as the final answer.
    """
    thought = _extract_thought(text)

    # Try final answer first — if the model says <answer>, we're done.
    final_answer = _extract_final_answer(text)
    if final_answer is not None:
        return thought, None, final_answer

    # Try tool call.
    tool_call = _extract_tool_call(text)
    if tool_call is not None:
        return thought, tool_call, None

    # Fallback: treat entire output as a direct answer.
    return thought, None, text.strip()


# ---------------------------------------------------------------------------
# Internal helpers
# ---------------------------------------------------------------------------


def _extract_thought(text: str) -> str:
    """Extract the ``Thought:`` line, or everything before the first tag."""
    m = _THOUGHT_RE.search(text)
    if m:
        return m.group(1).strip()
    # Fallback: everything before the first < tag.
    idx = text.find("<")
    if idx > 0:
        return text[:idx].strip()
    return ""


def _extract_tool_call(text: str) -> ToolCall | None:
    """Try to extract tool calls, with fallback for alternative formats.

    Primary format: ``<tool>name</tool>`` + ``<param name="k">v</param>``
    Fallback format: ``<tool_name>key: value</tool_name>`` (common with small models)
    """
    # Primary format: <tool>name</tool> + <param> tags
    m = _TOOL_RE.search(text)
    if m is not None:
        tool_name = m.group(1)
        arguments: dict[str, str] = {}
        for pm in _PARAM_RE.finditer(text):
            arguments[pm.group(1)] = pm.group(2).strip()
        return ToolCall(tool_name=tool_name, arguments=arguments, raw_text=text)

    # Fallback: <tool_name>key: value\n...</tool_name>
    # e.g. <web_search>query: latest PyTorch\nnum_results: 3</web_search>
    for am in _ALT_TOOL_RE.finditer(text):
        tag_name = am.group(1)
        # Skip known non-tool tags
        if tag_name.lower() in ("answer", "think", "param"):
            continue
        body = am.group(2)
        arguments = {}
        for pm in _ALT_PARAM_RE.finditer(body):
            key = pm.group(1).strip().strip('"').strip("'")
            val = pm.group(2).strip().strip('"').strip("'")
            arguments[key] = val
        return ToolCall(tool_name=tag_name, arguments=arguments, raw_text=text)

    return None


def _extract_final_answer(text: str) -> str | None:
    """Try to extract ``<answer>...</answer>`` content."""
    m = _ANSWER_RE.search(text)
    if m is None:
        return None
    return m.group(1).strip()


def coerce_param(value: str, expected_type: str):
    """Best-effort type coercion for tool parameters."""
    if expected_type == "int":
        try:
            return int(value)
        except (ValueError, TypeError):
            return value
    if expected_type == "float":
        try:
            return float(value)
        except (ValueError, TypeError):
            return value
    return value