Merge branch 'master' of https://github.com/BillSchumacher/Auto-GPT into plugin-support

tests/integration/weaviate_memory_tests.py

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+import unittest
+from unittest import mock
+import sys
+import os
+
+from weaviate import Client
+from weaviate.util import get_valid_uuid
+from uuid import uuid4
+
+from autogpt.config import Config
+from autogpt.memory.weaviate import WeaviateMemory
+from autogpt.memory.base import get_ada_embedding
+
+
+@mock.patch.dict(os.environ, {
+    "WEAVIATE_HOST": "127.0.0.1",
+    "WEAVIATE_PROTOCOL": "http",
+    "WEAVIATE_PORT": "8080",
+    "WEAVIATE_USERNAME": "",
+    "WEAVIATE_PASSWORD": "",
+    "MEMORY_INDEX": "AutogptTests"
+})
+class TestWeaviateMemory(unittest.TestCase):
+    cfg = None
+    client = None
+
+    @classmethod
+    def setUpClass(cls):
+        # only create the connection to weaviate once
+        cls.cfg = Config()
+
+        if cls.cfg.use_weaviate_embedded:
+            from weaviate.embedded import EmbeddedOptions
+
+            cls.client = Client(embedded_options=EmbeddedOptions(
+                hostname=cls.cfg.weaviate_host,
+                port=int(cls.cfg.weaviate_port),
+                persistence_data_path=cls.cfg.weaviate_embedded_path
+            ))
+        else:
+            cls.client = Client(f"{cls.cfg.weaviate_protocol}://{cls.cfg.weaviate_host}:{self.cfg.weaviate_port}")
+
+    """
+    In order to run these tests you will need a local instance of
+    Weaviate running. Refer to https://weaviate.io/developers/weaviate/installation/docker-compose
+    for creating local instances using docker.
+    Alternatively in your .env file set the following environmental variables to run Weaviate embedded (see: https://weaviate.io/developers/weaviate/installation/embedded):
+
+        USE_WEAVIATE_EMBEDDED=True
+        WEAVIATE_EMBEDDED_PATH="/home/me/.local/share/weaviate"
+    """
+    def setUp(self):
+        try:
+            self.client.schema.delete_class(self.cfg.memory_index)
+        except:
+            pass
+
+        self.memory = WeaviateMemory(self.cfg)
+
+    def test_add(self):
+        doc = 'You are a Titan name Thanos and you are looking for the Infinity Stones'
+        self.memory.add(doc)
+        result = self.client.query.get(self.cfg.memory_index, ['raw_text']).do()
+        actual = result['data']['Get'][self.cfg.memory_index]
+
+        self.assertEqual(len(actual), 1)
+        self.assertEqual(actual[0]['raw_text'], doc)
+
+    def test_get(self):
+        doc = 'You are an Avenger and swore to defend the Galaxy from a menace called Thanos'
+
+        with self.client.batch as batch:
+            batch.add_data_object(
+                uuid=get_valid_uuid(uuid4()),
+                data_object={'raw_text': doc},
+                class_name=self.cfg.memory_index,
+                vector=get_ada_embedding(doc)
+            )
+
+            batch.flush()
+
+        actual = self.memory.get(doc)
+
+        self.assertEqual(len(actual), 1)
+        self.assertEqual(actual[0], doc)
+
+    def test_get_stats(self):
+        docs = [
+            'You are now about to count the number of docs in this index',
+            'And then you about to find out if you can count correctly'
+        ]
+
+        [self.memory.add(doc) for doc in docs]
+
+        stats = self.memory.get_stats()
+
+        self.assertTrue(stats)
+        self.assertTrue('count' in stats)
+        self.assertEqual(stats['count'], 2)
+
+    def test_clear(self):
+        docs = [
+            'Shame this is the last test for this class',
+            'Testing is fun when someone else is doing it'
+        ]
+
+        [self.memory.add(doc) for doc in docs]
+
+        self.assertEqual(self.memory.get_stats()['count'], 2)
+
+        self.memory.clear()
+
+        self.assertEqual(self.memory.get_stats()['count'], 0)
+
+
+if __name__ == '__main__':
+    unittest.main()

tests/unit/test_chat.py

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+# Generated by CodiumAI
+import unittest
+import time
+from unittest.mock import patch
+
+from autogpt.chat import create_chat_message, generate_context
+
+
+class TestChat(unittest.TestCase):
+    # Tests that the function returns a dictionary with the correct keys and values when valid strings are provided for role and content.
+    def test_happy_path_role_content(self):
+        result = create_chat_message("system", "Hello, world!")
+        self.assertEqual(result, {"role": "system", "content": "Hello, world!"})
+
+    # Tests that the function returns a dictionary with the correct keys and values when empty strings are provided for role and content.
+    def test_empty_role_content(self):
+        result = create_chat_message("", "")
+        self.assertEqual(result, {"role": "", "content": ""})
+
+    # Tests the behavior of the generate_context function when all input parameters are empty.
+    @patch("time.strftime")
+    def test_generate_context_empty_inputs(self, mock_strftime):
+        # Mock the time.strftime function to return a fixed value
+        mock_strftime.return_value = "Sat Apr 15 00:00:00 2023"
+        # Arrange
+        prompt = ""
+        relevant_memory = ""
+        full_message_history = []
+        model = "gpt-3.5-turbo-0301"
+
+        # Act
+        result = generate_context(prompt, relevant_memory, full_message_history, model)
+
+        # Assert
+        expected_result = (
+            -1,
+            47,
+            3,
+            [
+                {"role": "system", "content": ""},
+                {
+                    "role": "system",
+                    "content": f"The current time and date is {time.strftime('%c')}",
+                },
+                {
+                    "role": "system",
+                    "content": f"This reminds you of these events from your past:\n\n\n",
+                },
+            ],
+        )
+        self.assertEqual(result, expected_result)
+
+    # Tests that the function successfully generates a current_context given valid inputs.
+    def test_generate_context_valid_inputs(self):
+        # Given
+        prompt = "What is your favorite color?"
+        relevant_memory = "You once painted your room blue."
+        full_message_history = [
+            create_chat_message("user", "Hi there!"),
+            create_chat_message("assistant", "Hello! How can I assist you today?"),
+            create_chat_message("user", "Can you tell me a joke?"),
+            create_chat_message(
+                "assistant",
+                "Why did the tomato turn red? Because it saw the salad dressing!",
+            ),
+            create_chat_message("user", "Haha, that's funny."),
+        ]
+        model = "gpt-3.5-turbo-0301"
+
+        # When
+        result = generate_context(prompt, relevant_memory, full_message_history, model)
+
+        # Then
+        self.assertIsInstance(result[0], int)
+        self.assertIsInstance(result[1], int)
+        self.assertIsInstance(result[2], int)
+        self.assertIsInstance(result[3], list)
+        self.assertGreaterEqual(result[0], 0)
+        self.assertGreaterEqual(result[1], 0)
+        self.assertGreaterEqual(result[2], 0)
+        self.assertGreaterEqual(
+            len(result[3]), 3
+        )  # current_context should have at least 3 messages
+        self.assertLessEqual(
+            result[1], 2048
+        )  # token limit for GPT-3.5-turbo-0301 is 2048 tokens