Setup New Project template

(Remove react agent code)

.env.example

@@ -1,7 +1,5 @@
-TAVILY_API_KEY=...
-
 # To separate your traces from other application
-LANGSMITH_PROJECT=retrieval-agent
+LANGSMITH_PROJECT=new-agent
 
 # The following depend on your selected configuration
 

.github/workflows/integration-tests.yml

@@ -36,7 +36,6 @@ jobs:
       - name: Run integration tests
         env:
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-          TAVILY_API_KEY: ${{ secrets.TAVILY_API_KEY }}
           LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
           LANGSMITH_TRACING: true
         run: |

Makefile

@@ -9,6 +9,9 @@ TEST_FILE ?= tests/unit_tests/
 test:
 	python -m pytest $(TEST_FILE)
 
+integration_tests:
+	python -m pytest tests/integration_tests 
+
 test_watch:
 	python -m ptw --snapshot-update --now . -- -vv tests/unit_tests
 

langgraph.json

@@ -1,7 +1,7 @@
 {
   "dependencies": ["."],
   "graphs": {
-    "agent": "./src/react_agent/graph.py:graph"
+    "agent": "./src/agent/graph.py:graph"
   },
   "env": ".env"
 }

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
-name = "react-agent"
+name = "agent"
 version = "0.0.1"
-description = "Starter template for making a custom Reasoning and Action agent (using tool calling) in LangGraph."
+description = "Starter template for making a new agent LangGraph."
 authors = [
     { name = "William Fu-Hinthorn", email = "[email protected]" },
 ]
@@ -10,13 +10,7 @@ license = { text = "MIT" }
 requires-python = ">=3.9"
 dependencies = [
     "langgraph>=0.2.6",
-    "langchain-openai>=0.1.22",
-    "langchain-anthropic>=0.1.23",
-    "langchain>=0.2.14",
-    "langchain-fireworks>=0.1.7",
     "python-dotenv>=1.0.1",
-    "langchain-community>=0.2.17",
-    "tavily-python>=0.4.0",
 ]
 
 
@@ -28,10 +22,10 @@ requires = ["setuptools>=73.0.0", "wheel"]
 build-backend = "setuptools.build_meta"
 
 [tool.setuptools]
-packages = ["langgraph.templates.react_agent", "react_agent"]
+packages = ["langgraph.templates.agent", "agent"]
 [tool.setuptools.package-dir]
-"langgraph.templates.react_agent" = "src/react_agent"
-"react_agent" = "src/react_agent"
+"langgraph.templates.agent" = "src/agent"
+"agent" = "src/agent"
 
 
 [tool.setuptools.package-data]

src/agent/__init__.py

@@ -0,0 +1,8 @@
+"""New LangGraph Agent.
+
+This module defines a custom graph.
+"""
+
+from agent.graph import graph
+
+__all__ = ["graph"]

src/agent/configuration.py

@@ -0,0 +1,24 @@
+"""Define the configurable parameters for the agent."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, fields
+from typing import Optional
+
+from langchain_core.runnables import RunnableConfig
+
+
+@dataclass(kw_only=True)
+class Configuration:
+    """The configuration for the agent."""
+
+    model_name: str = "my-model"
+
+    @classmethod
+    def from_runnable_config(
+        cls, config: Optional[RunnableConfig] = None
+    ) -> Configuration:
+        """Create a Configuration instance from a RunnableConfig object."""
+        configurable = (config.get("configurable") or {}) if config else {}
+        _fields = {f.name for f in fields(cls) if f.init}
+        return cls(**{k: v for k, v in configurable.items() if k in _fields})

src/agent/graph.py

@@ -0,0 +1,66 @@
+"""Define a simple chatbot agent.
+
+This agent returns a predefined response without using an actual LLM.
+"""
+
+from typing import Dict, List
+
+from langchain_core.messages import AIMessage
+from langchain_core.runnables import RunnableConfig
+from langgraph.graph import StateGraph
+
+from agent.configuration import Configuration
+from agent.state import State
+
+# Define the function that simulates calling a model
+
+
+async def call_model(
+    state: State, config: RunnableConfig
+) -> Dict[str, List[AIMessage]]:
+    """Simulate calling an LLM by returning a predefined response.
+
+    Args:
+        _state (State): The current state of the conversation (unused).
+        _config (RunnableConfig): Configuration for the run (unused).
+
+    Returns:
+        dict: A dictionary containing the predefined response message.
+    """
+    configuration = Configuration.from_runnable_config(config)
+    # Return a predefined response
+    return {
+        "messages": [AIMessage(content=f"Hi there! This is {configuration.model_name}")]
+    }
+
+
+# Define the routing function
+def route(state: State) -> str:
+    """Determine whether to continue the conversation or end it.
+
+    Args:
+        state (State): The current state of the conversation.
+
+    Returns:
+        str: Either "call_model" to continue or "__end__" to finish.
+    """
+    if len(state.messages) > 5:  # End after 5 interactions
+        return "__end__"
+    return "call_model"
+
+
+# Define a new graph
+workflow = StateGraph(State, config_schema=Configuration)
+
+# Add the node to the graph
+workflow.add_node("call_model", call_model)
+
+# Set the entrypoint as `call_model`
+workflow.add_edge("__start__", "call_model")
+
+# Add conditional edge
+workflow.add_conditional_edges("call_model", route)
+
+# Compile the workflow into an executable graph
+graph = workflow.compile()
+graph.name = "Simple Chatbot"  # This defines the custom name in LangSmith

src/agent/state.py

@@ -0,0 +1,25 @@
+"""Define the state structures for the agent."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import List
+
+from langchain_core.messages import AnyMessage
+from langgraph.graph import add_messages
+from typing_extensions import Annotated
+
+
+@dataclass
+class State:
+    """Defines the input state for the agent, representing a narrower interface to the outside world.
+
+    This class is used to define the initial state and structure of incoming data.
+    """
+
+    messages: Annotated[List[AnyMessage], add_messages] = field(default_factory=list)
+    """
+    Messages tracking the primary execution state of the agent.
+
+    Typically accumulates a pattern of user, assistant, user, ... etc. messages.
+    """