feat(rnd): Add IPC support on autogpt_server (#7212)

### Background

This PR adds support on IPC on autogpt_server.
To make this happen, there are a couple of refactoring efforts being made (will be described in the `Changes` section).
Currently, there are three independent processes:

```
AgentServer ----> ExecutionManager
    | 
     --> ExecutionScheduler
```


### Changes 🏗️

* Added Pyro5 for IPC support.
* Introduced `AppService`: a class to construct an independent process that can expose a method to other running processes (this is analogous to a microservice).
* Introduced `AppProcess`: used by `AppService` a class for creating a child process that can be executed in the background.
* Adapting existing codebase to user `AppService`.

rnd/autogpt_server/autogpt_server/app.py

@@ -1,27 +1,34 @@
-from multiprocessing import freeze_support
-from multiprocessing.spawn import freeze_support as freeze_support_spawn
-
-from autogpt_server.data.execution import ExecutionQueue
-from autogpt_server.executor import start_executor_manager
-from autogpt_server.server import start_server
+from autogpt_server.executor import ExecutionManager, ExecutionScheduler
+from autogpt_server.server import AgentServer
+from autogpt_server.util.process import AppProcess
+from autogpt_server.util.service import PyroNameServer
 
 
-def background_process() -> None:
+def run_processes(processes: list[AppProcess], **kwargs):
     """
-    Used by the cli to run the server and executor in the background.
-    This function runs the server and starts the executor in the background.
+    Execute all processes in the app. The last process is run in the foreground.
     """
-    # These directives are required to make multiprocessing work with cx_Freeze
-    # and are both required and safe across platforms (Windows, macOS, Linux)
-    # They must be placed at the beginning of the executions before any other
-    # multiprocessing code is run
-    freeze_support()
-    freeze_support_spawn()
-    # Start the application
-    queue = ExecutionQueue()
-    start_executor_manager(5, queue)
-    start_server(queue)
+    try:
+        for process in processes[:-1]:
+            process.start(background=True, **kwargs)
+        processes[-1].start(background=False, **kwargs)
+    except Exception as e:
+        for process in processes:
+            process.stop()
+        raise e
+
+
+def main(**kwargs):
+    run_processes(
+        [
+            PyroNameServer(),
+            ExecutionScheduler(),
+            ExecutionManager(pool_size=5),
+            AgentServer(),
+        ],
+        **kwargs
+    )
 
 
 if __name__ == "__main__":
-    background_process()
+    main()

rnd/autogpt_server/autogpt_server/cli.py

@@ -2,25 +2,53 @@
 The command line interface for the agent server
 """
 
-from multiprocessing import freeze_support
-from multiprocessing.spawn import freeze_support as freeze_support_spawn
+import os
+import pathlib
 
 import click
+import psutil
+
+from autogpt_server import app
+from autogpt_server.util.process import AppProcess
+
+
+def get_pid_path() -> pathlib.Path:
+    home_dir = pathlib.Path.home()
+    new_dir = home_dir / ".config" / "agpt"
+    file_path = new_dir / "running.tmp"
+    return file_path
+
+
+def get_pid() -> int | None:
+    file_path = get_pid_path()
+    if not file_path.exists():
+        return None
+
+    os.makedirs(file_path.parent, exist_ok=True)
+    with open(file_path, "r", encoding="utf-8") as file:
+        pid = file.read()
+    try:
+        return int(pid)
+    except ValueError:
+        return None
+
+
+def write_pid(pid: int):
+    file_path = get_pid_path()
+    os.makedirs(file_path.parent, exist_ok=True)
+    with open(file_path, "w", encoding="utf-8") as file:
+        file.write(str(pid))
+
+
+class MainApp(AppProcess):
+    def run(self):
+        app.main(silent=True)
 
 
 @click.group()
 def main():
     """AutoGPT Server CLI Tool"""
-
-
-@main.command()
-def background() -> None:
-    """
-    Command to run the server in the background. Used by the run command
-    """
-    from autogpt_server.app import background_process
-
-    background_process()
+    pass
 
 
 @main.command()
@@ -28,37 +56,22 @@ def start():
     """
     Starts the server in the background and saves the PID
     """
-    import os
-    import pathlib
-    import subprocess
-    import psutil
-
     # Define the path for the new directory and file
-    home_dir = pathlib.Path.home()
-    new_dir = home_dir / ".config" / "agpt"
-    file_path = new_dir / "running.tmp"
+    pid = get_pid()
+    if pid and psutil.pid_exists(pid):
+        print("Server is already running")
+        exit(1)
+    elif pid:
+        print("PID does not exist deleting file")
+        os.remove(get_pid_path())
 
-    # Create the directory if it does not exist
-    os.makedirs(new_dir, exist_ok=True)
-    if file_path.exists():
-        with open(file_path, "r", encoding="utf-8") as file:
-            pid = int(file.read())
-            if psutil.pid_exists(pid):
-                print("Server is already running")
-                exit(1)
-            else:
-                print("PID does not exist deleting file")
-                os.remove(file_path)
+    print("Starting server")
+    pid = MainApp().start(background=True, silent=True)
+    print(f"Server running in process: {pid}")
 
-    sp = subprocess.Popen(
-        ["poetry", "run", "python", "autogpt_server/cli.py", "background"],
-        stdout=subprocess.DEVNULL,  # Redirect standard output to devnull
-        stderr=subprocess.DEVNULL,  # Redirect standard error to devnull
-    )
-    print(f"Server running in process: {sp.pid}")
-
-    with open(file_path, "w", encoding="utf-8") as file:
-        file.write(str(sp.pid))
+    write_pid(pid)
+    print("done")
+    os._exit(status=0)
 
 
 @main.command()
@@ -66,22 +79,17 @@ def stop():
     """
     Stops the server
     """
-    import os
-    import pathlib
-    import subprocess
-
-    home_dir = pathlib.Path.home()
-    new_dir = home_dir / ".config" / "agpt"
-    file_path = new_dir / "running.tmp"
-    if not file_path.exists():
+    pid = get_pid()
+    if not pid:
         print("Server is not running")
         return
 
-    with open(file_path, "r", encoding="utf-8") as file:
-        pid = file.read()
-    os.remove(file_path)
+    os.remove(get_pid_path())
+    process = psutil.Process(int(pid))
+    for child in process.children(recursive=True):
+        child.terminate()
+    process.terminate()
 
-    subprocess.Popen(["kill", pid])
     print("Server Stopped")
 
 
@@ -90,6 +98,7 @@ def test():
     """
     Group for test commands
     """
+    pass
 
 
 @test.command()
@@ -100,17 +109,5 @@ def event():
     print("Event sent")
 
 
-main.add_command(test)
-
-
-def start_cli() -> None:
-    """
-    Entry point into the cli
-    """
-    freeze_support()
-    freeze_support_spawn()
-    main()
-
-
 if __name__ == "__main__":
-    start_cli()
+    main()

rnd/autogpt_server/autogpt_server/data/block.py

@@ -2,9 +2,10 @@ import json
 import jsonschema
 
 from abc import ABC, abstractmethod
+from typing import Any, ClassVar
+
 from prisma.models import AgentBlock
 from pydantic import BaseModel
-from typing import Any, ClassVar
 
 BlockData = dict[str, Any]
 
@@ -49,7 +50,7 @@ class BlockSchema(BaseModel):
             self,
             properties: dict[str, str | dict],
             required: list[str] | None = None,
-            **kwargs: Any
+            **kwargs: Any,
     ):
         schema = {
             "type": "object",
@@ -125,7 +126,7 @@ class Block(ABC, BaseModel):
         pass
 
     @abstractmethod
-    async def run(self, input_data: BlockData) -> tuple[str, Any]:
+    def run(self, input_data: BlockData) -> tuple[str, Any]:
         """
         Run the block with the given input data.
         Args:
@@ -140,13 +141,21 @@ class Block(ABC, BaseModel):
     def name(cls):
         return cls.__name__
 
-    async def execute(self, input_data: BlockData) -> tuple[str, Any]:
+    def to_dict(self):
+        return {
+            "id": self.id,
+            "name": self.name,
+            "inputSchema": self.input_schema.jsonschema,
+            "outputSchema": self.output_schema.jsonschema,
+        }
+
+    def execute(self, input_data: BlockData) -> tuple[str, Any]:
         if error := self.input_schema.validate_data(input_data):
             raise ValueError(
                 f"Unable to execute block with invalid input data: {error}"
             )
 
-        output_name, output_data = await self.run(input_data)
+        output_name, output_data = self.run(input_data)
 
         if error := self.output_schema.validate_field(output_name, output_data):
             raise ValueError(
@@ -161,29 +170,37 @@ class Block(ABC, BaseModel):
 
 class ParrotBlock(Block):
     id: ClassVar[str] = "1ff065e9-88e8-4358-9d82-8dc91f622ba9"  # type: ignore
-    input_schema: ClassVar[BlockSchema] = BlockSchema({  # type: ignore
-        "input": "string",
-    })
-    output_schema: ClassVar[BlockSchema] = BlockSchema({  # type: ignore
-        "output": "string",
-    })
+    input_schema: ClassVar[BlockSchema] = BlockSchema(  # type: ignore
+        {
+            "input": "string",
+        }
+    )
+    output_schema: ClassVar[BlockSchema] = BlockSchema(  # type: ignore
+        {
+            "output": "string",
+        }
+    )
 
-    async def run(self, input_data: BlockData) -> tuple[str, Any]:
+    def run(self, input_data: BlockData) -> tuple[str, Any]:
         return "output", input_data["input"]
 
 
 class TextCombinerBlock(Block):
     id: ClassVar[str] = "db7d8f02-2f44-4c55-ab7a-eae0941f0c30"  # type: ignore
-    input_schema: ClassVar[BlockSchema] = BlockSchema({  # type: ignore
-        "text1": "string",
-        "text2": "string",
-        "format": "string",
-    })
-    output_schema: ClassVar[BlockSchema] = BlockSchema({  # type: ignore
-        "combined_text": "string",
-    })
+    input_schema: ClassVar[BlockSchema] = BlockSchema(  # type: ignore
+        {
+            "text1": "string",
+            "text2": "string",
+            "format": "string",
+        }
+    )
+    output_schema: ClassVar[BlockSchema] = BlockSchema(  # type: ignore
+        {
+            "combined_text": "string",
+        }
+    )
 
-    async def run(self, input_data: BlockData) -> tuple[str, Any]:
+    def run(self, input_data: BlockData) -> tuple[str, Any]:
         return "combined_text", input_data["format"].format(
             text1=input_data["text1"],
             text2=input_data["text2"],
@@ -192,15 +209,18 @@ class TextCombinerBlock(Block):
 
 class PrintingBlock(Block):
     id: ClassVar[str] = "f3b1c1b2-4c4f-4f0d-8d2f-4c4f0d8d2f4c"  # type: ignore
-    input_schema: ClassVar[BlockSchema] = BlockSchema({  # type: ignore
-        "text": "string",
-    })
-    output_schema: ClassVar[BlockSchema] = BlockSchema({  # type: ignore
-        "status": "string",
-    })
+    input_schema: ClassVar[BlockSchema] = BlockSchema(  # type: ignore
+        {
+            "text": "string",
+        }
+    )
+    output_schema: ClassVar[BlockSchema] = BlockSchema(  # type: ignore
+        {
+            "status": "string",
+        }
+    )
 
-    async def run(self, input_data: BlockData) -> tuple[str, Any]:
-        print(input_data["text"])
+    def run(self, input_data: BlockData) -> tuple[str, Any]:
         return "status", "printed"
 
 
@@ -215,10 +235,7 @@ async def initialize_blocks() -> None:
     AVAILABLE_BLOCKS = {block.id: block() for block in Block.__subclasses__()}
 
     for block in AVAILABLE_BLOCKS.values():
-        existing_block = await AgentBlock.prisma().find_unique(
-            where={"id": block.id}
-        )
-        if existing_block:
+        if await AgentBlock.prisma().find_unique(where={"id": block.id}):
             continue
 
         await AgentBlock.prisma().create(
@@ -231,7 +248,13 @@ async def initialize_blocks() -> None:
         )
 
 
-async def get_block(block_id: str) -> Block:
+async def get_blocks() -> list[Block]:
     if not AVAILABLE_BLOCKS:
         await initialize_blocks()
-    return AVAILABLE_BLOCKS[block_id]
+    return list(AVAILABLE_BLOCKS.values())
+
+
+async def get_block(block_id: str) -> Block | None:
+    if not AVAILABLE_BLOCKS:
+        await initialize_blocks()
+    return AVAILABLE_BLOCKS.get(block_id)

rnd/autogpt_server/autogpt_server/data/db.py

@@ -1,4 +1,3 @@
-import asyncio
 from uuid import uuid4
 from prisma import Prisma
 from pydantic import BaseModel
@@ -6,16 +5,14 @@ from pydantic import BaseModel
 prisma = Prisma(auto_register=True)
 
 
-def connect_sync():
-    asyncio.get_event_loop().run_until_complete(connect())
-
-
 async def connect():
-    await prisma.connect()
+    if not prisma.is_connected():
+        await prisma.connect()
 
 
 async def disconnect():
-    await prisma.disconnect()
+    if prisma.is_connected():
+        await prisma.disconnect()
 
 
 class BaseDbModel(BaseModel):

rnd/autogpt_server/autogpt_server/data/execution.py

@@ -2,15 +2,16 @@ import json
 from datetime import datetime
 from enum import Enum
 from multiprocessing import Queue
+from typing import Any
 
 from prisma.models import AgentNodeExecution
-from typing import Any
 
 from autogpt_server.data.db import BaseDbModel
 
 
 class Execution(BaseDbModel):
     """Data model for an execution of an Agent"""
+
     run_id: str
     node_id: str
     data: dict[str, Any]
@@ -23,11 +24,6 @@ class ExecutionStatus(str, Enum):
     FAILED = "FAILED"
 
 
-# TODO: This shared class make api & executor coupled in one machine.
-# Replace this with a persistent & remote-hosted queue.
-# One very likely candidate would be persisted Redis (Redis Queue).
-# It will also open the possibility of using it for other purposes like
-# caching, execution engine broker (like Celery), user session management etc.
 class ExecutionQueue:
     """
     Queue for managing the execution of agents.
@@ -48,7 +44,38 @@ class ExecutionQueue:
         return self.queue.empty()
 
 
-async def add_execution(execution: Execution, queue: ExecutionQueue) -> Execution:
+class ExecutionResult(BaseDbModel):
+    run_id: str
+    execution_id: str
+    node_id: str
+    status: ExecutionStatus
+    input_data: dict[str, Any]
+    output_name: str
+    output_data: Any
+    creation_time: datetime
+    start_time: datetime | None
+    end_time: datetime | None
+
+    @staticmethod
+    def from_db(execution: AgentNodeExecution):
+        return ExecutionResult(
+            run_id=execution.executionId,
+            node_id=execution.agentNodeId,
+            execution_id=execution.id,
+            status=ExecutionStatus(execution.executionStatus),
+            input_data=json.loads(execution.inputData or "{}"),
+            output_name=execution.outputName or "",
+            output_data=json.loads(execution.outputData or "{}"),
+            creation_time=execution.creationTime,
+            start_time=execution.startTime,
+            end_time=execution.endTime,
+        )
+
+
+# --------------------- Model functions --------------------- #
+
+
+async def enqueue_execution(execution: Execution) -> None:
     await AgentNodeExecution.prisma().create(
         data={
             "id": execution.id,
@@ -59,7 +86,6 @@ async def add_execution(execution: Execution, queue: ExecutionQueue) -> Executio
             "creationTime": datetime.now(),
         }
     )
-    return queue.add(execution)
 
 
 async def start_execution(exec_id: str) -> None:
@@ -96,3 +122,12 @@ async def fail_execution(exec_id: str, error: Exception) -> None:
             "endTime": datetime.now(),
         },
     )
+
+
+async def get_executions(run_id: str) -> list[ExecutionResult]:
+    executions = await AgentNodeExecution.prisma().find_many(
+        where={"executionId": run_id},
+        order={"startTime": "asc"},
+    )
+    res = [ExecutionResult.from_db(execution) for execution in executions]
+    return res

rnd/autogpt_server/autogpt_server/data/graph.py

@@ -1,11 +1,11 @@
 import asyncio
 import json
 import uuid
-from typing import Any
 
-from prisma.models import AgentGraph, AgentNode, AgentNodeLink, AgentNodeExecution
+from typing import Any
+from prisma.models import AgentGraph, AgentNode, AgentNodeExecution, AgentNodeLink
+
 from autogpt_server.data.db import BaseDbModel
-from autogpt_server.data.block import get_block
 
 
 class Node(BaseDbModel):
@@ -33,10 +33,6 @@ class Node(BaseDbModel):
         self.output_nodes[source_name] = node.id
         node.input_nodes[sink_name] = self.id
 
-    @property
-    async def block(self):
-        return await get_block(self.block_id)
-
 
 class Graph(BaseDbModel):
     name: str
@@ -64,6 +60,9 @@ EXECUTION_NODE_INCLUDE = {
 }
 
 
+# --------------------- Model functions --------------------- #
+
+
 async def get_node(node_id: str) -> Node | None:
     node = await AgentNode.prisma().find_unique_or_raise(
         where={"id": node_id},
@@ -72,6 +71,10 @@ async def get_node(node_id: str) -> Node | None:
     return Node.from_db(node) if node else None
 
 
+async def get_graph_ids() -> list[str]:
+    return [graph.id for graph in await AgentGraph.prisma().find_many()]  # type: ignore
+
+
 async def get_graph(graph_id: str) -> Graph | None:
     graph = await AgentGraph.prisma().find_unique(
         where={"id": graph_id},
@@ -89,7 +92,7 @@ async def get_node_input(node: Node, exec_id: str) -> dict[str, Any]:
     Returns:
         dictionary of input data, key is the input name, value is the input data.
     """
-    query = AgentNodeExecution.prisma().find_many(
+    query = await AgentNodeExecution.prisma().find_many(
         where={  # type: ignore
             "executionId": exec_id,
             "agentNodeId": {"in": list(node.input_nodes.values())},
@@ -100,7 +103,7 @@ async def get_node_input(node: Node, exec_id: str) -> dict[str, Any]:
     )
 
     latest_executions: dict[str, AgentNodeExecution] = {
-        execution.agentNodeId: execution for execution in await query
+        execution.agentNodeId: execution for execution in query
     }
 
     return {
@@ -114,6 +117,7 @@ async def get_node_input(node: Node, exec_id: str) -> dict[str, Any]:
 
 
 async def create_graph(graph: Graph) -> Graph:
+
     await AgentGraph.prisma().create(
         data={
             "id": graph.id,
@@ -123,19 +127,14 @@ async def create_graph(graph: Graph) -> Graph:
     )
 
     # TODO: replace bulk creation using create_many
-    await asyncio.gather(
-        *[
-            AgentNode.prisma().create(
-                {
-                    "id": node.id,
-                    "agentBlockId": node.block_id,
-                    "agentGraphId": graph.id,
-                    "constantInput": json.dumps(node.input_default),
-                }
-            )
-            for node in graph.nodes
-        ]
-    )
+    await asyncio.gather(*[
+        AgentNode.prisma().create({
+            "id": node.id,
+            "agentBlockId": node.block_id,
+            "agentGraphId": graph.id,
+            "constantInput": json.dumps(node.input_default),
+        }) for node in graph.nodes
+    ])
 
     edge_source_names = {
         (source_node.id, sink_node_id): output_name
@@ -149,22 +148,16 @@ async def create_graph(graph: Graph) -> Graph:
     }
 
     # TODO: replace bulk creation using create_many
-    await asyncio.gather(
-        *[
-            AgentNodeLink.prisma().create(
-                {
-                    "id": str(uuid.uuid4()),
-                    "sourceName": edge_source_names.get((input_node, output_node), ""),
-                    "sinkName": edge_sink_names.get((input_node, output_node), ""),
-                    "agentNodeSourceId": input_node,
-                    "agentNodeSinkId": output_node,
-                }
-            )
-            for input_node, output_node in (
-                    edge_source_names.keys() | edge_sink_names.keys()
-            )
-        ]
-    )
+    await asyncio.gather(*[
+        AgentNodeLink.prisma().create({
+            "id": str(uuid.uuid4()),
+            "sourceName": edge_source_names.get((input_node, output_node), ""),
+            "sinkName": edge_sink_names.get((input_node, output_node), ""),
+            "agentNodeSourceId": input_node,
+            "agentNodeSinkId": output_node,
+        })
+        for input_node, output_node in edge_source_names.keys() | edge_sink_names.keys()
+    ])
 
     if created_graph := await get_graph(graph.id):
         return created_graph

rnd/autogpt_server/autogpt_server/executor/__init__.py

@@ -1 +1,8 @@
-from .executor import start_executor_manager  # type: ignore # noqa
+from .manager import ExecutionManager
+from .scheduler import ExecutionScheduler
+
+__all__ = [
+    "ExecutionManager",
+    "ExecutionScheduler",
+]
+

rnd/autogpt_server/autogpt_server/executor/executor.py

@@ -1,138 +0,0 @@
-import asyncio
-import logging
-from concurrent.futures import ProcessPoolExecutor
-from multiprocessing import Process
-from typing import Optional
-
-from autogpt_server.data import block, db, graph
-from autogpt_server.data.execution import (
-    Execution,
-    ExecutionQueue,
-    add_execution,
-    complete_execution,
-    fail_execution,
-    start_execution,
-)
-
-logger = logging.getLogger(__name__)
-
-
-def get_log_prefix(run_id: str, exec_id: str, block_name: str = "-"):
-    return f"[Execution graph-{run_id}|node-{exec_id}|{block_name}]"
-
-
-async def execute_node(data: Execution) -> Execution | None:
-    """
-    Execute a node in the graph. This will trigger a block execution on a node,
-    persist the execution result, and return the subsequent node to be executed.
-
-    Args:
-        data: The execution data for executing the current node.
-
-    Returns:
-        The subsequent node to be enqueued, or None if there is no subsequent node.
-    """
-    run_id = data.run_id
-    exec_id = data.id
-    exec_data = data.data
-    node_id = data.node_id
-
-    node = await graph.get_node(node_id)
-    if not node:
-        logger.error(f"Node {node_id} not found.")
-        return None
-
-    node_block = await block.get_block(node.block_id)
-    if not node_block:
-        logger.error(f"Block {node.block_id} not found.")
-        return None
-
-    # Execute the node
-    prefix = get_log_prefix(run_id, exec_id, node_block.name)
-    logger.warning(f"{prefix} execute with input:\n{exec_data}")
-    await start_execution(exec_id)
-
-    try:
-        output_name, output_data = await node_block.execute(exec_data)
-        logger.warning(f"{prefix} executed with output: `{output_name}`:{output_data}")
-        await complete_execution(exec_id, (output_name, output_data))
-    except Exception as e:
-        logger.exception(f"{prefix} failed with error: %s", e)
-        await fail_execution(exec_id, e)
-        raise e
-
-    # Try to enqueue next eligible nodes
-    if output_name not in node.output_nodes:
-        logger.error(f"{prefix} output name `{output_name}` has no subsequent node.")
-        return None
-
-    next_node_id = node.output_nodes[output_name]
-    next_node = await graph.get_node(next_node_id)
-    if not next_node:
-        logger.error(f"{prefix} Error, next node {next_node_id} not found.")
-        return None
-
-    next_node_input = await graph.get_node_input(next_node, run_id)
-    next_node_block = await next_node.block
-
-    if not set(next_node.input_nodes).issubset(next_node_input):
-        logger.warning(f"{prefix} Skipped {next_node_id}-{next_node_block.name}, "
-                       f"missing: {set(next_node.input_nodes) - set(next_node_input)}")
-        return None
-
-    if error := next_node_block.input_schema.validate_data(next_node_input):
-        logger.warning(
-            f"{prefix} Skipped {next_node_id}-{next_node_block.name}, {error}")
-        return None
-
-    logger.warning(f"{prefix} Enqueue next node {next_node_id}-{next_node_block.name}")
-    return Execution(
-        run_id=run_id, node_id=next_node_id, data=next_node_input
-    )
-
-
-def execute_node_sync(data: Execution) -> Optional[Execution | None]:
-    """
-    A synchronous version of `execute_node`, to be used in the ProcessPoolExecutor.
-    """
-    prefix = get_log_prefix(data.run_id, data.id)
-    try:
-        logger.warning(f"{prefix} Start execution")
-        loop = asyncio.get_event_loop()
-        return loop.run_until_complete(execute_node(data))
-    except Exception as e:
-        logger.error(f"{prefix} Error: {e}")
-
-
-def start_executor(pool_size: int, queue: ExecutionQueue) -> None:
-    loop = asyncio.get_event_loop()
-    loop.run_until_complete(db.connect())
-    loop.run_until_complete(block.initialize_blocks())
-
-    def on_complete_execution(f: asyncio.Future[Execution | None]):
-        exception = f.exception()
-        if exception:
-            logger.exception("Error during execution!! %s", exception)
-            return exception
-
-        execution = f.result()
-        if execution:
-            loop.run_until_complete(add_execution(execution, queue))
-            return exception
-
-        return None
-
-    logger.warning("Executor started!")
-
-    with ProcessPoolExecutor(
-            max_workers=pool_size,
-            initializer=db.connect_sync,
-    ) as executor:
-        while True:
-            future = executor.submit(execute_node_sync, queue.get())
-            future.add_done_callback(on_complete_execution)  # type: ignore
-
-
-def start_executor_manager(pool_size: int, queue: ExecutionQueue) -> None:
-    executor_process = Process(target=start_executor, args=(pool_size, queue))
-    executor_process.start()

rnd/autogpt_server/autogpt_server/executor/manager.py

@@ -0,0 +1,168 @@
+import asyncio
+import logging
+
+from concurrent.futures import ProcessPoolExecutor
+from typing import Optional, Any
+
+from autogpt_server.data import db
+from autogpt_server.data.block import Block, get_block
+from autogpt_server.data.graph import Node, get_node, get_node_input
+from autogpt_server.data.execution import (
+    Execution,
+    ExecutionQueue,
+    enqueue_execution,
+    complete_execution,
+    fail_execution,
+    start_execution,
+)
+from autogpt_server.util.service import AppService, expose
+
+logger = logging.getLogger(__name__)
+
+
+def get_log_prefix(run_id: str, exec_id: str, block_name: str = "-"):
+    return f"[Execution graph-{run_id}|node-{exec_id}|{block_name}]"
+
+
+def execute_node(loop: asyncio.AbstractEventLoop, data: Execution) -> Execution | None:
+    """
+    Execute a node in the graph. This will trigger a block execution on a node,
+    persist the execution result, and return the subsequent node to be executed.
+
+    Args:
+        loop: The event loop to run the async functions.
+        data: The execution data for executing the current node.
+
+    Returns:
+        The subsequent node to be enqueued, or None if there is no subsequent node.
+    """
+    run_id = data.run_id
+    exec_id = data.id
+    exec_data = data.data
+    node_id = data.node_id
+
+    asyncio.set_event_loop(loop)
+    wait = lambda f: loop.run_until_complete(f)
+
+    node: Optional[Node] = wait(get_node(node_id))
+    if not node:
+        logger.error(f"Node {node_id} not found.")
+        return None
+
+    node_block: Optional[Block] = wait(get_block(node.block_id))
+    if not node_block:
+        logger.error(f"Block {node.block_id} not found.")
+        return None
+
+    # Execute the node
+    prefix = get_log_prefix(run_id, exec_id, node_block.name)
+    logger.warning(f"{prefix} execute with input:\n`{exec_data}`")
+    wait(start_execution(exec_id))
+
+    try:
+        output_name, output_data = node_block.execute(exec_data)
+        logger.warning(f"{prefix} executed with output [{output_name}]:`{output_data}`")
+        wait(complete_execution(exec_id, (output_name, output_data)))
+    except Exception as e:
+        logger.exception(f"{prefix} failed with error: %s", e)
+        wait(fail_execution(exec_id, e))
+        raise e
+
+    # Try to enqueue next eligible nodes
+    if output_name not in node.output_nodes:
+        logger.error(f"{prefix} Output [{output_name}] has no subsequent node.")
+        return None
+
+    next_node_id = node.output_nodes[output_name]
+    next_node: Optional[Node] = wait(get_node(next_node_id))
+    if not next_node:
+        logger.error(f"{prefix} Error, next node {next_node_id} not found.")
+        return None
+
+    next_node_input: dict[str, Any] = wait(get_node_input(next_node, run_id))
+    next_node_block: Block | None = wait(get_block(next_node.block_id))
+    if not next_node_block:
+        logger.error(f"{prefix} Error, next block {next_node.block_id} not found.")
+        return None
+
+    if not set(next_node.input_nodes).issubset(next_node_input):
+        logger.warning(
+            f"{prefix} Skipped {next_node_id}-{next_node_block.name}, "
+            f"missing: {set(next_node.input_nodes) - set(next_node_input)}"
+        )
+        return None
+
+    if error := next_node_block.input_schema.validate_data(next_node_input):
+        logger.warning(
+            f"{prefix} Skipped {next_node_id}-{next_node_block.name}, {error}"
+        )
+        return None
+
+    logger.warning(f"{prefix} Enqueue next node {next_node_id}-{next_node_block.name}")
+    return Execution(run_id=run_id, node_id=next_node_id, data=next_node_input)
+
+
+class Executor:
+    loop: asyncio.AbstractEventLoop
+
+    @classmethod
+    def on_executor_start(cls):
+        cls.loop = asyncio.new_event_loop()
+        cls.loop.run_until_complete(db.connect())
+
+    @classmethod
+    def on_start_execution(cls, data: Execution) -> Optional[Execution | None]:
+        """
+        A synchronous version of `execute_node`, to be used in the ProcessPoolExecutor.
+        """
+        prefix = get_log_prefix(data.run_id, data.id)
+        try:
+            logger.warning(f"{prefix} Start execution")
+            return execute_node(cls.loop, data)
+        except Exception as e:
+            logger.error(f"{prefix} Error: {e}")
+
+
+class ExecutionManager(AppService):
+
+    def __init__(self, pool_size: int):
+        self.pool_size = pool_size
+        self.queue = ExecutionQueue()
+
+    def run_service(self):
+        def on_complete_execution(f: asyncio.Future[Execution | None]):
+            exception = f.exception()
+            if exception:
+                logger.exception("Error during execution!! %s", exception)
+                return exception
+
+            execution = f.result()
+            if execution:
+                return self.__add_execution(execution)
+
+            return None
+
+        with ProcessPoolExecutor(
+                max_workers=self.pool_size,
+                initializer=Executor.on_executor_start,
+        ) as executor:
+            logger.warning(f"Execution manager started with {self.pool_size} workers.")
+            while True:
+                future = executor.submit(
+                    Executor.on_start_execution,
+                    self.queue.get()
+                )
+                future.add_done_callback(on_complete_execution)  # type: ignore
+
+    @expose
+    def add_execution(self, run_id: str, node_id: str, data: dict[str, Any]) -> str:
+        try:
+            execution = Execution(run_id=run_id, node_id=node_id, data=data)
+            self.__add_execution(execution)
+            return execution.id
+        except Exception as e:
+            raise Exception("Error adding execution ", e)
+
+    def __add_execution(self, execution: Execution) -> Execution:
+        self.run_and_wait(enqueue_execution(execution))
+        return self.queue.add(execution)

rnd/autogpt_server/autogpt_server/executor/scheduler.py

@@ -0,0 +1,23 @@
+import time
+
+from autogpt_server.util.service import AppService, expose
+
+
+class ExecutionScheduler(AppService):
+
+    def run_service(self):
+        while True:
+            time.sleep(1)  # This will be replaced with apscheduler executor.
+
+    @expose
+    def add_execution_schedule(self, agent_id: str, cron: str, input_data: dict) -> str:
+        print(
+            f"Adding execution schedule for agent {agent_id} with cron {cron} and "
+            f"input data {input_data}"
+        )
+        return "dummy_schedule_id"
+
+    @expose
+    def get_execution_schedules(self, agent_id: str) -> list[dict]:
+        print(f"Getting execution schedules for agent {agent_id}")
+        return [{"cron": "dummy_cron", "input_data": {"dummy_input": "dummy_value"}}]

rnd/autogpt_server/autogpt_server/server/__init__.py

@@ -1 +1,3 @@
-from .server import start_server  # type: ignore # noqa
+from .server import AgentServer
+
+__all__ = ["AgentServer"]

rnd/autogpt_server/autogpt_server/server/server.py

@@ -1,25 +1,25 @@
-import asyncio
-from contextlib import asynccontextmanager
-
 import uuid
-
 import uvicorn
+
+from contextlib import asynccontextmanager
 from fastapi import APIRouter, FastAPI, HTTPException
 
-from autogpt_server.data import db, execution, graph
+from autogpt_server.data import db, execution, graph, block
+from autogpt_server.executor import ExecutionManager, ExecutionScheduler
+from autogpt_server.util.process import AppProcess
+from autogpt_server.util.service import get_service_client
 
 
-class AgentServer:
+class AgentServer(AppProcess):
 
-    def __init__(self, queue: execution.ExecutionQueue):
+    @asynccontextmanager
+    async def lifespan(self, _: FastAPI):
+        await db.connect()
+        yield
+        await db.disconnect()
 
-        @asynccontextmanager
-        async def lifespan(app: FastAPI):
-            await db.connect()
-            yield
-            await db.disconnect()
-
-        self.app = FastAPI(
+    def run(self):
+        app = FastAPI(
             title="AutoGPT Agent Server",
             description=(
                 "This server is used to execute agents that are created by the "
@@ -27,46 +27,139 @@ class AgentServer:
             ),
             summary="AutoGPT Agent Server",
             version="0.1",
-            lifespan=lifespan,
+            lifespan=self.lifespan,
         )
-        self.execution_queue = queue
 
         # Define the API routes
-        self.router = APIRouter()
-        self.router.add_api_route(
-            path="/agents/{agent_id}/execute",
-            endpoint=self.execute_agent,
+        router = APIRouter()
+        router.add_api_route(
+            path="/blocks",
+            endpoint=AgentServer.get_agent_blocks,
+            methods=["GET"],
+        )
+        router.add_api_route(
+            path="/agents",
+            endpoint=AgentServer.get_agents,
+            methods=["GET"],
+        )
+        router.add_api_route(
+            path="/agents/{agent_id}",
+            endpoint=AgentServer.get_agent,
+            methods=["GET"],
+        )
+        router.add_api_route(
+            path="/agents",
+            endpoint=AgentServer.create_agent,
             methods=["POST"],
         )
-        self.app.include_router(self.router)
+        router.add_api_route(
+            path="/agents/{agent_id}/execute",
+            endpoint=AgentServer.execute_agent,
+            methods=["POST"],
+        )
+        router.add_api_route(
+            path="/agents/{agent_id}/executions/{run_id}",
+            endpoint=AgentServer.get_executions,
+            methods=["GET"],
+        )
+        router.add_api_route(
+            path="/agents/{agent_id}/schedules",
+            endpoint=AgentServer.schedule_agent,
+            methods=["POST"],
+        )
+        router.add_api_route(
+            path="/agents/{agent_id}/schedules",
+            endpoint=AgentServer.get_execution_schedules,
+            methods=["GET"],
+        )
 
-    async def execute_agent(self, agent_id: str, node_input: dict):
+        app.include_router(router)
+        uvicorn.run(app, host="0.0.0.0", port=8000)
+
+    @staticmethod
+    async def get_agent_blocks() -> list[dict]:
+        return [v.to_dict() for v in await block.get_blocks()]
+
+    @staticmethod
+    async def get_agents() -> list[str]:
+        return await graph.get_graph_ids()
+
+    @staticmethod
+    async def get_agent(agent_id: str) -> graph.Graph:
+        agent = await graph.get_graph(agent_id)
+        if not agent:
+            raise HTTPException(status_code=404, detail=f"Agent #{agent_id} not found.")
+
+        return agent
+
+    @staticmethod
+    async def create_agent(agent: graph.Graph) -> graph.Graph:
+        agent.id = str(uuid.uuid4())
+
+        id_map = {node.id: str(uuid.uuid4()) for node in agent.nodes}
+        for node in agent.nodes:
+            node.id = id_map[node.id]
+            node.input_nodes = {k: id_map[v] for k, v in node.input_nodes.items()}
+            node.output_nodes = {k: id_map[v] for k, v in node.output_nodes.items()}
+
+        return await graph.create_graph(agent)
+
+    @staticmethod
+    async def execute_agent(agent_id: str, node_input: dict) -> dict:
         agent = await graph.get_graph(agent_id)
         if not agent:
             raise HTTPException(status_code=404, detail=f"Agent #{agent_id} not found.")
 
         run_id = str(uuid.uuid4())
-        tasks = []
+        executions = []
+        execution_manager = get_service_client(ExecutionManager)
 
         # Currently, there is no constraint on the number of root nodes in the graph.
         for node in agent.starting_nodes:
-            block = await node.block
-            if error := block.input_schema.validate_data(node_input):
+            node_block = await block.get_block(node.block_id)
+            if not node_block:
+                raise HTTPException(
+                    status_code=404,
+                    detail=f"Block #{node.block_id} not found.",
+                )
+            if error := node_block.input_schema.validate_data(node_input):
                 raise HTTPException(
                     status_code=400,
-                    detail=f"Input data doesn't match {block.name} input: {error}",
+                    detail=f"Input data doesn't match {node_block.name} input: {error}",
                 )
 
-            task = execution.add_execution(
-                execution.Execution(run_id=run_id, node_id=node.id, data=node_input),
-                self.execution_queue,
+            exec_id = execution_manager.add_execution(
+                run_id=run_id, node_id=node.id, data=node_input
             )
+            executions.append({
+                "exec_id": exec_id,
+                "node_id": node.id,
+            })
 
-            tasks.append(task)
+        return {
+            "run_id": run_id,
+            "executions": executions,
+        }
 
-        return await asyncio.gather(*tasks)
+    @staticmethod
+    async def get_executions(
+            agent_id: str,
+            run_id: str
+    ) -> list[execution.ExecutionResult]:
+        agent = await graph.get_graph(agent_id)
+        if not agent:
+            raise HTTPException(status_code=404, detail=f"Agent #{agent_id} not found.")
 
+        return await execution.get_executions(run_id)
 
-def start_server(queue: execution.ExecutionQueue):
-    agent_server = AgentServer(queue)
-    uvicorn.run(agent_server.app)
+    @staticmethod
+    def schedule_agent(agent_id: str, cron: str, input_data: dict) -> dict:
+        execution_scheduler = get_service_client(ExecutionScheduler)
+        return {
+            "id": execution_scheduler.add_execution_schedule(agent_id, cron, input_data)
+        }
+
+    @staticmethod
+    def get_execution_schedules(agent_id: str) -> list[dict]:
+        execution_scheduler = get_service_client(ExecutionScheduler)
+        return execution_scheduler.get_execution_schedules(agent_id)

rnd/autogpt_server/autogpt_server/util/process.py

@@ -0,0 +1,73 @@
+import os
+import sys
+from abc import ABC, abstractmethod
+from multiprocessing import Process, freeze_support, set_start_method
+from multiprocessing.spawn import freeze_support as freeze_support_spawn
+from typing import Optional
+
+
+class AppProcess(ABC):
+    """
+    A class to represent an object that can be executed in a background process.
+    """
+    process: Optional[Process] = None
+    set_start_method('spawn', force=True)
+    freeze_support()
+    freeze_support_spawn()
+
+    @abstractmethod
+    def run(self):
+        """
+        The method that will be executed in the process.
+        """
+        pass
+
+    def execute_run_command(self, silent):
+        try:
+            if silent:
+                sys.stdout = open(os.devnull, "w")
+                sys.stderr = open(os.devnull, "w")
+            self.run()
+        except KeyboardInterrupt or SystemExit as e:
+            print(f"Process terminated: {e}")
+
+    def __enter__(self):
+        self.start(background=True)
+        return self
+
+    def __exit__(self, *args, **kwargs):
+        self.stop()
+
+    def start(self, background: bool = False, silent: bool = False, **proc_args) -> int:
+        """
+        Start the background process.
+        Args:
+            background: Whether to run the process in the background.
+            silent: Whether to disable stdout and stderr.
+            proc_args: Additional arguments to pass to the process.
+        Returns:
+            the process id or 0 if the process is not running in the background.
+        """
+        if not background:
+            self.execute_run_command(silent)
+            return 0
+
+        self.process = Process(
+            name=self.__class__.__name__,
+            target=self.execute_run_command,
+            args=(silent,),
+            **proc_args,
+        )
+        self.process.start()
+        return self.process.pid or 0
+
+    def stop(self):
+        """
+        Stop the background process.
+        """
+        if not self.process:
+            return
+
+        self.process.terminate()
+        self.process.join()
+        self.process = None

rnd/autogpt_server/autogpt_server/util/service.py

@@ -0,0 +1,100 @@
+import time
+import asyncio
+import logging
+import threading
+
+from abc import abstractmethod
+from typing import Any, Callable, Type, TypeVar, cast, Coroutine
+
+from Pyro5 import api as pyro
+from Pyro5 import nameserver
+from tenacity import retry, stop_after_delay, wait_exponential
+
+from autogpt_server.data import db
+from autogpt_server.util.process import AppProcess
+
+logger = logging.getLogger(__name__)
+conn_retry = retry(stop=stop_after_delay(5), wait=wait_exponential(multiplier=0.1))
+expose = pyro.expose
+
+
+class PyroNameServer(AppProcess):
+    def run(self):
+        try:
+            print("Starting NameServer loop")
+            nameserver.start_ns_loop()
+        except KeyboardInterrupt:
+            print("Shutting down NameServer")
+
+
+class AppService(AppProcess):
+
+    shared_event_loop: asyncio.AbstractEventLoop
+
+    @classmethod
+    @property
+    def service_name(cls) -> str:
+        return cls.__name__
+
+    @abstractmethod
+    def run_service(self):
+        while True:
+            time.sleep(10)
+
+    def run_async(self, coro: Coroutine):
+        return asyncio.run_coroutine_threadsafe(coro, self.shared_event_loop)
+
+    def run_and_wait(self, coro: Coroutine):
+        future = self.run_async(coro)
+        return future.result()
+
+    def run(self):
+        self.shared_event_loop = asyncio.get_event_loop()
+        self.shared_event_loop.run_until_complete(db.connect())
+
+        # Initialize the async loop.
+        async_thread = threading.Thread(target=self.__start_async_loop)
+        async_thread.daemon = True
+        async_thread.start()
+
+        # Initialize pyro service
+        daemon_thread = threading.Thread(target=self.__start_pyro)
+        daemon_thread.daemon = True
+        daemon_thread.start()
+
+        # Run the main service (if it's not implemented, just sleep).
+        self.run_service()
+
+    @conn_retry
+    def __start_pyro(self):
+        daemon = pyro.Daemon()
+        ns = pyro.locate_ns()
+        uri = daemon.register(self)
+        ns.register(self.service_name, uri)
+        logger.warning(f"Service [{self.service_name}] Ready. Object URI = {uri}")
+        daemon.requestLoop()
+
+    def __start_async_loop(self):
+        # asyncio.set_event_loop(self.shared_event_loop)
+        self.shared_event_loop.run_forever()
+
+
+AS = TypeVar("AS", bound=AppService)
+
+
+def get_service_client(service_type: Type[AS]) -> AS:
+    service_name = service_type.service_name
+
+    class DynamicClient:
+
+        @conn_retry
+        def __init__(self):
+            ns = pyro.locate_ns()
+            uri = ns.lookup(service_name)
+            self.proxy = pyro.Proxy(uri)
+            self.proxy._pyroBind()
+
+        def __getattr__(self, name: str) -> Callable[..., Any]:
+            return getattr(self.proxy, name)
+
+    return cast(AS, DynamicClient())

rnd/autogpt_server/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
 [[package]]
 name = "annotated-types"
@@ -216,18 +216,18 @@ all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)"
 
 [[package]]
 name = "filelock"
-version = "3.14.0"
+version = "3.15.1"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "filelock-3.14.0-py3-none-any.whl", hash = "sha256:43339835842f110ca7ae60f1e1c160714c5a6afd15a2873419ab185334975c0f"},
-    {file = "filelock-3.14.0.tar.gz", hash = "sha256:6ea72da3be9b8c82afd3edcf99f2fffbb5076335a5ae4d03248bb5b6c3eae78a"},
+    {file = "filelock-3.15.1-py3-none-any.whl", hash = "sha256:71b3102950e91dfc1bb4209b64be4dc8854f40e5f534428d8684f953ac847fac"},
+    {file = "filelock-3.15.1.tar.gz", hash = "sha256:58a2549afdf9e02e10720eaa4d4470f56386d7a6f72edd7d0596337af8ed7ad8"},
 ]
 
 [package.extras]
 docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-asyncio (>=0.21)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
 typing = ["typing-extensions (>=4.8)"]
 
 [[package]]
@@ -695,13 +695,13 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "2.7.3"
+version = "2.7.4"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic-2.7.3-py3-none-any.whl", hash = "sha256:ea91b002777bf643bb20dd717c028ec43216b24a6001a280f83877fd2655d0b4"},
-    {file = "pydantic-2.7.3.tar.gz", hash = "sha256:c46c76a40bb1296728d7a8b99aa73dd70a48c3510111ff290034f860c99c419e"},
+    {file = "pydantic-2.7.4-py3-none-any.whl", hash = "sha256:ee8538d41ccb9c0a9ad3e0e5f07bf15ed8015b481ced539a1759d8cc89ae90d0"},
+    {file = "pydantic-2.7.4.tar.gz", hash = "sha256:0c84efd9548d545f63ac0060c1e4d39bb9b14db8b3c0652338aecc07b5adec52"},
 ]
 
 [package.dependencies]
@@ -814,6 +814,20 @@ files = [
     {file = "pyflakes-3.2.0.tar.gz", hash = "sha256:1c61603ff154621fb2a9172037d84dca3500def8c8b630657d1701f026f8af3f"},
 ]
 
+[[package]]
+name = "pyro5"
+version = "5.15"
+description = "Remote object communication library, fifth major version"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "Pyro5-5.15-py3-none-any.whl", hash = "sha256:4d85428ed75985e63f159d2486ad5680743ea76f766340fd30b65dd20f83d471"},
+    {file = "Pyro5-5.15.tar.gz", hash = "sha256:82c3dfc9860b49f897b28ff24fe6716c841672c600af8fe40d0e3a7fac9a3f5e"},
+]
+
+[package.dependencies]
+serpent = ">=1.41"
+
 [[package]]
 name = "pytest"
 version = "8.2.2"
@@ -836,24 +850,6 @@ tomli = {version = ">=1", markers = "python_version < \"3.11\""}
 [package.extras]
 dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
-[[package]]
-name = "pytest-asyncio"
-version = "0.23.7"
-description = "Pytest support for asyncio"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "pytest_asyncio-0.23.7-py3-none-any.whl", hash = "sha256:009b48127fbe44518a547bddd25611551b0e43ccdbf1e67d12479f569832c20b"},
-    {file = "pytest_asyncio-0.23.7.tar.gz", hash = "sha256:5f5c72948f4c49e7db4f29f2521d4031f1c27f86e57b046126654083d4770268"},
-]
-
-[package.dependencies]
-pytest = ">=7.0.0,<9"
-
-[package.extras]
-docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1.0)"]
-testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
-
 [[package]]
 name = "pytest-watcher"
 version = "0.4.2"
@@ -908,6 +904,7 @@ files = [
     {file = "PyYAML-6.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:bf07ee2fef7014951eeb99f56f39c9bb4af143d8aa3c21b1677805985307da34"},
     {file = "PyYAML-6.0.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:855fb52b0dc35af121542a76b9a84f8d1cd886ea97c84703eaa6d88e37a2ad28"},
     {file = "PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40df9b996c2b73138957fe23a16a4f0ba614f4c0efce1e9406a184b6d07fa3a9"},
+    {file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a08c6f0fe150303c1c6b71ebcd7213c2858041a7e01975da3a99aed1e7a378ef"},
     {file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c22bec3fbe2524cde73d7ada88f6566758a8f7227bfbf93a408a9d86bcc12a0"},
     {file = "PyYAML-6.0.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8d4e9c88387b0f5c7d5f281e55304de64cf7f9c0021a3525bd3b1c542da3b0e4"},
     {file = "PyYAML-6.0.1-cp312-cp312-win32.whl", hash = "sha256:d483d2cdf104e7c9fa60c544d92981f12ad66a457afae824d146093b8c294c54"},
@@ -1091,6 +1088,17 @@ files = [
     {file = "ruff-0.4.8.tar.gz", hash = "sha256:16d717b1d57b2e2fd68bd0bf80fb43931b79d05a7131aa477d66fc40fbd86268"},
 ]
 
+[[package]]
+name = "serpent"
+version = "1.41"
+description = "Serialization based on ast.literal_eval"
+optional = false
+python-versions = ">=3.2"
+files = [
+    {file = "serpent-1.41-py3-none-any.whl", hash = "sha256:5fd776b3420441985bc10679564c2c9b4a19f77bea59f018e473441d98ae5dd7"},
+    {file = "serpent-1.41.tar.gz", hash = "sha256:0407035fe3c6644387d48cff1467d5aa9feff814d07372b78677ed0ee3ed7095"},
+]
+
 [[package]]
 name = "setuptools"
 version = "69.5.1"
@@ -1151,6 +1159,21 @@ docs = ["myst-parser[linkify]", "sphinx", "sphinx-rtd-theme"]
 release = ["twine"]
 test = ["pylint", "pytest", "pytest-black", "pytest-cov", "pytest-pylint"]
 
+[[package]]
+name = "tenacity"
+version = "8.3.0"
+description = "Retry code until it succeeds"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "tenacity-8.3.0-py3-none-any.whl", hash = "sha256:3649f6443dbc0d9b01b9d8020a9c4ec7a1ff5f6f3c6c8a036ef371f573fe9185"},
+    {file = "tenacity-8.3.0.tar.gz", hash = "sha256:953d4e6ad24357bceffbc9707bc74349aca9d245f68eb65419cf0c249a1949a2"},
+]
+
+[package.extras]
+doc = ["reno", "sphinx"]
+test = ["pytest", "tornado (>=4.5)", "typeguard"]
+
 [[package]]
 name = "tomli"
 version = "2.0.1"
@@ -1483,4 +1506,4 @@ test = ["pytest (>=6.0.0)", "setuptools (>=65)"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "391567de870dbbf86ea217ff6b15f7c6d2c9406707c196661d29f45deb886812"
+content-hash = "de508427e9804ded3b3139e13f209baa6cc97bc138d83952ad2b129d3aedc4e2"

rnd/autogpt_server/pyproject.toml

@@ -16,11 +16,12 @@ prisma = "^0.13.1"
 pytest = "^8.2.1"
 uvicorn = { extras = ["standard"], version = "^0.30.1" }
 fastapi = "^0.109.0"
-pytest-asyncio = "^0.23.7"
 ruff = "^0.4.8"
 flake8 = "^7.0.0"
 jsonschema = "^4.22.0"
 psutil = "^5.9.8"
+pyro5 = "^5.15"
+tenacity = "^8.3.0"
 
 
 [tool.poetry.group.dev.dependencies]
@@ -35,7 +36,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry.scripts]
 app = "autogpt_server.app:main"
-cli = "autogpt_server.cli:start_cli"
+cli = "autogpt_server.cli:main"
 
 # https://poethepoet.natn.io/index.html
 [tool.poe]

rnd/autogpt_server/setup.py

@@ -29,11 +29,14 @@ setup(
             icon=icon,
         ),
         Executable(
-            "autogpt_server/cli.py", target_name="agpt_server_cli", base="console", icon=icon
+            "autogpt_server/cli.py",
+            target_name="agpt_server_cli",
+            base="console",
+            icon=icon,
         ),
     ],
     options={
-      # Options for building all the executables
+        # Options for building all the executables
         "build_exe": {
             "packages": packages,
             "includes": [

rnd/autogpt_server/test/executor/test_manager.py

@@ -0,0 +1,121 @@
+import asyncio
+import time
+
+from autogpt_server.data import block, db, execution, graph
+from autogpt_server.executor import ExecutionManager
+from autogpt_server.server import AgentServer
+from autogpt_server.util.service import PyroNameServer
+
+
+async def create_test_graph() -> graph.Graph:
+    """
+    ParrotBlock
+                \
+                 ---- TextCombinerBlock ---- PrintingBlock
+                /
+    ParrotBlock
+    """
+    nodes = [
+        graph.Node(block_id=block.ParrotBlock.id),
+        graph.Node(block_id=block.ParrotBlock.id),
+        graph.Node(
+            block_id=block.TextCombinerBlock.id,
+            input_default={"format": "{text1},{text2}"},
+        ),
+        graph.Node(block_id=block.PrintingBlock.id),
+    ]
+    nodes[0].connect(nodes[2], "output", "text1")
+    nodes[1].connect(nodes[2], "output", "text2")
+    nodes[2].connect(nodes[3], "combined_text", "text")
+
+    test_graph = graph.Graph(
+        name="TestGraph",
+        description="Test graph",
+        nodes=nodes,
+    )
+    await block.initialize_blocks()
+    result = await graph.create_graph(test_graph)
+
+    # Assertions
+    assert result.name == test_graph.name
+    assert result.description == test_graph.description
+    assert len(result.nodes) == len(test_graph.nodes)
+
+    return test_graph
+
+
+def execute_agent(test_manager: ExecutionManager, test_graph: graph.Graph, wait_db):
+    # --- Test adding new executions --- #
+    text = "Hello, World!"
+    input_data = {"input": text}
+    response = wait_db(AgentServer.execute_agent(test_graph.id, input_data))
+    executions = response["executions"]
+    run_id = response["run_id"]
+    assert len(executions) == 2
+
+    async def is_execution_completed():
+        execs = await AgentServer.get_executions(test_graph.id, run_id)
+        return test_manager.queue.empty() and len(execs) == 4
+
+    # Wait for the executions to complete
+    for i in range(10):
+        if wait_db(is_execution_completed()):
+            break
+        time.sleep(1)
+
+    # Execution queue should be empty
+    assert wait_db(is_execution_completed())
+    executions = wait_db(AgentServer.get_executions(test_graph.id, run_id))
+
+    # Executing ParrotBlock1
+    exec = executions[0]
+    assert exec.status == execution.ExecutionStatus.COMPLETED
+    assert exec.run_id == run_id
+    assert exec.output_name == "output"
+    assert exec.output_data == "Hello, World!"
+    assert exec.input_data == input_data
+    assert exec.node_id == test_graph.nodes[0].id
+
+    # Executing ParrotBlock2
+    exec = executions[1]
+    assert exec.status == execution.ExecutionStatus.COMPLETED
+    assert exec.run_id == run_id
+    assert exec.output_name == "output"
+    assert exec.output_data == "Hello, World!"
+    assert exec.input_data == input_data
+    assert exec.node_id == test_graph.nodes[1].id
+
+    # Executing TextCombinerBlock
+    exec = executions[2]
+    assert exec.status == execution.ExecutionStatus.COMPLETED
+    assert exec.run_id == run_id
+    assert exec.output_name == "combined_text"
+    assert exec.output_data == "Hello, World!,Hello, World!"
+    assert exec.input_data == {
+        "format": "{text1},{text2}",
+        "text1": "Hello, World!",
+        "text2": "Hello, World!",
+    }
+    assert exec.node_id == test_graph.nodes[2].id
+
+    # Executing PrintingBlock
+    exec = executions[3]
+    assert exec.status == execution.ExecutionStatus.COMPLETED
+    assert exec.run_id == run_id
+    assert exec.output_name == "status"
+    assert exec.output_data == "printed"
+    assert exec.input_data == {"text": "Hello, World!,Hello, World!"}
+    assert exec.node_id == test_graph.nodes[3].id
+
+
+def test_agent_execution():
+    with PyroNameServer():
+        time.sleep(0.5)
+        with ExecutionManager(1) as test_manager:
+            loop = asyncio.new_event_loop()
+            wait = loop.run_until_complete
+            
+            wait(db.connect())
+            test_graph = wait(create_test_graph())
+    
+            execute_agent(test_manager, test_graph, wait)

rnd/autogpt_server/test/test_app.py

@@ -1,97 +0,0 @@
-import pytest
-
-from autogpt_server.data import block, db, graph
-from autogpt_server.data.execution import ExecutionQueue, add_execution
-from autogpt_server.executor import executor
-from autogpt_server.server import server
-
-
-async def create_test_graph() -> graph.Graph:
-    """
-    ParrotBlock
-                \
-                 ---- TextCombinerBlock ---- PrintingBlock
-                /
-    ParrotBlock
-    """
-    nodes = [
-        graph.Node(block_id=block.ParrotBlock.id),
-        graph.Node(block_id=block.ParrotBlock.id),
-        graph.Node(
-            block_id=block.TextCombinerBlock.id,
-            input_default={"format": "{text1},{text2}"}
-        ),
-        graph.Node(block_id=block.PrintingBlock.id),
-    ]
-    nodes[0].connect(nodes[2], "output", "text1")
-    nodes[1].connect(nodes[2], "output", "text2")
-    nodes[2].connect(nodes[3], "combined_text", "text")
-
-    test_graph = graph.Graph(
-        name="TestGraph",
-        description="Test graph",
-        nodes=nodes,
-    )
-    await block.initialize_blocks()
-    result = await graph.create_graph(test_graph)
-
-    # Assertions
-    assert result.name == test_graph.name
-    assert result.description == test_graph.description
-    assert len(result.nodes) == len(test_graph.nodes)
-
-    return result
-
-
-async def execute_node(queue: ExecutionQueue) -> dict | None:
-    next_exec = await executor.execute_node(queue.get())
-    if not next_exec:
-        return None
-    await add_execution(next_exec, queue)
-    return next_exec.data
-
-
-@pytest.mark.asyncio
-async def test_agent_execution():
-    await db.connect()
-    test_graph = await create_test_graph()
-    test_queue = ExecutionQueue()
-    test_server = server.AgentServer(test_queue)
-
-    # --- Test adding new executions --- #
-    text = "Hello, World!"
-    input_data = {"input": text}
-    executions = await test_server.execute_agent(test_graph.id, input_data)
-
-    # 2 executions should be created, one for each ParrotBlock, with same run_id.
-    assert len(executions) == 2
-    assert executions[0].run_id == executions[1].run_id
-    assert executions[0].node_id != executions[1].node_id
-    assert executions[0].data == executions[1].data == input_data
-
-    # --- Test Executing added tasks --- #
-
-    # Executing ParrotBlock1, TextCombinerBlock won't be enqueued yet.
-    assert not test_queue.empty()
-    next_execution = await execute_node(test_queue)
-    assert next_execution is None
-
-    # Executing ParrotBlock2, TextCombinerBlock will be enqueued.
-    assert not test_queue.empty()
-    next_execution = await execute_node(test_queue)
-    assert test_queue.empty()
-    assert next_execution
-    assert next_execution.keys() == {"text1", "text2", "format"}
-    assert next_execution["text1"] == text
-    assert next_execution["text2"] == text
-    assert next_execution["format"] == "{text1},{text2}"
-
-    # Executing TextCombinerBlock, PrintingBlock will be enqueued.
-    next_execution = await execute_node(test_queue)
-    assert next_execution
-    assert next_execution.keys() == {"text"}
-    assert next_execution["text"] == f"{text},{text}"
-
-    # Executing PrintingBlock, no more tasks will be enqueued.
-    next_execution = await execute_node(test_queue)
-    assert next_execution is None

rnd/autogpt_server/test/util/test_service.py

@@ -0,0 +1,38 @@
+import time
+
+from autogpt_server.util.service import (
+    AppService,
+    PyroNameServer,
+    expose,
+    get_service_client,
+)
+
+
+class TestService(AppService):
+
+    def run_service(self):
+        super().run_service()
+
+    @expose
+    def add(self, a: int, b: int) -> int:
+        return a + b
+
+    @expose
+    def subtract(self, a: int, b: int) -> int:
+        return a - b
+
+    @expose
+    def fun_with_async(self, a: int, b: int) -> int:
+        async def add_async(a: int, b: int) -> int:
+            return a + b
+        return self.run_and_wait(add_async(a, b))
+
+
+def test_service_creation():
+    with PyroNameServer():
+        time.sleep(0.5)
+        with TestService():
+            client = get_service_client(TestService)
+            assert client.add(5, 3) == 8
+            assert client.subtract(10, 4) == 6
+            assert client.fun_with_async(5, 3) == 8