Update environment configuration and dependencies

.env.example

@@ -1,5 +1,7 @@
 # To separate your traces from other application
 LANGSMITH_PROJECT=memory-graph
+# LANGSMITH_API_KEY=
+# MODEL=
 
 # The following depend on your selected configuration
 

pyproject.toml

@@ -7,16 +7,18 @@ authors = [
 ]
 readme = "README.md"
 license = { text = "MIT" }
-requires-python = ">=3.9"
+requires-python = ">=3.11"
 dependencies = [
-    "langgraph>=0.2.34,<0.3.0",
+    "langgraph>=0.6.0,<0.7.0",
+    "langgraph-api>=0.2.109,<0.3.0",
     # Optional (for selecting different models)
     "langchain-openai>=0.2.1",
     "langchain-anthropic>=0.2.1",
     "langchain>=0.3.8",
     "langchain-core>=0.3.8",
     "python-dotenv>=1.0.1",
-    "langgraph-sdk>=0.1.32",
+    "langgraph-sdk>=0.2.0",
+    "langgraph-cli>=0.3.6",
 ]
 
 [project.optional-dependencies]

src/memory_agent/configuration.py

@@ -17,7 +17,7 @@ class Configuration:
     user_id: str = "default"
     """The ID of the user to remember in the conversation."""
     model: Annotated[str, {"__template_metadata__": {"kind": "llm"}}] = field(
-        default="anthropic/claude-3-5-sonnet-20240620",
+        default_factory=lambda: os.environ.get("MODEL", "anthropic/claude-3-5-sonnet-20240620"),
         metadata={
             "description": "The name of the language model to use for the agent. "
             "Should be in the form: provider/model-name."

src/memory_agent/graph.py

@@ -89,7 +89,7 @@ def route_message(state: State):
 
 
 # Create the graph + all nodes
-builder = StateGraph(State, config_schema=configuration.Configuration)
+builder = StateGraph(State, context_schema=configuration.Configuration)
 
 # Define the flow of the memory extraction process
 builder.add_node(call_model)