From b21ce8ab4c9163d02bfea0483a9be9d408a1ab29 Mon Sep 17 00:00:00 2001
From: Siraj R Aizlewood <siraj@aurelio.ai>
Date: Wed, 14 Feb 2024 12:25:27 +0400
Subject: [PATCH] New PyTest
test_from_file_with_llm()
---
tests/unit/test_layer.py | 54 ++++++++++++++++++++++++++++++----------
1 file changed, 41 insertions(+), 13 deletions(-)
diff --git a/tests/unit/test_layer.py b/tests/unit/test_layer.py
index ae0a6263..cbf10f10 100644
--- a/tests/unit/test_layer.py
+++ b/tests/unit/test_layer.py
@@ -1,12 +1,14 @@
import os
import tempfile
-from unittest.mock import mock_open, patch
+from unittest.mock import mock_open, patch, MagicMock, create_autospec
import pytest
from semantic_router.encoders import BaseEncoder, CohereEncoder, OpenAIEncoder
from semantic_router.layer import LayerConfig, RouteLayer
from semantic_router.route import Route
+from semantic_router.llms.base import BaseLLM
+from semantic_router.schema import Message
def mock_encoder_call(utterances):
@@ -334,18 +336,6 @@ class TestRouteLayer:
assert len(layer_config.routes) == 2
assert layer_config.routes[0].name == "politics"
- # def test_from_file_with_llm(openai_encoder, tmp_path):
- # # Create a temporary JSON file with LLM information in one of the routes
- # config_with_llm = layer_json_with_llm() # You need to define this function to include LLM data
- # config_path = tmp_path / "config_with_llm.json"
- # config_path.write_text(config_with_llm)
-
- # # Load the LayerConfig from the temporary file
- # layer_config = LayerConfig.from_file(str(config_path))
-
- # # Assertions to verify LLM handling
- # assert isinstance(layer_config.routes[0].llm, BaseLLM) # Or the specific LLM class you expect
-
def test_from_file_invalid_path(self):
with pytest.raises(FileNotFoundError) as excinfo:
LayerConfig.from_file("nonexistent_path.json")
@@ -362,6 +352,44 @@ class TestRouteLayer:
LayerConfig.from_file(str(config_path))
assert "Unsupported file type" in str(excinfo.value)
+ def test_from_file_with_llm(self, tmp_path):
+ llm_config_json = """
+ {
+ "encoder_type": "cohere",
+ "encoder_name": "embed-english-v3.0",
+ "routes": [
+ {
+ "name": "llm_route",
+ "utterances": ["tell me a joke", "say something funny"],
+ "llm": {
+ "module": "semantic_router.llms.base",
+ "class": "BaseLLM",
+ "model": "fake-model-v1"
+ }
+ }
+ ]
+ }"""
+
+ # Instead of mocking, directly instantiate BaseLLM with a name
+ fake_llm_instance = BaseLLM(name="fake-model-v1")
+
+ config_path = tmp_path / "config_with_llm.json"
+ with open(config_path, "w") as file:
+ file.write(llm_config_json)
+
+ # Load the LayerConfig from the temporary file
+ layer_config = LayerConfig.from_file(str(config_path))
+
+ # Assertions to verify the behavior
+ # Since we're not mocking importlib.import_module, we skip the assertion
+ # that checks if the module was imported. Instead, we focus on the result.
+ assert isinstance(
+ layer_config.routes[0].llm, BaseLLM
+ ), "LLM should be instantiated and associated with the route based on the config"
+ assert (
+ layer_config.routes[0].llm.name == "fake-model-v1"
+ ), "LLM instance should have the 'name' attribute set correctly"
+
def test_config(self, openai_encoder, routes):
os.environ["OPENAI_API_KEY"] = "test_api_key"
route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
--
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