from __future__ import annotations

from dataclasses import dataclass
from typing import Any

from jinja2 import Template
from pydantic_ai import RunContext
from pydantic_ai.tools import SystemPromptFunc, ToolDefinition
from pydantic_ai.toolsets import AgentToolset
from pydantic_ai.toolsets.external import ExternalToolset

from phoenix.server.agents.capabilities.base import AbstractDynamicCapability
from phoenix.server.agents.types import AgentDependencies

NAME = "read_llm_evaluator_draft"

DESCRIPTION = (
    "Read the open LLM-evaluator draft. Returns the draft's name, description, "
    "judge prompt messages, model, provider, invocationParameters, outputConfigs, "
    "inputMapping, includeExplanation, testPayload, and form mode "
    "(`create` or `edit`). Call this before `edit_llm_evaluator_draft` or "
    "`test_llm_evaluator_draft` to see the current draft."
)

PARAMETERS: dict[str, Any] = {
    "type": "object",
    "properties": {},
    "additionalProperties": False,
}

TOOL_DEFINITION = ToolDefinition(
    name=NAME,
    description=DESCRIPTION,
    parameters_json_schema=PARAMETERS,
    kind="external",
)


@dataclass
class ReadLlmEvaluatorDraftCapability(AbstractDynamicCapability[AgentDependencies]):
    instructions: Template

    def get_toolset(self) -> AgentToolset[AgentDependencies] | None:
        return ExternalToolset[AgentDependencies]([TOOL_DEFINITION])

    def get_dynamic_instructions(self) -> SystemPromptFunc[AgentDependencies]:
        instructions = self.instructions

        def _instructions(ctx: RunContext[AgentDependencies]) -> str:
            return instructions.render()

        return _instructions

    def include_for_run(self, ctx: RunContext[AgentDependencies]) -> bool:
        return ctx.deps.contexts.llm_evaluator is not None
