cr

README.md

@@ -26,6 +26,8 @@ pip install langchain langchain-mcp-adapters langchain-anthropic
 
 ## Example
 
+A full version of this in one file can be found [here](examples/math.py)
+
 ### 1. Define your tools
 
 You can use any tools you want, including custom tools, LangChain tools, or MCP tools. In this example, we define a few simple math functions.
@@ -117,7 +119,7 @@ import io
 def eval(code: str, _locals: dict) -> tuple:
     # Store original keys before execution
     original_keys = set(_locals.keys())
-    
+
     try:
         with contextlib.redirect_stdout(io.StringIO()) as f:
             exec(code, builtins.__dict__, _locals)
@@ -126,7 +128,7 @@ def eval(code: str, _locals: dict) -> tuple:
             result = "<code ran, no output printed to stdout>"
     except Exception as e:
         result = f"Error during execution: {repr(e)}"
-        
+
     # Determine new variables created during execution
     new_keys = set(_locals.keys()) - original_keys
     new_vars = {key: _locals[key] for key in new_keys}
@@ -144,7 +146,8 @@ from langgraph.checkpoint.memory import MemorySaver
 
 model = init_chat_model("claude-3-7-sonnet-latest", model_provider="anthropic")
 
-code_act = create_codeact(tools, model, eval, checkpointer=MemorySaver())
+code_act = create_codeact(model, tools, eval)
+agent = code_act.compile(checkpointer=MemorySaver())
 ```
 
 ### 4. Run it!
@@ -153,9 +156,14 @@ You can use the `.invoke()` method to get the final result, or the `.stream()` m
 
 ```py
 
-for typ, chunk in code_act.stream(
-    "A batter hits a baseball at 45.847 m/s at an angle of 23.474° above the horizontal. The outfielder, who starts facing the batter, picks up the baseball as it lands, then throws it back towards the batter at 24.12 m/s at an angle of 39.12 degrees. How far is the baseball from where the batter originally hit it? Assume zero air resistance.",
+messages = [{
+    "role": "user",
+    "content": "A batter hits a baseball at 45.847 m/s at an angle of 23.474° above the horizontal. The outfielder, who starts facing the batter, picks up the baseball as it lands, then throws it back towards the batter at 24.12 m/s at an angle of 39.12 degrees. How far is the baseball from where the batter originally hit it? Assume zero air resistance."
+}]
+for typ, chunk in agent.stream(
+    {"messages": messages},
     stream_mode=["values", "messages"],
+    config={"configurable": {"thread_id": 1}},
 ):
     if typ == "messages":
         print(chunk[0].content, end="")

examples/math_example.py

@@ -0,0 +1,113 @@
+import math
+
+from langchain_core.tools import tool
+import builtins
+import contextlib
+import io
+
+from langchain.chat_models import init_chat_model
+from langgraph_codeact import create_codeact
+from langgraph.checkpoint.memory import MemorySaver
+
+
+def eval(code: str, _locals: dict) -> tuple:
+    # Store original keys before execution
+    original_keys = set(_locals.keys())
+
+    try:
+        with contextlib.redirect_stdout(io.StringIO()) as f:
+            exec(code, builtins.__dict__, _locals)
+        result = f.getvalue()
+        if not result:
+            result = "<code ran, no output printed to stdout>"
+    except Exception as e:
+        result = f"Error during execution: {repr(e)}"
+
+    # Determine new variables created during execution
+    new_keys = set(_locals.keys()) - original_keys
+    new_vars = {key: _locals[key] for key in new_keys}
+    return result, new_vars
+@tool
+def add(a: float, b: float) -> float:
+    """Add two numbers together."""
+    return a + b
+
+@tool
+def multiply(a: float, b: float) -> float:
+    """Multiply two numbers together."""
+    return a * b
+
+@tool
+def divide(a: float, b: float) -> float:
+    """Divide two numbers."""
+    return a / b
+
+@tool
+def subtract(a: float, b: float) -> float:
+    """Subtract two numbers."""
+    return a - b
+
+@tool
+def sin(a: float) -> float:
+    """Take the sine of a number."""
+    return math.sin(a)
+
+@tool
+def cos(a: float) -> float:
+    """Take the cosine of a number."""
+    return math.cos(a)
+
+@tool
+def radians(a: float) -> float:
+    """Convert degrees to radians."""
+    return math.radians(a)
+
+@tool
+def exponentiation(a: float, b: float) -> float:
+    """Raise one number to the power of another."""
+    return a**b
+
+@tool
+def sqrt(a: float) -> float:
+    """Take the square root of a number."""
+    return math.sqrt(a)
+
+@tool
+def ceil(a: float) -> float:
+    """Round a number up to the nearest integer."""
+    return math.ceil(a)
+
+tools = [
+    add,
+    multiply,
+    divide,
+    subtract,
+    sin,
+    cos,
+    radians,
+    exponentiation,
+    sqrt,
+    ceil,
+]
+
+model = init_chat_model("claude-3-7-sonnet-latest", model_provider="anthropic")
+
+code_act = create_codeact(model, tools, eval)
+agent = code_act.compile(checkpointer=MemorySaver())
+
+if __name__ == "__main__":
+    messages = [{
+        "role": "user",
+        "content": "A batter hits a baseball at 45.847 m/s at an angle of 23.474° above the horizontal. The outfielder, who starts facing the batter, picks up the baseball as it lands, then throws it back towards the batter at 24.12 m/s at an angle of 39.12 degrees. How far is the baseball from where the batter originally hit it? Assume zero air resistance."
+    }]
+    for typ, chunk in agent.stream(
+        {"messages": messages},
+        stream_mode=["values", "messages"],
+        config={"configurable": {"thread_id": 1}},
+    ):
+        if typ == "messages":
+            print(chunk[0].content, end="")
+        elif typ == "values":
+            print("\n\n---answer---\n\n", chunk)
+
+

langgraph_codeact/__init__.py

@@ -69,10 +69,11 @@ Reminder: use python code snippets to call tools"""
 
     def sandbox(state: CodeActState):
         script = state["script"]
-        context = state.get("context", {})
+        old_context = state.get("context", {})
+        context = {**old_context, **{tool.name: tool.func for tool in _tools}}
         # execute the script
         output, new_vars = eval_fn(script, context)
-        new_context = {**context, **new_vars}
+        new_context = {**old_context, **new_vars}
         return {"messages": [{"role": "user", "content": output}], "context": new_context}
 
     agent = StateGraph(CodeActState)