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update examples
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‎examples/basic/1d-screen-click.py

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"""
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A Bit-Shooter Game played on a 1-dimensional binary screen.
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Given an LLM Agent access to a 1-dimensional "screen" represented
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as a string of bits (0s and 1s), e.g. "101010",
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and equip it with a "Click tool" (like a mouse click) that allows it to
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click on a bit -- clicking the bit causes it to flip.
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The Agent plays a "Bit Shooter" game where the goal is to get rid of all
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1s in the "screen".
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To use the Click tool, the Agent must specify the position (zero-based)
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where it wants to click. This causes the bit to flip.
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The LLM is then presented with the new state of the screen,
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and the process repeats until all 1s are gone.
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Clearly the Agent (LLM) needs to be able to accurately count the bit positions,
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to be able to correctly click on the 1s.
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Run like this (--model is optional, defaults to GPT4o):
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python3 examples/basic/1d-screen-click.py --model litellm/anthropic/claude-3-5-sonnet-20241022
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At the beginning you get to specify the initial state of the screen:
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- size of the screen (how many bits)
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- the (0-based) locations of the 1s (SPACE-separated) in the screen.
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E.g. try this:
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- size = 50,
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- 1-indices: 0 20 30 40
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The loop is set to run in interactive mode (to prevent runaway loops),
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so you have to keep hitting enter to see the LLM's next move.
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The main observation is that when you run it with claude-3.5-sonnet,
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the accuracy of the Agent's clicks is far superior to other LLMs like GPT-4o
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and even GPT-4.
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To try with other LLMs, you can set the --model param to, for example:
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- gpt-4 (set OPENAI_API_KEY in your env or .env file)
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- gpt-4o (ditto, set OPENAI_API_KEY)
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- groq/llama-3.1-70b-versatile (set GROQ_API_KEY in your env or .env file)
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- cerebras/llama3.1-70b (set CEREBRAS_API_KEY in your env or .env file)
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- ollama/qwen2.5-coder:latest
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See here for a full guide on local/open LLM setup with Langroid:
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https://langroid.github.io/langroid/tutorials/local-llm-setup/
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And here for how to use with other non-OpenAPI LLMs:
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https://langroid.github.io/langroid/tutorials/non-openai-llms/
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"""
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from typing import List, Tuple
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from mypy.dmypy.client import show_stats
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import langroid as lr
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import langroid.language_models as lm
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from langroid.agent.tools.orchestration import AgentDoneTool
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from langroid.pydantic_v1 import BaseModel
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from langroid.utils.globals import GlobalState
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from rich.prompt import Prompt
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import fire
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class ScreenState(BaseModel):
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"""
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Represents the state of the 1-dimensional binary screen
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"""
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screen: str | None = None # binary string, e.g. "101010"
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def __init__(
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self,
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one_indices: List[int] = [1],
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size: int = 1,
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):
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super().__init__()
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# Initialize with all zeros
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screen_list = ["0"] * size
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# Set 1s at specified indices
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for idx in one_indices:
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if 0 <= idx < size:
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screen_list[idx] = "1"
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# Join into string
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self.screen = "".join(screen_list)
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@classmethod
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def set_state(
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cls,
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one_indices: List[int],
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size: int,
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) -> "ScreenState":
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"""
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Factory method to create and set initial state.
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"""
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initial_state = cls(
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one_indices=one_indices,
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size=size,
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)
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GlobalScreenState.set_values(state=initial_state)
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def flip(self, i: int):
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"""
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Flip the i-th bit
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"""
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if self.screen is None or i < 0 or i >= len(self.screen):
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return
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screen_list = list(self.screen)
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screen_list[i] = "1" if screen_list[i] == "0" else "0"
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self.screen = "".join(screen_list)
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class GlobalScreenState(GlobalState):
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state: ScreenState = ScreenState()
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def get_state() -> ScreenState:
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return GlobalScreenState.get_value("state")
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class ClickTool(lr.ToolMessage):
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request: str = "click_tool"
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purpose: str = """
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To click at <position> on the 1-dimensional binary screen,
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which causes the bit at that position to FLIP.
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IMPORTANT: the position numbering starts from 0!!!
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"""
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position: int
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@classmethod
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def examples(cls) -> List[lr.ToolMessage | Tuple[str, lr.ToolMessage]]:
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return [
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cls(position=3),
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(
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"I want to click at position 5",
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cls(position=5),
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),
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]
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def handle(self) -> str | AgentDoneTool:
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state = get_state()
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state.flip(self.position)
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print("SCREEN STATE = ", state.screen)
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if "1" not in state.screen:
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return AgentDoneTool()
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return state.screen
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def main(model: str = ""):
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llm_config = lm.OpenAIGPTConfig(
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chat_model=model or lm.OpenAIChatModel.GPT4o,
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)
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click_tool_name = ClickTool.default_value("request")
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agent = lr.ChatAgent(
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lr.ChatAgentConfig(
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name="Clicker",
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llm=llm_config,
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use_functions_api=False,
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use_tools=True,
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show_stats=False,
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system_message=f"""
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You are an expert at COMPUTER USE.
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In this task you only have to be able to understand a 1-dimensional
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screen presented to you as a string of bits (0s and 1s).
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You will play a 1-dimensional BIT-shooter game!
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Your task is to CLICK ON THE LEFTMOST 1 in the bit-string,
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to flip it to a 0.
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Always try to click on the LEFTMOST 1 in the bit-sequence.
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To CLICK on the screen you
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must use the TOOL `{click_tool_name}` where the
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`position` field specifies the position (zero-based) to click.
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If you CORRECTLY click on a 1, the bit at that position will be
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turned to 0.
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But if you click on a 0, it will turn into a 1,
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taking you further from your goal.
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So you MUST ACCURATELY specify the position of the LEFTMOST 1 to click,
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making SURE there is a 1 at that position.
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In other words, it is critical that you are able to ACCURATELY COUNT
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the bit positions so that you are able to correctly identify the position
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of the LEFTMOST 1 bit in the "screen" given to you as a string of bits.
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""",
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)
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)
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agent.enable_message(ClickTool)
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task = lr.Task(agent, interactive=True, only_user_quits_root=False)
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# kick it off with initial screen state (set below by user)
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task.run(get_state())
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if __name__ == "__main__":
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size = int(Prompt.ask("Size of screen (how many bits)"))
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ones = Prompt.ask("Indices of 1s (SPACE-separated)").split(" ")
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ones = [int(x) for x in ones]
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ScreenState.set_state(ones, size)
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print("SCREEN STATE = ", get_state().screen)
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fire.Fire(main)

‎examples/basic/xml_tool.py

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"""
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Example of defining a variant of an existing tool, but inheriting from XMLToolMessage,
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to have the LLM use XML rather than JSON to generate the tool.
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This will not work with built-in functions/tools of OpenAI,
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so in the `ChatAgentConfig` , you have to set the following to ensure
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that Langroid's built-in XML Tool calls are activated:
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- `use_functions_api = False`
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- `use_tools = True`
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Run like this (--model is optional, defaults to GPT4o):
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python3 examples/basic/xml_tool.py --model groq/llama-3.1-8b-instant
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"""
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import langroid as lr
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import langroid.language_models as lm
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from langroid.pydantic_v1 import Field
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from langroid.agent.tools.orchestration import SendTool
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from langroid.agent.xml_tool_message import XMLToolMessage
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import fire
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class XMLSendTool(SendTool, XMLToolMessage):
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"""
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Variant of SendTool, using XML rather than JSON.
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"""
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request: str = "xml_send_tool"
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purpose: str = """
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To send <content> to an entity/agent identified in the <to> field.
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"""
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content: str = Field(
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...,
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description="The content to send",
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verbatim=True, # enforces content enclosed within CDATA block in xml.
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)
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to: str
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xml_send_tool_name = XMLSendTool.default_value("request")
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def main(model: str = ""):
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llm_config = lm.OpenAIGPTConfig(
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chat_model=model or lm.OpenAIChatModel.GPT4o,
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)
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alice = lr.ChatAgent(
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lr.ChatAgentConfig(
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name="Alice",
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llm=llm_config,
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use_functions_api=False,
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use_tools=True,
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system_message=f"""
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Whatever number you receive, send it to Bob using the
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`{xml_send_tool_name}` tool.
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""",
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)
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)
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bob = lr.ChatAgent(
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lr.ChatAgentConfig(
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name="Bob",
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llm=llm_config,
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use_functions_api=False,
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use_tools=True,
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system_message=f"""
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Whatever number you receive, add 1 to it and send
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the result back to Alice
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using the `{xml_send_tool_name}` tool.
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""",
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)
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)
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alice.enable_message(XMLSendTool)
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bob.enable_message(XMLSendTool)
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# specialize alice_task to return an int
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alice_task = lr.Task(alice, interactive=False)[int]
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bob_task = lr.Task(bob, interactive=False)
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alice_task.add_sub_task(bob_task)
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result = alice_task.run("5", turns=6)
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assert result == 7
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if __name__ == "__main__":
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fire.Fire(main)

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