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Merge branch 'dev' into pwuts/open-2995-copilot-microservice-with-block-refactor

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This commit is contained in:
Reinier van der Leer
2026-02-12 13:31:04 +01:00
parent 80659d90e4 113e87a23c
commit d652821ed5
25 changed files with 577 additions and 354 deletions
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56
autogpt_platform/backend/backend/blocks/human_in_the_loop.py
View File

@@ -21,43 +21,71 @@ logger = logging.getLogger(__name__)
class HumanInTheLoopBlock(Block):
"""
This block pauses execution and waits for human approval or modification of the data.
Pauses execution and waits for human approval or rejection of the data.
When executed, it creates a pending review entry and sets the node execution status
to REVIEW. The execution will remain paused until a human user either:
- Approves the data (with or without modifications)
- Rejects the data
When executed, this block creates a pending review entry and sets the node execution
status to REVIEW. The execution remains paused until a human user either approves
or rejects the data.
This is useful for workflows that require human validation or intervention before
proceeding to the next steps.
**How it works:**
- The input data is presented to a human reviewer
- The reviewer can approve or reject (and optionally modify the data if editable)
- On approval: the data flows out through the `approved_data` output pin
- On rejection: the data flows out through the `rejected_data` output pin
**Important:** The output pins yield the actual data itself, NOT status strings.
The approval/rejection decision determines WHICH output pin fires, not the value.
You do NOT need to compare the output to "APPROVED" or "REJECTED" - simply connect
downstream blocks to the appropriate output pin for each case.
**Example usage:**
- Connect `approved_data` → next step in your workflow (data was approved)
- Connect `rejected_data` → error handling or notification (data was rejected)
"""
class Input(BlockSchemaInput):
data: Any = SchemaField(description="The data to be reviewed by a human user")
data: Any = SchemaField(
description="The data to be reviewed by a human user. "
"This exact data will be passed through to either approved_data or "
"rejected_data output based on the reviewer's decision."
)
name: str = SchemaField(
description="A descriptive name for what this data represents",
description="A descriptive name for what this data represents. "
"This helps the reviewer understand what they are reviewing.",
)
editable: bool = SchemaField(
description="Whether the human reviewer can edit the data",
description="Whether the human reviewer can edit the data before "
"approving or rejecting it",
default=True,
advanced=True,
)
class Output(BlockSchemaOutput):
approved_data: Any = SchemaField(
description="The data when approved (may be modified by reviewer)"
description="Outputs the input data when the reviewer APPROVES it. "
"The value is the actual data itself (not a status string like 'APPROVED'). "
"If the reviewer edited the data, this contains the modified version. "
"Connect downstream blocks here for the 'approved' workflow path."
)
rejected_data: Any = SchemaField(
description="The data when rejected (may be modified by reviewer)"
description="Outputs the input data when the reviewer REJECTS it. "
"The value is the actual data itself (not a status string like 'REJECTED'). "
"If the reviewer edited the data, this contains the modified version. "
"Connect downstream blocks here for the 'rejected' workflow path."
)
review_message: str = SchemaField(
description="Any message provided by the reviewer", default=""
description="Optional message provided by the reviewer explaining their "
"decision. Only outputs when the reviewer provides a message; "
"this pin does not fire if no message was given.",
default="",
)
def __init__(self):
super().__init__(
id="8b2a7b3c-6e9d-4a5f-8c1b-2e3f4a5b6c7d",
description="Pause execution and wait for human approval or modification of data",
description="Pause execution for human review. Data flows through "
"approved_data or rejected_data output based on the reviewer's decision. "
"Outputs contain the actual data, not status strings.",
categories={BlockCategory.BASIC},
input_schema=HumanInTheLoopBlock.Input,
output_schema=HumanInTheLoopBlock.Output,

65
autogpt_platform/backend/backend/copilot/model.py
View File

@@ -2,7 +2,7 @@ import asyncio
import logging
import uuid
from datetime import UTC, datetime
from typing import Any
from typing import Any, cast
from weakref import WeakValueDictionary
from openai.types.chat import (
@@ -74,6 +74,26 @@ class ChatSession(BaseModel):
successful_agent_runs: dict[str, int] = {}
successful_agent_schedules: dict[str, int] = {}
def add_tool_call_to_current_turn(self, tool_call: dict) -> None:
"""Attach a tool_call to the current turn's assistant message.
Searches backwards for the most recent assistant message (stopping at
any user message boundary). If found, appends the tool_call to it.
Otherwise creates a new assistant message with the tool_call.
"""
for msg in reversed(self.messages):
if msg.role == "user":
break
if msg.role == "assistant":
if not msg.tool_calls:
msg.tool_calls = []
msg.tool_calls.append(tool_call)
return
self.messages.append(
ChatMessage(role="assistant", content="", tool_calls=[tool_call])
)
@staticmethod
def new(user_id: str) -> "ChatSession":
return ChatSession(
@@ -142,6 +162,47 @@ class ChatSession(BaseModel):
successful_agent_schedules=successful_agent_schedules,
)
@staticmethod
def _merge_consecutive_assistant_messages(
messages: list[ChatCompletionMessageParam],
) -> list[ChatCompletionMessageParam]:
"""Merge consecutive assistant messages into single messages.
Long-running tool flows can create split assistant messages: one with
text content and another with tool_calls. Anthropic's API requires
tool_result blocks to reference a tool_use in the immediately preceding
assistant message, so these splits cause 400 errors via OpenRouter.
"""
if len(messages) < 2:
return messages
result: list[ChatCompletionMessageParam] = [messages[0]]
for msg in messages[1:]:
prev = result[-1]
if prev.get("role") != "assistant" or msg.get("role") != "assistant":
result.append(msg)
continue
prev = cast(ChatCompletionAssistantMessageParam, prev)
curr = cast(ChatCompletionAssistantMessageParam, msg)
curr_content = curr.get("content") or ""
if curr_content:
prev_content = prev.get("content") or ""
prev["content"] = (
f"{prev_content}\n{curr_content}" if prev_content else curr_content
)
curr_tool_calls = curr.get("tool_calls")
if curr_tool_calls:
prev_tool_calls = prev.get("tool_calls")
prev["tool_calls"] = (
list(prev_tool_calls) + list(curr_tool_calls)
if prev_tool_calls
else list(curr_tool_calls)
)
return result
def to_openai_messages(self) -> list[ChatCompletionMessageParam]:
messages = []
for message in self.messages:
@@ -228,7 +289,7 @@ class ChatSession(BaseModel):
name=message.name or "",
)
)
return messages
return self._merge_consecutive_assistant_messages(messages)
def _parse_json_field(value: str | dict | list | None, default: Any = None) -> Any:

214
autogpt_platform/backend/backend/copilot/model_test.py
View File

@@ -1,4 +1,16 @@
from typing import cast
import pytest
from openai.types.chat import (
ChatCompletionAssistantMessageParam,
ChatCompletionMessageParam,
ChatCompletionToolMessageParam,
ChatCompletionUserMessageParam,
)
from openai.types.chat.chat_completion_message_tool_call_param import (
ChatCompletionMessageToolCallParam,
Function,
)
from .model import (
ChatMessage,
@@ -117,3 +129,205 @@ async def test_chatsession_db_storage(setup_test_user, test_user_id):
loaded.tool_calls is not None
), f"Tool calls missing for {orig.role} message"
assert len(orig.tool_calls) == len(loaded.tool_calls)
# --------------------------------------------------------------------------- #
# _merge_consecutive_assistant_messages #
# --------------------------------------------------------------------------- #
_tc = ChatCompletionMessageToolCallParam(
id="tc1", type="function", function=Function(name="do_stuff", arguments="{}")
)
_tc2 = ChatCompletionMessageToolCallParam(
id="tc2", type="function", function=Function(name="other", arguments="{}")
)
def test_merge_noop_when_no_consecutive_assistants():
"""Messages without consecutive assistants are returned unchanged."""
msgs = [
ChatCompletionUserMessageParam(role="user", content="hi"),
ChatCompletionAssistantMessageParam(role="assistant", content="hello"),
ChatCompletionUserMessageParam(role="user", content="bye"),
]
merged = ChatSession._merge_consecutive_assistant_messages(msgs)
assert len(merged) == 3
assert [m["role"] for m in merged] == ["user", "assistant", "user"]
def test_merge_splits_text_and_tool_calls():
"""The exact bug scenario: text-only assistant followed by tool_calls-only assistant."""
msgs = [
ChatCompletionUserMessageParam(role="user", content="build agent"),
ChatCompletionAssistantMessageParam(
role="assistant", content="Let me build that"
),
ChatCompletionAssistantMessageParam(
role="assistant", content="", tool_calls=[_tc]
),
ChatCompletionToolMessageParam(role="tool", content="ok", tool_call_id="tc1"),
]
merged = ChatSession._merge_consecutive_assistant_messages(msgs)
assert len(merged) == 3
assert merged[0]["role"] == "user"
assert merged[2]["role"] == "tool"
a = cast(ChatCompletionAssistantMessageParam, merged[1])
assert a["role"] == "assistant"
assert a.get("content") == "Let me build that"
assert a.get("tool_calls") == [_tc]
def test_merge_combines_tool_calls_from_both():
"""Both consecutive assistants have tool_calls — they get merged."""
msgs: list[ChatCompletionAssistantMessageParam] = [
ChatCompletionAssistantMessageParam(
role="assistant", content="text", tool_calls=[_tc]
),
ChatCompletionAssistantMessageParam(
role="assistant", content="", tool_calls=[_tc2]
),
]
merged = ChatSession._merge_consecutive_assistant_messages(msgs) # type: ignore[arg-type]
assert len(merged) == 1
a = cast(ChatCompletionAssistantMessageParam, merged[0])
assert a.get("tool_calls") == [_tc, _tc2]
assert a.get("content") == "text"
def test_merge_three_consecutive_assistants():
"""Three consecutive assistants collapse into one."""
msgs: list[ChatCompletionAssistantMessageParam] = [
ChatCompletionAssistantMessageParam(role="assistant", content="a"),
ChatCompletionAssistantMessageParam(role="assistant", content="b"),
ChatCompletionAssistantMessageParam(
role="assistant", content="", tool_calls=[_tc]
),
]
merged = ChatSession._merge_consecutive_assistant_messages(msgs) # type: ignore[arg-type]
assert len(merged) == 1
a = cast(ChatCompletionAssistantMessageParam, merged[0])
assert a.get("content") == "a\nb"
assert a.get("tool_calls") == [_tc]
def test_merge_empty_and_single_message():
"""Edge cases: empty list and single message."""
assert ChatSession._merge_consecutive_assistant_messages([]) == []
single: list[ChatCompletionMessageParam] = [
ChatCompletionUserMessageParam(role="user", content="hi")
]
assert ChatSession._merge_consecutive_assistant_messages(single) == single
# --------------------------------------------------------------------------- #
# add_tool_call_to_current_turn #
# --------------------------------------------------------------------------- #
_raw_tc = {
"id": "tc1",
"type": "function",
"function": {"name": "f", "arguments": "{}"},
}
_raw_tc2 = {
"id": "tc2",
"type": "function",
"function": {"name": "g", "arguments": "{}"},
}
def test_add_tool_call_appends_to_existing_assistant():
"""When the last assistant is from the current turn, tool_call is added to it."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="hi"),
ChatMessage(role="assistant", content="working on it"),
]
session.add_tool_call_to_current_turn(_raw_tc)
assert len(session.messages) == 2 # no new message created
assert session.messages[1].tool_calls == [_raw_tc]
def test_add_tool_call_creates_assistant_when_none_exists():
"""When there's no current-turn assistant, a new one is created."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="hi"),
]
session.add_tool_call_to_current_turn(_raw_tc)
assert len(session.messages) == 2
assert session.messages[1].role == "assistant"
assert session.messages[1].tool_calls == [_raw_tc]
def test_add_tool_call_does_not_cross_user_boundary():
"""A user message acts as a boundary — previous assistant is not modified."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="assistant", content="old turn"),
ChatMessage(role="user", content="new message"),
]
session.add_tool_call_to_current_turn(_raw_tc)
assert len(session.messages) == 3 # new assistant was created
assert session.messages[0].tool_calls is None # old assistant untouched
assert session.messages[2].role == "assistant"
assert session.messages[2].tool_calls == [_raw_tc]
def test_add_tool_call_multiple_times():
"""Multiple long-running tool calls accumulate on the same assistant."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="hi"),
ChatMessage(role="assistant", content="doing stuff"),
]
session.add_tool_call_to_current_turn(_raw_tc)
# Simulate a pending tool result in between (like _yield_tool_call does)
session.messages.append(
ChatMessage(role="tool", content="pending", tool_call_id="tc1")
)
session.add_tool_call_to_current_turn(_raw_tc2)
assert len(session.messages) == 3 # user, assistant, tool — no extra assistant
assert session.messages[1].tool_calls == [_raw_tc, _raw_tc2]
def test_to_openai_messages_merges_split_assistants():
"""End-to-end: session with split assistants produces valid OpenAI messages."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="build agent"),
ChatMessage(role="assistant", content="Let me build that"),
ChatMessage(
role="assistant",
content="",
tool_calls=[
{
"id": "tc1",
"type": "function",
"function": {"name": "create_agent", "arguments": "{}"},
}
],
),
ChatMessage(role="tool", content="done", tool_call_id="tc1"),
ChatMessage(role="assistant", content="Saved!"),
ChatMessage(role="user", content="show me an example run"),
]
openai_msgs = session.to_openai_messages()
# The two consecutive assistants at index 1,2 should be merged
roles = [m["role"] for m in openai_msgs]
assert roles == ["user", "assistant", "tool", "assistant", "user"]
# The merged assistant should have both content and tool_calls
merged = cast(ChatCompletionAssistantMessageParam, openai_msgs[1])
assert merged.get("content") == "Let me build that"
tc_list = merged.get("tool_calls")
assert tc_list is not None and len(list(tc_list)) == 1
assert list(tc_list)[0]["id"] == "tc1"

14
autogpt_platform/backend/backend/copilot/response_model.py
View File

@@ -10,6 +10,8 @@ from typing import Any
from pydantic import BaseModel, Field
from backend.util.json import dumps as json_dumps
class ResponseType(str, Enum):
"""Types of streaming responses following AI SDK protocol."""
@@ -193,6 +195,18 @@ class StreamError(StreamBaseResponse):
default=None, description="Additional error details"
)
def to_sse(self) -> str:
"""Convert to SSE format, only emitting fields required by AI SDK protocol.
The AI SDK uses z.strictObject({type, errorText}) which rejects
any extra fields like `code` or `details`.
"""
data = {
"type": self.type.value,
"errorText": self.errorText,
}
return f"data: {json_dumps(data)}\n\n"
class StreamHeartbeat(StreamBaseResponse):
"""Heartbeat to keep SSE connection alive during long-running operations.

18
autogpt_platform/backend/backend/copilot/service.py
View File

@@ -800,9 +800,13 @@ async def stream_chat_completion(
# Build the messages list in the correct order
messages_to_save: list[ChatMessage] = []
# Add assistant message with tool_calls if any
# Add assistant message with tool_calls if any.
# Use extend (not assign) to preserve tool_calls already added by
# _yield_tool_call for long-running tools.
if accumulated_tool_calls:
assistant_response.tool_calls = accumulated_tool_calls
if not assistant_response.tool_calls:
assistant_response.tool_calls = []
assistant_response.tool_calls.extend(accumulated_tool_calls)
logger.info(
f"Added {len(accumulated_tool_calls)} tool calls to assistant message"
)
@@ -1404,13 +1408,9 @@ async def _yield_tool_call(
operation_id=operation_id,
)
# Save assistant message with tool_call FIRST (required by LLM)
assistant_message = ChatMessage(
role="assistant",
content="",
tool_calls=[tool_calls[yield_idx]],
)
session.messages.append(assistant_message)
# Attach the tool_call to the current turn's assistant message
# (or create one if this is a tool-only response with no text).
session.add_tool_call_to_current_turn(tool_calls[yield_idx])
# Then save pending tool result
pending_message = ChatMessage(

45
autogpt_platform/backend/backend/util/prompt.py
View File

@@ -364,6 +364,44 @@ def _remove_orphan_tool_responses(
return result
def validate_and_remove_orphan_tool_responses(
messages: list[dict],
log_warning: bool = True,
) -> list[dict]:
"""
Validate tool_call/tool_response pairs and remove orphaned responses.
Scans messages in order, tracking all tool_call IDs. Any tool response
referencing an ID not seen in a preceding message is considered orphaned
and removed. This prevents API errors like Anthropic's "unexpected tool_use_id".
Args:
messages: List of messages to validate (OpenAI or Anthropic format)
log_warning: Whether to log a warning when orphans are found
Returns:
A new list with orphaned tool responses removed
"""
available_ids: set[str] = set()
orphan_ids: set[str] = set()
for msg in messages:
available_ids |= _extract_tool_call_ids_from_message(msg)
for resp_id in _extract_tool_response_ids_from_message(msg):
if resp_id not in available_ids:
orphan_ids.add(resp_id)
if not orphan_ids:
return messages
if log_warning:
logger.warning(
f"Removing {len(orphan_ids)} orphan tool response(s): {orphan_ids}"
)
return _remove_orphan_tool_responses(messages, orphan_ids)
def _ensure_tool_pairs_intact(
recent_messages: list[dict],
all_messages: list[dict],
@@ -723,6 +761,13 @@ async def compress_context(
# Filter out any None values that may have been introduced
final_msgs: list[dict] = [m for m in msgs if m is not None]
# ---- STEP 6: Final tool-pair validation ---------------------------------
# After all compression steps, verify that every tool response has a
# matching tool_call in a preceding assistant message. Remove orphans
# to prevent API errors (e.g., Anthropic's "unexpected tool_use_id").
final_msgs = validate_and_remove_orphan_tool_responses(final_msgs)
final_count = sum(_msg_tokens(m, enc) for m in final_msgs)
error = None
if final_count + reserve > target_tokens:

31
autogpt_platform/frontend/src/app/(platform)/build/components/BuilderViewTabs/BuilderViewTabs.tsx
View File

@@ -1,31 +0,0 @@
"use client";
import { Tabs, TabsList, TabsTrigger } from "@/components/__legacy__/ui/tabs";
export type BuilderView = "old" | "new";
export function BuilderViewTabs({
value,
onChange,
}: {
value: BuilderView;
onChange: (value: BuilderView) => void;
}) {
return (
<div className="pointer-events-auto fixed right-4 top-20 z-50">
<Tabs
value={value}
onValueChange={(v: string) => onChange(v as BuilderView)}
>
<TabsList className="w-fit bg-zinc-900">
<TabsTrigger value="old" className="text-gray-100">
Old
</TabsTrigger>
<TabsTrigger value="new" className="text-gray-100">
New
</TabsTrigger>
</TabsList>
</Tabs>
</div>
);
}

3
autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/Flow.tsx
View File

@@ -23,6 +23,9 @@ import { useCopyPaste } from "./useCopyPaste";
import { useFlow } from "./useFlow";
import { useFlowRealtime } from "./useFlowRealtime";
import "@xyflow/react/dist/style.css";
import "./flow.css";
export const Flow = () => {
const [{ flowID, flowExecutionID }] = useQueryStates({
flowID: parseAsString,

9
autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/flow.css Normal file
View File

@@ -0,0 +1,9 @@
/* Reset default xyflow handle styles so custom Phosphor icon handles render correctly */
.react-flow__handle {
background: transparent;
width: auto;
height: auto;
border: 0;
position: relative;
transform: none;
}

83
autogpt_platform/frontend/src/app/(platform)/build/components/RIghtSidebar.tsx
View File

@@ -1,83 +0,0 @@
import { useMemo } from "react";
import { Link } from "@/app/api/__generated__/models/link";
import { useEdgeStore } from "../stores/edgeStore";
import { useNodeStore } from "../stores/nodeStore";
import { scrollbarStyles } from "@/components/styles/scrollbars";
import { cn } from "@/lib/utils";
import { customEdgeToLink } from "./helper";
export const RightSidebar = () => {
const edges = useEdgeStore((s) => s.edges);
const nodes = useNodeStore((s) => s.nodes);
const backendLinks: Link[] = useMemo(
() => edges.map(customEdgeToLink),
[edges],
);
return (
<div
className={cn(
"flex h-full w-full flex-col border-l border-slate-200 bg-white p-4 dark:border-slate-700 dark:bg-slate-900",
scrollbarStyles,
)}
>
<div className="mb-4">
<h2 className="text-lg font-semibold text-slate-800 dark:text-slate-200">
Graph Debug Panel
</h2>
</div>
<div className="flex-1 overflow-y-auto">
<h3 className="mb-2 text-sm font-semibold text-slate-700 dark:text-slate-200">
Nodes ({nodes.length})
</h3>
<div className="mb-6 space-y-3">
{nodes.map((n) => (
<div
key={n.id}
className="rounded border p-2 text-xs dark:border-slate-700"
>
<div className="mb-1 font-medium">
#{n.id} {n.data?.title ? `– ${n.data.title}` : ""}
</div>
<div className="text-slate-500 dark:text-slate-400">
hardcodedValues
</div>
<pre className="mt-1 max-h-40 overflow-auto rounded bg-slate-50 p-2 dark:bg-slate-800">
{JSON.stringify(n.data?.hardcodedValues ?? {}, null, 2)}
</pre>
</div>
))}
</div>
<h3 className="mb-2 text-sm font-semibold text-slate-700 dark:text-slate-200">
Links ({backendLinks.length})
</h3>
<div className="mb-6 space-y-3">
{backendLinks.map((l) => (
<div
key={l.id}
className="rounded border p-2 text-xs dark:border-slate-700"
>
<div className="font-medium">
{l.source_id}[{l.source_name}] → {l.sink_id}[{l.sink_name}]
</div>
<div className="mt-1 text-slate-500 dark:text-slate-400">
edge.id: {l.id}
</div>
</div>
))}
</div>
<h4 className="mb-2 text-xs font-semibold text-slate-600 dark:text-slate-300">
Backend Links JSON
</h4>
<pre className="max-h-64 overflow-auto rounded bg-slate-50 p-2 text-[11px] dark:bg-slate-800">
{JSON.stringify(backendLinks, null, 2)}
</pre>
</div>
</div>
);
};

63
autogpt_platform/frontend/src/app/(platform)/build/page.tsx
View File

@@ -1,64 +1,13 @@
"use client";
import FlowEditor from "@/app/(platform)/build/components/legacy-builder/Flow/Flow";
import { useOnboarding } from "@/providers/onboarding/onboarding-provider";
// import LoadingBox from "@/components/__legacy__/ui/loading";
import { GraphID } from "@/lib/autogpt-server-api/types";
import { ReactFlowProvider } from "@xyflow/react";
import { useSearchParams } from "next/navigation";
import { useEffect } from "react";
import { BuilderViewTabs } from "./components/BuilderViewTabs/BuilderViewTabs";
import { Flow } from "./components/FlowEditor/Flow/Flow";
import { useBuilderView } from "./useBuilderView";
function BuilderContent() {
const query = useSearchParams();
const { completeStep } = useOnboarding();
useEffect(() => {
completeStep("BUILDER_OPEN");
}, [completeStep]);
const _graphVersion = query.get("flowVersion");
const graphVersion = _graphVersion ? parseInt(_graphVersion) : undefined;
return (
<FlowEditor
className="flex h-full w-full"
flowID={(query.get("flowID") as GraphID | null) ?? undefined}
flowVersion={graphVersion}
/>
);
}
export default function BuilderPage() {
const {
isSwitchEnabled,
selectedView,
setSelectedView,
isNewFlowEditorEnabled,
} = useBuilderView();
// Switch is temporary, we will remove it once our new flow editor is ready
if (isSwitchEnabled) {
return (
<div className="relative h-full w-full">
<BuilderViewTabs value={selectedView} onChange={setSelectedView} />
{selectedView === "new" ? (
<ReactFlowProvider>
<Flow />
</ReactFlowProvider>
) : (
<BuilderContent />
)}
</div>
);
}
return isNewFlowEditorEnabled ? (
<ReactFlowProvider>
<Flow />
</ReactFlowProvider>
) : (
<BuilderContent />
return (
<div className="relative h-full w-full">
<ReactFlowProvider>
<Flow />
</ReactFlowProvider>
</div>
);
}

44
autogpt_platform/frontend/src/app/(platform)/build/useBuilderView.ts
View File

@@ -1,44 +0,0 @@
import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
import { usePathname, useRouter, useSearchParams } from "next/navigation";
import { useEffect, useMemo } from "react";
import { BuilderView } from "./components/BuilderViewTabs/BuilderViewTabs";
export function useBuilderView() {
const isNewFlowEditorEnabled = useGetFlag(Flag.NEW_FLOW_EDITOR);
const isBuilderViewSwitchEnabled = useGetFlag(Flag.BUILDER_VIEW_SWITCH);
const router = useRouter();
const pathname = usePathname();
const searchParams = useSearchParams();
const currentView = searchParams.get("view");
const defaultView = "old";
const selectedView = useMemo<BuilderView>(() => {
if (currentView === "new" || currentView === "old") return currentView;
return defaultView;
}, [currentView, defaultView]);
useEffect(() => {
if (isBuilderViewSwitchEnabled === true) {
if (currentView !== "new" && currentView !== "old") {
const params = new URLSearchParams(searchParams);
params.set("view", defaultView);
router.replace(`${pathname}?${params.toString()}`);
}
}
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [isBuilderViewSwitchEnabled, defaultView, pathname, router, searchParams]);
const setSelectedView = (value: BuilderView) => {
const params = new URLSearchParams(searchParams);
params.set("view", value);
router.push(`${pathname}?${params.toString()}`);
};
return {
isSwitchEnabled: isBuilderViewSwitchEnabled === true,
selectedView,
setSelectedView,
isNewFlowEditorEnabled: Boolean(isNewFlowEditorEnabled),
} as const;
}

26
autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx
View File

@@ -10,8 +10,9 @@ import {
MessageResponse,
} from "@/components/ai-elements/message";
import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
import { toast } from "@/components/molecules/Toast/use-toast";
import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
import { useEffect, useState } from "react";
import { useEffect, useRef, useState } from "react";
import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent";
import { EditAgentTool } from "../../tools/EditAgent/EditAgent";
import { FindAgentsTool } from "../../tools/FindAgents/FindAgents";
@@ -121,6 +122,7 @@ export const ChatMessagesContainer = ({
isLoading,
}: ChatMessagesContainerProps) => {
const [thinkingPhrase, setThinkingPhrase] = useState(getRandomPhrase);
const lastToastTimeRef = useRef(0);
useEffect(() => {
if (status === "submitted") {
@@ -128,6 +130,20 @@ export const ChatMessagesContainer = ({
}
}, [status]);
// Show a toast when a new error occurs, debounced to avoid spam
useEffect(() => {
if (!error) return;
const now = Date.now();
if (now - lastToastTimeRef.current < 3_000) return;
lastToastTimeRef.current = now;
toast({
variant: "destructive",
title: "Something went wrong",
description:
"The assistant encountered an error. Please try sending your message again.",
});
}, [error]);
const lastMessage = messages[messages.length - 1];
const lastAssistantHasVisibleContent =
lastMessage?.role === "assistant" &&
@@ -263,8 +279,12 @@ export const ChatMessagesContainer = ({
</Message>
)}
{error && (
<div className="rounded-lg bg-red-50 p-3 text-red-600">
Error: {error.message}
<div className="rounded-lg bg-red-50 p-4 text-sm text-red-700">
<p className="font-medium">Something went wrong</p>
<p className="mt-1 text-red-600">
The assistant encountered an error. Please try sending your
message again.
</p>
</div>
)}
</ConversationContent>

3
autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx
View File

@@ -4,7 +4,6 @@ import { WarningDiamondIcon } from "@phosphor-icons/react";
import type { ToolUIPart } from "ai";
import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
import {
ContentCardDescription,
@@ -77,7 +76,7 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
isOperationInProgressOutput(output)
) {
return {
icon: <OrbitLoader size={32} />,
icon,
title: "Creating agent, this may take a few minutes. Sit back and relax.",
};
}

2
autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/helpers.tsx
View File

@@ -203,7 +203,7 @@ export function getAccordionMeta(output: RunAgentToolOutput): {
? output.status.trim()
: "started";
return {
icon: <OrbitLoader size={28} className="text-neutral-700" />,
icon,
title: output.graph_name,
description: `Status: ${statusText}`,
};

2
autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/helpers.tsx
View File

@@ -149,7 +149,7 @@ export function getAccordionMeta(output: RunBlockToolOutput): {
if (isRunBlockBlockOutput(output)) {
const keys = Object.keys(output.outputs ?? {});
return {
icon: <OrbitLoader size={24} className="text-neutral-700" />,
icon,
title: output.block_name,
description:
keys.length > 0

44
autogpt_platform/frontend/src/app/api/chat/sessions/[sessionId]/stream/route.ts
View File

@@ -1,11 +1,8 @@
import { environment } from "@/services/environment";
import { getServerAuthToken } from "@/lib/autogpt-server-api/helpers";
import { NextRequest } from "next/server";
import { normalizeSSEStream, SSE_HEADERS } from "../../../sse-helpers";
/**
* SSE Proxy for chat streaming.
* Supports POST with context (page content + URL) in the request body.
*/
export async function POST(
request: NextRequest,
{ params }: { params: Promise<{ sessionId: string }> },
@@ -23,17 +20,14 @@ export async function POST(
);
}
// Get auth token from server-side session
const token = await getServerAuthToken();
// Build backend URL
const backendUrl = environment.getAGPTServerBaseUrl();
const streamUrl = new URL(
`/api/chat/sessions/${sessionId}/stream`,
backendUrl,
);
// Forward request to backend with auth header
const headers: Record<string, string> = {
"Content-Type": "application/json",
Accept: "text/event-stream",
@@ -63,14 +57,15 @@ export async function POST(
});
}
// Return the SSE stream directly
return new Response(response.body, {
headers: {
"Content-Type": "text/event-stream",
"Cache-Control": "no-cache, no-transform",
Connection: "keep-alive",
"X-Accel-Buffering": "no",
},
if (!response.body) {
return new Response(
JSON.stringify({ error: "Empty response from chat service" }),
{ status: 502, headers: { "Content-Type": "application/json" } },
);
}
return new Response(normalizeSSEStream(response.body), {
headers: SSE_HEADERS,
});
} catch (error) {
console.error("SSE proxy error:", error);
@@ -87,13 +82,6 @@ export async function POST(
}
}
/**
* Resume an active stream for a session.
*
* Called by the AI SDK's `useChat(resume: true)` on page load.
* Proxies to the backend which checks for an active stream and either
* replays it (200 + SSE) or returns 204 No Content.
*/
export async function GET(
_request: NextRequest,
{ params }: { params: Promise<{ sessionId: string }> },
@@ -124,7 +112,6 @@ export async function GET(
headers,
});
// 204 = no active stream to resume
if (response.status === 204) {
return new Response(null, { status: 204 });
}
@@ -137,12 +124,13 @@ export async function GET(
});
}
return new Response(response.body, {
if (!response.body) {
return new Response(null, { status: 204 });
}
return new Response(normalizeSSEStream(response.body), {
headers: {
"Content-Type": "text/event-stream",
"Cache-Control": "no-cache, no-transform",
Connection: "keep-alive",
"X-Accel-Buffering": "no",
...SSE_HEADERS,
"x-vercel-ai-ui-message-stream": "v1",
},
});

72
autogpt_platform/frontend/src/app/api/chat/sse-helpers.ts Normal file
View File

@@ -0,0 +1,72 @@
export const SSE_HEADERS = {
"Content-Type": "text/event-stream",
"Cache-Control": "no-cache, no-transform",
Connection: "keep-alive",
"X-Accel-Buffering": "no",
} as const;
export function normalizeSSEStream(
input: ReadableStream<Uint8Array>,
): ReadableStream<Uint8Array> {
const decoder = new TextDecoder();
const encoder = new TextEncoder();
let buffer = "";
return input.pipeThrough(
new TransformStream<Uint8Array, Uint8Array>({
transform(chunk, controller) {
buffer += decoder.decode(chunk, { stream: true });
const parts = buffer.split("\n\n");
buffer = parts.pop() ?? "";
for (const part of parts) {
const normalized = normalizeSSEEvent(part);
controller.enqueue(encoder.encode(normalized + "\n\n"));
}
},
flush(controller) {
if (buffer.trim()) {
const normalized = normalizeSSEEvent(buffer);
controller.enqueue(encoder.encode(normalized + "\n\n"));
}
},
}),
);
}
function normalizeSSEEvent(event: string): string {
const lines = event.split("\n");
const dataLines: string[] = [];
const otherLines: string[] = [];
for (const line of lines) {
if (line.startsWith("data: ")) {
dataLines.push(line.slice(6));
} else {
otherLines.push(line);
}
}
if (dataLines.length === 0) return event;
const dataStr = dataLines.join("\n");
try {
const parsed = JSON.parse(dataStr) as Record<string, unknown>;
if (parsed.type === "error") {
const normalized = {
type: "error",
errorText:
typeof parsed.errorText === "string"
? parsed.errorText
: "An unexpected error occurred",
};
const newData = `data: ${JSON.stringify(normalized)}`;
return [...otherLines.filter((l) => l.length > 0), newData].join("\n");
}
} catch {
// Not valid JSON — pass through as-is
}
return event;
}

31
autogpt_platform/frontend/src/app/api/chat/tasks/[taskId]/stream/route.ts
View File

@@ -1,20 +1,8 @@
import { environment } from "@/services/environment";
import { getServerAuthToken } from "@/lib/autogpt-server-api/helpers";
import { NextRequest } from "next/server";
import { normalizeSSEStream, SSE_HEADERS } from "../../../sse-helpers";
/**
* SSE Proxy for task stream reconnection.
*
* This endpoint allows clients to reconnect to an ongoing or recently completed
* background task's stream. It replays missed messages from Redis Streams and
* subscribes to live updates if the task is still running.
*
* Client contract:
* 1. When receiving an operation_started event, store the task_id
* 2. To reconnect: GET /api/chat/tasks/{taskId}/stream?last_message_id={idx}
* 3. Messages are replayed from the last_message_id position
* 4. Stream ends when "finish" event is received
*/
export async function GET(
request: NextRequest,
{ params }: { params: Promise<{ taskId: string }> },
@@ -24,15 +12,12 @@ export async function GET(
const lastMessageId = searchParams.get("last_message_id") || "0-0";
try {
// Get auth token from server-side session
const token = await getServerAuthToken();
// Build backend URL
const backendUrl = environment.getAGPTServerBaseUrl();
const streamUrl = new URL(`/api/chat/tasks/${taskId}/stream`, backendUrl);
streamUrl.searchParams.set("last_message_id", lastMessageId);
// Forward request to backend with auth header
const headers: Record<string, string> = {
Accept: "text/event-stream",
"Cache-Control": "no-cache",
@@ -56,14 +41,12 @@ export async function GET(
});
}
// Return the SSE stream directly
return new Response(response.body, {
headers: {
"Content-Type": "text/event-stream",
"Cache-Control": "no-cache, no-transform",
Connection: "keep-alive",
"X-Accel-Buffering": "no",
},
if (!response.body) {
return new Response(null, { status: 204 });
}
return new Response(normalizeSSEStream(response.body), {
headers: SSE_HEADERS,
});
} catch (error) {
console.error("Task stream proxy error:", error);

4
autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts
View File

@@ -10,8 +10,6 @@ export enum Flag {
NEW_AGENT_RUNS = "new-agent-runs",
GRAPH_SEARCH = "graph-search",
ENABLE_ENHANCED_OUTPUT_HANDLING = "enable-enhanced-output-handling",
NEW_FLOW_EDITOR = "new-flow-editor",
BUILDER_VIEW_SWITCH = "builder-view-switch",
SHARE_EXECUTION_RESULTS = "share-execution-results",
AGENT_FAVORITING = "agent-favoriting",
MARKETPLACE_SEARCH_TERMS = "marketplace-search-terms",
@@ -27,8 +25,6 @@ const defaultFlags = {
[Flag.NEW_AGENT_RUNS]: false,
[Flag.GRAPH_SEARCH]: false,
[Flag.ENABLE_ENHANCED_OUTPUT_HANDLING]: false,
[Flag.NEW_FLOW_EDITOR]: false,
[Flag.BUILDER_VIEW_SWITCH]: false,
[Flag.SHARE_EXECUTION_RESULTS]: false,
[Flag.AGENT_FAVORITING]: false,
[Flag.MARKETPLACE_SEARCH_TERMS]: DEFAULT_SEARCH_TERMS,

8
autogpt_platform/frontend/src/tests/agent-activity.spec.ts
View File

@@ -11,24 +11,18 @@ test.beforeEach(async ({ page }) => {
const buildPage = new BuildPage(page);
const testUser = await getTestUser();
const { getId } = getSelectors(page);
await page.goto("/login");
await loginPage.login(testUser.email, testUser.password);
await hasUrl(page, "/marketplace");
await page.goto("/build");
await buildPage.closeTutorial();
await buildPage.openBlocksPanel();
const [dictionaryBlock] = await buildPage.getFilteredBlocksFromAPI(
(block) => block.name === "AddToDictionaryBlock",
);
const blockCard = getId(`block-name-${dictionaryBlock.id}`);
await blockCard.click();
const blockInEditor = getId(dictionaryBlock.id).first();
expect(blockInEditor).toBeAttached();
await buildPage.addBlock(dictionaryBlock);
await buildPage.saveAgent("Test Agent", "Test Description");
await test

5
autogpt_platform/frontend/src/tests/build.spec.ts
View File

@@ -1,3 +1,6 @@
// TODO: These tests were written for the old (legacy) builder.
// They need to be updated to work with the new flow editor.
// Note: all the comments with //(number)! are for the docs
//ignore them when reading the code, but if you change something,
//make sure to update the docs! Your autoformmater will break this page,
@@ -12,7 +15,7 @@ import { getTestUser } from "./utils/auth";
// Reason Ignore: admonishment is in the wrong place visually with correct prettier rules
// prettier-ignore
test.describe("Build", () => { //(1)!
test.describe.skip("Build", () => { //(1)!
let buildPage: BuildPage; //(2)!
// Reason Ignore: admonishment is in the wrong place visually with correct prettier rules

73
autogpt_platform/frontend/src/tests/pages/build.page.ts
View File

@@ -1,7 +1,6 @@
import { expect, Locator, Page } from "@playwright/test";
import { Locator, Page } from "@playwright/test";
import { Block as APIBlock } from "../../lib/autogpt-server-api/types";
import { beautifyString } from "../../lib/utils";
import { isVisible } from "../utils/assertion";
import { BasePage } from "./base.page";
export interface Block {
@@ -27,32 +26,39 @@ export class BuildPage extends BasePage {
try {
await this.page
.getByRole("button", { name: "Skip Tutorial", exact: true })
.click();
} catch (error) {
console.info("Error closing tutorial:", error);
.click({ timeout: 3000 });
} catch (_error) {
console.info("Tutorial not shown or already dismissed");
}
}
async openBlocksPanel(): Promise<void> {
const isPanelOpen = await this.page
.getByTestId("blocks-control-blocks-label")
.isVisible();
const popoverContent = this.page.locator(
'[data-id="blocks-control-popover-content"]',
);
const isPanelOpen = await popoverContent.isVisible();
if (!isPanelOpen) {
await this.page.getByTestId("blocks-control-blocks-button").click();
await popoverContent.waitFor({ state: "visible", timeout: 5000 });
}
}
async closeBlocksPanel(): Promise<void> {
await this.page.getByTestId("profile-popout-menu-trigger").click();
const popoverContent = this.page.locator(
'[data-id="blocks-control-popover-content"]',
);
if (await popoverContent.isVisible()) {
await this.page.getByTestId("blocks-control-blocks-button").click();
}
}
async saveAgent(
name: string = "Test Agent",
description: string = "",
): Promise<void> {
console.log(`💾 Saving agent '${name}' with description '${description}'`);
await this.page.getByTestId("blocks-control-save-button").click();
console.log(`Saving agent '${name}' with description '${description}'`);
await this.page.getByTestId("save-control-save-button").click();
await this.page.getByTestId("save-control-name-input").fill(name);
await this.page
.getByTestId("save-control-description-input")
@@ -107,32 +113,34 @@ export class BuildPage extends BasePage {
await this.openBlocksPanel();
const searchInput = this.page.locator(
'[data-id="blocks-control-search-input"]',
'[data-id="blocks-control-search-bar"] input[type="text"]',
);
const displayName = this.getDisplayName(block.name);
await searchInput.clear();
await searchInput.fill(displayName);
const blockCard = this.page.getByTestId(`block-name-${block.id}`);
const blockCardId = block.id.replace(/[^a-zA-Z0-9]/g, "");
const blockCard = this.page.locator(
`[data-id="block-card-${blockCardId}"]`,
);
try {
// Wait for the block card to be visible with a reasonable timeout
await blockCard.waitFor({ state: "visible", timeout: 10000 });
await blockCard.click();
const blockInEditor = this.page.getByTestId(block.id).first();
expect(blockInEditor).toBeAttached();
} catch (error) {
console.log(
`❌ ❌ Block ${block.name} (display: ${displayName}) returned from the API but not found in block list`,
`Block ${block.name} (display: ${displayName}) returned from the API but not found in block list`,
);
console.log(`Error: ${error}`);
}
}
async hasBlock(block: Block) {
const blockInEditor = this.page.getByTestId(block.id).first();
await blockInEditor.isVisible();
async hasBlock(_block: Block) {
// In the new flow editor, verify a node exists on the canvas
const node = this.page.locator('[data-id^="custom-node-"]').first();
await node.isVisible();
}
async getBlockInputs(blockId: string): Promise<string[]> {
@@ -159,7 +167,7 @@ export class BuildPage extends BasePage {
// Clear any existing search to ensure we see all blocks in the category
const searchInput = this.page.locator(
'[data-id="blocks-control-search-input"]',
'[data-id="blocks-control-search-bar"] input[type="text"]',
);
await searchInput.clear();
@@ -391,13 +399,13 @@ export class BuildPage extends BasePage {
async isRunButtonEnabled(): Promise<boolean> {
console.log(`checking if run button is enabled`);
const runButton = this.page.getByTestId("primary-action-run-agent");
const runButton = this.page.locator('[data-id="run-graph-button"]');
return await runButton.isEnabled();
}
async runAgent(): Promise<void> {
console.log(`clicking run button`);
const runButton = this.page.getByTestId("primary-action-run-agent");
const runButton = this.page.locator('[data-id="run-graph-button"]');
await runButton.click();
await this.page.waitForTimeout(1000);
await runButton.click();
@@ -424,7 +432,7 @@ export class BuildPage extends BasePage {
async waitForSaveButton(): Promise<void> {
console.log(`waiting for save button`);
await this.page.waitForSelector(
'[data-testid="blocks-control-save-button"]:not([disabled])',
'[data-testid="save-control-save-button"]:not([disabled])',
);
}
@@ -526,27 +534,22 @@ export class BuildPage extends BasePage {
async createDummyAgent() {
await this.closeTutorial();
await this.openBlocksPanel();
const dictionaryBlock = await this.getDictionaryBlockDetails();
const searchInput = this.page.locator(
'[data-id="blocks-control-search-input"]',
'[data-id="blocks-control-search-bar"] input[type="text"]',
);
const displayName = this.getDisplayName(dictionaryBlock.name);
await searchInput.clear();
await searchInput.fill("Add to Dictionary");
await isVisible(this.page.getByText("Output"));
await searchInput.fill(displayName);
const blockCard = this.page.getByTestId(`block-name-${dictionaryBlock.id}`);
if (await blockCard.isVisible()) {
const blockCard = this.page.locator('[data-id^="block-card-"]').first();
try {
await blockCard.waitFor({ state: "visible", timeout: 10000 });
await blockCard.click();
const blockInEditor = this.page.getByTestId(dictionaryBlock.id).first();
expect(blockInEditor).toBeAttached();
} catch (error) {
console.log("Could not find Add to Dictionary block:", error);
}
await this.saveAgent("Test Agent", "Test Description");
await expect(this.isRunButtonEnabled()).resolves.toBeTruthy();
}
}

2
docs/integrations/README.md
View File

@@ -61,7 +61,7 @@ Below is a comprehensive list of all available blocks, categorized by their prim
| [Get List Item](block-integrations/basic.md#get-list-item) | Returns the element at the given index |
| [Get Store Agent Details](block-integrations/system/store_operations.md#get-store-agent-details) | Get detailed information about an agent from the store |
| [Get Weather Information](block-integrations/basic.md#get-weather-information) | Retrieves weather information for a specified location using OpenWeatherMap API |
| [Human In The Loop](block-integrations/basic.md#human-in-the-loop) | Pause execution and wait for human approval or modification of data |
| [Human In The Loop](block-integrations/basic.md#human-in-the-loop) | Pause execution for human review |
| [List Is Empty](block-integrations/basic.md#list-is-empty) | Checks if a list is empty |
| [List Library Agents](block-integrations/system/library_operations.md#list-library-agents) | List all agents in your personal library |
| [Note](block-integrations/basic.md#note) | A visual annotation block that displays a sticky note in the workflow editor for documentation and organization purposes |

14
docs/integrations/block-integrations/basic.md
View File

@@ -975,7 +975,7 @@ A travel planning application could use this block to provide users with current
## Human In The Loop
### What it is
Pause execution and wait for human approval or modification of data
Pause execution for human review. Data flows through approved_data or rejected_data output based on the reviewer's decision. Outputs contain the actual data, not status strings.
### How it works
<!-- MANUAL: how_it_works -->
@@ -988,18 +988,18 @@ This enables human oversight at critical points in automated workflows, ensuring
| Input | Description | Type | Required |
|-------|-------------|------|----------|
| data | The data to be reviewed by a human user | Data | Yes |
| name | A descriptive name for what this data represents | str | Yes |
| editable | Whether the human reviewer can edit the data | bool | No |
| data | The data to be reviewed by a human user. This exact data will be passed through to either approved_data or rejected_data output based on the reviewer's decision. | Data | Yes |
| name | A descriptive name for what this data represents. This helps the reviewer understand what they are reviewing. | str | Yes |
| editable | Whether the human reviewer can edit the data before approving or rejecting it | bool | No |
### Outputs
| Output | Description | Type |
|--------|-------------|------|
| error | Error message if the operation failed | str |
| approved_data | The data when approved (may be modified by reviewer) | Approved Data |
| rejected_data | The data when rejected (may be modified by reviewer) | Rejected Data |
| review_message | Any message provided by the reviewer | str |
| approved_data | Outputs the input data when the reviewer APPROVES it. The value is the actual data itself (not a status string like 'APPROVED'). If the reviewer edited the data, this contains the modified version. Connect downstream blocks here for the 'approved' workflow path. | Approved Data |
| rejected_data | Outputs the input data when the reviewer REJECTS it. The value is the actual data itself (not a status string like 'REJECTED'). If the reviewer edited the data, this contains the modified version. Connect downstream blocks here for the 'rejected' workflow path. | Rejected Data |
| review_message | Optional message provided by the reviewer explaining their decision. Only outputs when the reviewer provides a message; this pin does not fire if no message was given. | str |
### Possible use case
<!-- MANUAL: use_case -->