Update configuration

Author: hinthornw

pyproject.toml

@@ -15,8 +15,7 @@ dependencies = [
     "langchain>=0.2.14",
     "langchain-fireworks>=0.1.7",
     "python-dotenv>=1.0.1",
-    "langchain-community>=0.2.17",
-    "tavily-python>=0.4.0",
+    "langchain-tavily>=0.1",
 ]
 
 
@@ -64,4 +63,5 @@ convention = "google"
 [dependency-groups]
 dev = [
     "langgraph-cli[inmem]>=0.1.71",
+    "pytest>=8.3.5",
 ]

src/react_agent/configuration.py

@@ -3,9 +3,10 @@
 from __future__ import annotations
 
 from dataclasses import dataclass, field, fields
-from typing import Annotated, Optional
+from typing import Annotated
 
-from langchain_core.runnables import RunnableConfig, ensure_config
+from langchain_core.runnables import ensure_config
+from langgraph.config import get_config
 
 from react_agent import prompts
 
@@ -38,10 +39,12 @@ class Configuration:
     )
 
     @classmethod
-    def from_runnable_config(
-        cls, config: Optional[RunnableConfig] = None
-    ) -> Configuration:
+    def from_context(cls) -> Configuration:
         """Create a Configuration instance from a RunnableConfig object."""
+        try:
+            config = get_config()
+        except RuntimeError:
+            config = None
         config = ensure_config(config)
         configurable = config.get("configurable") or {}
         _fields = {f.name for f in fields(cls) if f.init}

src/react_agent/graph.py

@@ -3,11 +3,10 @@
 Works with a chat model with tool calling support.
 """
 
-from datetime import datetime, timezone
+from datetime import UTC, datetime
 from typing import Dict, List, Literal, cast
 
 from langchain_core.messages import AIMessage
-from langchain_core.runnables import RunnableConfig
 from langgraph.graph import StateGraph
 from langgraph.prebuilt import ToolNode
 
@@ -19,9 +18,7 @@
 # Define the function that calls the model
 
 
-async def call_model(
-    state: State, config: RunnableConfig
-) -> Dict[str, List[AIMessage]]:
+async def call_model(state: State) -> Dict[str, List[AIMessage]]:
     """Call the LLM powering our "agent".
 
     This function prepares the prompt, initializes the model, and processes the response.
@@ -33,21 +30,21 @@ async def call_model(
     Returns:
         dict: A dictionary containing the model's response message.
     """
-    configuration = Configuration.from_runnable_config(config)
+    configuration = Configuration.from_context()
 
     # Initialize the model with tool binding. Change the model or add more tools here.
     model = load_chat_model(configuration.model).bind_tools(TOOLS)
 
     # Format the system prompt. Customize this to change the agent's behavior.
     system_message = configuration.system_prompt.format(
-        system_time=datetime.now(tz=timezone.utc).isoformat()
+        system_time=datetime.now(tz=UTC).isoformat()
     )
 
     # Get the model's response
     response = cast(
         AIMessage,
         await model.ainvoke(
-            [{"role": "system", "content": system_message}, *state.messages], config
+            [{"role": "system", "content": system_message}, *state.messages]
         ),
     )
 
@@ -115,9 +112,4 @@ def route_model_output(state: State) -> Literal["__end__", "tools"]:
 builder.add_edge("tools", "call_model")
 
 # Compile the builder into an executable graph
-# You can customize this by adding interrupt points for state updates
-graph = builder.compile(
-    interrupt_before=[],  # Add node names here to update state before they're called
-    interrupt_after=[],  # Add node names here to update state after they're called
-)
-graph.name = "ReAct Agent"  # This customizes the name in LangSmith
+graph = builder.compile(name="ReAct Agent")

src/react_agent/tools.py

@@ -8,27 +8,21 @@
 
 from typing import Any, Callable, List, Optional, cast
 
-from langchain_community.tools.tavily_search import TavilySearchResults
-from langchain_core.runnables import RunnableConfig
-from langchain_core.tools import InjectedToolArg
-from typing_extensions import Annotated
+from langchain_tavily import TavilySearch  # type: ignore[import-not-found]
 
 from react_agent.configuration import Configuration
 
 
-async def search(
-    query: str, *, config: Annotated[RunnableConfig, InjectedToolArg]
-) -> Optional[list[dict[str, Any]]]:
+async def search(query: str) -> Optional[dict[str, Any]]:
     """Search for general web results.
 
     This function performs a search using the Tavily search engine, which is designed
     to provide comprehensive, accurate, and trusted results. It's particularly useful
     for answering questions about current events.
     """
-    configuration = Configuration.from_runnable_config(config)
-    wrapped = TavilySearchResults(max_results=configuration.max_search_results)
-    result = await wrapped.ainvoke({"query": query})
-    return cast(list[dict[str, Any]], result)
+    configuration = Configuration.from_context()
+    wrapped = TavilySearch(max_results=configuration.max_search_results)
+    return cast(dict[str, Any], await wrapped.ainvoke({"query": query}))
 
 
 TOOLS: List[Callable[..., Any]] = [search]

tests/unit_tests/test_configuration.py

@@ -2,4 +2,4 @@
 
 
 def test_configuration_empty() -> None:
-    Configuration.from_runnable_config({})
+    Configuration.from_context()