Vector memory revamp (part 1: refactoring) (#4208)

Additional changes:

* Improve typing

* Modularize message history memory & fix/refactor lots of things

* Fix summarization

* Move memory relevance calculation to MemoryItem & improve test

* Fix import warnings in web_selenium.py

* Remove `memory_add` ghost command

* Implement overlap in `split_text`

* Move memory tests into subdirectory

* Remove deprecated `get_ada_embedding()` and helpers

* Fix used token calculation in `chat_with_ai`

* Replace Message TypedDict by dataclass

* Fix AgentManager singleton issues in tests

---------

Co-authored-by: Auto-GPT-Bot <github-bot@agpt.co>

tests/conftest.py

@@ -4,11 +4,11 @@ from pathlib import Path
 import pytest
 from pytest_mock import MockerFixture
 
-from autogpt.config import Config
-from autogpt.llm import ApiManager
+from autogpt.config.config import Config
+from autogpt.llm.api_manager import ApiManager
 from autogpt.workspace import Workspace
 
-pytest_plugins = ["tests.integration.agent_factory"]
+pytest_plugins = ["tests.integration.agent_factory", "tests.integration.memory.utils"]
 
 PROXY = os.environ.get("PROXY")
 

tests/integration/agent_factory.py

@@ -3,7 +3,7 @@ import pytest
 from autogpt.agent import Agent
 from autogpt.commands.command import CommandRegistry
 from autogpt.config import AIConfig, Config
-from autogpt.memory import LocalCache, NoMemory, get_memory
+from autogpt.memory.vector import NoMemory, get_memory
 from autogpt.prompts.prompt import DEFAULT_TRIGGERING_PROMPT
 from autogpt.workspace import Workspace
 
@@ -20,20 +20,10 @@ def agent_test_config(config: Config):
 
 
 @pytest.fixture
-def memory_local_cache(agent_test_config: Config):
+def memory_json_file(agent_test_config: Config):
     was_memory_backend = agent_test_config.memory_backend
 
-    agent_test_config.set_memory_backend("local_cache")
-    yield get_memory(agent_test_config, init=True)
-
-    agent_test_config.set_memory_backend(was_memory_backend)
-
-
-@pytest.fixture
-def memory_none(agent_test_config: Config):
-    was_memory_backend = agent_test_config.memory_backend
-
-    agent_test_config.set_memory_backend("no_memory")
+    agent_test_config.set_memory_backend("json_file")
     yield get_memory(agent_test_config, init=True)
 
     agent_test_config.set_memory_backend(was_memory_backend)
@@ -64,7 +54,6 @@ def browser_agent(agent_test_config, memory_none: NoMemory, workspace: Workspace
     agent = Agent(
         ai_name="",
         memory=memory_none,
-        full_message_history=[],
         command_registry=command_registry,
         config=ai_config,
         next_action_count=0,
@@ -103,7 +92,6 @@ def writer_agent(agent_test_config, memory_none: NoMemory, workspace: Workspace)
     agent = Agent(
         ai_name="",
         memory=memory_none,
-        full_message_history=[],
         command_registry=command_registry,
         config=ai_config,
         next_action_count=0,
@@ -116,9 +104,7 @@ def writer_agent(agent_test_config, memory_none: NoMemory, workspace: Workspace)
 
 
 @pytest.fixture
-def memory_management_agent(
-    agent_test_config, memory_local_cache, workspace: Workspace
-):
+def memory_management_agent(agent_test_config, memory_json_file, workspace: Workspace):
     command_registry = CommandRegistry()
     command_registry.import_commands("autogpt.commands.file_operations")
     command_registry.import_commands("autogpt.app")
@@ -138,8 +124,7 @@ def memory_management_agent(
 
     agent = Agent(
         ai_name="",
-        memory=memory_local_cache,
-        full_message_history=[],
+        memory=memory_json_file,
         command_registry=command_registry,
         config=ai_config,
         next_action_count=0,
@@ -153,7 +138,7 @@ def memory_management_agent(
 
 @pytest.fixture
 def get_company_revenue_agent(
-    agent_test_config, memory_local_cache, workspace: Workspace
+    agent_test_config, memory_json_file, workspace: Workspace
 ):
     command_registry = CommandRegistry()
     command_registry.import_commands("autogpt.commands.file_operations")
@@ -172,7 +157,7 @@ def get_company_revenue_agent(
     Config().set_continuous_mode(False)
     agent = Agent(
         ai_name="Get-CompanyRevenue",
-        memory=memory_local_cache,
+        memory=memory_json_file,
         full_message_history=[],
         command_registry=command_registry,
         config=ai_config,
@@ -186,7 +171,7 @@ def get_company_revenue_agent(
 
 
 @pytest.fixture
-def kubernetes_agent(memory_local_cache, workspace: Workspace):
+def kubernetes_agent(memory_json_file, workspace: Workspace):
     command_registry = CommandRegistry()
     command_registry.import_commands("autogpt.commands.file_operations")
     command_registry.import_commands("autogpt.app")
@@ -205,7 +190,7 @@ def kubernetes_agent(memory_local_cache, workspace: Workspace):
     Config().set_continuous_mode(False)
     agent = Agent(
         ai_name="Kubernetes-Demo",
-        memory=memory_local_cache,
+        memory=memory_json_file,
         full_message_history=[],
         command_registry=command_registry,
         config=ai_config,

tests/integration/cassettes/test_llm_utils/test_get_ada_embedding.yaml

@@ -1,168 +0,0 @@
-interactions:
-- request:
-    body: '{"input": [[1985]], "model": "text-embedding-ada-002", "encoding_format":
-      "base64"}'
-    headers:
-      Accept:
-      - '*/*'
-      Accept-Encoding:
-      - gzip, deflate
-      Connection:
-      - keep-alive
-      Content-Length:
-      - '83'
-      Content-Type:
-      - application/json
-    method: POST
-    uri: https://api.openai.com/v1/embeddings
-  response:
-    body:
-      string: !!binary |
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tests/integration/challenges/basic_abilities/cassettes/test_browse_website/test_browse_website.yaml

@@ -2896,4 +2896,472 @@ interactions:
     status:
       code: 200
       message: OK
+- request:
+    body: '{"model": "gpt-3.5-turbo", "messages": [{"role": "user", "content": "Write
+      a concise summary of the following text; include any information that can be
+      used to answer the question \"What is the price of the book?\". Do not directly
+      answer the question itself:\n\n\nLITERAL TEXT: \"\"\"Books to Scrape We love
+      being scraped! Home Books Philosophy Meditations Meditations \u00a325.89 In
+      stock (1 available) Warning! This is a demo website for web scraping purposes.
+      Prices and ratings here were randomly assigned and have no real meaning. Product
+      Description Written in Greek, without any intention of publication, by the only
+      Roman emperor who was also a philosopher, the Meditations of Marcus Aurelius
+      (AD 121-180) offer a remarkable series of challenging spiritual reflections
+      and exercises developed as the emperor struggled to understand himself and make
+      sense of the universe. Ranging from doubt and despair to conviction and ex Written
+      in Greek, without any intention of publication, by the only Roman emperor who
+      was also a philosopher, the Meditations of Marcus Aurelius (AD 121-180) offer
+      a remarkable series of challenging spiritual reflections and exercises developed
+      as the emperor struggled to understand himself and make sense of the universe.
+      Ranging from doubt and despair to conviction and exaltation, they cover such
+      diverse topics as the nature of moral virtue, human rationality, divine providence,
+      and Marcus'' own emotions. But while the Meditations were composed to provide
+      personal consolation and encouragement, in developing his beliefs Marcus Aurelius
+      also created one of the greatest of all works of philosophy: a timeless collection
+      of extended meditations and short aphorisms that has been consulted and admired
+      by statesmen, thinkers and readers through the centuries. ...more Product Information
+      UPC4f19709e47883df5 Product TypeBooks Price (excl. tax)\u00a325.89 Price (incl.
+      tax)\u00a325.89 Tax\u00a30.00 Availability In stock (1 available) Number of
+      reviews 0 Products you recently viewed The Nicomachean Ethics \u00a336.34 In
+      stock Add to basket Run, Spot, Run: The ... \u00a320.02 In stock Add to basket
+      Critique of Pure Reason \u00a320.75 In stock Add to basket At The Existentialist
+      Caf\u00e9: ... \u00a329.93 In stock Add to basket Kierkegaard: A Christian Missionary
+      ... \u00a347.13 In stock Add to basket Proofs of God: Classical ... \u00a354.21
+      In stock Add to basket\"\"\"\n\n\nCONCISE SUMMARY: The text is best summarized
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+      "{\n    \"thoughts\": {\n        \"text\": \"I need to use the browse_website
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+      \"What is the price of the book?\"\n        }\n    }\n}"}, {"role": "system",
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+      \"\u00a325.89\"\n        }\n    }\n}"}, {"role": "system", "content": "Command
+      write_to_file returned: File written to successfully."}, {"role": "user", "content":
+      "Determine which next command to use, and respond using the format specified
+      above:"}], "temperature": 0, "max_tokens": 0}'
+    headers:
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tests/integration/challenges/basic_abilities/cassettes/test_write_file/test_write_file.yaml

@@ -1350,4 +1350,231 @@ interactions:
     status:
       code: 200
       message: OK
+- request:
+    body: '{"model": "gpt-3.5-turbo", "messages": [{"role": "system", "content": "You
+      are write_to_file-GPT, an AI designed to use the write_to_file command to write
+      ''Hello World'' into a file named \"hello_world.txt\" and then use the task_complete
+      command to complete the task.\nYour decisions must always be made independently
+      without seeking user assistance. Play to your strengths as an LLM and pursue
+      simple strategies with no legal complications.\n\nGOALS:\n\n1. Use the write_to_file
+      command to write ''Hello World'' into a file named \"hello_world.txt\".\n2.
+      Use the task_complete command to complete the task.\n3. Do not use any other
+      commands.\n\n\nConstraints:\n1. ~4000 word limit for short term memory. Your
+      short term memory is short, so immediately save important information to files.\n2.
+      If you are unsure how you previously did something or want to recall past events,
+      thinking about similar events will help you remember.\n3. No user assistance\n4.
+      Exclusively use the commands listed below e.g. command_name\n\nCommands:\n1.
+      append_to_file: Append to file, args: \"filename\": \"<filename>\", \"text\":
+      \"<text>\"\n2. delete_file: Delete file, args: \"filename\": \"<filename>\"\n3.
+      list_files: List Files in Directory, args: \"directory\": \"<directory>\"\n4.
+      read_file: Read a file, args: \"filename\": \"<filename>\"\n5. write_to_file:
+      Write to file, args: \"filename\": \"<filename>\", \"text\": \"<text>\"\n6.
+      delete_agent: Delete GPT Agent, args: \"key\": \"<key>\"\n7. get_hyperlinks:
+      Get hyperlinks, args: \"url\": \"<url>\"\n8. get_text_summary: Get text summary,
+      args: \"url\": \"<url>\", \"question\": \"<question>\"\n9. list_agents: List
+      GPT Agents, args: () -> str\n10. message_agent: Message GPT Agent, args: \"key\":
+      \"<key>\", \"message\": \"<message>\"\n11. start_agent: Start GPT Agent, args:
+      \"name\": \"<name>\", \"task\": \"<short_task_desc>\", \"prompt\": \"<prompt>\"\n12.
+      task_complete: Task Complete (Shutdown), args: \"reason\": \"<reason>\"\n\nResources:\n1.
+      Internet access for searches and information gathering.\n2. Long Term memory
+      management.\n3. GPT-3.5 powered Agents for delegation of simple tasks.\n4. File
+      output.\n\nPerformance Evaluation:\n1. Continuously review and analyze your
+      actions to ensure you are performing to the best of your abilities.\n2. Constructively
+      self-criticize your big-picture behavior constantly.\n3. Reflect on past decisions
+      and strategies to refine your approach.\n4. Every command has a cost, so be
+      smart and efficient. Aim to complete tasks in the least number of steps.\n5.
+      Write all code to a file.\n\nYou should only respond in JSON format as described
+      below \nResponse Format: \n{\n    \"thoughts\": {\n        \"text\": \"thought\",\n        \"reasoning\":
+      \"reasoning\",\n        \"plan\": \"- short bulleted\\n- list that conveys\\n-
+      long-term plan\",\n        \"criticism\": \"constructive self-criticism\",\n        \"speak\":
+      \"thoughts summary to say to user\"\n    },\n    \"command\": {\n        \"name\":
+      \"command name\",\n        \"args\": {\n            \"arg name\": \"value\"\n        }\n    }\n}
+      \nEnsure the response can be parsed by Python json.loads"}, {"role": "system",
+      "content": "The current time and date is Tue Jan  1 00:00:00 2000"}, {"role":
+      "system", "content": "This reminds you of these events from your past: \nI was
+      created"}, {"role": "user", "content": "Determine which next command to use,
+      and respond using the format specified above:"}, {"role": "assistant", "content":
+      "{\n    \"thoughts\": {\n        \"text\": \"I need to use the write_to_file
+      command to write ''Hello World'' into a file named ''hello_world.txt''.\",\n        \"reasoning\":
+      \"The task requires me to write ''Hello World'' into a file named ''hello_world.txt'',
+      and the write_to_file command is the appropriate command for this task.\",\n        \"plan\":
+      \"- Use the write_to_file command to write ''Hello World'' into a file named
+      ''hello_world.txt''.\",\n        \"criticism\": \"I need to ensure that I use
+      the correct filename and text to write to the file.\",\n        \"speak\": \"I
+      will use the write_to_file command to write ''Hello World'' into a file named
+      ''hello_world.txt''.\"\n    },\n    \"command\": {\n        \"name\": \"write_to_file\",\n        \"args\":
+      {\n            \"filename\": \"hello_world.txt\",\n            \"text\": \"Hello
+      World\"\n        }\n    }\n}"}, {"role": "system", "content": "Command write_to_file
+      returned: File written to successfully."}, {"role": "user", "content": "Determine
+      which next command to use, and respond using the format specified above:"}],
+      "temperature": 0, "max_tokens": 0}'
+    headers:
+      AGENT-MODE:
+      - AAAAAAAAAAAAAAAAAAAAAMLheAAaAAAA0%2BuSeid%2BULvsea4JtiGRiSDSJSI%3DEUifiRBkKG5E2XzMDjRfl76ZC9Ub0wnz4XsNiRVBChTYbJcE3F
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+      - '4608'
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+    method: POST
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+      - Thu, 25 May 2023 18:18:06 GMT
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+      - yvvlex8job2h
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+      - gpt-3.5-turbo-0301
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+      - significant-gravitas
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+      - '22621'
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+      - 827e911ff253a9d12783cb62e669dc20;o=1
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+      - Express
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+      - '3500'
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+      - 2.663s
+      X-Request-Id:
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+    status:
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+- request:
+    body: '{"model": "gpt-3.5-turbo", "messages": [{"role": "user", "content": "Write
+      a concise summary of the following text:\n\n\nLITERAL TEXT: \"\"\"Hello World\"\"\"\n\n\nCONCISE
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+      0}'
+    headers:
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+    method: POST
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+        JPbQSMIBCtZ39AVdzG/z3Q8AAAD//wMAv00f4UIBAAA=
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 version: 1

tests/integration/challenges/basic_abilities/test_browse_website.py

@@ -1,8 +1,6 @@
 import pytest
-from pytest_mock import MockerFixture
 
 from autogpt.agent import Agent
-from autogpt.commands.file_operations import read_file
 from tests.integration.challenges.utils import run_interaction_loop
 from tests.utils import requires_api_key
 
@@ -13,11 +11,11 @@ CYCLE_COUNT = 2
 @pytest.mark.vcr
 def test_browse_website(
     browser_agent: Agent,
-    patched_api_requestor: MockerFixture,
+    patched_api_requestor: None,
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
     file_path = browser_agent.workspace.get_path("browse_website.txt")
     run_interaction_loop(monkeypatch, browser_agent, CYCLE_COUNT)
 
-    content = read_file(file_path)
+    content = open(file_path, encoding="utf-8").read()
     assert "£25.89" in content, f"Expected £25.89, got {content}"

tests/integration/challenges/basic_abilities/test_write_file.py

@@ -1,5 +1,4 @@
 import pytest
-from pytest_mock import MockerFixture
 
 from autogpt.agent import Agent
 from autogpt.commands.file_operations import read_file
@@ -13,7 +12,7 @@ CYCLE_COUNT = 3
 @pytest.mark.vcr
 def test_write_file(
     writer_agent: Agent,
-    patched_api_requestor: MockerFixture,
+    patched_api_requestor: None,
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
     file_path = str(writer_agent.workspace.get_path("hello_world.txt"))

tests/integration/challenges/information_retrieval/test_information_retrieval_challenge_a.py

@@ -1,5 +1,4 @@
 import pytest
-from pytest_mock import MockerFixture
 
 from autogpt.commands.file_operations import read_file, write_to_file
 from tests.integration.challenges.utils import run_interaction_loop, run_multiple_times
@@ -16,7 +15,7 @@ from autogpt.agent import Agent
 def test_information_retrieval_challenge_a(
     get_company_revenue_agent: Agent,
     monkeypatch: pytest.MonkeyPatch,
-    patched_api_requestor: MockerFixture,
+    patched_api_requestor: None,
 ) -> None:
     """
     Test the challenge_a function in a given agent by mocking user inputs and checking the output file content.

tests/integration/challenges/memory/test_memory_challenge_a.py

@@ -1,5 +1,4 @@
 import pytest
-from pytest_mock import MockerFixture
 
 from autogpt.agent import Agent
 from autogpt.commands.file_operations import read_file, write_to_file
@@ -15,7 +14,7 @@ MAX_LEVEL = 3
 def test_memory_challenge_a(
     memory_management_agent: Agent,
     user_selected_level: int,
-    patched_api_requestor: MockerFixture,
+    patched_api_requestor: None,
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
     """

tests/integration/challenges/memory/test_memory_challenge_b.py

@@ -1,5 +1,4 @@
 import pytest
-from pytest_mock import MockerFixture
 
 from autogpt.agent import Agent
 from autogpt.commands.file_operations import read_file, write_to_file
@@ -20,7 +19,7 @@ NOISE = 1000
 def test_memory_challenge_b(
     memory_management_agent: Agent,
     user_selected_level: int,
-    patched_api_requestor: MockerFixture,
+    patched_api_requestor: None,
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
     """

tests/integration/challenges/memory/test_memory_challenge_c.py

@@ -1,6 +1,4 @@
 import pytest
-from _pytest.monkeypatch import MonkeyPatch
-from pytest_mock import MockerFixture
 
 from autogpt.agent import Agent
 from autogpt.commands.file_operations import read_file, write_to_file
@@ -21,7 +19,7 @@ NOISE = 1000
 def test_memory_challenge_c(
     memory_management_agent: Agent,
     user_selected_level: int,
-    patched_api_requestor: MockerFixture,
+    patched_api_requestor: None,
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
     """

tests/integration/conftest.py

@@ -1,7 +1,8 @@
 import os
 
-import openai
+import openai.api_requestor
 import pytest
+from pytest_mock import MockerFixture
 
 from tests.conftest import PROXY
 from tests.vcr.vcr_filter import before_record_request, before_record_response
@@ -30,7 +31,7 @@ def patch_api_base(requestor):
 
 
 @pytest.fixture
-def patched_api_requestor(mocker):
+def patched_api_requestor(mocker: MockerFixture):
     original_init = openai.api_requestor.APIRequestor.__init__
     original_validate_headers = openai.api_requestor.APIRequestor._validate_headers
 
@@ -51,5 +52,3 @@ def patched_api_requestor(mocker):
             "_validate_headers",
             new=patched_validate_headers,
         )
-
-    return mocker

tests/integration/memory/conftest.py

@@ -0,0 +1,18 @@
+import numpy
+import pytest
+
+from autogpt.memory.vector.memory_item import MemoryItem
+from autogpt.memory.vector.utils import Embedding
+
+
+@pytest.fixture
+def memory_item(mock_embedding: Embedding):
+    return MemoryItem(
+        raw_content="test content",
+        summary="test content summary",
+        chunks=["test content"],
+        chunk_summaries=["test content summary"],
+        e_summary=mock_embedding,
+        e_chunks=[mock_embedding],
+        metadata={},
+    )

tests/integration/memory/test_json_file_memory.py

@@ -0,0 +1,106 @@
+# sourcery skip: snake-case-functions
+"""Tests for JSONFileMemory class"""
+import orjson
+import pytest
+
+from autogpt.config import Config
+from autogpt.memory.vector import JSONFileMemory, MemoryItem
+from autogpt.workspace import Workspace
+from tests.utils import requires_api_key
+
+
+@pytest.fixture(autouse=True)
+def cleanup_sut_singleton():
+    if JSONFileMemory in JSONFileMemory._instances:
+        del JSONFileMemory._instances[JSONFileMemory]
+
+
+def test_json_memory_init_without_backing_file(config: Config, workspace: Workspace):
+    index_file = workspace.root / f"{config.memory_index}.json"
+
+    assert not index_file.exists()
+    JSONFileMemory(config)
+    assert index_file.exists()
+    assert index_file.read_text() == "[]"
+
+
+def test_json_memory_init_with_backing_empty_file(config: Config, workspace: Workspace):
+    index_file = workspace.root / f"{config.memory_index}.json"
+    index_file.touch()
+
+    assert index_file.exists()
+    JSONFileMemory(config)
+    assert index_file.exists()
+    assert index_file.read_text() == "[]"
+
+
+def test_json_memory_init_with_backing_file(config: Config, workspace: Workspace):
+    index_file = workspace.root / f"{config.memory_index}.json"
+    index_file.touch()
+
+    raw_data = {"texts": ["test"]}
+    data = orjson.dumps(raw_data, option=JSONFileMemory.SAVE_OPTIONS)
+    with index_file.open("wb") as f:
+        f.write(data)
+
+    assert index_file.exists()
+    JSONFileMemory(config)
+    assert index_file.exists()
+    assert index_file.read_text() == "[]"
+
+
+def test_json_memory_add(config: Config, memory_item: MemoryItem):
+    index = JSONFileMemory(config)
+    index.add(memory_item)
+    assert index.memories[0] == memory_item
+
+
+def test_json_memory_clear(config: Config, memory_item: MemoryItem):
+    index = JSONFileMemory(config)
+    assert index.memories == []
+
+    index.add(memory_item)
+    assert index.memories[0] == memory_item, "Cannot test clear() because add() fails"
+
+    index.clear()
+    assert index.memories == []
+
+
+def test_json_memory_get(config: Config, memory_item: MemoryItem, mock_get_embedding):
+    index = JSONFileMemory(config)
+    assert (
+        index.get("test") == None
+    ), "Cannot test get() because initial index is not empty"
+
+    index.add(memory_item)
+    retrieved = index.get("test")
+    assert retrieved is not None
+    assert retrieved.memory_item == memory_item
+
+
+@pytest.mark.vcr
+@requires_api_key("OPENAI_API_KEY")
+def test_json_memory_get_relevant(config: Config, patched_api_requestor: None) -> None:
+    index = JSONFileMemory(config)
+    mem1 = MemoryItem.from_text_file("Sample text", "sample.txt")
+    mem2 = MemoryItem.from_text_file("Grocery list:\n- Pancake mix", "groceries.txt")
+    mem3 = MemoryItem.from_text_file("What is your favorite color?", "color.txt")
+    lipsum = "Lorem ipsum dolor sit amet"
+    mem4 = MemoryItem.from_text_file(" ".join([lipsum] * 100), "lipsum.txt")
+    index.add(mem1)
+    index.add(mem2)
+    index.add(mem3)
+    index.add(mem4)
+
+    assert index.get_relevant(mem1.raw_content, 1)[0].memory_item == mem1
+    assert index.get_relevant(mem2.raw_content, 1)[0].memory_item == mem2
+    assert index.get_relevant(mem3.raw_content, 1)[0].memory_item == mem3
+    assert [mr.memory_item for mr in index.get_relevant(lipsum, 2)] == [mem4, mem1]
+
+
+def test_json_memory_get_stats(config: Config, memory_item: MemoryItem) -> None:
+    index = JSONFileMemory(config)
+    index.add(memory_item)
+    n_memories, n_chunks = index.get_stats()
+    assert n_memories == 1
+    assert n_chunks == 1

tests/integration/memory/utils.py

@@ -0,0 +1,44 @@
+import numpy
+import pytest
+from pytest_mock import MockerFixture
+
+import autogpt.memory.vector.memory_item as vector_memory_item
+import autogpt.memory.vector.providers.base as memory_provider_base
+from autogpt.config.config import Config
+from autogpt.llm.providers.openai import OPEN_AI_EMBEDDING_MODELS
+from autogpt.memory.vector import get_memory
+from autogpt.memory.vector.utils import Embedding
+
+
+@pytest.fixture
+def embedding_dimension(config: Config):
+    return OPEN_AI_EMBEDDING_MODELS[config.embedding_model].embedding_dimensions
+
+
+@pytest.fixture
+def mock_embedding(embedding_dimension: int) -> Embedding:
+    return numpy.full((1, embedding_dimension), 0.0255, numpy.float32)[0]
+
+
+@pytest.fixture
+def mock_get_embedding(mocker: MockerFixture, embedding_dimension: int):
+    mocker.patch.object(
+        vector_memory_item,
+        "get_embedding",
+        return_value=[0.0255] * embedding_dimension,
+    )
+    mocker.patch.object(
+        memory_provider_base,
+        "get_embedding",
+        return_value=[0.0255] * embedding_dimension,
+    )
+
+
+@pytest.fixture
+def memory_none(agent_test_config: Config, mock_get_embedding):
+    was_memory_backend = agent_test_config.memory_backend
+
+    agent_test_config.set_memory_backend("no_memory")
+    yield get_memory(agent_test_config)
+
+    agent_test_config.set_memory_backend(was_memory_backend)

tests/integration/memory_tests.py

@@ -1,50 +0,0 @@
-import random
-import string
-import sys
-import unittest
-from pathlib import Path
-
-from autogpt.config import Config
-from autogpt.memory.local import LocalCache
-
-
-class TestLocalCache(unittest.TestCase):
-    def generate_random_string(self, length):
-        return "".join(random.choice(string.ascii_letters) for _ in range(length))
-
-    def setUp(self):
-        """Set up the test environment for the LocalCache tests."""
-        cfg = cfg = Config()
-        self.cache = LocalCache(cfg)
-        self.cache.clear()
-
-        # Add example texts to the cache
-        self.example_texts = [
-            "The quick brown fox jumps over the lazy dog",
-            "I love machine learning and natural language processing",
-            "The cake is a lie, but the pie is always true",
-            "ChatGPT is an advanced AI model for conversation",
-        ]
-        for text in self.example_texts:
-            self.cache.add(text)
-
-        # Add some random strings to test noise
-        for _ in range(5):
-            self.cache.add(self.generate_random_string(10))
-
-    def test_get_relevant(self):
-        """Test getting relevant texts from the cache."""
-        query = "I'm interested in artificial intelligence and NLP"
-        k = 3
-        relevant_texts = self.cache.get_relevant(query, k)
-
-        print(f"Top {k} relevant texts for the query '{query}':")
-        for i, text in enumerate(relevant_texts, start=1):
-            print(f"{i}. {text}")
-
-        self.assertEqual(len(relevant_texts), k)
-        self.assertIn(self.example_texts[1], relevant_texts)
-
-
-if __name__ == "__main__":
-    unittest.main()

tests/integration/milvus_memory_tests.py

@@ -1,55 +0,0 @@
-# sourcery skip: snake-case-functions
-"""Tests for the MilvusMemory class."""
-import random
-import string
-import unittest
-
-from autogpt.config import Config
-from autogpt.memory.milvus import MilvusMemory
-
-try:
-
-    class TestMilvusMemory(unittest.TestCase):
-        """Unit tests for the MilvusMemory class."""
-
-        def generate_random_string(self, length: int) -> str:
-            return "".join(random.choice(string.ascii_letters) for _ in range(length))
-
-        def setUp(self) -> None:
-            cfg = Config()
-            cfg.milvus_addr = "localhost:19530"
-            self.memory = MilvusMemory(cfg)
-            self.memory.clear()
-
-            # Add example texts to the cache
-            self.example_texts = [
-                "The quick brown fox jumps over the lazy dog",
-                "I love machine learning and natural language processing",
-                "The cake is a lie, but the pie is always true",
-                "ChatGPT is an advanced AI model for conversation",
-            ]
-
-            for text in self.example_texts:
-                self.memory.add(text)
-
-            # Add some random strings to test noise
-            for _ in range(5):
-                self.memory.add(self.generate_random_string(10))
-
-        def test_get_relevant(self) -> None:
-            """Test getting relevant texts from the cache."""
-            query = "I'm interested in artificial intelligence and NLP"
-            num_relevant = 3
-            relevant_texts = self.memory.get_relevant(query, num_relevant)
-
-            print(f"Top {k} relevant texts for the query '{query}':")
-            for i, text in enumerate(relevant_texts, start=1):
-                print(f"{i}. {text}")
-
-            self.assertEqual(len(relevant_texts), k)
-            self.assertIn(self.example_texts[1], relevant_texts)
-
-except:
-    print(
-        "Skipping tests/integration/milvus_memory_tests.py as Milvus is not installed."
-    )

tests/integration/test_llm_utils.py

@@ -1,65 +0,0 @@
-import string
-from unittest.mock import MagicMock
-
-import pytest
-from numpy.random import RandomState
-from pytest_mock import MockerFixture
-
-from autogpt.config import Config
-from autogpt.llm import llm_utils
-from autogpt.llm.api_manager import ApiManager
-from autogpt.llm.modelsinfo import COSTS
-from tests.utils import requires_api_key
-
-
-@pytest.fixture(scope="session")
-def random_large_string():
-    """Big string used to overwhelm token limits."""
-    seed = 42
-    n_characters = 30_000
-    random = RandomState(seed)
-    return "".join(random.choice(list(string.ascii_lowercase), size=n_characters))
-
-
-@pytest.fixture()
-def api_manager(mocker: MockerFixture):
-    api_manager = ApiManager()
-    mocker.patch.multiple(
-        api_manager,
-        total_prompt_tokens=0,
-        total_completion_tokens=0,
-        total_cost=0,
-    )
-    yield api_manager
-
-
-@pytest.fixture()
-def spy_create_embedding(mocker: MockerFixture):
-    return mocker.spy(llm_utils, "create_embedding")
-
-
-@pytest.mark.vcr
-@requires_api_key("OPENAI_API_KEY")
-def test_get_ada_embedding(
-    config: Config,
-    api_manager: ApiManager,
-    spy_create_embedding: MagicMock,
-    patched_api_requestor,
-):
-    token_cost = COSTS[config.embedding_model]["prompt"]
-    llm_utils.get_ada_embedding("test")
-
-    spy_create_embedding.assert_called_once_with("test", model=config.embedding_model)
-
-    assert (prompt_tokens := api_manager.get_total_prompt_tokens()) == 1
-    assert api_manager.get_total_completion_tokens() == 0
-    assert api_manager.get_total_cost() == (prompt_tokens * token_cost) / 1000
-
-
-@pytest.mark.vcr
-@requires_api_key("OPENAI_API_KEY")
-def test_get_ada_embedding_large_context(random_large_string):
-    # This test should be able to mock the openai call after we have a fix.  We don't need
-    # to hit the API to test the logic of the function (so not using vcr). This is a quick
-    # regression test to document the issue.
-    llm_utils.get_ada_embedding(random_large_string)

tests/integration/test_local_cache.py

@@ -1,110 +0,0 @@
-# sourcery skip: snake-case-functions
-"""Tests for LocalCache class"""
-import unittest
-
-import orjson
-import pytest
-
-from autogpt.memory.local import EMBED_DIM, SAVE_OPTIONS
-from autogpt.memory.local import LocalCache as LocalCache_
-from tests.utils import requires_api_key
-
-
-@pytest.fixture
-def LocalCache():
-    # Hack, real gross. Singletons are not good times.
-    if LocalCache_ in LocalCache_._instances:
-        del LocalCache_._instances[LocalCache_]
-    return LocalCache_
-
-
-@pytest.fixture
-def mock_embed_with_ada(mocker):
-    mocker.patch(
-        "autogpt.memory.local.get_ada_embedding",
-        return_value=[0.1] * EMBED_DIM,
-    )
-
-
-def test_init_without_backing_file(LocalCache, config, workspace):
-    cache_file = workspace.root / f"{config.memory_index}.json"
-
-    assert not cache_file.exists()
-    LocalCache(config)
-    assert cache_file.exists()
-    assert cache_file.read_text() == "{}"
-
-
-def test_init_with_backing_empty_file(LocalCache, config, workspace):
-    cache_file = workspace.root / f"{config.memory_index}.json"
-    cache_file.touch()
-
-    assert cache_file.exists()
-    LocalCache(config)
-    assert cache_file.exists()
-    assert cache_file.read_text() == "{}"
-
-
-def test_init_with_backing_file(LocalCache, config, workspace):
-    cache_file = workspace.root / f"{config.memory_index}.json"
-    cache_file.touch()
-
-    raw_data = {"texts": ["test"]}
-    data = orjson.dumps(raw_data, option=SAVE_OPTIONS)
-    with cache_file.open("wb") as f:
-        f.write(data)
-
-    assert cache_file.exists()
-    LocalCache(config)
-    assert cache_file.exists()
-    assert cache_file.read_text() == "{}"
-
-
-def test_add(LocalCache, config, mock_embed_with_ada):
-    cache = LocalCache(config)
-    cache.add("test")
-    assert cache.data.texts == ["test"]
-    assert cache.data.embeddings.shape == (1, EMBED_DIM)
-
-
-def test_clear(LocalCache, config, mock_embed_with_ada):
-    cache = LocalCache(config)
-    assert cache.data.texts == []
-    assert cache.data.embeddings.shape == (0, EMBED_DIM)
-
-    cache.add("test")
-    assert cache.data.texts == ["test"]
-    assert cache.data.embeddings.shape == (1, EMBED_DIM)
-
-    cache.clear()
-    assert cache.data.texts == []
-    assert cache.data.embeddings.shape == (0, EMBED_DIM)
-
-
-def test_get(LocalCache, config, mock_embed_with_ada):
-    cache = LocalCache(config)
-    assert cache.get("test") == []
-
-    cache.add("test")
-    assert cache.get("test") == ["test"]
-
-
-@pytest.mark.vcr
-@requires_api_key("OPENAI_API_KEY")
-def test_get_relevant(LocalCache, config, patched_api_requestor) -> None:
-    cache = LocalCache(config)
-    text1 = "Sample text 1"
-    text2 = "Sample text 2"
-    cache.add(text1)
-    cache.add(text2)
-
-    result = cache.get_relevant(text1, 1)
-    assert result == [text1]
-
-
-def test_get_stats(LocalCache, config, mock_embed_with_ada) -> None:
-    cache = LocalCache(config)
-    text = "Sample text"
-    cache.add(text)
-    stats = cache.get_stats()
-    assert stats == (1, cache.data.embeddings.shape)

tests/integration/test_memory_management.py

@@ -1,67 +0,0 @@
-import json
-
-import pytest
-
-from autogpt.config import Config
-from autogpt.memory import get_memory
-from autogpt.memory_management.store_memory import (
-    save_memory_trimmed_from_context_window,
-)
-from tests.utils import requires_api_key
-
-
-@pytest.fixture
-def message_history_fixture():
-    assistant_reply = {
-        "thoughts": {
-            "text": "thoughts",
-            "reasoning": "reasoning",
-            "plan": "plan",
-            "criticism": "criticism",
-            "speak": "speak",
-        },
-        "command": {"name": "google", "args": {"query": "google_query"}},
-    }
-    return [
-        {"content": json.dumps(assistant_reply, indent=4)},
-        {"content": "Command Result: Important Information."},
-    ]
-
-
-@pytest.fixture
-def expected_permanent_memory() -> str:
-    return """Assistant Reply: {
-    "thoughts": {
-        "text": "thoughts",
-        "reasoning": "reasoning",
-        "plan": "plan",
-        "criticism": "criticism",
-        "speak": "speak"
-    },
-    "command": {
-        "name": "google",
-        "args": {
-            "query": "google_query"
-        }
-    }
-}
-Result: None
-Human Feedback:Command Result: Important Information."""
-
-
-@requires_api_key("OPENAI_API_KEY")
-@pytest.mark.vcr
-def test_save_memory_trimmed_from_context_window(
-    message_history_fixture,
-    expected_permanent_memory,
-    config: Config,
-    patched_api_requestor,
-):
-    next_message_to_add_index = len(message_history_fixture) - 1
-    memory = get_memory(config, init=True)
-    save_memory_trimmed_from_context_window(
-        message_history_fixture, next_message_to_add_index, memory
-    )
-
-    memory_found = memory.get_relevant("Important Information", 5)
-    assert memory_found[0] == expected_permanent_memory

tests/integration/test_plugins.py

@@ -0,0 +1,71 @@
+import pytest
+
+from autogpt.config import Config
+from autogpt.plugins import scan_plugins
+
+PLUGINS_TEST_DIR = "tests/unit/data/test_plugins"
+PLUGIN_TEST_OPENAI = "https://weathergpt.vercel.app/"
+
+
+@pytest.fixture
+def mock_config_denylist_allowlist_check():
+    class MockConfig:
+        """Mock config object for testing the denylist_allowlist_check function"""
+
+        plugins_denylist = ["BadPlugin"]
+        plugins_allowlist = ["GoodPlugin"]
+        authorise_key = "y"
+        exit_key = "n"
+
+    return MockConfig()
+
+
+@pytest.fixture
+def config_with_plugins():
+    """Mock config object for testing the scan_plugins function"""
+    # Test that the function returns the correct number of plugins
+    cfg = Config()
+    cfg.plugins_dir = PLUGINS_TEST_DIR
+    cfg.plugins_openai = ["https://weathergpt.vercel.app/"]
+    return cfg
+
+
+@pytest.fixture
+def mock_config_openai_plugin():
+    """Mock config object for testing the scan_plugins function"""
+
+    class MockConfig:
+        """Mock config object for testing the scan_plugins function"""
+
+        plugins_dir = PLUGINS_TEST_DIR
+        plugins_openai = [PLUGIN_TEST_OPENAI]
+        plugins_denylist = ["AutoGPTPVicuna"]
+        plugins_allowlist = [PLUGIN_TEST_OPENAI]
+
+    return MockConfig()
+
+
+def test_scan_plugins_openai(mock_config_openai_plugin):
+    # Test that the function returns the correct number of plugins
+    result = scan_plugins(mock_config_openai_plugin, debug=True)
+    assert len(result) == 1
+
+
+@pytest.fixture
+def mock_config_generic_plugin():
+    """Mock config object for testing the scan_plugins function"""
+
+    # Test that the function returns the correct number of plugins
+    class MockConfig:
+        plugins_dir = PLUGINS_TEST_DIR
+        plugins_openai = []
+        plugins_denylist = []
+        plugins_allowlist = ["AutoGPTPVicuna"]
+
+    return MockConfig()
+
+
+def test_scan_plugins_generic(mock_config_generic_plugin):
+    # Test that the function returns the correct number of plugins
+    result = scan_plugins(mock_config_generic_plugin, debug=True)
+    assert len(result) == 1

tests/integration/weaviate_memory_tests.py

@@ -1,120 +0,0 @@
-import unittest
-from uuid import uuid4
-
-from weaviate import Client
-from weaviate.util import get_valid_uuid
-
-from autogpt.config import Config
-from autogpt.llm import get_ada_embedding
-from autogpt.memory.weaviate import WeaviateMemory
-
-
-class TestWeaviateMemory(unittest.TestCase):
-    cfg = None
-    client = None
-    index = None
-
-    @classmethod
-    def setUpClass(cls):
-        """Set up the test environment for the WeaviateMemory tests."""
-        # 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}"
-            )
-
-        cls.index = WeaviateMemory.format_classname(cls.cfg.memory_index)
-
-    """
-    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):
-        """Set up the test environment for the WeaviateMemory tests."""
-        try:
-            self.client.schema.delete_class(self.index)
-        except:
-            pass
-
-        self.memory = WeaviateMemory(self.cfg)
-
-    def test_add(self):
-        """Test adding a text to the cache"""
-        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.index, ["raw_text"]).do()
-        actual = result["data"]["Get"][self.index]
-
-        self.assertEqual(len(actual), 1)
-        self.assertEqual(actual[0]["raw_text"], doc)
-
-    def test_get(self):
-        """Test getting a text from the cache"""
-        doc = "You are an Avenger and swore to defend the Galaxy from a menace called Thanos"
-        # add the document to the cache
-        with self.client.batch as batch:
-            batch.add_data_object(
-                uuid=get_valid_uuid(uuid4()),
-                data_object={"raw_text": doc},
-                class_name=self.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):
-        """Test getting the stats of the cache"""
-        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):
-        """Test clearing the cache"""
-        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/milvus_memory_test.py

@@ -1,72 +0,0 @@
-# sourcery skip: snake-case-functions
-"""Tests for the MilvusMemory class."""
-import os
-import sys
-import unittest
-
-try:
-    from autogpt.config import Config
-    from autogpt.memory.milvus import MilvusMemory
-
-    def mock_config() -> Config:
-        """Mock the config object for testing purposes."""
-
-        # Return a mock config object with the required attributes
-        class MockConfig(Config):
-            debug_mode = False
-            continuous_mode = False
-            speak_mode = False
-            milvus_collection = "autogpt"
-            milvus_addr = "localhost:19530"
-
-        return MockConfig()
-
-    class TestMilvusMemory(unittest.TestCase):
-        """Tests for the MilvusMemory class."""
-
-        def setUp(self) -> None:
-            """Set up the test environment"""
-            self.cfg = mock_config()
-            self.memory = MilvusMemory(self.cfg)
-
-        def test_add(self) -> None:
-            """Test adding a text to the cache"""
-            text = "Sample text"
-            self.memory.clear()
-            self.memory.add(text)
-            result = self.memory.get(text)
-            self.assertEqual([text], result)
-
-        def test_clear(self) -> None:
-            """Test clearing the cache"""
-            self.memory.clear()
-            self.assertEqual(self.memory.collection.num_entities, 0)
-
-        def test_get(self) -> None:
-            """Test getting a text from the cache"""
-            text = "Sample text"
-            self.memory.clear()
-            self.memory.add(text)
-            result = self.memory.get(text)
-            self.assertEqual(result, [text])
-
-        def test_get_relevant(self) -> None:
-            """Test getting relevant texts from the cache"""
-            text1 = "Sample text 1"
-            text2 = "Sample text 2"
-            self.memory.clear()
-            self.memory.add(text1)
-            self.memory.add(text2)
-            result = self.memory.get_relevant(text1, 1)
-            self.assertEqual(result, [text1])
-
-        def test_get_stats(self) -> None:
-            """Test getting the cache stats"""
-            text = "Sample text"
-            self.memory.clear()
-            self.memory.add(text)
-            stats = self.memory.get_stats()
-            self.assertEqual(15, len(stats))
-
-except ImportError as err:
-    print(f"Skipping tests for MilvusMemory: {err}")

tests/test_agent.py

@@ -3,17 +3,16 @@ from unittest.mock import MagicMock
 import pytest
 
 from autogpt.agent import Agent
-from autogpt.config import Config
+from autogpt.config import AIConfig
 
 
 @pytest.fixture
 def agent():
     ai_name = "Test AI"
     memory = MagicMock()
-    full_message_history = []
     next_action_count = 0
     command_registry = MagicMock()
-    config = Config()
+    config = AIConfig()
     system_prompt = "System prompt"
     triggering_prompt = "Triggering prompt"
     workspace_directory = "workspace_directory"
@@ -21,7 +20,6 @@ def agent():
     agent = Agent(
         ai_name,
         memory,
-        full_message_history,
         next_action_count,
         command_registry,
         config,
@@ -32,10 +30,10 @@ def agent():
     return agent
 
 
-def test_agent_initialization(agent):
+def test_agent_initialization(agent: Agent):
     assert agent.ai_name == "Test AI"
     assert agent.memory == agent.memory
-    assert agent.full_message_history == []
+    assert agent.history.messages == []
     assert agent.next_action_count == 0
     assert agent.command_registry == agent.command_registry
     assert agent.config == agent.config

tests/test_agent_manager.py

@@ -1,15 +1,14 @@
 import pytest
 
 from autogpt.agent.agent_manager import AgentManager
-from autogpt.llm import create_chat_completion
+from autogpt.llm.chat import create_chat_completion
 
 
 @pytest.fixture
 def agent_manager():
     # Hack, real gross. Singletons are not good times.
-    if AgentManager in AgentManager._instances:
-        del AgentManager._instances[AgentManager]
-    return AgentManager()
+    yield AgentManager()
+    del AgentManager._instances[AgentManager]
 
 
 @pytest.fixture
@@ -37,28 +36,28 @@ def mock_create_chat_completion(mocker):
     return mock_create_chat_completion
 
 
-def test_create_agent(agent_manager, task, prompt, model):
+def test_create_agent(agent_manager: AgentManager, task, prompt, model):
     key, agent_reply = agent_manager.create_agent(task, prompt, model)
     assert isinstance(key, int)
     assert isinstance(agent_reply, str)
     assert key in agent_manager.agents
 
 
-def test_message_agent(agent_manager, task, prompt, model):
+def test_message_agent(agent_manager: AgentManager, task, prompt, model):
     key, _ = agent_manager.create_agent(task, prompt, model)
     user_message = "Please translate 'Good morning' to French."
     agent_reply = agent_manager.message_agent(key, user_message)
     assert isinstance(agent_reply, str)
 
 
-def test_list_agents(agent_manager, task, prompt, model):
+def test_list_agents(agent_manager: AgentManager, task, prompt, model):
     key, _ = agent_manager.create_agent(task, prompt, model)
     agents_list = agent_manager.list_agents()
     assert isinstance(agents_list, list)
     assert (key, task) in agents_list
 
 
-def test_delete_agent(agent_manager, task, prompt, model):
+def test_delete_agent(agent_manager: AgentManager, task, prompt, model):
     key, _ = agent_manager.create_agent(task, prompt, model)
     success = agent_manager.delete_agent(key)
     assert success

tests/test_api_manager.py

@@ -2,7 +2,7 @@ from unittest.mock import MagicMock, patch
 
 import pytest
 
-from autogpt.llm import COSTS, ApiManager
+from autogpt.llm.api_manager import COSTS, ApiManager
 
 api_manager = ApiManager()
 

tests/unit/test_chat.py

@@ -1,78 +0,0 @@
-# Generated by CodiumAI
-import time
-from unittest.mock import patch
-
-from autogpt.llm import create_chat_message, generate_context
-
-
-def test_happy_path_role_content():
-    """Test that the function returns a dictionary with the correct keys and values when valid strings are provided for role and content."""
-    result = create_chat_message("system", "Hello, world!")
-    assert result == {"role": "system", "content": "Hello, world!"}
-
-
-def test_empty_role_content():
-    """Test that the function returns a dictionary with the correct keys and values when empty strings are provided for role and content."""
-    result = create_chat_message("", "")
-    assert result == {"role": "", "content": ""}
-
-
-def test_generate_context_empty_inputs(mocker):
-    """Test the behavior of the generate_context function when all input parameters are empty."""
-    # Mock the time.strftime function to return a fixed value
-    mocker.patch("time.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,
-        32,
-        2,
-        [
-            {"role": "system", "content": ""},
-            {
-                "role": "system",
-                "content": f"The current time and date is {time.strftime('%c')}",
-            },
-        ],
-    )
-    assert result == expected_result
-
-
-def test_generate_context_valid_inputs():
-    """Test that the function successfully generates a current_context given valid inputs."""
-    # 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
-    assert isinstance(result[0], int)
-    assert isinstance(result[1], int)
-    assert isinstance(result[2], int)
-    assert isinstance(result[3], list)
-    assert result[0] >= 0
-    assert result[2] >= 0
-    assert result[1] >= 0
-    assert len(result[3]) >= 2  # current_context should have at least 2 messages
-    assert result[1] <= 2048  # token limit for GPT-3.5-turbo-0301 is 2048 tokens

tests/unit/test_file_operations.py

@@ -13,6 +13,8 @@ from pytest_mock import MockerFixture
 
 import autogpt.commands.file_operations as file_ops
 from autogpt.config import Config
+from autogpt.memory.vector.memory_item import MemoryItem
+from autogpt.memory.vector.utils import Embedding
 from autogpt.utils import readable_file_size
 from autogpt.workspace import Workspace
 
@@ -22,6 +24,23 @@ def file_content():
     return "This is a test file.\n"
 
 
+@pytest.fixture()
+def mock_MemoryItem_from_text(mocker: MockerFixture, mock_embedding: Embedding):
+    mocker.patch.object(
+        file_ops.MemoryItem,
+        "from_text",
+        new=lambda content, source_type, metadata: MemoryItem(
+            raw_content=content,
+            summary=f"Summary of content '{content}'",
+            chunk_summaries=[f"Summary of content '{content}'"],
+            chunks=[content],
+            e_summary=mock_embedding,
+            e_chunks=[mock_embedding],
+            metadata=metadata | {"source_type": source_type},
+        ),
+    )
+
+
 @pytest.fixture()
 def test_file_path(config, workspace: Workspace):
     return workspace.get_path("test_file.txt")
@@ -188,7 +207,11 @@ def test_split_file(max_length, overlap, content, expected):
     )
 
 
-def test_read_file(test_file_with_content_path: Path, file_content):
+def test_read_file(
+    mock_MemoryItem_from_text,
+    test_file_with_content_path: Path,
+    file_content,
+):
     content = file_ops.read_file(test_file_with_content_path)
     assert content == file_content
 

tests/unit/test_get_self_feedback.py

@@ -2,7 +2,7 @@ from datetime import datetime
 
 from autogpt.agent.agent import Agent
 from autogpt.config import AIConfig
-from autogpt.llm import create_chat_completion
+from autogpt.llm.chat import create_chat_completion
 from autogpt.log_cycle.log_cycle import LogCycleHandler
 
 

tests/unit/test_llm_utils.py

@@ -1,11 +1,9 @@
 from unittest.mock import patch
 
 import pytest
-from openai import InvalidRequestError
 from openai.error import APIError, RateLimitError
 
-from autogpt.llm import llm_utils
-from autogpt.llm.llm_utils import check_model
+from autogpt.llm import utils as llm_utils
 
 
 @pytest.fixture(params=[RateLimitError, APIError])
@@ -107,36 +105,6 @@ def test_retry_openapi_other_api_error(capsys):
     assert output.out == ""
 
 
-def test_chunked_tokens():
-    text = "Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model"
-    expected_output = [
-        (
-            13556,
-            12279,
-            2898,
-            374,
-            459,
-            22772,
-            1825,
-            31874,
-            3851,
-            67908,
-            279,
-            17357,
-            315,
-            279,
-            480,
-            2898,
-            12,
-            19,
-            4221,
-            1646,
-        )
-    ]
-    output = list(llm_utils.chunked_tokens(text, "cl100k_base", 8191))
-    assert output == expected_output
-
-
 def test_check_model(api_manager):
     """
     Test if check_model() returns original model when valid.
@@ -145,7 +113,7 @@ def test_check_model(api_manager):
     with patch("openai.Model.list") as mock_list_models:
         # Test when correct model is returned
         mock_list_models.return_value = {"data": [{"id": "gpt-4"}]}
-        result = check_model("gpt-4", "smart_llm_model")
+        result = llm_utils.check_model("gpt-4", "smart_llm_model")
         assert result == "gpt-4"
 
         # Reset api manager models
@@ -153,7 +121,7 @@ def test_check_model(api_manager):
 
         # Test when incorrect model is returned
         mock_list_models.return_value = {"data": [{"id": "gpt-3.5-turbo"}]}
-        result = check_model("gpt-4", "fast_llm_model")
+        result = llm_utils.check_model("gpt-4", "fast_llm_model")
         assert result == "gpt-3.5-turbo"
 
         # Reset api manager models

tests/unit/test_plugins.py

@@ -1,16 +1,11 @@
 import pytest
 
 from autogpt.config import Config
-from autogpt.plugins import (
-    denylist_allowlist_check,
-    inspect_zip_for_modules,
-    scan_plugins,
-)
+from autogpt.plugins import denylist_allowlist_check, inspect_zip_for_modules
 
 PLUGINS_TEST_DIR = "tests/unit/data/test_plugins"
 PLUGIN_TEST_ZIP_FILE = "Auto-GPT-Plugin-Test-master.zip"
 PLUGIN_TEST_INIT_PY = "Auto-GPT-Plugin-Test-master/src/auto_gpt_vicuna/__init__.py"
-PLUGIN_TEST_OPENAI = "https://weathergpt.vercel.app/"
 
 
 def test_inspect_zip_for_modules():
@@ -77,54 +72,3 @@ def test_denylist_allowlist_check_user_input_invalid(
     assert not denylist_allowlist_check(
         "UnknownPlugin", mock_config_denylist_allowlist_check
     )
-
-
-@pytest.fixture
-def config_with_plugins():
-    """Mock config object for testing the scan_plugins function"""
-    # Test that the function returns the correct number of plugins
-    cfg = Config()
-    cfg.plugins_dir = PLUGINS_TEST_DIR
-    cfg.plugins_openai = ["https://weathergpt.vercel.app/"]
-    return cfg
-
-
-@pytest.fixture
-def mock_config_openai_plugin():
-    """Mock config object for testing the scan_plugins function"""
-
-    class MockConfig:
-        """Mock config object for testing the scan_plugins function"""
-
-        plugins_dir = PLUGINS_TEST_DIR
-        plugins_openai = [PLUGIN_TEST_OPENAI]
-        plugins_denylist = ["AutoGPTPVicuna"]
-        plugins_allowlist = [PLUGIN_TEST_OPENAI]
-
-    return MockConfig()
-
-
-def test_scan_plugins_openai(mock_config_openai_plugin):
-    # Test that the function returns the correct number of plugins
-    result = scan_plugins(mock_config_openai_plugin, debug=True)
-    assert len(result) == 1
-
-
-@pytest.fixture
-def mock_config_generic_plugin():
-    """Mock config object for testing the scan_plugins function"""
-
-    # Test that the function returns the correct number of plugins
-    class MockConfig:
-        plugins_dir = PLUGINS_TEST_DIR
-        plugins_openai = []
-        plugins_denylist = []
-        plugins_allowlist = ["AutoGPTPVicuna"]
-
-    return MockConfig()
-
-
-def test_scan_plugins_generic(mock_config_generic_plugin):
-    # Test that the function returns the correct number of plugins
-    result = scan_plugins(mock_config_generic_plugin, debug=True)
-    assert len(result) == 1

tests/unit/test_token_counter.py

@@ -1,20 +1,13 @@
 import pytest
 
-from autogpt.llm import count_message_tokens, count_string_tokens
+from autogpt.llm.base import Message
+from autogpt.llm.utils import count_message_tokens, count_string_tokens
 
 
 def test_count_message_tokens():
     messages = [
-        {"role": "user", "content": "Hello"},
-        {"role": "assistant", "content": "Hi there!"},
-    ]
-    assert count_message_tokens(messages) == 17
-
-
-def test_count_message_tokens_with_name():
-    messages = [
-        {"role": "user", "content": "Hello", "name": "John"},
-        {"role": "assistant", "content": "Hi there!"},
+        Message("user", "Hello"),
+        Message("assistant", "Hi there!"),
     ]
     assert count_message_tokens(messages) == 17
 
@@ -25,19 +18,19 @@ def test_count_message_tokens_empty_input():
 
 
 def test_count_message_tokens_invalid_model():
-    """Invalid model should raise a KeyError"""
+    """Invalid model should raise a NotImplementedError"""
     messages = [
-        {"role": "user", "content": "Hello"},
-        {"role": "assistant", "content": "Hi there!"},
+        Message("user", "Hello"),
+        Message("assistant", "Hi there!"),
     ]
-    with pytest.raises(KeyError):
+    with pytest.raises(NotImplementedError):
         count_message_tokens(messages, model="invalid_model")
 
 
 def test_count_message_tokens_gpt_4():
     messages = [
-        {"role": "user", "content": "Hello"},
-        {"role": "assistant", "content": "Hi there!"},
+        Message("user", "Hello"),
+        Message("assistant", "Hi there!"),
     ]
     assert count_message_tokens(messages, model="gpt-4-0314") == 15
 
@@ -55,16 +48,6 @@ def test_count_string_tokens_empty_input():
     assert count_string_tokens("", model_name="gpt-3.5-turbo-0301") == 0
 
 
-def test_count_message_tokens_invalid_model():
-    """Invalid model should raise a NotImplementedError"""
-    messages = [
-        {"role": "user", "content": "Hello"},
-        {"role": "assistant", "content": "Hi there!"},
-    ]
-    with pytest.raises(NotImplementedError):
-        count_message_tokens(messages, model="invalid_model")
-
-
 def test_count_string_tokens_gpt_4():
     """Test that the string tokens are counted correctly."""