move action and tool classes to actions module

Author: ollmer

src/agentlab/actions.py

@@ -1,14 +1,81 @@
 import json
 import logging
+from typing import Any, Callable, Literal
 
 from bgym import AbstractActionSet
+from langchain_core.utils.function_calling import convert_to_openai_tool
+from pydantic import BaseModel
 
-from agentlab.backends.browser.base import FunctionCall, ToolCallAction, ToolSpec
 from agentlab.llm.llm_utils import parse_html_tags_raise
 
 logger = logging.getLogger(__name__)
 
 
+class FunctionSpec(BaseModel):
+    """
+    A class representing the specification of a function.
+
+    Attributes:
+        name (str): The name of the function.
+        description (str): A brief description of the function.
+        parameters (dict): A dictionary containing the parameters of the function.
+    """
+
+    name: str
+    description: str
+    parameters: dict
+
+
+class FunctionCall(BaseModel):
+    """
+    A class representing a function call.
+
+    Attributes:
+        name (str): The name of the function being called.
+        arguments (Any): The arguments to be passed to the function.
+    """
+
+    name: str
+    arguments: Any
+
+
+class ToolCallAction(BaseModel):
+    id: str = ""
+    function: FunctionCall
+
+    def llm_view(self, **kwargs) -> str:
+        return self.model_dump_json(indent=2)
+
+
+class ToolSpec(BaseModel):
+    """
+    ToolSpec is a model that represents a tool specification with a type and a function.
+
+    Attributes:
+        type (Literal["function"]): The type of the tool, which is always "function".
+        function (FunctionSpec): The specification of the function.
+    """
+
+    type: Literal["function"] = "function"
+    function: FunctionSpec
+
+    def description(self) -> str:
+        return f"{self.function.name} - {self.function.description}"
+
+    @classmethod
+    def from_function(cls, function: Callable):
+        """
+        Creates an instance of the class by validating the model from a given function.
+
+        Args:
+            function (Callable): The function to be converted and validated.
+
+        Returns:
+            (ToolSpec): An instance of the class with the validated model.
+        """
+        return cls.model_validate(convert_to_openai_tool(function))
+
+
 class ToolsActionSet(AbstractActionSet):
     multiaction: bool = False
     strict: bool = False
@@ -49,19 +116,15 @@ def parse_action(cls, llm_output: str) -> ToolCallAction:
         if "<action>" in llm_output:
             content_dict, valid, retry_message = parse_html_tags_raise(llm_output, keys=["action"])
             if not valid or "action" not in content_dict:
-                raise ValueError(
-                    f"Invalid action: llm_output: {llm_output}, retry_message: {retry_message}"
-                )
+                raise ValueError(f"Invalid action: llm_output: {llm_output}, retry_message: {retry_message}")
             action_str = content_dict["action"]
         else:
             action_str = llm_output
         try:
             action_dict = json.loads(action_str)
         except json.JSONDecodeError:
             raise ValueError(f"Failed to parse action: {action_str}")
-        return ToolCallAction(
-            function=FunctionCall(name=action_dict["name"], arguments=action_dict["arguments"])
-        )
+        return ToolCallAction(function=FunctionCall(name=action_dict["name"], arguments=action_dict["arguments"]))
 
     def to_python_code(self, action) -> str:
         return action

src/agentlab/agents/tapeagent/agent.py

@@ -27,8 +27,8 @@
 from tapeagents.tool_calling import ToolSpec
 from termcolor import colored
 
+from agentlab.actions import ToolSpec as AgentlabToolSpec
 from agentlab.agents.agent_args import AgentArgs
-from agentlab.backends.browser.base import ToolSpec as AgentlabToolSpec
 
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.INFO)

src/agentlab/backends/browser/__init__.py

@@ -1,4 +1,5 @@
-from agentlab.backends.browser.base import BrowserBackend, FunctionCall, ToolCallAction, ToolSpec
+from agentlab.actions import FunctionCall, ToolCallAction, ToolSpec
+from agentlab.backends.browser.base import BrowserBackend
 from agentlab.backends.browser.env import BrowserEnv, BrowserEnvArgs
 from agentlab.backends.browser.mcp import MCPBrowserBackend, MCPClient
 from agentlab.backends.browser.mcp_playwright import MCPPlaywright

src/agentlab/backends/browser/base.py

@@ -1,77 +1,12 @@
 import logging
 from abc import ABC, abstractmethod
-from typing import Any, Callable, Literal
 
-from langchain_core.utils.function_calling import convert_to_openai_tool
 from PIL import Image
 from pydantic import BaseModel
 
-logger = logging.getLogger(__name__)
-
-
-class FunctionCall(BaseModel):
-    """
-    A class representing a function call.
-
-    Attributes:
-        name (str): The name of the function being called.
-        arguments (Any): The arguments to be passed to the function.
-    """
-
-    name: str
-    arguments: Any
-
-
-class FunctionSpec(BaseModel):
-    """
-    A class representing the specification of a function.
-
-    Attributes:
-        name (str): The name of the function.
-        description (str): A brief description of the function.
-        parameters (dict): A dictionary containing the parameters of the function.
-    """
-
-    name: str
-    description: str
-    parameters: dict
-
+from agentlab.actions import ToolCallAction, ToolSpec
 
-class ToolCallAction(BaseModel):
-    id: str = ""
-    function: FunctionCall
-
-    def llm_view(self, **kwargs) -> str:
-        return self.model_dump_json(indent=2)
-
-
-class ToolSpec(BaseModel):
-    """
-    ToolSpec is a model that represents a tool specification with a type and a function.
-
-    Attributes:
-        type (Literal["function"]): The type of the tool, which is always "function".
-        function (FunctionSpec): The specification of the function.
-    """
-
-    type: Literal["function"] = "function"
-    function: FunctionSpec
-
-    def description(self) -> str:
-        return f"{self.function.name} - {self.function.description}"
-
-    @classmethod
-    def from_function(cls, function: Callable):
-        """
-        Creates an instance of the class by validating the model from a given function.
-
-        Args:
-            function (Callable): The function to be converted and validated.
-
-        Returns:
-            (ToolSpec): An instance of the class with the validated model.
-        """
-        return cls.model_validate(convert_to_openai_tool(function))
+logger = logging.getLogger(__name__)
 
 
 class BrowserBackend(BaseModel, ABC):

src/agentlab/backends/browser/env.py

@@ -3,8 +3,8 @@
 from dataclasses import dataclass
 from pathlib import Path
 
-from agentlab.actions import ToolsActionSet
-from agentlab.backends.browser.base import BrowserBackend, ToolCallAction, ToolSpec
+from agentlab.actions import ToolCallAction, ToolsActionSet, ToolSpec
+from agentlab.backends.browser.base import BrowserBackend
 from agentlab.benchmarks.abstract_env import AbstractEnv, AbstractEnvArgs
 from agentlab.benchmarks.web_task import AbstractWebTask
 

src/agentlab/backends/browser/mcp.py

@@ -10,7 +10,8 @@
 from mcp import Tool as MCPTool
 from mcp.types import CallToolResult, ImageContent, TextContent
 
-from agentlab.backends.browser.base import BrowserBackend, FunctionSpec, ToolCallAction, ToolSpec
+from agentlab.actions import FunctionSpec, ToolCallAction, ToolSpec
+from agentlab.backends.browser.base import BrowserBackend
 
 logger = logging.getLogger(__name__)
 

src/agentlab/backends/browser/mcp_playwright.py

@@ -4,7 +4,8 @@
 
 from PIL import Image
 
-from agentlab.backends.browser.mcp import MCPBrowserBackend, ToolCallAction
+from agentlab.actions import ToolCallAction
+from agentlab.backends.browser.mcp import MCPBrowserBackend
 
 logger = logging.getLogger(__name__)
 

src/agentlab/backends/browser/playwright.py

@@ -6,7 +6,8 @@
 from PIL import Image
 from playwright.async_api import Browser, Page, async_playwright
 
-from agentlab.backends.browser.base import BrowserBackend, ToolCallAction, ToolSpec
+from agentlab.actions import ToolCallAction, ToolSpec
+from agentlab.backends.browser.base import BrowserBackend
 
 logger = logging.getLogger(__name__)
 

src/agentlab/benchmarks/web_task.py

@@ -2,7 +2,7 @@
 
 from pydantic import BaseModel
 
-from agentlab.backends.browser.base import ToolSpec
+from agentlab.actions import ToolSpec
 
 
 class AbstractWebTask(BaseModel):