Merge branch 'main' of https://github.com/confident-ai/deepeval into …

…anindya/harness

deepeval/__init__.py

@@ -4,17 +4,17 @@
 # Optionally add telemtry
 from ._version import __version__
 
-from .decorators.hyperparameters import set_hyperparameters
 from deepeval.event import track
-from deepeval.evaluate import evaluate, run_test, assert_test
-from deepeval.test_run import on_test_run_end
+from deepeval.evaluate import evaluate, assert_test
+from deepeval.test_run import on_test_run_end, log_hyperparameters
+from deepeval.utils import login_with_confident_api_key
 from deepeval.telemetry import *
 
 __all__ = [
-    "set_hyperparameters",
+    "login_with_confident_api_key",
+    "log_hyperparameters",
     "track",
     "evaluate",
-    "run_test",
     "assert_test",
     "on_test_run_end",
 ]

deepeval/_version.py

@@ -1 +1 @@
-__version__: str = "0.20.78"
+__version__: str = "0.20.85"

deepeval/cli/main.py

@@ -1,11 +1,7 @@
 import typer
 from typing_extensions import Annotated
 
-# Rich has a few dependency issues
-try:
-    from rich import print
-except Exception as e:
-    pass
+from rich import print
 from deepeval.key_handler import KEY_FILE_HANDLER, KeyValues
 from deepeval.cli.test import app as test_app
 from typing import Optional

deepeval/dataset/dataset.py

@@ -2,7 +2,10 @@
 from dataclasses import dataclass
 from rich.console import Console
 import json
+import csv
 import webbrowser
+import os
+import datetime
 
 from deepeval.metrics import BaseMetric
 from deepeval.api import Api, Endpoints
@@ -20,6 +23,8 @@
 from deepeval.utils import is_confident
 from deepeval.synthesizer.base_synthesizer import BaseSynthesizer
 
+valid_file_types = ["csv", "json"]
+
 
 @dataclass
 class EvaluationDataset:
@@ -335,3 +340,56 @@ def generate_goldens(
         self.goldens.extend(
             synthesizer.generate_goldens(contexts, max_goldens_per_context)
         )
+
+    # TODO: add save test cases as well
+    def save_as(self, file_type: str, directory: str):
+        if file_type not in valid_file_types:
+            raise ValueError(
+                f"Invalid file type. Available file types to save as: {', '.join(type for type in valid_file_types)}"
+            )
+
+        if len(self.goldens) == 0:
+            raise ValueError(
+                f"No synthetic goldens found. Please generate goldens before attempting to save data as {file_type}"
+            )
+
+        new_filename = (
+            datetime.datetime.now().strftime("%Y%m%d_%H%M%S") + f".{file_type}"
+        )
+
+        if not os.path.exists(directory):
+            os.makedirs(directory)
+
+        full_file_path = os.path.join(directory, new_filename)
+
+        if file_type == "json":
+            with open(full_file_path, "w") as file:
+                json_data = [
+                    {
+                        "input": golden.input,
+                        "actual_output": golden.actual_output,
+                        "expected_output": golden.expected_output,
+                        "context": golden.context,
+                    }
+                    for golden in self.goldens
+                ]
+                json.dump(json_data, file, indent=4)
+
+        elif file_type == "csv":
+            with open(full_file_path, "w", newline="") as file:
+                writer = csv.writer(file)
+                writer.writerow(
+                    ["input", "actual_output", "expected_output", "context"]
+                )
+                for golden in self.goldens:
+                    context_str = "|".join(golden.context)
+                    writer.writerow(
+                        [
+                            golden.input,
+                            golden.actual_output,
+                            golden.expected_output,
+                            context_str,
+                        ]
+                    )
+
+        print(f"Evaluation dataset saved at {full_file_path}!")