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_playground_output"

DESCRIPTION = (
    "Read the output from the currently mounted playground's latest run. The result "
    "includes each matching instance's raw output, run status, errors, tool calls, "
    "and traceId when the run produced a Phoenix trace. Use this after `run_playground` "
    "finishes so you can inspect the model response and analyze the trace."
)

PARAMETERS: dict[str, Any] = {
    "type": "object",
    "properties": {
        "instanceId": {
            "type": "integer",
            "description": (
                "Optional playground instance ID to read. Omit to read outputs for all "
                "visible comparison instances."
            ),
        },
        "repetitionNumber": {
            "type": "integer",
            "minimum": 1,
            "description": (
                "Optional repetition number to read for each selected instance. Omit to "
                "read every available repetition."
            ),
        },
    },
    "additionalProperties": False,
}

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


@dataclass
class ReadPlaygroundOutputCapability(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.playground is not None
