# pylint: disable=line-too-long,useless-suppression
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------

"""
DESCRIPTION:
    Given an AIProjectClient, this sample demonstrates how to use the synchronous
    `openai.evals.*` methods to create, get and list eval group and and eval runs
    for Tool Success evaluator using inline dataset content.

USAGE:
    python sample_tool_success.py

    Before running the sample:

    pip install "azure-ai-projects>=2.0.0b1" azure-identity python-dotenv

    Set these environment variables with your own values:
    1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
       Microsoft Foundry project. It has the form: https://<account_name>.services.ai.azure.com/api/projects/<project_name>.
    2) AZURE_AI_MODEL_DEPLOYMENT_NAME - Required. The name of the model deployment to use for evaluation.
"""

from dotenv import load_dotenv
import os
import json
import time
from pprint import pprint

from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
from openai.types.evals.create_eval_jsonl_run_data_source_param import (
    CreateEvalJSONLRunDataSourceParam,
    SourceFileContent,
    SourceFileContentContent,
)


load_dotenv()


def main() -> None:
    endpoint = os.environ[
        "AZURE_AI_PROJECT_ENDPOINT"
    ]  # Sample : https://<account_name>.services.ai.azure.com/api/projects/<project_name>
    model_deployment_name = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME", "")  # Sample : gpt-4o-mini

    with DefaultAzureCredential() as credential:
        with AIProjectClient(endpoint=endpoint, credential=credential) as project_client:
            print("Creating an OpenAI client from the AI Project client")

            client = project_client.get_openai_client()

            data_source_config = {
                "type": "custom",
                "item_schema": {
                    "type": "object",
                    "properties": {
                        "tool_definitions": {
                            "anyOf": [{"type": "object"}, {"type": "array", "items": {"type": "object"}}]
                        },
                        "response": {"anyOf": [{"type": "string"}, {"type": "array", "items": {"type": "object"}}]},
                    },
                    "required": ["response"],
                },
                "include_sample_schema": True,
            }

            testing_criteria = [
                {
                    "type": "azure_ai_evaluator",
                    "name": "tool_success",
                    "evaluator_name": "builtin.tool_success",
                    "initialization_parameters": {"deployment_name": f"{model_deployment_name}"},
                    "data_mapping": {"tool_definitions": "{{item.tool_definitions}}", "response": "{{item.response}}"},
                }
            ]

            print("Creating Eval Group")
            eval_object = client.evals.create(
                name="Test Tool Success Evaluator with inline data",
                data_source_config=data_source_config, # type: ignore
                testing_criteria=testing_criteria, # type: ignore
            )
            print(f"Eval Group created")

            print("Get Eval Group by Id")
            eval_object_response = client.evals.retrieve(eval_object.id)
            print("Eval Run Response:")
            pprint(eval_object_response)

            # Example 1: Successful tool execution
            response1 = [
                {
                    "createdAt": "2025-03-26T17:27:35Z",
                    "run_id": "run_ToolSuccess123",
                    "role": "assistant",
                    "content": [
                        {
                            "type": "tool_call",
                            "tool_call_id": "call_FileUpload456",
                            "name": "upload_file",
                            "arguments": {"file_path": "/documents/report.pdf", "destination": "cloud_storage"},
                        }
                    ],
                },
                {
                    "createdAt": "2025-03-26T17:27:37Z",
                    "run_id": "run_ToolSuccess123",
                    "tool_call_id": "call_FileUpload456",
                    "role": "tool",
                    "content": [
                        {
                            "type": "tool_result",
                            "tool_result": {
                                "status": "success",
                                "file_id": "file_12345",
                                "upload_url": "https://storage.example.com/file_12345",
                                "message": "File uploaded successfully",
                            },
                        }
                    ],
                },
                {
                    "createdAt": "2025-03-26T17:27:39Z",
                    "run_id": "run_ToolSuccess123",
                    "role": "assistant",
                    "content": [
                        {
                            "type": "text",
                            "text": "I've successfully uploaded your report.pdf to cloud storage. The file ID is file_12345 and it's available at the provided URL.",
                        }
                    ],
                },
            ]
            tool_definitions1 = [
                {
                    "name": "upload_file",
                    "description": "Upload a file to cloud storage",
                    "parameters": {
                        "type": "object",
                        "properties": {
                            "file_path": {"type": "string", "description": "Path to the file to upload"},
                            "destination": {"type": "string", "description": "Destination storage location"},
                        },
                    },
                }
            ]

            # Example 2: Failed tool execution
            response2 = [
                {
                    "createdAt": "2025-03-26T17:28:10Z",
                    "run_id": "run_ToolFail789",
                    "role": "assistant",
                    "content": [
                        {
                            "type": "tool_call",
                            "tool_call_id": "call_DatabaseQuery101",
                            "name": "query_database",
                            "arguments": {"table": "users", "query": "SELECT * FROM users WHERE age > 25"},
                        }
                    ],
                },
                {
                    "createdAt": "2025-03-26T17:28:12Z",
                    "run_id": "run_ToolFail789",
                    "tool_call_id": "call_DatabaseQuery101",
                    "role": "tool",
                    "content": [
                        {
                            "type": "tool_result",
                            "tool_result": {
                                "status": "error",
                                "error_code": "DB_CONNECTION_FAILED",
                                "message": "Unable to connect to database. Connection timeout after 30 seconds.",
                            },
                        }
                    ],
                },
                {
                    "createdAt": "2025-03-26T17:28:14Z",
                    "run_id": "run_ToolFail789",
                    "role": "assistant",
                    "content": [
                        {
                            "type": "text",
                            "text": "I encountered an error while trying to query the database. The connection timed out after 30 seconds. Please try again later or contact your database administrator.",
                        }
                    ],
                },
            ]
            tool_definitions2 = [
                {
                    "name": "query_database",
                    "description": "Execute SQL queries on the database",
                    "parameters": {
                        "type": "object",
                        "properties": {
                            "table": {"type": "string", "description": "Database table name"},
                            "query": {"type": "string", "description": "SQL query to execute"},
                        },
                    },
                }
            ]

            print("Creating Eval Run with Inline Data")
            eval_run_object = client.evals.runs.create(
                eval_id=eval_object.id,
                name="inline_data_run",
                metadata={"team": "eval-exp", "scenario": "inline-data-v1"},
                data_source=CreateEvalJSONLRunDataSourceParam(
                    type="jsonl",
                    source=SourceFileContent(
                        type="file_content",
                        content=[
                            # Example 1: Successful tool execution
                            SourceFileContentContent(
                                item={"tool_definitions": tool_definitions1, "response": response1}
                            ),
                            # Example 2: Failed tool execution
                            SourceFileContentContent(
                                item={"tool_definitions": tool_definitions2, "response": response2}
                            ),
                        ],
                    ),
                ),
            )

            print(f"Eval Run created")
            pprint(eval_run_object)

            print("Get Eval Run by Id")
            eval_run_response = client.evals.runs.retrieve(run_id=eval_run_object.id, eval_id=eval_object.id)
            print("Eval Run Response:")
            pprint(eval_run_response)

            print("\n\n----Eval Run Output Items----\n\n")

            while True:
                run = client.evals.runs.retrieve(run_id=eval_run_response.id, eval_id=eval_object.id)
                if run.status == "completed" or run.status == "failed":
                    output_items = list(client.evals.runs.output_items.list(run_id=run.id, eval_id=eval_object.id))
                    pprint(output_items)
                    print(f"Eval Run Status: {run.status}")
                    print(f"Eval Run Report URL: {run.report_url}")
                    break
                time.sleep(5)
                print("Waiting for eval run to complete...")


if __name__ == "__main__":
    main()
