Merge branch 'main' into feature/implement-a-simple

Author: abrookins

.github/workflows/python-tests.yml

@@ -81,11 +81,12 @@ jobs:
     - name: Set up Docker Buildx
       uses: docker/setup-buildx-action@v3
 
-    - name: Log in to Docker Hub
+    - name: Log in to GitHub Container Registry
       uses: docker/login-action@v3
       with:
-        username: ${{ secrets.DOCKER_USERNAME }}
-        password: ${{ secrets.DOCKER_TOKEN }}
+        registry: ghcr.io
+        username: ${{ github.actor }}
+        password: ${{ secrets.GITHUB_TOKEN }}
 
     - name: Extract version from __init__.py
       id: version
@@ -102,7 +103,7 @@ jobs:
         platforms: linux/amd64,linux/arm64
         push: true
         tags: |
-          andrewbrookins510/agent-memory-server:latest
-          andrewbrookins510/agent-memory-server:${{ steps.version.outputs.version }}
+          ghcr.io/${{ github.repository }}:latest
+          ghcr.io/${{ github.repository }}:${{ steps.version.outputs.version }}
         cache-from: type=gha
         cache-to: type=gha,mode=max

CLAUDE.md

@@ -14,9 +14,7 @@ uv install --all-extras      # Install dependencies
 uv sync --all-extras         # Sync latest dependencies
 uv run ruff check            # Run linting
 uv run ruff format           # Format code
-uv run pytest                # Run tests
-uv run pytest tests/         # Run specific test directory
-uv run pytest --run-api-tests # Run all tests, including API tests
+uv run pytest --run-api-tests # Run all tests
 uv add <dependency>          # Add a dependency to pyproject.toml and update lock file
 uv remove <dependency>       # Remove a dependency from pyproject.toml and update lock file
 

agent-memory-client/README.md

@@ -301,7 +301,7 @@ mypy agent_memory_client/
 - Python 3.10+
 - httpx >= 0.25.0
 - pydantic >= 2.0.0
-- ulid-py >= 1.1.0
+- python-ulid >= 3.0.0
 
 ## License
 

agent-memory-client/agent_memory_client/__init__.py

@@ -5,7 +5,7 @@
 memory management capabilities for AI agents and applications.
 """
 
-__version__ = "0.9.0b6"
+__version__ = "0.9.0b7"
 
 from .client import MemoryAPIClient, MemoryClientConfig, create_memory_client
 from .exceptions import (

agent-memory-client/agent_memory_client/client.py

@@ -31,6 +31,7 @@
     AckResponse,
     ClientMemoryRecord,
     HealthCheckResponse,
+    MemoryMessage,
     MemoryRecord,
     MemoryRecordResults,
     MemoryTypeEnum,
@@ -675,7 +676,7 @@ async def search_long_term_memory(
 
         try:
             response = await self._client.post(
-                "/v1/memory/search",
+                "/v1/long-term-memory/search",
                 json=payload,
             )
             response.raise_for_status()
@@ -2055,7 +2056,7 @@ async def update_working_memory_data(
     async def append_messages_to_working_memory(
         self,
         session_id: str,
-        messages: list[dict[str, Any]],  # Expect proper message dicts
+        messages: list[dict[str, Any] | MemoryMessage],
         namespace: str | None = None,
         model_name: str | None = None,
         context_window_max: int | None = None,
@@ -2068,7 +2069,7 @@ async def append_messages_to_working_memory(
 
         Args:
             session_id: Target session
-            messages: List of message dictionaries with 'role' and 'content' keys
+            messages: List of message dictionaries or MemoryMessage objects
             namespace: Optional namespace
             model_name: Optional model name for token-based summarization
             context_window_max: Optional direct specification of context window max tokens
@@ -2081,29 +2082,49 @@ async def append_messages_to_working_memory(
             session_id=session_id, namespace=namespace, user_id=user_id
         )
 
-        # Validate new messages have required structure
+        # Convert messages to MemoryMessage objects
+        converted_messages = []
         for msg in messages:
-            if not isinstance(msg, dict) or "role" not in msg or "content" not in msg:
+            if isinstance(msg, MemoryMessage):
+                converted_messages.append(msg)
+            elif isinstance(msg, dict):
+                if "role" not in msg or "content" not in msg:
+                    raise ValueError("All messages must have 'role' and 'content' keys")
+                # Build message kwargs, only including non-None values
+                message_kwargs = {
+                    "role": msg["role"],
+                    "content": msg["content"],
+                }
+                if msg.get("id") is not None:
+                    message_kwargs["id"] = msg["id"]
+                if msg.get("persisted_at") is not None:
+                    message_kwargs["persisted_at"] = msg["persisted_at"]
+
+                converted_messages.append(MemoryMessage(**message_kwargs))
+            else:
                 raise ValueError(
-                    "All messages must be dictionaries with 'role' and 'content' keys"
+                    "All messages must be dictionaries or MemoryMessage objects"
                 )
 
-        # Get existing messages (already in proper dict format from get_working_memory)
+        # Get existing messages
         existing_messages = []
         if existing_memory and existing_memory.messages:
             existing_messages = existing_memory.messages
 
-        final_messages = existing_messages + messages
+        final_messages = existing_messages + converted_messages
 
         # Create updated working memory
-        working_memory = WorkingMemory(
-            session_id=session_id,
-            namespace=namespace or self.config.default_namespace,
-            messages=final_messages,
-            memories=existing_memory.memories if existing_memory else [],
-            data=existing_memory.data if existing_memory else {},
-            context=existing_memory.context if existing_memory else None,
-            user_id=existing_memory.user_id if existing_memory else None,
+        working_memory = (
+            existing_memory.model_copy(
+                update={"messages": final_messages},
+            )
+            if existing_memory
+            else WorkingMemory(
+                session_id=session_id,
+                namespace=namespace or self.config.default_namespace,
+                messages=final_messages,
+                user_id=user_id or None,
+            )
         )
 
         return await self.put_working_memory(
@@ -2198,7 +2219,6 @@ async def memory_prompt(
             payload["long_term_search"] = long_term_search
 
         try:
-            print("Payload: ", payload)
             response = await self._client.post(
                 "/v1/memory/prompt",
                 json=payload,

agent-memory-client/agent_memory_client/models.py

@@ -7,7 +7,7 @@
 
 from datetime import datetime, timezone
 from enum import Enum
-from typing import Any, Literal, TypedDict
+from typing import Any, Literal
 
 from pydantic import BaseModel, Field
 from ulid import ULID
@@ -48,11 +48,23 @@ class MemoryTypeEnum(str, Enum):
     MESSAGE = "message"
 
 
-class MemoryMessage(TypedDict):
+class MemoryMessage(BaseModel):
     """A message in the memory system"""
 
     role: str
     content: str
+    id: str = Field(
+        default_factory=lambda: str(ULID()),
+        description="Unique identifier for the message (auto-generated)",
+    )
+    persisted_at: datetime | None = Field(
+        default=None,
+        description="Server-assigned timestamp when message was persisted to long-term storage",
+    )
+    discrete_memory_extracted: Literal["t", "f"] = Field(
+        default="f",
+        description="Whether memory extraction has run for this message",
+    )
 
 
 class MemoryRecord(BaseModel):
@@ -134,9 +146,9 @@ class WorkingMemory(BaseModel):
     """Working memory for a session - contains both messages and structured memory records"""
 
     # Support both message-based memory (conversation) and structured memory records
-    messages: list[dict[str, Any]] = Field(
+    messages: list[MemoryMessage] = Field(
         default_factory=list,
-        description="Conversation messages (role/content pairs)",
+        description="Conversation messages with tracking fields",
     )
     memories: list[MemoryRecord | ClientMemoryRecord] = Field(
         default_factory=list,

agent-memory-client/tests/test_client.py

@@ -546,9 +546,9 @@ async def test_append_messages_to_working_memory(self, enhanced_test_client):
             # Check that messages were appended
             working_memory_arg = mock_put.call_args[0][1]
             assert len(working_memory_arg.messages) == 3
-            assert working_memory_arg.messages[0]["content"] == "First message"
-            assert working_memory_arg.messages[1]["content"] == "Second message"
-            assert working_memory_arg.messages[2]["content"] == "Third message"
+            assert working_memory_arg.messages[0].content == "First message"
+            assert working_memory_arg.messages[1].content == "Second message"
+            assert working_memory_arg.messages[2].content == "Third message"
 
     def test_deep_merge_dicts(self, enhanced_test_client):
         """Test the deep merge dictionary utility method."""

agent_memory_server/__init__.py

@@ -1,3 +1,3 @@
 """Redis Agent Memory Server - A memory system for conversational AI."""
 
-__version__ = "0.9.0b6"
+__version__ = "0.9.0b7"