From c9bbe7e7f301179b4c9b9a3984bdd795947755c1 Mon Sep 17 00:00:00 2001 From: Tyler Rockwood Date: Thu, 27 Mar 2025 03:39:31 +0000 Subject: [PATCH] my first agent --- .../mcp/resources/caches/directory.yaml | 8 + .../mcp/resources/processors/dev_tools.star | 78 ++ .../resources/yaml/check_weather_tool.yaml | 12 + examples/connect_integration/pipeline_dev.py | 75 ++ pyproject.toml | 19 +- src/agents/__init__.py | 20 +- src/agents/agent.py | 276 +++++++ src/agents/mcp.py | 190 +++++ src/agents/tools.py | 79 ++ tests/test_agents.py | 21 +- uv.lock | 726 +++++++++++++++++- 11 files changed, 1485 insertions(+), 19 deletions(-) create mode 100644 examples/connect_integration/mcp/resources/caches/directory.yaml create mode 100644 examples/connect_integration/mcp/resources/processors/dev_tools.star create mode 100644 examples/connect_integration/mcp/resources/yaml/check_weather_tool.yaml create mode 100644 examples/connect_integration/pipeline_dev.py create mode 100644 src/agents/agent.py create mode 100644 src/agents/mcp.py create mode 100644 src/agents/tools.py diff --git a/examples/connect_integration/mcp/resources/caches/directory.yaml b/examples/connect_integration/mcp/resources/caches/directory.yaml new file mode 100644 index 0000000..cefa84e --- /dev/null +++ b/examples/connect_integration/mcp/resources/caches/directory.yaml @@ -0,0 +1,8 @@ +label: project_directory_file_contents +file: + directory: "${PROJECT_DIR}" + +meta: + mcp: + enabled: true + description: "the project directory where the user stores files" diff --git a/examples/connect_integration/mcp/resources/processors/dev_tools.star b/examples/connect_integration/mcp/resources/processors/dev_tools.star new file mode 100644 index 0000000..8f30a18 --- /dev/null +++ b/examples/connect_integration/mcp/resources/processors/dev_tools.star @@ -0,0 +1,78 @@ +validate_file_path = mapping(""" + let file = content().string() + root.file = if $file.contains("..") { + throw("invalid file path") + } else { + $file + } +""") + +mcp_tool( + label = "list_files", + description = "List files in a directory. Use `.` for the current directory.", + processor = processors( + attempt( + validate_file_path, + command( + name="ls", + args_mapping='[["{}", this.file].filepath_join()]'.format(secret("PROJECT_DIR")), + ), + mapping(""" + root.files = content().split("\\n") + if root.files == [""] { + root = "no files found" + } + """) + ), + catch( + mapping( + """root = ["Directory does not exist"]""", + ) + ), + ) +) + +mcp_tool( + label = "lint_connect_configuration_file", + description = "Lint a Connect configuration file, the `value` should be a path to a configuration file.", + processor = processors( + attempt( + validate_file_path, + command( + name="rpk", + args_mapping="""[ + "connect", + "lint", + ["{}", this.file].filepath_join(), + ]""".format(secret("PROJECT_DIR")), + ), + mapping('root = "lint success"'), + ), + catch( + mapping("root.error = error()"), + ) + ) +) + +mcp_tool( + label = "ask_docs_agent", + description = " ".join([ + "Ask the documentation agent for help.", + "This agent has access to the full documentation for Redpanda.", + "The `value` should be the question and mention that's it's for Redpanda Connect specifically.", + ]), + processor = attempt( + mapping("""root.query = content().string()"""), + http( + verb = "POST", + url = "https://api.kapa.ai/query/v1/projects/{project_id}/chat/".format( + project_id=secret("KAPA_PROJECT_ID"), + ), + headers = { + "Content-Type": "application/json", + "X-API-KEY": secret("KAPA_API_KEY"), + }, + timeout = "60s", + ) + ) +) diff --git a/examples/connect_integration/mcp/resources/yaml/check_weather_tool.yaml b/examples/connect_integration/mcp/resources/yaml/check_weather_tool.yaml new file mode 100644 index 0000000..ffa39b8 --- /dev/null +++ b/examples/connect_integration/mcp/resources/yaml/check_weather_tool.yaml @@ -0,0 +1,12 @@ +label: 'check_weather' +processors: + - http: + verb: GET + url: 'https://wttr.in/${!content().string()}?T' + headers: + User-Agent: curl/8.11.1 # Returns a text string from the weather website + +meta: + mcp: + enabled: true + description: 'A tool that can tell you what the weather is in a city passed as the value' diff --git a/examples/connect_integration/pipeline_dev.py b/examples/connect_integration/pipeline_dev.py new file mode 100644 index 0000000..e317047 --- /dev/null +++ b/examples/connect_integration/pipeline_dev.py @@ -0,0 +1,75 @@ +import asyncio +from pathlib import Path +from typing import Any, override + +from agents import Agent, RPKMCPEndpoint +from agents.agent import AgentHooks +from agents.tools import Tool + + +class MyHooks(AgentHooks): + @override + async def on_start(self, agent: Agent) -> None: + print("Agent started") + + @override + async def on_end(self, agent: Agent, output: Any) -> None: + print("Agent ended") + + @override + async def on_tool_start( + self, + agent: Agent, + tool: Tool, + args: str, + ) -> None: + print(f"Agent calling tool {tool.name} with args: {args}") + + @override + async def on_tool_end( + self, + agent: Agent, + tool: Tool, + result: str, + ) -> None: + print(f"Agent tool {tool.name} resulted in: {result}") + + +my_agent = Agent( + name="ConnectPipelineDevAgent", + model="openai/gpt-4o", + instructions=""" + You are a development agent that helps an engineer create Redpanda Connect pipelines. + Redpanda Connect is a stream processing tool that allows you to move data between different systems. + Redpanda Connect pipelines are defined in a single YAML file usually called `connect.yaml`. + You have access to the developer's project with filesystem access as well as a file to lint pipelines, + which is usually a good idea to use after modifying the `connect.yaml` file. + Additionally, you have access to another agent that has full access to the Redpanda documentation that + can lookup functionality or how the project works in more depth. However, that agent is not specific + for Redpanda Connect so make sure you provide it with context when asking it questions. Please feel free + to ask multiple questions. + + Always write the output to the directory. + + NOTE: You really need to ask the documentation agent for help. Also there is no opportunity to ask the user + for comfirmation. + """.strip().replace("\n", ""), + mcp=[ + RPKMCPEndpoint(directory=Path("mcp")), + ], + hooks=MyHooks(), +) + + +async def main() -> None: + while True: + try: + prompt = input("> ") + except EOFError: + return + response = await my_agent.run(input=prompt) + print(response) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pyproject.toml b/pyproject.toml index fe2e603..d2072bd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,7 +7,13 @@ authors = [ { name = "Tyler Rockwood", email = "rockwood@redpanda.com" } ] requires-python = ">=3.13" -dependencies = [] +dependencies = [ + "litellm>=1.63.14", + "mcp>=1.5.0", + "pydantic>=2.10.6", + "pyright>=1.1.397", + "websockets>=15.0.1", +] license = "Apache-2.0" license-files = ["LICENSE"] @@ -60,7 +66,18 @@ packages = ["src/agents"] [tool.pyright] reportUnusedCallResult = false +reportExplicitAny = false +reportAny = false +reportUnknownParameterType = false [tool.pytest.ini_options] asyncio_mode = "auto" asyncio_default_fixture_loop_scope = "session" +filterwarnings = [ + # https://github.com/BerriAI/litellm/pull/9372 + "ignore:.*ConfigDict.*:pydantic.PydanticDeprecatedSince20", + # An error in litellm caching module + "ignore:::litellm", +] + + diff --git a/src/agents/__init__.py b/src/agents/__init__.py index 6fcfd8c..1be98ca 100644 --- a/src/agents/__init__.py +++ b/src/agents/__init__.py @@ -1,8 +1,14 @@ -def hello() -> str: - """ - Returns a greeting message. +from .agent import Agent, AgentHooks +from .mcp import MCPEndpoint, RPKMCPEndpoint, SSEMCPEndpoint, StdioMCPEndpoint, WebsocketMCPEndpoint +from .tools import Tool - Returns: - A greeting message. - """ - return "Hello from agent!" +__all__ = [ + "Agent", + "AgentHooks", + "Tool", + "MCPEndpoint", + "StdioMCPEndpoint", + "SSEMCPEndpoint", + "WebsocketMCPEndpoint", + "RPKMCPEndpoint", +] diff --git a/src/agents/agent.py b/src/agents/agent.py new file mode 100644 index 0000000..2760fba --- /dev/null +++ b/src/agents/agent.py @@ -0,0 +1,276 @@ +import json +from contextlib import AsyncExitStack +from typing import Any, override + +from litellm import ( + CustomStreamWrapper, + acompletion, # pyright: ignore[reportUnknownVariableType] +) +from litellm.types.utils import ( # pyright: ignore[reportMissingTypeStubs] + ChatCompletionMessageToolCall, + Message, + StreamingChoices, +) +from pydantic import BaseModel + +from .mcp import MCPClient, MCPEndpoint, mcp_client +from .tools import Tool, ToolResponse + + +class AgentHooks: + """ + A class that receives callbacks on various lifecycle events for a specific agent. + """ + + async def on_start( + self, + agent: "Agent", + ) -> None: + """Called before the agent is invoked.""" + _ = agent + + async def on_end( + self, + agent: "Agent", + output: Any, + ) -> None: + """Called when the agent produces a final output.""" + _ = agent, output + + async def on_tool_start( + self, + agent: "Agent", + tool: Tool, + args: str, + ) -> None: + """Called before a tool is invoked.""" + _ = agent, tool, args + + async def on_tool_end( + self, + agent: "Agent", + tool: Tool, + result: str, + ) -> None: + """Called after a tool is invoked.""" + _ = agent, tool, result + + +class Agent: + """ + An agent is a wrapper around a LLM model that can generate responses to input text. + + Attributes: + name: The name of the agent. + model: The LLM model that the agent will use. Models follow the format of + "/" and are loaded using [litellm](https://docs.litellm.ai/docs/providers). + Examples: + "openai/gpt-4o" + "gemini/gemini-pro" + "bedrock/bedrock-claude-v1" + response_format: The Pydantic model that the response will be validated against. + parameters: A dictionary of parameters that the model will use. + These parameters are specific to the model. + Examples: + {"temperature": 0.5} + {"max_tokens": 100} + {"temperature": 0.5, "max_tokens": 100} + tools: The tools exposed to the agent. + mcp: The MCP endpoints that the agent can invoke. + hooks: Callbacks to invoke during various points of the agent runtime. + """ + + name: str + model: str + instructions: str | None + response_format: type[BaseModel] | None + parameters: dict[str, Any] + tools: list[Tool] + mcp: list[MCPEndpoint] + hooks: AgentHooks + + def __init__( + self, + name: str, + model: str, + instructions: str | None = None, + response_type: type[BaseModel] | None = None, + tools: list[Tool] | None = None, + mcp: list[MCPEndpoint] | None = None, + hooks: AgentHooks | None = None, + **kwargs: Any, + ): + """ + Args: + name: The name of the agent. + model: The LLM model that the agent will use. Models follow the format of + "/" and are loaded using [litellm](https://docs.litellm.ai/docs/providers). + Examples: + "openai/gpt-4o" + "gemini/gemini-pro" + "bedrock/bedrock-claude-v1" + instructions: The system prompt for the agent. + response_type: The Pydantic model that the response will be validated against. + If None, the response will be a string. + tools: The tools exposed to the agent. + mcp: The MCP endpoints that the agent can invoke. + hooks: Callbacks to invoke during various points of the agent runtime. + **kwargs: A dictionary of parameters that the model will use. + These parameters are specific to the model. + Examples: + {"temperature": 0.5} + {"max_tokens": 100} + {"temperature": 0.5, "max_tokens": 100} + """ + self.name = name + self.model = model + self.instructions = instructions + self.response_format = response_type + self.parameters = kwargs + self.tools = tools or [] + self.mcp = mcp or [] + self.hooks = hooks or AgentHooks() + + async def run(self, input: str) -> Any: + """ + Generate a response from the model given an input text. + + Args: + input: The input text that the model will use to generate a response. + Returns: + The generated response from the model. + """ + await self.hooks.on_start(self) + async with AsyncExitStack() as stack: + mcp_clients: list[MCPClient] = [] + for server in self.mcp: + mcp_clients.append(await stack.enter_async_context(mcp_client(server))) + + tools = {tool.name: tool for tool in self.tools} + + for client in mcp_clients: + await client.initialize() + for tool in await client.list_tools(): + if tool.name not in tools: + tools[tool.name] = tool + else: + # TODO: Warn on conflicting tools? + pass + + tool_defs = [ + { + "type": "function", + "function": { + "name": tool.name, + "description": tool.description, + "parameters": tool.parameters, + }, + } + for tool in tools.values() + ] + messages: list[dict[str, str] | Message] = [{"role": "user", "content": input}] + if self.instructions: + messages = [{"role": "system", "content": self.instructions}] + messages + while True: + model_resp = await acompletion( + model=self.model, + response_format=self.response_format, + messages=messages, + tools=tool_defs, + **self.parameters, + ) + if isinstance(model_resp, CustomStreamWrapper): + raise Exception("unexpected response type of CustomStreamWrapper") + choice_resp = model_resp.choices[-1] + if isinstance(choice_resp, StreamingChoices): + raise Exception("unexpected streaming response type") + if choice_resp.message.tool_calls: + messages.append(choice_resp.message) + messages.extend(await self._call_tools(choice_resp.message.tool_calls, tools)) + continue + output = choice_resp.message.content + if output is None: + raise Exception("unexpected response type of None") + if self.response_format is not None: + output = self.response_format.model_validate_json(output) + await self.hooks.on_end(self, output) + return output + + async def _call_tools( + self, tool_calls: list[ChatCompletionMessageToolCall], tools: dict[str, Tool] + ) -> list[dict[str, Any]]: + messages: list[dict[str, Any]] = [] + for tool_call in tool_calls: + func = tool_call.function + selected = func.name and tools.get(func.name) + if not selected: + raise Exception(f"tool {func.name} not found") + await self.hooks.on_tool_start(self, selected, func.arguments) + resp = await selected(json.loads(func.arguments)) + if isinstance(resp, ToolResponse): + output: Any = [] + for content in resp.content: + if content.type == "text": + output.append( + { + "type": "text", + "text": content.data, + } + ) + elif content.type == "image": + output.append( + { + "type": "image_url", + "image_url": { + "url": f"data:{content.mime_type};base64,{content.data}", + }, + } + ) + else: + raise NotImplementedError(f"Unknown content type: {content.type}") + if isinstance(resp, BaseModel): + output = resp.model_dump_json() + else: + output = json.dumps(resp) + await self.hooks.on_tool_end( + self, selected, output if isinstance(output, str) else json.dumps(output) + ) + messages.append( + { + "tool_call_id": tool_call.id, + "role": "tool", + "name": selected.name, + "content": output, + } + ) + return messages + + def as_tool(self) -> Tool: + # TODO(rockwood): support handoffs and passing more context + return AgentTool(self) + + +class AgentTool(Tool): + """ + A tool that wraps an agent and allows it to be called another agent. + """ + + agent: Agent + """ + The agent that this tool will call. + """ + + class Input(BaseModel): + input: str + + def __init__(self, agent: Agent): + super().__init__( + name=agent.name, + description=f"An agent called {agent.name} you can pass text to and get a response.", + parameters=AgentTool.Input.model_json_schema(), + ) + self.agent = agent + + @override + async def __call__(self, args: dict[str, Any]) -> Any: + return await self.agent.run(args["input"]) diff --git a/src/agents/mcp.py b/src/agents/mcp.py new file mode 100644 index 0000000..557077d --- /dev/null +++ b/src/agents/mcp.py @@ -0,0 +1,190 @@ +import os +from contextlib import asynccontextmanager +from pathlib import Path +from typing import Any, override + +from mcp import ClientSession, Tool as MCPToolDef +from mcp.client.sse import sse_client +from mcp.client.stdio import StdioServerParameters, stdio_client +from mcp.client.websocket import websocket_client +from mcp.shared.exceptions import McpError + +from .tools import Tool, ToolResponse, ToolResponseImageContent, ToolResponseTextContent + + +class MCPEndpoint: + """ + An Base class for all endpoints (ways to connect) to MCP servers. + """ + + # TODO(rockwood): support list change notifications + _cache_enabled: bool + _cached_tool_list: list[MCPToolDef] | None = None + + def __init__(self, cache_enabled: bool) -> None: + self._cache_enabled = cache_enabled + + +class StdioMCPEndpoint(MCPEndpoint): + """ + A MCP endpoint that invokes a local process and communicates over stdin/stdout. + """ + + params: StdioServerParameters + + def __init__(self, params: StdioServerParameters, cache_enabled: bool = True): + """ + Create a new StdioMCPEndpoint instance. + + Args: + params: The parameters for the server. + cache_enabled: Whether to cache the list of {tools,resources,prompts} from the server. + """ + super().__init__(cache_enabled) + self.params = params + + +class SSEMCPEndpoint(MCPEndpoint): + """ + A MCP endpoint that communicates with an MCP server over Server-Sent Events. + """ + + url: str + + def __init__(self, url: str, cache_enabled: bool = True): + """ + Create a new SSEMCPEndpoint instance. + + Args: + url: The URL of the SSE server. + cache_enabled: Whether to cache the list of {tools,resources,prompts} from the server. + """ + super().__init__(cache_enabled) + self.url = url + + +class WebsocketMCPEndpoint(MCPEndpoint): + """ + A MCP endpoint that communicates with an MCP server over a WebSocket. + """ + + url: str + + def __init__(self, url: str, cache_enabled: bool = True): + """ + Create a new WebsocketMCPEndpoint instance. + + Args: + url: The URL of the WebSocket server. + cache_enabled: Whether to cache the list of {tools,resources,prompts} from the server. + """ + super().__init__(cache_enabled) + self.url = url + + +class RPKMCPEndpoint(StdioMCPEndpoint): + """ + A MCP endpoint that runs a local `rpk connect mcp-server` in a directory + communicating over stdio. + """ + + def __init__(self, directory: Path | str | None, cache_tools: bool = True): + super().__init__( + params=StdioServerParameters( + command="redpanda-connect", + args=["mcp-server", "."], + env={**os.environ}, + cwd=directory, + ), + cache_enabled=cache_tools, + ) + + +# TODO(rockwood): Add support for RedpandaCloudPipelineMCPServer + + +@asynccontextmanager +async def mcp_client(server: MCPEndpoint): + """ + Create a new MCP client for the given server. + """ + if isinstance(server, StdioMCPEndpoint): + async with stdio_client(server.params) as (read, write): + async with ClientSession(read, write) as client: + yield MCPClient(server, client) + elif isinstance(server, SSEMCPEndpoint): + async with sse_client(server.url) as (read, write): + async with ClientSession(read, write) as client: + yield MCPClient(server, client) + elif isinstance(server, WebsocketMCPEndpoint): + async with websocket_client(server.url) as (read, write): + async with ClientSession(read, write) as client: + yield MCPClient(server, client) + else: + raise NotImplementedError(f"Unknown server type: {server}") + + +class MCPClient: + """ + A wrapper around an MCP client session. + """ + + _server: MCPEndpoint + _session: ClientSession + + def __init__(self, server: MCPEndpoint, session: ClientSession): + self._server = server + self._session = session + + async def initialize(self): + await self._session.initialize() + + async def list_tools(self) -> list[Tool]: + if self._server._cache_enabled and self._server._cached_tool_list: + return [MCPTool(self, t) for t in self._server._cached_tool_list] + try: + result = await self._session.list_tools() + except McpError as e: + if e.error.message == "tools not supported": + return [] + raise + tools = result.tools + if self._server._cache_enabled: + self._server._cached_tool_list = tools + return [MCPTool(self, t) for t in tools] + + async def call_tool(self, tool: str, args: dict[str, Any]) -> Any: + result = await self._session.call_tool(tool, args) + if result.isError: + raise Exception(f"error invoking tool {tool}") + # TODO: get this into a better format + resp = ToolResponse() + for content in result.content: + if content.type == "text": + resp.content.append(ToolResponseTextContent(data=content.text)) + elif content.type == "image": + resp.content.append( + ToolResponseImageContent(mime_type=content.mimeType, data=content.data) + ) + else: + raise NotImplementedError(f"Unknown content type: {content.type}") + return resp + + +class MCPTool(Tool): + """ + A wrapper around an MCP server's tool call. + """ + + _client: MCPClient + + def __init__(self, client: MCPClient, tool_def: MCPToolDef): + """ + Create a new MCPTool instance from an MCPClient and one of it's tools. + """ + super().__init__(tool_def.name, tool_def.description, tool_def.inputSchema) + self._client = client + + @override + async def __call__(self, args: dict[str, Any]) -> Any: + return await self._client.call_tool(self.name, args) diff --git a/src/agents/tools.py b/src/agents/tools.py new file mode 100644 index 0000000..feb57df --- /dev/null +++ b/src/agents/tools.py @@ -0,0 +1,79 @@ +from typing import Any, Literal + +from pydantic import BaseModel + + +class Tool: + """ + A tool is a function that can be called by an LLM with a set of parameters. + """ + + name: str + """ + The name of the tool. + """ + description: str | None + """ + An optional description of the tool. + """ + parameters: dict[str, Any] + """ + A dictionary of parameters (json_schema) that the tool requires. + """ + + def __init__(self, name: str, description: str | None, parameters: dict[str, Any]): + """ + Initialize a new tool. + """ + self.name = name + self.description = description + self.parameters = parameters + + async def __call__(self, args: dict[str, Any]) -> Any: + """ + Call the tool with the given arguments (should match the provided schema). + + The return result can be: + - Pydantic model, which will be serialized to JSON and passed back to the model as text. + - string, which will be passed back to the model as text. + - ToolResponse, which allows for more structured content to be passed back to the model. + - Anything else will be serialized using `json.dumps` and passed back to the model as text. + """ + raise NotImplementedError() + + +class ToolResponseTextContent(BaseModel): + """ + Content when the tool responds with text. + """ + + type: Literal["text"] = "text" + data: str + """ + The text content. + """ + + +class ToolResponseImageContent(BaseModel): + """ + Content when the tool responds with an image. + """ + + type: Literal["image"] = "image" + data: str + """ + The base64 encoded image data. + """ + mime_type: str + """ + The mime type of the image. + """ + + +class ToolResponse(BaseModel): + """ + A special responce type from a tool that allows passing back more structured + content to the Agent, such as images or multiple contents at once. + """ + + content: list[ToolResponseTextContent | ToolResponseImageContent] = [] diff --git a/tests/test_agents.py b/tests/test_agents.py index 22187ec..be42a86 100644 --- a/tests/test_agents.py +++ b/tests/test_agents.py @@ -1,8 +1,25 @@ +import os + import pytest +from pydantic import BaseModel import agents +class MyModel(BaseModel): + color: str + + +@pytest.mark.skipif( + "OPENAI_API_KEY" not in os.environ, reason="Yo dog someone has to pay for those tokens" +) @pytest.mark.asyncio -async def test_hello(): - assert agents.hello() == "Hello from agent!" +async def test_llm_prompt(): + my_agent = agents.Agent( + name="GPT Agent", + model="openai/gpt-4o", + response_type=MyModel, + max_tokens=10, + ) + resp = await my_agent.run(input="In one word what color is the sky?") + assert resp.color in ["blue", "azure"], f"expected color to be blue or azure, got: {resp.color}" diff --git a/uv.lock b/uv.lock index 9441298..bf9522b 100644 --- a/uv.lock +++ b/uv.lock @@ -2,6 +2,91 @@ version = 1 revision = 1 requires-python = ">=3.13" +[[package]] +name = "aiohappyeyeballs" +version = "2.6.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = 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