fix: patch AutoGen integration for 0.3.5 + add AutoGen integration tests (#1081)

.github/workflows/tests.yml

@@ -41,6 +41,7 @@ jobs:
         PGVECTOR_TEST_DB_URL: postgresql+pg8000://memgpt:memgpt@localhost:8888/memgpt
         OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
         MEMGPT_SERVER_PASS: test_server_token
+        PYTHONPATH: ${{ github.workspace }}:${{ env.PYTHONPATH }}
       run: |
         poetry run pytest -s -vv -k "not test_storage and not test_server and not test_openai_client" tests
 

memgpt/agent.py

@@ -14,7 +14,7 @@ from memgpt.models import chat_completion_response
 from memgpt.interface import AgentInterface
 from memgpt.persistence_manager import LocalStateManager
 from memgpt.system import get_login_event, package_function_response, package_summarize_message, get_initial_boot_messages
-from memgpt.memory import CoreMemory as InContextMemory, summarize_messages
+from memgpt.memory import CoreMemory as InContextMemory, summarize_messages, ArchivalMemory, RecallMemory
 from memgpt.llm_api_tools import create, is_context_overflow_error
 from memgpt.utils import (
     create_random_username,
@@ -45,7 +45,7 @@ from .errors import LLMError
 from .functions.functions import USER_FUNCTIONS_DIR, load_all_function_sets
 
 
-def link_functions(function_schemas):
+def link_functions(function_schemas: list):
     """Link function definitions to list of function schemas"""
 
     # need to dynamically link the functions
@@ -93,7 +93,7 @@ def link_functions(function_schemas):
     return linked_function_set
 
 
-def initialize_memory(ai_notes, human_notes):
+def initialize_memory(ai_notes: Union[str, None], human_notes: Union[str, None]):
     if ai_notes is None:
         raise ValueError(ai_notes)
     if human_notes is None:
@@ -104,7 +104,14 @@ def initialize_memory(ai_notes, human_notes):
     return memory
 
 
-def construct_system_with_memory(system, memory, memory_edit_timestamp, archival_memory=None, recall_memory=None, include_char_count=True):
+def construct_system_with_memory(
+    system: str,
+    memory: InContextMemory,
+    memory_edit_timestamp: str,
+    archival_memory: ArchivalMemory = None,
+    recall_memory: RecallMemory = None,
+    include_char_count: bool = True,
+):
     full_system_message = "\n".join(
         [
             system,
@@ -125,13 +132,13 @@ def construct_system_with_memory(system, memory, memory_edit_timestamp, archival
 
 
 def initialize_message_sequence(
-    model,
-    system,
-    memory,
-    archival_memory=None,
-    recall_memory=None,
-    memory_edit_timestamp=None,
-    include_initial_boot_message=True,
+    model: str,
+    system: str,
+    memory: InContextMemory,
+    archival_memory: ArchivalMemory = None,
+    recall_memory: RecallMemory = None,
+    memory_edit_timestamp: str = None,
+    include_initial_boot_message: bool = True,
 ):
     if memory_edit_timestamp is None:
         memory_edit_timestamp = get_local_time()

memgpt/autogen/examples/agent_docs.py

@@ -161,7 +161,7 @@ memgpt_agent.load_and_attach(
 )
 
 # Initialize the group chat between the agents
-groupchat = autogen.GroupChat(agents=[user_proxy, memgpt_agent], messages=[], max_round=12, speaker_selection_method="round_robin")
+groupchat = autogen.GroupChat(agents=[user_proxy, memgpt_agent], messages=[], max_round=3, speaker_selection_method="round_robin")
 manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)
 
 # Begin the group chat with a message from the user

memgpt/autogen/examples/agent_groupchat.py

@@ -185,7 +185,7 @@ else:
 
 
 # Initialize the group chat between the user and two LLM agents (PM and coder)
-groupchat = autogen.GroupChat(agents=[user_proxy, pm, coder], messages=[], max_round=12, speaker_selection_method="round_robin")
+groupchat = autogen.GroupChat(agents=[user_proxy, pm, coder], messages=[], max_round=3, speaker_selection_method="round_robin")
 manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)
 
 # Begin the group chat with a message from the user

memgpt/autogen/memgpt_agent.py

@@ -1,8 +1,10 @@
 import uuid
+import sys
 from typing import Callable, Optional, List, Dict, Union, Any, Tuple
 
 from autogen.agentchat import Agent, ConversableAgent, UserProxyAgent, GroupChat, GroupChatManager
 
+from memgpt.metadata import MetadataStore
 from memgpt.agent import Agent as MemGPTAgent
 from memgpt.agent import save_agent
 from memgpt.autogen.interface import AutoGenInterface
@@ -12,10 +14,10 @@ import memgpt.utils as utils
 import memgpt.presets.presets as presets
 from memgpt.config import MemGPTConfig
 from memgpt.credentials import MemGPTCredentials
-from memgpt.cli.cli import attach
-from memgpt.cli.cli_load import load_directory, load_webpage, load_index, load_database, load_vector_database
+from memgpt.cli.cli_load import load_directory, load_vector_database
 from memgpt.agent_store.storage import StorageConnector, TableType
 from memgpt.data_types import AgentState, User, LLMConfig, EmbeddingConfig
+from memgpt.utils import get_human_text, get_persona_text
 
 
 class MemGPTConversableAgent(ConversableAgent):
@@ -332,23 +334,33 @@ def create_autogen_memgpt_agent(
         user_id = uuid.UUID(agent_config["user_id"])
         user = ms.get_user(user_id=user_id)
 
-    agent_state = AgentState(
-        name=agent_config["name"],
-        user_id=user_id,
-        persona=agent_config["persona"],
-        human=agent_config["human"],
-        llm_config=llm_config,
-        embedding_config=embedding_config,
-        preset=agent_config["preset"],
-    )
     try:
-        preset = ms.get_preset(preset_name=agent_state.preset, user_id=user_id)
-        memgpt_agent = presets.create_agent_from_preset(
-            agent_state=agent_state,
-            preset=preset,
+        preset_obj = ms.get_preset(preset_name=agent_config["preset"] if "preset" in agent_config else config.preset, user_id=user.id)
+        if preset_obj is None:
+            # create preset records in metadata store
+            from memgpt.presets.presets import add_default_presets
+
+            add_default_presets(user.id, ms)
+            # try again
+            preset_obj = ms.get_preset(preset_name=agent_config["preset"] if "preset" in agent_config else config.preset, user_id=user.id)
+            if preset_obj is None:
+                print("Couldn't find presets in database, please run `memgpt configure`")
+                sys.exit(1)
+
+        # Overwrite fields in the preset if they were specified
+        # TODO make sure that the human/persona aren't filenames but actually real values
+        preset_obj.human = agent_config["human"] if "human" in agent_config else get_human_text(config.human)
+        preset_obj.persona = agent_config["persona"] if "persona" in agent_config else get_persona_text(config.persona)
+
+        memgpt_agent = MemGPTAgent(
             interface=interface,
-            persona_is_file=False,
-            human_is_file=False,
+            name=agent_config["name"] if "name" in agent_config else None,
+            created_by=user.id,
+            preset=preset_obj,
+            llm_config=llm_config,
+            embedding_config=embedding_config,
+            # gpt-3.5-turbo tends to omit inner monologue, relax this requirement for now
+            first_message_verify_mono=True if (llm_config.model is not None and "gpt-4" in llm_config.model) else False,
         )
         # Save agent in database immediately after writing
         save_agent(agent=memgpt_agent, ms=ms)
@@ -357,7 +369,7 @@ def create_autogen_memgpt_agent(
 
     # After creating the agent, we then need to wrap it in a ConversableAgent so that it can be plugged into AutoGen
     autogen_memgpt_agent = MemGPTConversableAgent(
-        name=agent_state.name,
+        name=memgpt_agent.agent_state.name,
         agent=memgpt_agent,
         default_auto_reply=default_auto_reply,
         is_termination_msg=is_termination_msg,

tests/test_autogen_integration.py

@@ -0,0 +1,36 @@
+import os
+import sys
+import subprocess
+import pytest
+
+
+def test_agent_groupchat():
+    # Define the path to the script you want to test
+    script_path = "memgpt/autogen/examples/agent_groupchat.py"
+
+    # Dynamically get the project's root directory (assuming this script is run from the root)
+    # project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))
+    # print(project_root)
+    # project_root = os.path.join(project_root, "MemGPT")
+    # print(project_root)
+    # sys.exit(1)
+
+    project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
+    project_root = os.path.join(project_root, "memgpt")
+    print(f"Adding the following to PATH: {project_root}")
+
+    # Prepare the environment, adding the project root to PYTHONPATH
+    env = os.environ.copy()
+    env["PYTHONPATH"] = f"{project_root}:{env.get('PYTHONPATH', '')}"
+
+    # Run the script using subprocess.run
+    # Capture the output (stdout) and the exit code
+    # result = subprocess.run(["python", script_path], capture_output=True, text=True)
+    result = subprocess.run(["poetry", "run", "python", script_path], capture_output=True, text=True)
+
+    # Check the exit code (0 indicates success)
+    assert result.returncode == 0, f"Script exited with code {result.returncode}: {result.stderr}"
+
+    # Optionally, check the output for expected content
+    # For example, if you expect a specific line in the output, uncomment and adapt the following line:
+    # assert "expected output" in result.stdout, "Expected output not found in script's output"