# -*- coding: utf-8 -*-
# Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""The eval command."""
from __future__ import annotations

from typing import Sequence

from google.generativeai.notebook import command
from google.generativeai.notebook import command_utils
from google.generativeai.notebook import input_utils
from google.generativeai.notebook import ipython_env
from google.generativeai.notebook import model_registry
from google.generativeai.notebook import output_utils
from google.generativeai.notebook import parsed_args_lib
from google.generativeai.notebook import post_process_utils
import pandas


class EvalCommand(command.Command):
  """Implementation of "eval" command."""

  def __init__(
      self,
      models: model_registry.ModelRegistry,
      env: ipython_env.IPythonEnv | None = None,
  ):
    """Constructor.

    Args:
      models: ModelRegistry instance.
      env: The IPythonEnv environment.
    """
    super().__init__()
    self._models = models
    self._ipython_env = env

  def execute(
      self,
      parsed_args: parsed_args_lib.ParsedArgs,
      cell_content: str,
      post_processing_fns: Sequence[post_process_utils.ParsedPostProcessExpr],
  ) -> pandas.DataFrame:
    # We expect CmdLineParser to have already read the inputs once to validate
    # that the placeholders in the prompt are present in the inputs, so we can
    # suppress the status messages here.
    inputs = input_utils.join_inputs_sources(
        parsed_args, suppress_status_msgs=True
    )

    llm_cmp_fn = command_utils.create_llm_eval_function(
        models=self._models,
        env=self._ipython_env,
        parsed_args=parsed_args,
        cell_content=cell_content,
        post_processing_fns=post_processing_fns,
    )

    results = llm_cmp_fn(inputs=inputs)
    output_utils.write_to_outputs(results=results, parsed_args=parsed_args)
    return results.as_pandas_dataframe()

  def parse_post_processing_tokens(
      self, tokens: Sequence[Sequence[str]]
  ) -> Sequence[post_process_utils.ParsedPostProcessExpr]:
    return post_process_utils.resolve_post_processing_tokens(tokens)