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Merge branch 'dev' into add-llm-manager-ui

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Bently
2026-03-02 10:41:40 +00:00
committed by GitHub
parent 3f78cb95df 1c51dd18aa
commit 7d8414f277
61 changed files with 3008 additions and 1065 deletions
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4
.gitignore vendored
View File

@@ -180,4 +180,6 @@ autogpt_platform/backend/settings.py
.claude/settings.local.json
CLAUDE.local.md
/autogpt_platform/backend/logs
.next
.next
# Implementation plans (generated by AI agents)
plans/

143
.pre-commit-config.yaml
View File

@@ -1,3 +1,10 @@
default_install_hook_types:
- pre-commit
- pre-push
- post-checkout
default_stages: [pre-commit]
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.4.0
@@ -17,6 +24,7 @@ repos:
name: Detect secrets
description: Detects high entropy strings that are likely to be passwords.
files: ^autogpt_platform/
exclude: pnpm-lock\.yaml$
stages: [pre-push]
- repo: local
@@ -26,49 +34,106 @@ repos:
- id: poetry-install
name: Check & Install dependencies - AutoGPT Platform - Backend
alias: poetry-install-platform-backend
entry: poetry -C autogpt_platform/backend install
# include autogpt_libs source (since it's a path dependency)
files: ^autogpt_platform/(backend|autogpt_libs)/poetry\.lock$
types: [file]
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^autogpt_platform/(backend|autogpt_libs)/poetry\.lock$" || exit 0;
poetry -C autogpt_platform/backend install
'
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - AutoGPT Platform - Libs
alias: poetry-install-platform-libs
entry: poetry -C autogpt_platform/autogpt_libs install
files: ^autogpt_platform/autogpt_libs/poetry\.lock$
types: [file]
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^autogpt_platform/autogpt_libs/poetry\.lock$" || exit 0;
poetry -C autogpt_platform/autogpt_libs install
'
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: pnpm-install
name: Check & Install dependencies - AutoGPT Platform - Frontend
alias: pnpm-install-platform-frontend
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^autogpt_platform/frontend/pnpm-lock\.yaml$" || exit 0;
pnpm --prefix autogpt_platform/frontend install
'
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - Classic - AutoGPT
alias: poetry-install-classic-autogpt
entry: poetry -C classic/original_autogpt install
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^classic/(original_autogpt|forge)/poetry\.lock$" || exit 0;
poetry -C classic/original_autogpt install
'
# include forge source (since it's a path dependency)
files: ^classic/(original_autogpt|forge)/poetry\.lock$
types: [file]
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - Classic - Forge
alias: poetry-install-classic-forge
entry: poetry -C classic/forge install
files: ^classic/forge/poetry\.lock$
types: [file]
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^classic/forge/poetry\.lock$" || exit 0;
poetry -C classic/forge install
'
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - Classic - Benchmark
alias: poetry-install-classic-benchmark
entry: poetry -C classic/benchmark install
files: ^classic/benchmark/poetry\.lock$
types: [file]
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^classic/benchmark/poetry\.lock$" || exit 0;
poetry -C classic/benchmark install
'
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- repo: local
# For proper type checking, Prisma client must be up-to-date.
@@ -76,12 +141,54 @@ repos:
- id: prisma-generate
name: Prisma Generate - AutoGPT Platform - Backend
alias: prisma-generate-platform-backend
entry: bash -c 'cd autogpt_platform/backend && poetry run prisma generate'
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^autogpt_platform/((backend|autogpt_libs)/poetry\.lock|backend/schema\.prisma)$" || exit 0;
cd autogpt_platform/backend
&& poetry run prisma generate
&& poetry run gen-prisma-stub
'
# include everything that triggers poetry install + the prisma schema
files: ^autogpt_platform/((backend|autogpt_libs)/poetry\.lock|backend/schema.prisma)$
types: [file]
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: export-api-schema
name: Export API schema - AutoGPT Platform - Backend -> Frontend
alias: export-api-schema-platform
entry: >
bash -c '
cd autogpt_platform/backend
&& poetry run export-api-schema --output ../frontend/src/app/api/openapi.json
&& cd ../frontend
&& pnpm prettier --write ./src/app/api/openapi.json
'
files: ^autogpt_platform/backend/
language: system
pass_filenames: false
- id: generate-api-client
name: Generate API client - AutoGPT Platform - Frontend
alias: generate-api-client-platform-frontend
entry: >
bash -c '
SCHEMA=autogpt_platform/frontend/src/app/api/openapi.json;
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --quiet "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF" -- "$SCHEMA" && exit 0
else
git diff --quiet HEAD -- "$SCHEMA" && exit 0
fi;
cd autogpt_platform/frontend && pnpm generate:api
'
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.7.2

15
autogpt_platform/backend/backend/api/external/middleware.py vendored
View File

@@ -88,20 +88,23 @@ async def require_auth(
)
def require_permission(permission: APIKeyPermission):
def require_permission(*permissions: APIKeyPermission):
"""
Dependency function for checking specific permissions
Dependency function for checking required permissions.
All listed permissions must be present.
(works with API keys and OAuth tokens)
"""
async def check_permission(
async def check_permissions(
auth: APIAuthorizationInfo = Security(require_auth),
) -> APIAuthorizationInfo:
if permission not in auth.scopes:
missing = [p for p in permissions if p not in auth.scopes]
if missing:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=f"Missing required permission: {permission.value}",
detail=f"Missing required permission(s): "
f"{', '.join(p.value for p in missing)}",
)
return auth
return check_permission
return check_permissions

38
autogpt_platform/backend/backend/api/external/v1/routes.py vendored
View File

@@ -18,6 +18,7 @@ from backend.data import user as user_db
from backend.data.auth.base import APIAuthorizationInfo
from backend.data.block import BlockInput, CompletedBlockOutput
from backend.executor.utils import add_graph_execution
from backend.integrations.webhooks.graph_lifecycle_hooks import on_graph_activate
from backend.util.settings import Settings
from .integrations import integrations_router
@@ -95,6 +96,43 @@ async def execute_graph_block(
return output
@v1_router.post(
path="/graphs",
tags=["graphs"],
status_code=201,
dependencies=[
Security(
require_permission(
APIKeyPermission.WRITE_GRAPH, APIKeyPermission.WRITE_LIBRARY
)
)
],
)
async def create_graph(
graph: graph_db.Graph,
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.WRITE_GRAPH, APIKeyPermission.WRITE_LIBRARY)
),
) -> graph_db.GraphModel:
"""
Create a new agent graph.
The graph will be validated and assigned a new ID.
It is automatically added to the user's library.
"""
from backend.api.features.library import db as library_db
graph_model = graph_db.make_graph_model(graph, auth.user_id)
graph_model.reassign_ids(user_id=auth.user_id, reassign_graph_id=True)
graph_model.validate_graph(for_run=False)
await graph_db.create_graph(graph_model, user_id=auth.user_id)
await library_db.create_library_agent(graph_model, auth.user_id)
activated_graph = await on_graph_activate(graph_model, user_id=auth.user_id)
return activated_graph
@v1_router.post(
path="/graphs/{graph_id}/execute/{graph_version}",
tags=["graphs"],

9
autogpt_platform/backend/backend/api/features/chat/routes.py
View File

@@ -621,11 +621,10 @@ async def resume_session_stream(
if not active_session:
return Response(status_code=204)
# Subscribe from the beginning ("0-0") to replay all chunks for this turn.
# This is necessary because hydrated messages filter out incomplete tool calls
# to avoid "No tool invocation found" errors. The resume stream delivers
# those tool calls fresh with proper SDK state.
# The AI SDK's deduplication will handle any duplicate chunks.
# Always replay from the beginning ("0-0") on resume.
# We can't use last_message_id because it's the latest ID in the backend
# stream, not the latest the frontend received — the gap causes lost
# messages. The frontend deduplicates replayed content.
subscriber_queue = await stream_registry.subscribe_to_session(
session_id=session_id,
user_id=user_id,

6
autogpt_platform/backend/backend/cli/generate_openapi_json.py
View File

@@ -34,10 +34,12 @@ def main(output: Path, pretty: bool):
"""Generate and output the OpenAPI JSON specification."""
openapi_schema = get_openapi_schema()
json_output = json.dumps(openapi_schema, indent=2 if pretty else None)
json_output = json.dumps(
openapi_schema, indent=2 if pretty else None, ensure_ascii=False
)
if output:
output.write_text(json_output)
output.write_text(json_output, encoding="utf-8")
click.echo(f"✅ OpenAPI specification written to {output}\n\nPreview:")
click.echo(f"\n{json_output[:500]} ...")
else:

2
autogpt_platform/backend/backend/copilot/config.py
View File

@@ -85,7 +85,7 @@ class ChatConfig(BaseSettings):
)
claude_agent_max_subtasks: int = Field(
default=10,
description="Max number of sub-agent Tasks the SDK can spawn per session.",
description="Max number of concurrent sub-agent Tasks the SDK can run per session.",
)
claude_agent_use_resume: bool = Field(
default=True,

10
autogpt_platform/backend/backend/copilot/executor/manager.py
View File

@@ -4,6 +4,7 @@ This module contains the CoPilotExecutor class that consumes chat tasks from
RabbitMQ and processes them using a thread pool, following the graph executor pattern.
"""
import asyncio
import logging
import os
import threading
@@ -409,14 +410,19 @@ class CoPilotExecutor(AppProcess):
def on_run_done(f: Future):
logger.info(f"Run completed for {session_id}")
error_msg = None
try:
if exec_error := f.exception():
logger.error(f"Execution for {session_id} failed: {exec_error}")
error_msg = str(exec_error) or type(exec_error).__name__
logger.error(f"Execution for {session_id} failed: {error_msg}")
ack_message(reject=True, requeue=False)
else:
ack_message(reject=False, requeue=False)
except asyncio.CancelledError:
logger.info(f"Run completion callback cancelled for {session_id}")
except BaseException as e:
logger.exception(f"Error in run completion callback: {e}")
error_msg = str(e) or type(e).__name__
logger.exception(f"Error in run completion callback: {error_msg}")
finally:
# Release the cluster lock
if session_id in self._task_locks:

92
autogpt_platform/backend/backend/copilot/executor/processor.py
View File

@@ -125,7 +125,10 @@ class CoPilotProcessor:
)
future.result(timeout=5)
except Exception as e:
logger.warning(f"[CoPilotExecutor] Worker {self.tid} cleanup error: {e}")
error_msg = str(e) or type(e).__name__
logger.warning(
f"[CoPilotExecutor] Worker {self.tid} cleanup error: {error_msg}"
)
# Stop the event loop
self.execution_loop.call_soon_threadsafe(self.execution_loop.stop)
@@ -157,47 +160,30 @@ class CoPilotProcessor:
start_time = time.monotonic()
try:
# Run the async execution in our event loop
future = asyncio.run_coroutine_threadsafe(
self._execute_async(entry, cancel, cluster_lock, log),
self.execution_loop,
)
# Run the async execution in our event loop
future = asyncio.run_coroutine_threadsafe(
self._execute_async(entry, cancel, cluster_lock, log),
self.execution_loop,
)
# Wait for completion, checking cancel periodically
while not future.done():
try:
future.result(timeout=1.0)
except asyncio.TimeoutError:
if cancel.is_set():
log.info("Cancellation requested")
future.cancel()
break
# Refresh cluster lock to maintain ownership
cluster_lock.refresh()
if not future.cancelled():
# Get result to propagate any exceptions
future.result()
elapsed = time.monotonic() - start_time
log.info(f"Execution completed in {elapsed:.2f}s")
except BaseException as e:
elapsed = time.monotonic() - start_time
log.error(f"Execution failed after {elapsed:.2f}s: {e}")
# Safety net: if _execute_async's error handler failed to mark
# the session (e.g. RuntimeError from SDK cleanup), do it here.
# Wait for completion, checking cancel periodically
while not future.done():
try:
asyncio.run_coroutine_threadsafe(
stream_registry.mark_session_completed(
entry.session_id, error_message=str(e) or "Unknown error"
),
self.execution_loop,
).result(timeout=5.0)
except Exception as cleanup_err:
log.error(f"Safety net mark_session_completed failed: {cleanup_err}")
raise
future.result(timeout=1.0)
except asyncio.TimeoutError:
if cancel.is_set():
log.info("Cancellation requested")
future.cancel()
break
# Refresh cluster lock to maintain ownership
cluster_lock.refresh()
if not future.cancelled():
# Get result to propagate any exceptions
future.result()
elapsed = time.monotonic() - start_time
log.info(f"Execution completed in {elapsed:.2f}s")
async def _execute_async(
self,
@@ -219,6 +205,7 @@ class CoPilotProcessor:
"""
last_refresh = time.monotonic()
refresh_interval = 30.0 # Refresh lock every 30 seconds
error_msg = None
try:
# Choose service based on LaunchDarkly flag
@@ -264,17 +251,26 @@ class CoPilotProcessor:
exc_info=True,
)
error_message = "Operation cancelled" if cancel.is_set() else None
await stream_registry.mark_session_completed(
entry.session_id, error_message=error_message
)
# Stream loop completed
if cancel.is_set():
log.info("Stream cancelled by user")
except BaseException as e:
log.error(f"Turn failed: {e}")
# Handle all exceptions (including CancelledError) with appropriate logging
if isinstance(e, asyncio.CancelledError):
log.info("Turn cancelled")
error_msg = "Operation cancelled"
else:
error_msg = str(e) or type(e).__name__
log.error(f"Turn failed: {error_msg}")
raise
finally:
# If no exception but user cancelled, still mark as cancelled
if not error_msg and cancel.is_set():
error_msg = "Operation cancelled"
try:
await stream_registry.mark_session_completed(
entry.session_id, error_message=str(e) or "Unknown error"
entry.session_id, error_message=error_msg
)
except Exception as mark_err:
log.error(f"mark_session_completed also failed: {mark_err}")
raise
log.error(f"Failed to mark session completed: {mark_err}")

172
autogpt_platform/backend/backend/copilot/sdk/otel_setup_test.py Normal file
View File

@@ -0,0 +1,172 @@
"""Tests for OTEL tracing setup in the SDK copilot path."""
import os
from unittest.mock import MagicMock, patch
class TestSetupLangfuseOtel:
"""Tests for _setup_langfuse_otel()."""
def test_noop_when_langfuse_not_configured(self):
"""No env vars should be set when Langfuse credentials are missing."""
with patch(
"backend.copilot.sdk.service._is_langfuse_configured", return_value=False
):
from backend.copilot.sdk.service import _setup_langfuse_otel
# Clear any previously set env vars
env_keys = [
"LANGSMITH_OTEL_ENABLED",
"LANGSMITH_OTEL_ONLY",
"LANGSMITH_TRACING",
"OTEL_EXPORTER_OTLP_ENDPOINT",
"OTEL_EXPORTER_OTLP_HEADERS",
]
saved = {k: os.environ.pop(k, None) for k in env_keys}
try:
_setup_langfuse_otel()
for key in env_keys:
assert key not in os.environ, f"{key} should not be set"
finally:
for k, v in saved.items():
if v is not None:
os.environ[k] = v
def test_sets_env_vars_when_langfuse_configured(self):
"""OTEL env vars should be set when Langfuse credentials exist."""
mock_settings = MagicMock()
mock_settings.secrets.langfuse_public_key = "pk-test-123"
mock_settings.secrets.langfuse_secret_key = "sk-test-456"
mock_settings.secrets.langfuse_host = "https://langfuse.example.com"
mock_settings.secrets.langfuse_tracing_environment = "test"
with (
patch(
"backend.copilot.sdk.service._is_langfuse_configured",
return_value=True,
),
patch("backend.copilot.sdk.service.Settings", return_value=mock_settings),
patch(
"backend.copilot.sdk.service.configure_claude_agent_sdk",
return_value=True,
) as mock_configure,
):
from backend.copilot.sdk.service import _setup_langfuse_otel
# Clear env vars so setdefault works
env_keys = [
"LANGSMITH_OTEL_ENABLED",
"LANGSMITH_OTEL_ONLY",
"LANGSMITH_TRACING",
"OTEL_EXPORTER_OTLP_ENDPOINT",
"OTEL_EXPORTER_OTLP_HEADERS",
"OTEL_RESOURCE_ATTRIBUTES",
]
saved = {k: os.environ.pop(k, None) for k in env_keys}
try:
_setup_langfuse_otel()
assert os.environ["LANGSMITH_OTEL_ENABLED"] == "true"
assert os.environ["LANGSMITH_OTEL_ONLY"] == "true"
assert os.environ["LANGSMITH_TRACING"] == "true"
assert (
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"]
== "https://langfuse.example.com/api/public/otel"
)
assert "Authorization=Basic" in os.environ["OTEL_EXPORTER_OTLP_HEADERS"]
assert (
os.environ["OTEL_RESOURCE_ATTRIBUTES"]
== "langfuse.environment=test"
)
mock_configure.assert_called_once_with(tags=["sdk"])
finally:
for k, v in saved.items():
if v is not None:
os.environ[k] = v
elif k in os.environ:
del os.environ[k]
def test_existing_env_vars_not_overwritten(self):
"""Explicit env-var overrides should not be clobbered."""
mock_settings = MagicMock()
mock_settings.secrets.langfuse_public_key = "pk-test"
mock_settings.secrets.langfuse_secret_key = "sk-test"
mock_settings.secrets.langfuse_host = "https://langfuse.example.com"
with (
patch(
"backend.copilot.sdk.service._is_langfuse_configured",
return_value=True,
),
patch("backend.copilot.sdk.service.Settings", return_value=mock_settings),
patch(
"backend.copilot.sdk.service.configure_claude_agent_sdk",
return_value=True,
),
):
from backend.copilot.sdk.service import _setup_langfuse_otel
saved = os.environ.get("OTEL_EXPORTER_OTLP_ENDPOINT")
try:
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://custom.endpoint/v1"
_setup_langfuse_otel()
assert (
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"]
== "https://custom.endpoint/v1"
)
finally:
if saved is not None:
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = saved
elif "OTEL_EXPORTER_OTLP_ENDPOINT" in os.environ:
del os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"]
def test_graceful_failure_on_exception(self):
"""Setup should not raise even if internal code fails."""
with (
patch(
"backend.copilot.sdk.service._is_langfuse_configured",
return_value=True,
),
patch(
"backend.copilot.sdk.service.Settings",
side_effect=RuntimeError("settings unavailable"),
),
):
from backend.copilot.sdk.service import _setup_langfuse_otel
# Should not raise — just logs and returns
_setup_langfuse_otel()
class TestPropagateAttributesImport:
"""Verify langfuse.propagate_attributes is available."""
def test_propagate_attributes_is_importable(self):
from langfuse import propagate_attributes
assert callable(propagate_attributes)
def test_propagate_attributes_returns_context_manager(self):
from langfuse import propagate_attributes
ctx = propagate_attributes(user_id="u1", session_id="s1", tags=["test"])
assert hasattr(ctx, "__enter__")
assert hasattr(ctx, "__exit__")
class TestReceiveResponseCompat:
"""Verify ClaudeSDKClient.receive_response() exists (langsmith patches it)."""
def test_receive_response_exists(self):
from claude_agent_sdk import ClaudeSDKClient
assert hasattr(ClaudeSDKClient, "receive_response")
def test_receive_response_is_async_generator(self):
import inspect
from claude_agent_sdk import ClaudeSDKClient
method = getattr(ClaudeSDKClient, "receive_response")
assert inspect.isfunction(method) or inspect.ismethod(method)

36
autogpt_platform/backend/backend/copilot/sdk/security_hooks.py
View File

@@ -160,7 +160,7 @@ def create_security_hooks(
Args:
user_id: Current user ID for isolation validation
sdk_cwd: SDK working directory for workspace-scoped tool validation
max_subtasks: Maximum Task (sub-agent) spawns allowed per session
max_subtasks: Maximum concurrent Task (sub-agent) spawns allowed per session
on_stop: Callback ``(transcript_path, sdk_session_id)`` invoked when
the SDK finishes processing — used to read the JSONL transcript
before the CLI process exits.
@@ -172,8 +172,9 @@ def create_security_hooks(
from claude_agent_sdk import HookMatcher
from claude_agent_sdk.types import HookContext, HookInput, SyncHookJSONOutput
# Per-session counter for Task sub-agent spawns
task_spawn_count = 0
# Per-session tracking for Task sub-agent concurrency.
# Set of tool_use_ids that consumed a slot — len() is the active count.
task_tool_use_ids: set[str] = set()
async def pre_tool_use_hook(
input_data: HookInput,
@@ -181,7 +182,6 @@ def create_security_hooks(
context: HookContext,
) -> SyncHookJSONOutput:
"""Combined pre-tool-use validation hook."""
nonlocal task_spawn_count
_ = context # unused but required by signature
tool_name = cast(str, input_data.get("tool_name", ""))
tool_input = cast(dict[str, Any], input_data.get("tool_input", {}))
@@ -200,18 +200,18 @@ def create_security_hooks(
"(remove the run_in_background parameter)."
),
)
if task_spawn_count >= max_subtasks:
if len(task_tool_use_ids) >= max_subtasks:
logger.warning(
f"[SDK] Task limit reached ({max_subtasks}), user={user_id}"
)
return cast(
SyncHookJSONOutput,
_deny(
f"Maximum {max_subtasks} sub-tasks per session. "
"Please continue in the main conversation."
f"Maximum {max_subtasks} concurrent sub-tasks. "
"Wait for running sub-tasks to finish, "
"or continue in the main conversation."
),
)
task_spawn_count += 1
# Strip MCP prefix for consistent validation
is_copilot_tool = tool_name.startswith(MCP_TOOL_PREFIX)
@@ -229,9 +229,24 @@ def create_security_hooks(
if result:
return cast(SyncHookJSONOutput, result)
# Reserve the Task slot only after all validations pass
if tool_name == "Task" and tool_use_id is not None:
task_tool_use_ids.add(tool_use_id)
logger.debug(f"[SDK] Tool start: {tool_name}, user={user_id}")
return cast(SyncHookJSONOutput, {})
def _release_task_slot(tool_name: str, tool_use_id: str | None) -> None:
"""Release a Task concurrency slot if one was reserved."""
if tool_name == "Task" and tool_use_id in task_tool_use_ids:
task_tool_use_ids.discard(tool_use_id)
logger.info(
"[SDK] Task slot released, active=%d/%d, user=%s",
len(task_tool_use_ids),
max_subtasks,
user_id,
)
async def post_tool_use_hook(
input_data: HookInput,
tool_use_id: str | None,
@@ -246,6 +261,8 @@ def create_security_hooks(
"""
_ = context
tool_name = cast(str, input_data.get("tool_name", ""))
_release_task_slot(tool_name, tool_use_id)
is_builtin = not tool_name.startswith(MCP_TOOL_PREFIX)
logger.info(
"[SDK] PostToolUse: %s (builtin=%s, tool_use_id=%s)",
@@ -289,6 +306,9 @@ def create_security_hooks(
f"[SDK] Tool failed: {tool_name}, error={error}, "
f"user={user_id}, tool_use_id={tool_use_id}"
)
_release_task_slot(tool_name, tool_use_id)
return cast(SyncHookJSONOutput, {})
async def pre_compact_hook(

105
autogpt_platform/backend/backend/copilot/sdk/security_hooks_test.py
View File

@@ -208,19 +208,22 @@ def test_bash_builtin_blocked_message_clarity():
@pytest.fixture()
def _hooks():
"""Create security hooks and return the PreToolUse handler."""
"""Create security hooks and return (pre, post, post_failure) handlers."""
from .security_hooks import create_security_hooks
hooks = create_security_hooks(user_id="u1", sdk_cwd=SDK_CWD, max_subtasks=2)
pre = hooks["PreToolUse"][0].hooks[0]
return pre
post = hooks["PostToolUse"][0].hooks[0]
post_failure = hooks["PostToolUseFailure"][0].hooks[0]
return pre, post, post_failure
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_task_background_blocked(_hooks):
"""Task with run_in_background=true must be denied."""
result = await _hooks(
pre, _, _ = _hooks
result = await pre(
{"tool_name": "Task", "tool_input": {"run_in_background": True, "prompt": "x"}},
tool_use_id=None,
context={},
@@ -233,9 +236,10 @@ async def test_task_background_blocked(_hooks):
@pytest.mark.asyncio
async def test_task_foreground_allowed(_hooks):
"""Task without run_in_background should be allowed."""
result = await _hooks(
pre, _, _ = _hooks
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "do stuff"}},
tool_use_id=None,
tool_use_id="tu-1",
context={},
)
assert not _is_denied(result)
@@ -245,25 +249,102 @@ async def test_task_foreground_allowed(_hooks):
@pytest.mark.asyncio
async def test_task_limit_enforced(_hooks):
"""Task spawns beyond max_subtasks should be denied."""
pre, _, _ = _hooks
# First two should pass
for _ in range(2):
result = await _hooks(
for i in range(2):
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "ok"}},
tool_use_id=None,
tool_use_id=f"tu-limit-{i}",
context={},
)
assert not _is_denied(result)
# Third should be denied (limit=2)
result = await _hooks(
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "over limit"}},
tool_use_id=None,
tool_use_id="tu-limit-2",
context={},
)
assert _is_denied(result)
assert "Maximum" in _reason(result)
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_task_slot_released_on_completion(_hooks):
"""Completing a Task should free a slot so new Tasks can be spawned."""
pre, post, _ = _hooks
# Fill both slots
for i in range(2):
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "ok"}},
tool_use_id=f"tu-comp-{i}",
context={},
)
assert not _is_denied(result)
# Third should be denied — at capacity
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "over"}},
tool_use_id="tu-comp-2",
context={},
)
assert _is_denied(result)
# Complete first task — frees a slot
await post(
{"tool_name": "Task", "tool_input": {}},
tool_use_id="tu-comp-0",
context={},
)
# Now a new Task should be allowed
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "after release"}},
tool_use_id="tu-comp-3",
context={},
)
assert not _is_denied(result)
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_task_slot_released_on_failure(_hooks):
"""A failed Task should also free its concurrency slot."""
pre, _, post_failure = _hooks
# Fill both slots
for i in range(2):
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "ok"}},
tool_use_id=f"tu-fail-{i}",
context={},
)
assert not _is_denied(result)
# At capacity
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "over"}},
tool_use_id="tu-fail-2",
context={},
)
assert _is_denied(result)
# Fail first task — should free a slot
await post_failure(
{"tool_name": "Task", "tool_input": {}, "error": "something broke"},
tool_use_id="tu-fail-0",
context={},
)
# New Task should be allowed
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "after failure"}},
tool_use_id="tu-fail-3",
context={},
)
assert not _is_denied(result)
# -- _is_tool_error_or_denial ------------------------------------------------
@@ -298,7 +379,9 @@ class TestIsToolErrorOrDenial:
def test_subtask_limit_denial(self):
assert (
_is_tool_error_or_denial(
"Maximum 2 sub-tasks per session. Please continue in the main conversation."
"Maximum 2 concurrent sub-tasks. "
"Wait for running sub-tasks to finish, "
"or continue in the main conversation."
)
is True
)

310
autogpt_platform/backend/backend/copilot/sdk/service.py
View File

@@ -1,17 +1,23 @@
"""Claude Agent SDK service layer for CoPilot chat completions."""
import asyncio
import base64
import json
import logging
import os
import sys
import uuid
from collections.abc import AsyncGenerator
from dataclasses import dataclass
from typing import Any, cast
from langfuse import propagate_attributes
from langsmith.integrations.claude_agent_sdk import configure_claude_agent_sdk
from backend.data.redis_client import get_redis_async
from backend.executor.cluster_lock import AsyncClusterLock
from backend.util.exceptions import NotFoundError
from backend.util.settings import Settings
from ..config import ChatConfig
from ..model import (
@@ -31,7 +37,11 @@ from ..response_model import (
StreamToolInputAvailable,
StreamToolOutputAvailable,
)
from ..service import _build_system_prompt, _generate_session_title
from ..service import (
_build_system_prompt,
_generate_session_title,
_is_langfuse_configured,
)
from ..tools.sandbox import WORKSPACE_PREFIX, make_session_path
from ..tracking import track_user_message
from .response_adapter import SDKResponseAdapter
@@ -56,6 +66,55 @@ logger = logging.getLogger(__name__)
config = ChatConfig()
def _setup_langfuse_otel() -> None:
"""Configure OTEL tracing for the Claude Agent SDK → Langfuse.
This uses LangSmith's built-in Claude Agent SDK integration to monkey-patch
``ClaudeSDKClient``, capturing every tool call and model turn as OTEL spans.
Spans are exported via OTLP to Langfuse (or any OTEL-compatible backend).
To route traces elsewhere, override ``OTEL_EXPORTER_OTLP_ENDPOINT`` and
``OTEL_EXPORTER_OTLP_HEADERS`` environment variables — no code changes needed.
"""
if not _is_langfuse_configured():
return
try:
settings = Settings()
pk = settings.secrets.langfuse_public_key
sk = settings.secrets.langfuse_secret_key
host = settings.secrets.langfuse_host
# OTEL exporter config — these are only set if not already present,
# so explicit env-var overrides always win.
creds = base64.b64encode(f"{pk}:{sk}".encode()).decode()
os.environ.setdefault("LANGSMITH_OTEL_ENABLED", "true")
os.environ.setdefault("LANGSMITH_OTEL_ONLY", "true")
os.environ.setdefault("LANGSMITH_TRACING", "true")
os.environ.setdefault("OTEL_EXPORTER_OTLP_ENDPOINT", f"{host}/api/public/otel")
os.environ.setdefault(
"OTEL_EXPORTER_OTLP_HEADERS", f"Authorization=Basic {creds}"
)
# Set the Langfuse environment via OTEL resource attributes so the
# Langfuse server maps it to the first-class environment field.
tracing_env = settings.secrets.langfuse_tracing_environment
os.environ.setdefault(
"OTEL_RESOURCE_ATTRIBUTES",
f"langfuse.environment={tracing_env}",
)
configure_claude_agent_sdk(tags=["sdk"])
logger.info(
"OTEL tracing configured for Claude Agent SDK → %s [%s]", host, tracing_env
)
except Exception:
logger.warning("OTEL setup skipped — failed to configure", exc_info=True)
_setup_langfuse_otel()
# Set to hold background tasks to prevent garbage collection
_background_tasks: set[asyncio.Task[Any]] = set()
@@ -75,14 +134,21 @@ class CapturedTranscript:
_SDK_CWD_PREFIX = WORKSPACE_PREFIX
# Special message prefixes for text-based markers (parsed by frontend)
COPILOT_ERROR_PREFIX = "[COPILOT_ERROR]" # Renders as ErrorCard
COPILOT_SYSTEM_PREFIX = "[COPILOT_SYSTEM]" # Renders as system info message
# Heartbeat interval — keep SSE alive through proxies/LBs during tool execution.
# IMPORTANT: Must be less than frontend timeout (12s in useCopilotPage.ts)
_HEARTBEAT_INTERVAL = 10.0 # seconds
# Appended to the system prompt to inform the agent about available tools.
# The SDK built-in Bash is NOT available — use mcp__copilot__bash_exec instead,
# which has kernel-level network isolation (unshare --net).
_SDK_TOOL_SUPPLEMENT = """
def _build_sdk_tool_supplement(cwd: str) -> str:
"""Build the SDK tool supplement with the actual working directory injected."""
return f"""
## Tool notes
@@ -90,9 +156,16 @@ _SDK_TOOL_SUPPLEMENT = """
- The SDK built-in Bash tool is NOT available. Use the `bash_exec` MCP tool
for shell commands — it runs in a network-isolated sandbox.
### Working directory
- Your working directory is: `{cwd}`
- All SDK Read/Write/Edit/Glob/Grep tools AND `bash_exec` operate inside this
directory. This is the ONLY writable path — do not attempt to read or write
anywhere else on the filesystem.
- Use relative paths or absolute paths under `{cwd}` for all file operations.
### Two storage systems — CRITICAL to understand
1. **Ephemeral working directory** (`/tmp/copilot-<session>/`):
1. **Ephemeral working directory** (`{cwd}`):
- Shared by SDK Read/Write/Edit/Glob/Grep tools AND `bash_exec`
- Files here are **lost between turns** — do NOT rely on them persisting
- Use for temporary work: running scripts, processing data, etc.
@@ -118,6 +191,21 @@ When you create or modify important files (code, configs, outputs), you MUST:
2. At the start of a new turn, call `list_workspace_files` to see what files
are available from previous turns
### Sharing files with the user
After saving a file to the persistent workspace with `write_workspace_file`,
share it with the user by embedding the `download_url` from the response in
your message as a Markdown link or image:
- **Any file** — shows as a clickable download link:
`[report.csv](workspace://file_id#text/csv)`
- **Image** — renders inline in chat:
`![chart](workspace://file_id#image/png)`
- **Video** — renders inline in chat with player controls:
`![recording](workspace://file_id#video/mp4)`
The `download_url` field in the `write_workspace_file` response is already
in the correct format — paste it directly after the `(` in the Markdown.
### Long-running tools
Long-running tools (create_agent, edit_agent, etc.) are handled
asynchronously. You will receive an immediate response; the actual result
@@ -128,6 +216,7 @@ is delivered to the user via a background stream.
All tasks must run in the foreground.
"""
STREAM_LOCK_PREFIX = "copilot:stream:lock:"
@@ -413,6 +502,20 @@ async def stream_chat_completion_sdk(
# Type narrowing: session is guaranteed ChatSession after the check above
session = cast(ChatSession, session)
# Clean up stale error markers from previous turn before starting new turn
# If the last message contains an error marker, remove it (user is retrying)
if (
len(session.messages) > 0
and session.messages[-1].role == "assistant"
and session.messages[-1].content
and COPILOT_ERROR_PREFIX in session.messages[-1].content
):
logger.info(
"[SDK] [%s] Removing stale error marker from previous turn",
session_id[:12],
)
session.messages.pop()
# Append the new message to the session if it's not already there
new_message_role = "user" if is_user_message else "assistant"
if message and (
@@ -442,14 +545,13 @@ async def stream_chat_completion_sdk(
_background_tasks.add(task)
task.add_done_callback(_background_tasks.discard)
# Build system prompt (reuses non-SDK path with Langfuse support)
has_history = len(session.messages) > 1
system_prompt, _ = await _build_system_prompt(
user_id, has_conversation_history=has_history
)
system_prompt += _SDK_TOOL_SUPPLEMENT
message_id = str(uuid.uuid4())
stream_id = str(uuid.uuid4())
stream_completed = False
use_resume = False
resume_file: str | None = None
captured_transcript = CapturedTranscript()
sdk_cwd = ""
# Acquire stream lock to prevent concurrent streams to the same session
lock = AsyncClusterLock(
@@ -472,21 +574,33 @@ async def stream_chat_completion_sdk(
)
return
yield StreamStart(messageId=message_id, sessionId=session_id)
stream_completed = False
# Initialise variables before the try so the finally block can
# always attempt transcript upload regardless of errors.
sdk_cwd = ""
use_resume = False
resume_file: str | None = None
captured_transcript = CapturedTranscript()
# OTEL context manager — initialized inside the try and cleaned up in finally.
_otel_ctx: Any = None
# Make sure there is no more code between the lock acquitition and try-block.
try:
# Use a session-specific temp dir to avoid cleanup race conditions
# between concurrent sessions.
sdk_cwd = _make_sdk_cwd(session_id)
os.makedirs(sdk_cwd, exist_ok=True)
# Build system prompt (reuses non-SDK path with Langfuse support).
# Pre-compute the cwd here so the exact working directory path can be
# injected into the supplement instead of the generic placeholder.
# Catch ValueError early so the failure yields a clean StreamError rather
# than propagating outside the stream error-handling path.
has_history = len(session.messages) > 1
try:
sdk_cwd = _make_sdk_cwd(session_id)
os.makedirs(sdk_cwd, exist_ok=True)
except (ValueError, OSError) as e:
logger.error("[SDK] [%s] Invalid SDK cwd: %s", session_id[:12], e)
yield StreamError(
errorText="Unable to initialize working directory.",
code="sdk_cwd_error",
)
return
system_prompt, _ = await _build_system_prompt(
user_id, has_conversation_history=has_history
)
system_prompt += _build_sdk_tool_supplement(sdk_cwd)
yield StreamStart(messageId=message_id, sessionId=session_id)
set_execution_context(user_id, session)
try:
@@ -581,6 +695,19 @@ async def stream_chat_completion_sdk(
adapter = SDKResponseAdapter(message_id=message_id, session_id=session_id)
# Propagate user_id/session_id as OTEL context attributes so the
# langsmith tracing integration attaches them to every span. This
# is what Langfuse (or any OTEL backend) maps to its native
# user/session fields.
_otel_ctx = propagate_attributes(
user_id=user_id,
session_id=session_id,
trace_name="copilot-sdk",
tags=["sdk"],
metadata={"resume": str(use_resume)},
)
_otel_ctx.__enter__()
async with ClaudeSDKClient(options=options) as client:
current_message = message or ""
if not current_message and session.messages:
@@ -624,7 +751,7 @@ async def stream_chat_completion_sdk(
# Instead, wrap __anext__() in a Task and use asyncio.wait()
# with a timeout. On timeout we emit a heartbeat but keep the
# Task alive so it can deliver the next message.
msg_iter = client.receive_messages().__aiter__()
msg_iter = client.receive_response().__aiter__()
pending_task: asyncio.Task[Any] | None = None
try:
while not stream_completed:
@@ -658,7 +785,7 @@ async def stream_chat_completion_sdk(
break
except Exception as stream_err:
# SDK sends {"type": "error"} which raises
# Exception in receive_messages() — capture it
# Exception in receive_response() — capture it
# so the session can still be saved and the
# frontend gets a clean finish.
logger.error(
@@ -725,6 +852,25 @@ async def stream_chat_completion_sdk(
- len(adapter.resolved_tool_calls),
)
# Log ResultMessage details for debugging
if isinstance(sdk_msg, ResultMessage):
logger.info(
"[SDK] [%s] Received: ResultMessage %s "
"(unresolved=%d, current=%d, resolved=%d)",
session_id[:12],
sdk_msg.subtype,
len(adapter.current_tool_calls)
- len(adapter.resolved_tool_calls),
len(adapter.current_tool_calls),
len(adapter.resolved_tool_calls),
)
if sdk_msg.subtype in ("error", "error_during_execution"):
logger.error(
"[SDK] [%s] SDK execution failed with error: %s",
session_id[:12],
sdk_msg.result or "(no error message provided)",
)
for response in adapter.convert_message(sdk_msg):
if isinstance(response, StreamStart):
continue
@@ -749,6 +895,15 @@ async def stream_chat_completion_sdk(
extra,
)
# Log errors being sent to frontend
if isinstance(response, StreamError):
logger.error(
"[SDK] [%s] Sending error to frontend: %s (code=%s)",
session_id[:12],
response.errorText,
response.code,
)
yield response
if isinstance(response, StreamTextDelta):
@@ -855,13 +1010,13 @@ async def stream_chat_completion_sdk(
yield response
# If the stream ended without a ResultMessage, the SDK
# CLI exited unexpectedly. Close any open text/step so
# the chunks are well-formed. StreamFinish is published
# by mark_session_completed in the processor.
# CLI exited unexpectedly or the user stopped execution.
# Close any open text/step so chunks are well-formed, and
# append a cancellation message so users see feedback.
# StreamFinish is published by mark_session_completed in the processor.
if not stream_completed:
logger.warning(
"[SDK] [%s] Stream ended without ResultMessage "
"(StopAsyncIteration)",
logger.info(
"[SDK] [%s] Stream ended without ResultMessage (stopped by user)",
session_id[:12],
)
closing_responses: list[StreamBaseResponse] = []
@@ -869,6 +1024,15 @@ async def stream_chat_completion_sdk(
for r in closing_responses:
yield r
# Add "Stopped by user" message so it persists after refresh
# Use COPILOT_SYSTEM_PREFIX so frontend renders it as system message, not assistant
session.messages.append(
ChatMessage(
role="assistant",
content=f"{COPILOT_SYSTEM_PREFIX} Execution stopped by user",
)
)
if (
assistant_response.content or assistant_response.tool_calls
) and not has_appended_assistant:
@@ -922,43 +1086,83 @@ async def stream_chat_completion_sdk(
"to use the OpenAI-compatible fallback."
)
session = cast(ChatSession, await asyncio.shield(upsert_chat_session(session)))
logger.info(
"[SDK] [%s] Session saved with %d messages",
"[SDK] [%s] Stream completed successfully with %d messages",
session_id[:12],
len(session.messages),
)
except asyncio.CancelledError:
# Client disconnect / server shutdown — save session before re-raising
# so accumulated messages aren't lost.
logger.warning("[SDK] [%s] Session cancelled (CancelledError)", session_id[:12])
except BaseException as e:
# Catch BaseException to handle both Exception and CancelledError
# (CancelledError inherits from BaseException in Python 3.8+)
if isinstance(e, asyncio.CancelledError):
logger.warning("[SDK] [%s] Session cancelled", session_id[:12])
error_msg = "Operation cancelled"
else:
error_msg = str(e) or type(e).__name__
# SDK cleanup RuntimeError is expected during cancellation, log as warning
if isinstance(e, RuntimeError) and "cancel scope" in str(e):
logger.warning(
"[SDK] [%s] SDK cleanup error: %s", session_id[:12], error_msg
)
else:
logger.error(
f"[SDK] [%s] Error: {error_msg}", session_id[:12], exc_info=True
)
# Append error marker to session (non-invasive text parsing approach)
# The finally block will persist the session with this error marker
if session:
session.messages.append(
ChatMessage(
role="assistant", content=f"{COPILOT_ERROR_PREFIX} {error_msg}"
)
)
logger.debug(
"[SDK] [%s] Appended error marker, will be persisted in finally",
session_id[:12],
)
# Yield StreamError for immediate feedback (only for non-cancellation errors)
# Skip for CancelledError and RuntimeError cleanup issues (both are cancellations)
is_cancellation = isinstance(e, asyncio.CancelledError) or (
isinstance(e, RuntimeError) and "cancel scope" in str(e)
)
if not is_cancellation:
yield StreamError(
errorText=error_msg,
code="sdk_error",
)
raise
finally:
# --- Close OTEL context ---
if _otel_ctx is not None:
try:
_otel_ctx.__exit__(*sys.exc_info())
except Exception:
logger.warning("OTEL context teardown failed", exc_info=True)
# --- Persist session messages ---
# This MUST run in finally to persist messages even when the generator
# is stopped early (e.g., user clicks stop, processor breaks stream loop).
# Without this, messages disappear after refresh because they were never
# saved to the database.
if session is not None:
try:
await asyncio.shield(upsert_chat_session(session))
logger.info(
"[SDK] [%s] Session saved on cancel (%d messages)",
"[SDK] [%s] Session persisted in finally with %d messages",
session_id[:12],
len(session.messages),
)
except Exception as save_err:
except Exception as persist_err:
logger.error(
"[SDK] [%s] Failed to save session on cancel: %s",
"[SDK] [%s] Failed to persist session in finally: %s",
session_id[:12],
save_err,
persist_err,
exc_info=True,
)
raise
except Exception as e:
logger.error(f"[SDK] Error: {e}", exc_info=True)
if session:
try:
await asyncio.shield(upsert_chat_session(session))
except Exception as save_err:
logger.error(f"[SDK] Failed to save session on error: {save_err}")
yield StreamError(
errorText="An error occurred. Please try again.",
code="sdk_error",
)
finally:
# --- Upload transcript for next-turn --resume ---
# This MUST run in finally so the transcript is uploaded even when
# the streaming loop raises an exception. The CLI uses

1
autogpt_platform/backend/backend/copilot/stream_registry.py
View File

@@ -707,7 +707,6 @@ async def mark_session_completed(
True if session was newly marked completed, False if already completed/failed
"""
status: Literal["completed", "failed"] = "failed" if error_message else "completed"
redis = await get_redis_async()
meta_key = _get_session_meta_key(session_id)

84
autogpt_platform/backend/backend/copilot/tools/agent_output.py
View File

@@ -5,7 +5,7 @@ import re
from datetime import datetime, timedelta, timezone
from typing import Any
from pydantic import BaseModel, field_validator
from pydantic import BaseModel, Field, field_validator
from backend.api.features.library.model import LibraryAgent
from backend.copilot.model import ChatSession
@@ -13,6 +13,7 @@ from backend.data.db_accessors import execution_db, library_db
from backend.data.execution import ExecutionStatus, GraphExecution, GraphExecutionMeta
from .base import BaseTool
from .execution_utils import TERMINAL_STATUSES, wait_for_execution
from .models import (
AgentOutputResponse,
ErrorResponse,
@@ -33,6 +34,7 @@ class AgentOutputInput(BaseModel):
store_slug: str = ""
execution_id: str = ""
run_time: str = "latest"
wait_if_running: int = Field(default=0, ge=0, le=300)
@field_validator(
"agent_name",
@@ -116,6 +118,11 @@ class AgentOutputTool(BaseTool):
Select which run to retrieve using:
- execution_id: Specific execution ID
- run_time: 'latest' (default), 'yesterday', 'last week', or ISO date 'YYYY-MM-DD'
Wait for completion (optional):
- wait_if_running: Max seconds to wait if execution is still running (0-300).
If the execution is running/queued, waits up to this many seconds for completion.
Returns current status on timeout. If already finished, returns immediately.
"""
@property
@@ -145,6 +152,13 @@ class AgentOutputTool(BaseTool):
"Time filter: 'latest', 'yesterday', 'last week', or 'YYYY-MM-DD'"
),
},
"wait_if_running": {
"type": "integer",
"description": (
"Max seconds to wait if execution is still running (0-300). "
"If running, waits for completion. Returns current state on timeout."
),
},
},
"required": [],
}
@@ -224,10 +238,14 @@ class AgentOutputTool(BaseTool):
execution_id: str | None,
time_start: datetime | None,
time_end: datetime | None,
include_running: bool = False,
) -> tuple[GraphExecution | None, list[GraphExecutionMeta], str | None]:
"""
Fetch execution(s) based on filters.
Returns (single_execution, available_executions_meta, error_message).
Args:
include_running: If True, also look for running/queued executions (for waiting)
"""
exec_db = execution_db()
@@ -242,11 +260,25 @@ class AgentOutputTool(BaseTool):
return None, [], f"Execution '{execution_id}' not found"
return execution, [], None
# Get completed executions with time filters
# Determine which statuses to query
statuses = [ExecutionStatus.COMPLETED]
if include_running:
statuses.extend(
[
ExecutionStatus.RUNNING,
ExecutionStatus.QUEUED,
ExecutionStatus.INCOMPLETE,
ExecutionStatus.REVIEW,
ExecutionStatus.FAILED,
ExecutionStatus.TERMINATED,
]
)
# Get executions with time filters
executions = await exec_db.get_graph_executions(
graph_id=graph_id,
user_id=user_id,
statuses=[ExecutionStatus.COMPLETED],
statuses=statuses,
created_time_gte=time_start,
created_time_lte=time_end,
limit=10,
@@ -313,10 +345,33 @@ class AgentOutputTool(BaseTool):
for e in available_executions[:5]
]
message = f"Found execution outputs for agent '{agent.name}'"
# Build appropriate message based on execution status
if execution.status == ExecutionStatus.COMPLETED:
message = f"Found execution outputs for agent '{agent.name}'"
elif execution.status == ExecutionStatus.FAILED:
message = f"Execution for agent '{agent.name}' failed"
elif execution.status == ExecutionStatus.TERMINATED:
message = f"Execution for agent '{agent.name}' was terminated"
elif execution.status == ExecutionStatus.REVIEW:
message = (
f"Execution for agent '{agent.name}' is awaiting human review. "
"The user needs to approve it before it can continue."
)
elif execution.status in (
ExecutionStatus.RUNNING,
ExecutionStatus.QUEUED,
ExecutionStatus.INCOMPLETE,
):
message = (
f"Execution for agent '{agent.name}' is still {execution.status.value}. "
"Results may be incomplete. Use wait_if_running to wait for completion."
)
else:
message = f"Found execution for agent '{agent.name}' (status: {execution.status.value})"
if len(available_executions) > 1:
message += (
f". Showing latest of {len(available_executions)} matching executions."
f" Showing latest of {len(available_executions)} matching executions."
)
return AgentOutputResponse(
@@ -431,13 +486,17 @@ class AgentOutputTool(BaseTool):
# Parse time expression
time_start, time_end = parse_time_expression(input_data.run_time)
# Fetch execution(s)
# Check if we should wait for running executions
wait_timeout = input_data.wait_if_running
# Fetch execution(s) - include running if we're going to wait
execution, available_executions, exec_error = await self._get_execution(
user_id=user_id,
graph_id=agent.graph_id,
execution_id=input_data.execution_id or None,
time_start=time_start,
time_end=time_end,
include_running=wait_timeout > 0,
)
if exec_error:
@@ -446,4 +505,17 @@ class AgentOutputTool(BaseTool):
session_id=session_id,
)
# If we have an execution that's still running and we should wait
if execution and wait_timeout > 0 and execution.status not in TERMINAL_STATUSES:
logger.info(
f"Execution {execution.id} is {execution.status}, "
f"waiting up to {wait_timeout}s for completion"
)
execution = await wait_for_execution(
user_id=user_id,
graph_id=agent.graph_id,
execution_id=execution.id,
timeout_seconds=wait_timeout,
)
return self._build_response(agent, execution, available_executions, session_id)

245
autogpt_platform/backend/backend/copilot/tools/agent_search.py
View File

@@ -1,8 +1,13 @@
"""Shared agent search functionality for find_agent and find_library_agent tools."""
from __future__ import annotations
import logging
import re
from typing import Literal
from typing import TYPE_CHECKING, Literal
if TYPE_CHECKING:
from backend.api.features.library.model import LibraryAgent
from backend.data.db_accessors import library_db, store_db
from backend.util.exceptions import DatabaseError, NotFoundError
@@ -24,94 +29,24 @@ _UUID_PATTERN = re.compile(
re.IGNORECASE,
)
def _is_uuid(text: str) -> bool:
"""Check if text is a valid UUID v4."""
return bool(_UUID_PATTERN.match(text.strip()))
async def _get_library_agent_by_id(user_id: str, agent_id: str) -> AgentInfo | None:
"""Fetch a library agent by ID (library agent ID or graph_id).
Tries multiple lookup strategies:
1. First by graph_id (AgentGraph primary key)
2. Then by library agent ID (LibraryAgent primary key)
Args:
user_id: The user ID
agent_id: The ID to look up (can be graph_id or library agent ID)
Returns:
AgentInfo if found, None otherwise
"""
lib_db = library_db()
try:
agent = await lib_db.get_library_agent_by_graph_id(user_id, agent_id)
if agent:
logger.debug(f"Found library agent by graph_id: {agent.name}")
return AgentInfo(
id=agent.id,
name=agent.name,
description=agent.description or "",
source="library",
in_library=True,
creator=agent.creator_name,
status=agent.status.value,
can_access_graph=agent.can_access_graph,
has_external_trigger=agent.has_external_trigger,
new_output=agent.new_output,
graph_id=agent.graph_id,
)
except DatabaseError:
raise
except Exception as e:
logger.warning(
f"Could not fetch library agent by graph_id {agent_id}: {e}",
exc_info=True,
)
try:
agent = await lib_db.get_library_agent(agent_id, user_id)
if agent:
logger.debug(f"Found library agent by library_id: {agent.name}")
return AgentInfo(
id=agent.id,
name=agent.name,
description=agent.description or "",
source="library",
in_library=True,
creator=agent.creator_name,
status=agent.status.value,
can_access_graph=agent.can_access_graph,
has_external_trigger=agent.has_external_trigger,
new_output=agent.new_output,
graph_id=agent.graph_id,
)
except NotFoundError:
logger.debug(f"Library agent not found by library_id: {agent_id}")
except DatabaseError:
raise
except Exception as e:
logger.warning(
f"Could not fetch library agent by library_id {agent_id}: {e}",
exc_info=True,
)
return None
# Keywords that should be treated as "list all" rather than a literal search
_LIST_ALL_KEYWORDS = frozenset({"all", "*", "everything", "any", ""})
async def search_agents(
query: str,
source: SearchSource,
session_id: str | None,
session_id: str | None = None,
user_id: str | None = None,
) -> ToolResponseBase:
"""
Search for agents in marketplace or user library.
For library searches, keywords like "all", "*", "everything", or an empty
query will list all agents without filtering.
Args:
query: Search query string
query: Search query string. Special keywords list all library agents.
source: "marketplace" or "library"
session_id: Chat session ID
user_id: User ID (required for library search)
@@ -119,7 +54,11 @@ async def search_agents(
Returns:
AgentsFoundResponse, NoResultsResponse, or ErrorResponse
"""
if not query:
# Normalize list-all keywords to empty string for library searches
if source == "library" and query.lower().strip() in _LIST_ALL_KEYWORDS:
query = ""
if source == "marketplace" and not query:
return ErrorResponse(
message="Please provide a search query", session_id=session_id
)
@@ -159,28 +98,18 @@ async def search_agents(
logger.info(f"Found agent by direct ID lookup: {agent.name}")
if not agents:
logger.info(f"Searching user library for: {query}")
search_term = query or None
logger.info(
f"{'Listing all agents in' if not query else 'Searching'} "
f"user library{'' if not query else f' for: {query}'}"
)
results = await library_db().list_library_agents(
user_id=user_id, # type: ignore[arg-type]
search_term=query,
page_size=10,
search_term=search_term,
page_size=50 if not query else 10,
)
for agent in results.agents:
agents.append(
AgentInfo(
id=agent.id,
name=agent.name,
description=agent.description or "",
source="library",
in_library=True,
creator=agent.creator_name,
status=agent.status.value,
can_access_graph=agent.can_access_graph,
has_external_trigger=agent.has_external_trigger,
new_output=agent.new_output,
graph_id=agent.graph_id,
)
)
agents.append(_library_agent_to_info(agent))
logger.info(f"Found {len(agents)} agents in {source}")
except NotFoundError:
pass
@@ -193,42 +122,62 @@ async def search_agents(
)
if not agents:
suggestions = (
[
if source == "marketplace":
suggestions = [
"Try more general terms",
"Browse categories in the marketplace",
"Check spelling",
]
if source == "marketplace"
else [
no_results_msg = (
f"No agents found matching '{query}'. Let the user know they can "
"try different keywords or browse the marketplace. Also let them "
"know you can create a custom agent for them based on their needs."
)
elif not query:
# User asked to list all but library is empty
suggestions = [
"Browse the marketplace to find and add agents",
"Use find_agent to search the marketplace",
]
no_results_msg = (
"Your library is empty. Let the user know they can browse the "
"marketplace to find agents, or you can create a custom agent "
"for them based on their needs."
)
else:
suggestions = [
"Try different keywords",
"Use find_agent to search the marketplace",
"Check your library at /library",
]
)
no_results_msg = (
f"No agents found matching '{query}'. Let the user know they can try different keywords or browse the marketplace. Also let them know you can create a custom agent for them based on their needs."
if source == "marketplace"
else f"No agents matching '{query}' found in your library. Let the user know you can create a custom agent for them based on their needs."
)
no_results_msg = (
f"No agents matching '{query}' found in your library. Let the "
"user know you can create a custom agent for them based on "
"their needs."
)
return NoResultsResponse(
message=no_results_msg, session_id=session_id, suggestions=suggestions
)
title = f"Found {len(agents)} agent{'s' if len(agents) != 1 else ''} "
title += (
f"for '{query}'"
if source == "marketplace"
else f"in your library for '{query}'"
)
if source == "marketplace":
title = (
f"Found {len(agents)} agent{'s' if len(agents) != 1 else ''} for '{query}'"
)
elif not query:
title = f"Found {len(agents)} agent{'s' if len(agents) != 1 else ''} in your library"
else:
title = f"Found {len(agents)} agent{'s' if len(agents) != 1 else ''} in your library for '{query}'"
message = (
"Now you have found some options for the user to choose from. "
"You can add a link to a recommended agent at: /marketplace/agent/agent_id "
"Please ask the user if they would like to use any of these agents. Let the user know we can create a custom agent for them based on their needs."
"Please ask the user if they would like to use any of these agents. "
"Let the user know we can create a custom agent for them based on their needs."
if source == "marketplace"
else "Found agents in the user's library. You can provide a link to view an agent at: "
"/library/agents/{agent_id}. Use agent_output to get execution results, or run_agent to execute. Let the user know we can create a custom agent for them based on their needs."
else "Found agents in the user's library. You can provide a link to view "
"an agent at: /library/agents/{agent_id}. Use agent_output to get "
"execution results, or run_agent to execute. Let the user know we can "
"create a custom agent for them based on their needs."
)
return AgentsFoundResponse(
@@ -238,3 +187,67 @@ async def search_agents(
count=len(agents),
session_id=session_id,
)
def _is_uuid(text: str) -> bool:
"""Check if text is a valid UUID v4."""
return bool(_UUID_PATTERN.match(text.strip()))
def _library_agent_to_info(agent: LibraryAgent) -> AgentInfo:
"""Convert a library agent model to an AgentInfo."""
return AgentInfo(
id=agent.id,
name=agent.name,
description=agent.description or "",
source="library",
in_library=True,
creator=agent.creator_name,
status=agent.status.value,
can_access_graph=agent.can_access_graph,
has_external_trigger=agent.has_external_trigger,
new_output=agent.new_output,
graph_id=agent.graph_id,
)
async def _get_library_agent_by_id(user_id: str, agent_id: str) -> AgentInfo | None:
"""Fetch a library agent by ID (library agent ID or graph_id).
Tries multiple lookup strategies:
1. First by graph_id (AgentGraph primary key)
2. Then by library agent ID (LibraryAgent primary key)
"""
lib_db = library_db()
try:
agent = await lib_db.get_library_agent_by_graph_id(user_id, agent_id)
if agent:
logger.debug(f"Found library agent by graph_id: {agent.name}")
return _library_agent_to_info(agent)
except NotFoundError:
logger.debug(f"Library agent not found by graph_id: {agent_id}")
except DatabaseError:
raise
except Exception as e:
logger.warning(
f"Could not fetch library agent by graph_id {agent_id}: {e}",
exc_info=True,
)
try:
agent = await lib_db.get_library_agent(agent_id, user_id)
if agent:
logger.debug(f"Found library agent by library_id: {agent.name}")
return _library_agent_to_info(agent)
except NotFoundError:
logger.debug(f"Library agent not found by library_id: {agent_id}")
except DatabaseError:
raise
except Exception as e:
logger.warning(
f"Could not fetch library agent by library_id {agent_id}: {e}",
exc_info=True,
)
return None

186
autogpt_platform/backend/backend/copilot/tools/execution_utils.py Normal file
View File

@@ -0,0 +1,186 @@
"""Shared utilities for execution waiting and status handling."""
import asyncio
import logging
from typing import Any
from backend.data.db_accessors import execution_db
from backend.data.execution import (
AsyncRedisExecutionEventBus,
ExecutionStatus,
GraphExecution,
GraphExecutionEvent,
)
logger = logging.getLogger(__name__)
# Terminal statuses that indicate execution is complete
TERMINAL_STATUSES = frozenset(
{
ExecutionStatus.COMPLETED,
ExecutionStatus.FAILED,
ExecutionStatus.TERMINATED,
}
)
# Statuses where execution is paused but not finished (e.g. human-in-the-loop)
PAUSED_STATUSES = frozenset(
{
ExecutionStatus.REVIEW,
}
)
# Statuses that mean "stop waiting" (terminal or paused)
STOP_WAITING_STATUSES = TERMINAL_STATUSES | PAUSED_STATUSES
_POST_SUBSCRIBE_RECHECK_DELAY = 0.1 # seconds to wait for subscription to establish
async def wait_for_execution(
user_id: str,
graph_id: str,
execution_id: str,
timeout_seconds: int,
) -> GraphExecution | None:
"""
Wait for an execution to reach a terminal or paused status using Redis pubsub.
Handles the race condition between checking status and subscribing by
re-checking the DB after the subscription is established.
Args:
user_id: User ID
graph_id: Graph ID
execution_id: Execution ID to wait for
timeout_seconds: Max seconds to wait
Returns:
The execution with current status, or None if not found
"""
exec_db = execution_db()
# Quick check — maybe it's already done
execution = await exec_db.get_graph_execution(
user_id=user_id,
execution_id=execution_id,
include_node_executions=False,
)
if not execution:
return None
if execution.status in STOP_WAITING_STATUSES:
logger.debug(
f"Execution {execution_id} already in stop-waiting state: "
f"{execution.status}"
)
return execution
logger.info(
f"Waiting up to {timeout_seconds}s for execution {execution_id} "
f"(current status: {execution.status})"
)
event_bus = AsyncRedisExecutionEventBus()
channel_key = f"{user_id}/{graph_id}/{execution_id}"
# Mutable container so _subscribe_and_wait can surface the task even if
# asyncio.wait_for cancels the coroutine before it returns.
task_holder: list[asyncio.Task] = []
try:
result = await asyncio.wait_for(
_subscribe_and_wait(
event_bus, channel_key, user_id, execution_id, exec_db, task_holder
),
timeout=timeout_seconds,
)
return result
except asyncio.TimeoutError:
logger.info(f"Timeout waiting for execution {execution_id}")
except Exception as e:
logger.error(f"Error waiting for execution: {e}", exc_info=True)
finally:
for task in task_holder:
if not task.done():
task.cancel()
try:
await task
except asyncio.CancelledError:
pass
await event_bus.close()
# Return current state on timeout/error
return await exec_db.get_graph_execution(
user_id=user_id,
execution_id=execution_id,
include_node_executions=False,
)
async def _subscribe_and_wait(
event_bus: AsyncRedisExecutionEventBus,
channel_key: str,
user_id: str,
execution_id: str,
exec_db: Any,
task_holder: list[asyncio.Task],
) -> GraphExecution | None:
"""
Subscribe to execution events and wait for a terminal/paused status.
Appends the consumer task to ``task_holder`` so the caller can clean it up
even if this coroutine is cancelled by ``asyncio.wait_for``.
To avoid the race condition where the execution completes between the
initial DB check and the Redis subscription, we:
1. Start listening (which subscribes internally)
2. Re-check the DB after subscription is active
3. If still running, wait for pubsub events
"""
listen_iter = event_bus.listen_events(channel_key).__aiter__()
done = asyncio.Event()
result_execution: GraphExecution | None = None
async def _consume() -> None:
nonlocal result_execution
try:
async for event in listen_iter:
if isinstance(event, GraphExecutionEvent):
logger.debug(f"Received execution update: {event.status}")
if event.status in STOP_WAITING_STATUSES:
result_execution = await exec_db.get_graph_execution(
user_id=user_id,
execution_id=execution_id,
include_node_executions=False,
)
done.set()
return
except Exception as e:
logger.error(f"Error in execution consumer: {e}", exc_info=True)
done.set()
consume_task = asyncio.create_task(_consume())
task_holder.append(consume_task)
# Give the subscription a moment to establish, then re-check DB
await asyncio.sleep(_POST_SUBSCRIBE_RECHECK_DELAY)
execution = await exec_db.get_graph_execution(
user_id=user_id,
execution_id=execution_id,
include_node_executions=False,
)
if execution and execution.status in STOP_WAITING_STATUSES:
return execution
# Wait for the pubsub consumer to find a terminal event
await done.wait()
return result_execution
def get_execution_outputs(execution: GraphExecution | None) -> dict[str, Any] | None:
"""Extract outputs from an execution, or return None."""
if execution is None:
return None
return execution.outputs

16
autogpt_platform/backend/backend/copilot/tools/find_library_agent.py
View File

@@ -19,9 +19,10 @@ class FindLibraryAgentTool(BaseTool):
@property
def description(self) -> str:
return (
"Search for agents in the user's library. Use this to find agents "
"the user has already added to their library, including agents they "
"created or added from the marketplace."
"Search for or list agents in the user's library. Use this to find "
"agents the user has already added to their library, including agents "
"they created or added from the marketplace. "
"Omit the query to list all agents."
)
@property
@@ -31,10 +32,13 @@ class FindLibraryAgentTool(BaseTool):
"properties": {
"query": {
"type": "string",
"description": "Search query to find agents by name or description.",
"description": (
"Search query to find agents by name or description. "
"Omit to list all agents in the library."
),
},
},
"required": ["query"],
"required": [],
}
@property
@@ -45,7 +49,7 @@ class FindLibraryAgentTool(BaseTool):
self, user_id: str | None, session: ChatSession, **kwargs
) -> ToolResponseBase:
return await search_agents(
query=kwargs.get("query", "").strip(),
query=(kwargs.get("query") or "").strip(),
source="library",
session_id=session.session_id,
user_id=user_id,

102
autogpt_platform/backend/backend/copilot/tools/run_agent.py
View File

@@ -9,6 +9,7 @@ from backend.copilot.config import ChatConfig
from backend.copilot.model import ChatSession
from backend.copilot.tracking import track_agent_run_success, track_agent_scheduled
from backend.data.db_accessors import graph_db, library_db, user_db
from backend.data.execution import ExecutionStatus
from backend.data.graph import GraphModel
from backend.data.model import CredentialsMetaInput
from backend.executor import utils as execution_utils
@@ -20,12 +21,15 @@ from backend.util.timezone_utils import (
)
from .base import BaseTool
from .execution_utils import get_execution_outputs, wait_for_execution
from .helpers import get_inputs_from_schema
from .models import (
AgentDetails,
AgentDetailsResponse,
AgentOutputResponse,
ErrorResponse,
ExecutionOptions,
ExecutionOutputInfo,
ExecutionStartedResponse,
InputValidationErrorResponse,
SetupInfo,
@@ -66,6 +70,7 @@ class RunAgentInput(BaseModel):
schedule_name: str = ""
cron: str = ""
timezone: str = "UTC"
wait_for_result: int = Field(default=0, ge=0, le=300)
@field_validator(
"username_agent_slug",
@@ -147,6 +152,14 @@ class RunAgentTool(BaseTool):
"type": "string",
"description": "IANA timezone for schedule (default: UTC)",
},
"wait_for_result": {
"type": "integer",
"description": (
"Max seconds to wait for execution to complete (0-300). "
"If >0, blocks until the execution finishes or times out. "
"Returns execution outputs when complete."
),
},
},
"required": [],
}
@@ -341,6 +354,7 @@ class RunAgentTool(BaseTool):
graph=graph,
graph_credentials=graph_credentials,
inputs=params.inputs,
wait_for_result=params.wait_for_result,
)
except NotFoundError as e:
@@ -424,8 +438,9 @@ class RunAgentTool(BaseTool):
graph: GraphModel,
graph_credentials: dict[str, CredentialsMetaInput],
inputs: dict[str, Any],
wait_for_result: int = 0,
) -> ToolResponseBase:
"""Execute an agent immediately."""
"""Execute an agent immediately, optionally waiting for completion."""
session_id = session.session_id
# Check rate limits
@@ -462,6 +477,91 @@ class RunAgentTool(BaseTool):
)
library_agent_link = f"/library/agents/{library_agent.id}"
# If wait_for_result is requested, wait for execution to complete
if wait_for_result > 0:
logger.info(
f"Waiting up to {wait_for_result}s for execution {execution.id}"
)
completed = await wait_for_execution(
user_id=user_id,
graph_id=library_agent.graph_id,
execution_id=execution.id,
timeout_seconds=wait_for_result,
)
if completed and completed.status == ExecutionStatus.COMPLETED:
outputs = get_execution_outputs(completed)
return AgentOutputResponse(
message=(
f"Agent '{library_agent.name}' completed successfully. "
f"View at {library_agent_link}."
),
session_id=session_id,
agent_name=library_agent.name,
agent_id=library_agent.graph_id,
library_agent_id=library_agent.id,
library_agent_link=library_agent_link,
execution=ExecutionOutputInfo(
execution_id=execution.id,
status=completed.status.value,
started_at=completed.started_at,
ended_at=completed.ended_at,
outputs=outputs or {},
),
)
elif completed and completed.status == ExecutionStatus.FAILED:
error_detail = completed.stats.error if completed.stats else None
return ErrorResponse(
message=(
f"Agent '{library_agent.name}' execution failed. "
f"View details at {library_agent_link}."
),
session_id=session_id,
error=error_detail,
)
elif completed and completed.status == ExecutionStatus.TERMINATED:
error_detail = completed.stats.error if completed.stats else None
return ErrorResponse(
message=(
f"Agent '{library_agent.name}' execution was terminated. "
f"View details at {library_agent_link}."
),
session_id=session_id,
error=error_detail,
)
elif completed and completed.status == ExecutionStatus.REVIEW:
return ExecutionStartedResponse(
message=(
f"Agent '{library_agent.name}' is awaiting human review. "
f"Check at {library_agent_link}."
),
session_id=session_id,
execution_id=execution.id,
graph_id=library_agent.graph_id,
graph_name=library_agent.name,
library_agent_id=library_agent.id,
library_agent_link=library_agent_link,
status=ExecutionStatus.REVIEW.value,
)
else:
status = completed.status.value if completed else "unknown"
return ExecutionStartedResponse(
message=(
f"Agent '{library_agent.name}' is still {status} after "
f"{wait_for_result}s. Check results later at "
f"{library_agent_link}. "
f"Use view_agent_output with wait_if_running to check again."
),
session_id=session_id,
execution_id=execution.id,
graph_id=library_agent.graph_id,
graph_name=library_agent.name,
library_agent_id=library_agent.id,
library_agent_link=library_agent_link,
status=status,
)
return ExecutionStartedResponse(
message=(
f"Agent '{library_agent.name}' execution started successfully. "

14
autogpt_platform/backend/backend/copilot/tools/workspace_files.py
View File

@@ -214,7 +214,11 @@ class WorkspaceWriteResponse(ToolResponseBase):
file_id: str
name: str
path: str
mime_type: str
size_bytes: int
# workspace:// URL the agent can embed directly in chat to give the user a link.
# Format: workspace://<file_id>#<mime_type> (frontend resolves to download URL)
download_url: str
source: str | None = None # "content", "base64", or "copied from <path>"
content_preview: str | None = None # First 200 chars for text files
@@ -680,11 +684,21 @@ class WriteWorkspaceFileTool(BaseTool):
except Exception:
pass
# Strip MIME parameters (e.g. "text/html; charset=utf-8" → "text/html")
# and normalise to lowercase so the fragment is URL-safe.
normalized_mime = (rec.mime_type or "").split(";", 1)[0].strip().lower()
download_url = (
f"workspace://{rec.id}#{normalized_mime}"
if normalized_mime
else f"workspace://{rec.id}"
)
return WorkspaceWriteResponse(
file_id=rec.id,
name=rec.name,
path=rec.path,
mime_type=normalized_mime,
size_bytes=rec.size_bytes,
download_url=download_url,
source=source,
content_preview=preview,
message=msg,

8
autogpt_platform/backend/backend/data/credit_test.py
View File

@@ -178,9 +178,13 @@ async def test_block_credit_reset(server: SpinTestServer):
assert month2_balance == 1100 # Balance persists, no reset
# Now test the refill behavior when balance is low
# Set balance below refill threshold
# Set balance below refill threshold and backdate updatedAt to month2 so
# the month3 refill check sees a different (month2 → month3) transition.
# Without the explicit updatedAt, Prisma sets it to real-world NOW which
# may share the same calendar month as the mocked month3, suppressing refill.
await UserBalance.prisma().update(
where={"userId": DEFAULT_USER_ID}, data={"balance": 400}
where={"userId": DEFAULT_USER_ID},
data={"balance": 400, "updatedAt": month2},
)
# Create a month 2 transaction to update the last transaction time

3
autogpt_platform/backend/backend/util/settings.py
View File

@@ -723,6 +723,9 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
langfuse_host: str = Field(
default="https://cloud.langfuse.com", description="Langfuse host URL"
)
langfuse_tracing_environment: str = Field(
default="local", description="Tracing environment tag (local/dev/production)"
)
# PostHog analytics
posthog_api_key: str = Field(default="", description="PostHog API key")

7
autogpt_platform/backend/migrations/20260225163452_add_library_api_key_permission/migration.sql Normal file
View File

@@ -0,0 +1,7 @@
-- This migration adds more than one value to an enum.
-- With PostgreSQL versions 11 and earlier, this is not possible
-- in a single migration. This can be worked around by creating
-- multiple migrations, each migration adding only one value to
-- the enum.
ALTER TYPE "APIKeyPermission" ADD VALUE 'WRITE_GRAPH';
ALTER TYPE "APIKeyPermission" ADD VALUE 'WRITE_LIBRARY';

312
autogpt_platform/backend/poetry.lock generated
View File

@@ -1610,6 +1610,101 @@ mccabe = ">=0.7.0,<0.8.0"
pycodestyle = ">=2.14.0,<2.15.0"
pyflakes = ">=3.4.0,<3.5.0"
[[package]]
name = "fonttools"
version = "4.61.1"
description = "Tools to manipulate font files"
optional = false
python-versions = ">=3.10"
groups = ["main"]
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]
[package.extras]
all = ["brotli (>=1.0.1) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\"", "lxml (>=4.0)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres ; platform_python_implementation == \"PyPy\"", "pycairo", "scipy ; platform_python_implementation != \"PyPy\"", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.45.0)", "unicodedata2 (>=17.0.0) ; python_version <= \"3.14\"", "xattr ; sys_platform == \"darwin\"", "zopfli (>=0.1.4)"]
graphite = ["lz4 (>=1.7.4.2)"]
interpolatable = ["munkres ; platform_python_implementation == \"PyPy\"", "pycairo", "scipy ; platform_python_implementation != \"PyPy\""]
lxml = ["lxml (>=4.0)"]
pathops = ["skia-pathops (>=0.5.0)"]
plot = ["matplotlib"]
repacker = ["uharfbuzz (>=0.45.0)"]
symfont = ["sympy"]
type1 = ["xattr ; sys_platform == \"darwin\""]
unicode = ["unicodedata2 (>=17.0.0) ; python_version <= \"3.14\""]
woff = ["brotli (>=1.0.1) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\"", "zopfli (>=0.1.4)"]
[[package]]
name = "fpdf2"
version = "2.8.6"
description = "Simple & fast PDF generation for Python"
optional = false
python-versions = ">=3.10"
groups = ["main"]
files = [
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]
[package.dependencies]
defusedxml = "*"
fonttools = ">=4.34.0"
Pillow = ">=8.3.2,<9.2.dev0 || >=9.3.dev0"
[package.extras]
dev = ["bandit", "black", "mypy", "pre-commit", "pylint", "pyright", "semgrep", "zizmor"]
docs = ["lxml", "mkdocs", "mkdocs-git-revision-date-localized-plugin", "mkdocs-include-markdown-plugin", "mkdocs-macros-plugin", "mkdocs-material", "mkdocs-minify-plugin", "mkdocs-redirects", "mkdocs-with-pdf", "mknotebooks", "pdoc3"]
test = ["brotli", "camelot-py[base]", "endesive[full]", "pytest", "pytest-cov", "qrcode", "tabula-py", "typing-extensions (>=4.0) ; python_version < \"3.11\"", "uharfbuzz"]
[[package]]
name = "frozenlist"
version = "1.8.0"
@@ -3135,6 +3230,39 @@ pydantic = ">=1.10.7,<3.0"
requests = ">=2,<3"
wrapt = ">=1.14,<2.0"
[[package]]
name = "langsmith"
version = "0.7.7"
description = "Client library to connect to the LangSmith Observability and Evaluation Platform."
optional = false
python-versions = ">=3.10"
groups = ["main"]
files = [
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httpx = ">=0.23.0,<1"
orjson = {version = ">=3.9.14", markers = "platform_python_implementation != \"PyPy\""}
packaging = ">=23.2"
pydantic = ">=2,<3"
requests = ">=2.0.0"
requests-toolbelt = ">=1.0.0"
uuid-utils = ">=0.12.0,<1.0"
xxhash = ">=3.0.0"
zstandard = ">=0.23.0"
[package.extras]
claude-agent-sdk = ["claude-agent-sdk (>=0.1.0) ; python_version >= \"3.10\""]
google-adk = ["google-adk (>=1.0.0)", "wrapt (>=1.16.0)"]
langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2)"]
openai-agents = ["openai-agents (>=0.0.3)"]
otel = ["opentelemetry-api (>=1.30.0)", "opentelemetry-exporter-otlp-proto-http (>=1.30.0)", "opentelemetry-sdk (>=1.30.0)"]
pytest = ["pytest (>=7.0.0)", "rich (>=13.9.4)", "vcrpy (>=7.0.0)"]
sandbox = ["websockets (>=15.0)"]
vcr = ["vcrpy (>=7.0.0)"]
[[package]]
name = "launchdarkly-eventsource"
version = "1.5.1"
@@ -7652,6 +7780,38 @@ h2 = ["h2 (>=4,<5)"]
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
zstd = ["backports-zstd (>=1.0.0) ; python_version < \"3.14\""]
[[package]]
name = "uuid-utils"
version = "0.14.1"
description = "Fast, drop-in replacement for Python's uuid module, powered by Rust."
optional = false
python-versions = ">=3.9"
groups = ["main"]
files = [
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]
[[package]]
name = "yarl"
version = "1.22.0"
@@ -8530,4 +8840,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt
[metadata]
lock-version = "2.1"
python-versions = ">=3.10,<3.14"
content-hash = "3ef62836d8321b9a3b8e897dade8dc6ca9022fd9468c53f384b0871b521ab343"
content-hash = "e7863413fda5e0a8b236e39a4c37390b52ae8c2f572c77df732abbd4280312b6"

2
autogpt_platform/backend/pyproject.toml
View File

@@ -89,6 +89,8 @@ croniter = "^6.0.0"
stagehand = "^0.5.1"
gravitas-md2gdocs = "^0.1.0"
posthog = "^7.6.0"
fpdf2 = "^2.8.6"
langsmith = "^0.7.7"
[tool.poetry.group.dev.dependencies]
aiohappyeyeballs = "^2.6.1"

2
autogpt_platform/backend/schema.prisma
View File

@@ -1130,9 +1130,11 @@ enum APIKeyPermission {
IDENTITY // Info about the authenticated user
EXECUTE_GRAPH // Can execute agent graphs
READ_GRAPH // Can get graph versions and details
WRITE_GRAPH // Can create and update agent graphs
EXECUTE_BLOCK // Can execute individual blocks
READ_BLOCK // Can get block information
READ_STORE // Can read store agents and creators
WRITE_LIBRARY // Can add agents to library
USE_TOOLS // Can use chat tools via external API
MANAGE_INTEGRATIONS // Can initiate OAuth flows and complete them
READ_INTEGRATIONS // Can list credentials and providers

1
autogpt_platform/frontend/.storybook/main.ts
View File

@@ -6,6 +6,7 @@ const config: StorybookConfig = {
"../src/components/tokens/**/*.stories.@(js|jsx|mjs|ts|tsx)",
"../src/components/atoms/**/*.stories.@(js|jsx|mjs|ts|tsx)",
"../src/components/molecules/**/*.stories.@(js|jsx|mjs|ts|tsx)",
"../src/components/ai-elements/**/*.stories.@(js|jsx|mjs|ts|tsx)",
],
addons: [
"@storybook/addon-a11y",

2
autogpt_platform/frontend/src/app/(platform)/auth/authorize/page.tsx
View File

@@ -19,6 +19,8 @@ const SCOPE_DESCRIPTIONS: { [key in APIKeyPermission]: string } = {
IDENTITY: "View your user ID, e-mail, and timezone",
EXECUTE_GRAPH: "Run your agents",
READ_GRAPH: "View your agents and their configurations",
WRITE_GRAPH: "Create agent graphs",
WRITE_LIBRARY: "Add agents to your library",
EXECUTE_BLOCK: "Execute individual blocks",
READ_BLOCK: "View available blocks",
READ_STORE: "Access the Marketplace",

4
autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/NodeOutput.tsx
View File

@@ -46,7 +46,7 @@ export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
<div className="space-y-2">
<Text variant="small-medium">Input</Text>
<ContentRenderer value={latestInputData} shortContent={false} />
<ContentRenderer value={latestInputData} shortContent={true} />
<div className="mt-1 flex justify-end gap-1">
<NodeDataViewer
@@ -98,7 +98,7 @@ export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
Data:
</Text>
<div className="relative space-y-2">
{value.map((item, index) => (
{value.slice(0, 3).map((item, index) => (
<div key={index}>
<ContentRenderer
value={item}

6
autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/components/ContentRenderer.tsx
View File

@@ -37,15 +37,15 @@ export const ContentRenderer: React.FC<{
!shortContent
) {
return (
<div className="[&>*]:rounded-xlarge [&>*]:!text-xs">
<div className="overflow-hidden [&>*]:rounded-xlarge [&>*]:!text-xs [&_pre]:whitespace-pre-wrap [&_pre]:break-words">
{renderer?.render(value, metadata)}
</div>
);
}
return (
<div className="[&>*]:rounded-xlarge [&>*]:!text-xs">
<TextRenderer value={value} truncateLengthLimit={100} />
<div className="overflow-hidden [&>*]:rounded-xlarge [&>*]:!text-xs">
<TextRenderer value={value} truncateLengthLimit={200} />
</div>
);
};

229
autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/components/NodeDataViewer/NodeDataViewer.tsx
View File

@@ -1,4 +1,3 @@
import { ScrollArea } from "@/components/__legacy__/ui/scroll-area";
import { Button } from "@/components/atoms/Button/Button";
import { Text } from "@/components/atoms/Text/Text";
import {
@@ -164,129 +163,119 @@ export const NodeDataViewer: FC<NodeDataViewerProps> = ({
</div>
</div>
<div className="flex-1 overflow-hidden">
<ScrollArea className="h-full">
<div className="my-4">
{shouldGroupExecutions ? (
<div className="space-y-4">
{groupedExecutions.map((execution) => (
<div
key={execution.execId}
className="rounded-3xl border border-slate-200 bg-white p-4 shadow-sm"
>
<div className="flex items-center gap-2">
<Text variant="body" className="text-slate-600">
Execution ID:
</Text>
<Text
variant="body-medium"
className="rounded-full border border-gray-300 bg-gray-50 px-2 py-1 font-mono text-xs"
>
{execution.execId}
</Text>
</div>
<div className="mt-2 space-y-4">
{execution.outputItems.length > 0 ? (
execution.outputItems.map((item, index) => (
<div
key={item.key}
className="group flex items-start gap-4"
>
<div className="w-full flex-1">
<OutputItem
value={item.value}
metadata={item.metadata}
renderer={item.renderer}
/>
</div>
<div className="flex w-fit gap-3">
<Button
variant="secondary"
className="min-w-0 p-1"
size="icon"
onClick={() =>
handleCopyGroupedItem(
execution.execId,
index,
item,
)
}
aria-label="Copy item"
>
{copiedKey ===
`${execution.execId}-${index}` ? (
<CheckIcon className="size-4 text-green-600" />
) : (
<CopyIcon className="size-4 text-black" />
)}
</Button>
<Button
variant="secondary"
size="icon"
className="min-w-0 p-1"
onClick={() =>
handleDownloadGroupedItem(item)
}
aria-label="Download item"
>
<DownloadIcon className="size-4 text-black" />
</Button>
</div>
<div className="flex-1">
<div className="my-4">
{shouldGroupExecutions ? (
<div className="space-y-4">
{groupedExecutions.map((execution) => (
<div
key={execution.execId}
className="rounded-3xl border border-slate-200 bg-white p-4 shadow-sm"
>
<div className="flex items-center gap-2">
<Text variant="body" className="text-slate-600">
Execution ID:
</Text>
<Text
variant="body-medium"
className="rounded-full border border-gray-300 bg-gray-50 px-2 py-1 font-mono text-xs"
>
{execution.execId}
</Text>
</div>
<div className="mt-2 space-y-4">
{execution.outputItems.length > 0 ? (
execution.outputItems.map((item, index) => (
<div key={item.key} className="group">
<OutputItem
value={item.value}
metadata={item.metadata}
renderer={item.renderer}
/>
<div className="mt-2 flex gap-3">
<Button
variant="secondary"
className="min-w-0 p-1"
size="icon"
onClick={() =>
handleCopyGroupedItem(
execution.execId,
index,
item,
)
}
aria-label="Copy item"
>
{copiedKey ===
`${execution.execId}-${index}` ? (
<CheckIcon className="size-4 text-green-600" />
) : (
<CopyIcon className="size-4 text-black" />
)}
</Button>
<Button
variant="secondary"
size="icon"
className="min-w-0 p-1"
onClick={() => handleDownloadGroupedItem(item)}
aria-label="Download item"
>
<DownloadIcon className="size-4 text-black" />
</Button>
</div>
))
) : (
<div className="py-4 text-center text-gray-500">
No data available
</div>
))
) : (
<div className="py-4 text-center text-gray-500">
No data available
</div>
)}
</div>
</div>
))}
</div>
) : dataArray.length > 0 ? (
<div className="space-y-4">
{outputItems.map((item, index) => (
<div key={item.key} className="group">
<OutputItem
value={item.value}
metadata={item.metadata}
renderer={item.renderer}
/>
<div className="mt-2 flex gap-3">
<Button
variant="secondary"
className="min-w-0 p-1"
size="icon"
onClick={() => handleCopyItem(index)}
aria-label="Copy item"
>
{copiedIndex === index ? (
<CheckIcon className="size-4 text-green-600" />
) : (
<CopyIcon className="size-4 text-black" />
)}
</div>
</Button>
<Button
variant="secondary"
size="icon"
className="min-w-0 p-1"
onClick={() => handleDownloadItem(index)}
aria-label="Download item"
>
<DownloadIcon className="size-4 text-black" />
</Button>
</div>
))}
</div>
) : dataArray.length > 0 ? (
<div className="space-y-4">
{outputItems.map((item, index) => (
<div key={item.key} className="group relative">
<OutputItem
value={item.value}
metadata={item.metadata}
renderer={item.renderer}
/>
<div className="absolute right-3 top-3 flex gap-3">
<Button
variant="secondary"
className="min-w-0 p-1"
size="icon"
onClick={() => handleCopyItem(index)}
aria-label="Copy item"
>
{copiedIndex === index ? (
<CheckIcon className="size-4 text-green-600" />
) : (
<CopyIcon className="size-4 text-black" />
)}
</Button>
<Button
variant="secondary"
size="icon"
className="min-w-0 p-1"
onClick={() => handleDownloadItem(index)}
aria-label="Download item"
>
<DownloadIcon className="size-4 text-black" />
</Button>
</div>
</div>
))}
</div>
) : (
<div className="py-8 text-center text-gray-500">
No data available
</div>
)}
</div>
</ScrollArea>
</div>
))}
</div>
) : (
<div className="py-8 text-center text-gray-500">
No data available
</div>
)}
</div>
</div>
<div className="flex justify-end pt-4">

165
autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/ChatInput.tsx
View File

@@ -1,12 +1,15 @@
import { Button } from "@/components/atoms/Button/Button";
import { cn } from "@/lib/utils";
import {
ArrowUpIcon,
CircleNotchIcon,
MicrophoneIcon,
StopIcon,
} from "@phosphor-icons/react";
import { ChangeEvent, useCallback } from "react";
PromptInputBody,
PromptInputButton,
PromptInputFooter,
PromptInputSubmit,
PromptInputTextarea,
PromptInputTools,
} from "@/components/ai-elements/prompt-input";
import { InputGroup } from "@/components/ui/input-group";
import { cn } from "@/lib/utils";
import { CircleNotchIcon, MicrophoneIcon } from "@phosphor-icons/react";
import { ChangeEvent } from "react";
import { RecordingIndicator } from "./components/RecordingIndicator";
import { useChatInput } from "./useChatInput";
import { useVoiceRecording } from "./useVoiceRecording";
@@ -33,14 +36,11 @@ export function ChatInput({
const {
value,
setValue,
handleKeyDown: baseHandleKeyDown,
handleSubmit,
handleChange: baseHandleChange,
hasMultipleLines,
} = useChatInput({
onSend,
disabled: disabled || isStreaming,
maxRows: 4,
inputId,
});
@@ -58,60 +58,35 @@ export function ChatInput({
disabled: disabled || isStreaming,
isStreaming,
value,
baseHandleKeyDown,
inputId,
});
// Block text changes when recording
const handleChange = useCallback(
(e: ChangeEvent<HTMLTextAreaElement>) => {
if (isRecording) return;
baseHandleChange(e);
},
[isRecording, baseHandleChange],
);
function handleChange(e: ChangeEvent<HTMLTextAreaElement>) {
if (isRecording) return;
baseHandleChange(e);
}
const canSend =
!disabled && !!value.trim() && !isRecording && !isTranscribing;
return (
<form onSubmit={handleSubmit} className={cn("relative flex-1", className)}>
<div className="relative">
<div
id={`${inputId}-wrapper`}
className={cn(
"relative overflow-hidden border bg-white shadow-sm",
"focus-within:ring-1",
isRecording
? "border-red-400 focus-within:border-red-400 focus-within:ring-red-400"
: "border-neutral-200 focus-within:border-zinc-400 focus-within:ring-zinc-400",
hasMultipleLines ? "rounded-xlarge" : "rounded-full",
)}
>
{!value && !isRecording && (
<div
className="pointer-events-none absolute inset-0 top-0.5 flex items-center justify-start pl-14 text-[1rem] text-zinc-400"
aria-hidden="true"
>
{isTranscribing ? "Transcribing..." : placeholder}
</div>
)}
<textarea
<InputGroup
className={cn(
"overflow-hidden has-[[data-slot=input-group-control]:focus-visible]:border-neutral-200 has-[[data-slot=input-group-control]:focus-visible]:ring-0",
isRecording &&
"border-red-400 ring-1 ring-red-400 has-[[data-slot=input-group-control]:focus-visible]:border-red-400 has-[[data-slot=input-group-control]:focus-visible]:ring-red-400",
)}
>
<PromptInputBody className="relative block w-full">
<PromptInputTextarea
id={inputId}
aria-label="Chat message input"
value={value}
onChange={handleChange}
onKeyDown={handleKeyDown}
disabled={isInputDisabled}
rows={1}
className={cn(
"w-full resize-none overflow-y-auto border-0 bg-transparent text-[1rem] leading-6 text-black",
"placeholder:text-zinc-400",
"focus:outline-none focus:ring-0",
"disabled:text-zinc-500",
hasMultipleLines
? "pb-6 pl-4 pr-4 pt-2"
: showMicButton
? "pb-4 pl-14 pr-14 pt-4"
: "pb-4 pl-4 pr-14 pt-4",
)}
placeholder={isTranscribing ? "Transcribing..." : placeholder}
/>
{isRecording && !value && (
<div className="pointer-events-none absolute inset-0 flex items-center justify-center">
@@ -121,67 +96,43 @@ export function ChatInput({
/>
</div>
)}
</div>
<span id="chat-input-hint" className="sr-only">
</PromptInputBody>
<span id={`${inputId}-hint`} className="sr-only">
Press Enter to send, Shift+Enter for new line, Space to record voice
</span>
{showMicButton && (
<div className="absolute bottom-[7px] left-2 flex items-center gap-1">
<Button
type="button"
variant="icon"
size="icon"
aria-label={isRecording ? "Stop recording" : "Start recording"}
onClick={toggleRecording}
disabled={disabled || isTranscribing || isStreaming}
className={cn(
isRecording
? "animate-pulse border-red-500 bg-red-500 text-white hover:border-red-600 hover:bg-red-600"
: isTranscribing
? "border-zinc-300 bg-zinc-100 text-zinc-400"
: "border-zinc-300 bg-white text-zinc-500 hover:border-zinc-400 hover:bg-zinc-50 hover:text-zinc-700",
isStreaming && "opacity-40",
)}
>
{isTranscribing ? (
<CircleNotchIcon className="h-4 w-4 animate-spin" />
) : (
<MicrophoneIcon className="h-4 w-4" weight="bold" />
)}
</Button>
</div>
)}
<PromptInputFooter>
<PromptInputTools>
{showMicButton && (
<PromptInputButton
aria-label={isRecording ? "Stop recording" : "Start recording"}
onClick={toggleRecording}
disabled={disabled || isTranscribing || isStreaming}
className={cn(
"size-[2.625rem] rounded-[96px] border border-zinc-300 bg-transparent text-black hover:border-zinc-600 hover:bg-zinc-100",
isRecording &&
"animate-pulse border-red-500 bg-red-500 text-white hover:border-red-600 hover:bg-red-600",
isTranscribing && "bg-zinc-100 text-zinc-400",
isStreaming && "opacity-40",
)}
>
{isTranscribing ? (
<CircleNotchIcon className="h-4 w-4 animate-spin" />
) : (
<MicrophoneIcon className="h-4 w-4" weight="bold" />
)}
</PromptInputButton>
)}
</PromptInputTools>
<div className="absolute bottom-[7px] right-2 flex items-center gap-1">
{isStreaming ? (
<Button
type="button"
variant="icon"
size="icon"
aria-label="Stop generating"
onClick={onStop}
className="border-red-600 bg-red-600 text-white hover:border-red-800 hover:bg-red-800"
>
<StopIcon className="h-4 w-4" weight="bold" />
</Button>
<PromptInputSubmit status="streaming" onStop={onStop} />
) : (
<Button
type="submit"
variant="icon"
size="icon"
aria-label="Send message"
className={cn(
"border-zinc-800 bg-zinc-800 text-white hover:border-zinc-900 hover:bg-zinc-900",
(disabled || !value.trim() || isRecording) && "opacity-20",
)}
disabled={disabled || !value.trim() || isRecording}
>
<ArrowUpIcon className="h-4 w-4" weight="bold" />
</Button>
<PromptInputSubmit disabled={!canSend} />
)}
</div>
</div>
</PromptInputFooter>
</InputGroup>
</form>
);
}

93
autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useChatInput.ts
View File

@@ -1,26 +1,17 @@
import {
ChangeEvent,
FormEvent,
KeyboardEvent,
useEffect,
useState,
} from "react";
import { ChangeEvent, FormEvent, useEffect, useState } from "react";
interface Args {
onSend: (message: string) => void;
disabled?: boolean;
maxRows?: number;
inputId?: string;
}
export function useChatInput({
onSend,
disabled = false,
maxRows = 5,
inputId = "chat-input",
}: Args) {
const [value, setValue] = useState("");
const [hasMultipleLines, setHasMultipleLines] = useState(false);
const [isSending, setIsSending] = useState(false);
useEffect(
@@ -40,67 +31,6 @@ export function useChatInput({
[disabled, inputId],
);
useEffect(() => {
const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
const wrapper = document.getElementById(
`${inputId}-wrapper`,
) as HTMLDivElement;
if (!textarea || !wrapper) return;
const isEmpty = !value.trim();
const lines = value.split("\n").length;
const hasExplicitNewlines = lines > 1;
const computedStyle = window.getComputedStyle(textarea);
const lineHeight = parseInt(computedStyle.lineHeight, 10);
const paddingTop = parseInt(computedStyle.paddingTop, 10);
const paddingBottom = parseInt(computedStyle.paddingBottom, 10);
const singleLinePadding = paddingTop + paddingBottom;
textarea.style.height = "auto";
const scrollHeight = textarea.scrollHeight;
const singleLineHeight = lineHeight + singleLinePadding;
const isMultiLine =
hasExplicitNewlines || scrollHeight > singleLineHeight + 2;
setHasMultipleLines(isMultiLine);
if (isEmpty) {
wrapper.style.height = `${singleLineHeight}px`;
wrapper.style.maxHeight = "";
textarea.style.height = `${singleLineHeight}px`;
textarea.style.maxHeight = "";
textarea.style.overflowY = "hidden";
return;
}
if (isMultiLine) {
const wrapperMaxHeight = 196;
const currentMultilinePadding = paddingTop + paddingBottom;
const contentMaxHeight = wrapperMaxHeight - currentMultilinePadding;
const minMultiLineHeight = lineHeight * 2 + currentMultilinePadding;
const contentHeight = scrollHeight;
const targetWrapperHeight = Math.min(
Math.max(contentHeight + currentMultilinePadding, minMultiLineHeight),
wrapperMaxHeight,
);
wrapper.style.height = `${targetWrapperHeight}px`;
wrapper.style.maxHeight = `${wrapperMaxHeight}px`;
textarea.style.height = `${contentHeight}px`;
textarea.style.maxHeight = `${contentMaxHeight}px`;
textarea.style.overflowY =
contentHeight > contentMaxHeight ? "auto" : "hidden";
} else {
wrapper.style.height = `${singleLineHeight}px`;
wrapper.style.maxHeight = "";
textarea.style.height = `${singleLineHeight}px`;
textarea.style.maxHeight = "";
textarea.style.overflowY = "hidden";
}
}, [value, maxRows, inputId]);
async function handleSend() {
if (disabled || isSending || !value.trim()) return;
@@ -108,30 +38,11 @@ export function useChatInput({
try {
await onSend(value.trim());
setValue("");
setHasMultipleLines(false);
const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
const wrapper = document.getElementById(
`${inputId}-wrapper`,
) as HTMLDivElement;
if (textarea) {
textarea.style.height = "auto";
}
if (wrapper) {
wrapper.style.height = "";
wrapper.style.maxHeight = "";
}
} finally {
setIsSending(false);
}
}
function handleKeyDown(event: KeyboardEvent<HTMLTextAreaElement>) {
if (event.key === "Enter" && !event.shiftKey) {
event.preventDefault();
void handleSend();
}
}
function handleSubmit(e: FormEvent<HTMLFormElement>) {
e.preventDefault();
void handleSend();
@@ -144,11 +55,9 @@ export function useChatInput({
return {
value,
setValue,
handleKeyDown,
handleSend,
handleSubmit,
handleChange,
hasMultipleLines,
isSending,
};
}

6
autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useVoiceRecording.ts
View File

@@ -14,7 +14,6 @@ interface Args {
disabled?: boolean;
isStreaming?: boolean;
value: string;
baseHandleKeyDown: (event: KeyboardEvent<HTMLTextAreaElement>) => void;
inputId?: string;
}
@@ -23,7 +22,6 @@ export function useVoiceRecording({
disabled = false,
isStreaming = false,
value,
baseHandleKeyDown,
inputId,
}: Args) {
const [isRecording, setIsRecording] = useState(false);
@@ -237,9 +235,9 @@ export function useVoiceRecording({
event.preventDefault();
return;
}
baseHandleKeyDown(event);
// Let PromptInputTextarea handle remaining keys (Enter → submit, etc.)
},
[value, isTranscribing, stopRecording, startRecording, baseHandleKeyDown],
[value, isTranscribing, stopRecording, startRecording],
);
const showMicButton = isSupported;

151
autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx
View File

@@ -10,6 +10,7 @@ import {
MessageResponse,
} from "@/components/ai-elements/message";
import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
import { useEffect, useState } from "react";
import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent";
@@ -27,9 +28,56 @@ import { GenericTool } from "../../tools/GenericTool/GenericTool";
import { ViewAgentOutputTool } from "../../tools/ViewAgentOutput/ViewAgentOutput";
// ---------------------------------------------------------------------------
// Workspace media support
// Special text parsing (error markers, workspace URLs, etc.)
// ---------------------------------------------------------------------------
// Special message prefixes for text-based markers (set by backend)
const COPILOT_ERROR_PREFIX = "[COPILOT_ERROR]";
const COPILOT_SYSTEM_PREFIX = "[COPILOT_SYSTEM]";
type MarkerType = "error" | "system" | null;
/**
* Parse special markers from message content (error, system).
*
* Detects markers added by the backend for special rendering:
* - `[COPILOT_ERROR] message` → ErrorCard
* - `[COPILOT_SYSTEM] message` → System info message
*
* Returns marker type, marker text, and cleaned text.
*/
function parseSpecialMarkers(text: string): {
markerType: MarkerType;
markerText: string;
cleanText: string;
} {
// Check for error marker
const errorMatch = text.match(
new RegExp(`\\${COPILOT_ERROR_PREFIX}\\s*(.+?)$`, "s"),
);
if (errorMatch) {
return {
markerType: "error",
markerText: errorMatch[1].trim(),
cleanText: text.replace(errorMatch[0], "").trim(),
};
}
// Check for system marker
const systemMatch = text.match(
new RegExp(`\\${COPILOT_SYSTEM_PREFIX}\\s*(.+?)$`, "s"),
);
if (systemMatch) {
return {
markerType: "system",
markerText: systemMatch[1].trim(),
cleanText: text.replace(systemMatch[0], "").trim(),
};
}
return { markerType: null, markerText: "", cleanText: text };
}
/**
* Resolve workspace:// URLs in markdown text to proxy download URLs.
*
@@ -56,11 +104,15 @@ function resolveWorkspaceUrls(text: string): string {
// These are blocked by Streamdown's rehype-harden sanitizer because
// "workspace://" is not in the allowed URL-scheme whitelist, which causes
// "[blocked]" to appear next to the link text.
// Use an absolute URL so Streamdown's "Copy link" button copies the full
// URL (including host) rather than just the path.
resolved = resolved.replace(
/(?<!!)\[([^\]]*)\]\(workspace:\/\/([^)#\s]+)(?:#[^)#\s]*)?\)/g,
(_match, linkText: string, fileId: string) => {
const apiPath = getGetWorkspaceDownloadFileByIdUrl(fileId);
const url = `/api/proxy${apiPath}`;
const origin =
typeof window !== "undefined" ? window.location.origin : "";
const url = `${origin}/api/proxy${apiPath}`;
return `[${linkText || "Download file"}](${url})`;
},
);
@@ -147,24 +199,42 @@ export const ChatMessagesContainer = ({
}: ChatMessagesContainerProps) => {
const [thinkingPhrase, setThinkingPhrase] = useState(getRandomPhrase);
useEffect(() => {
if (status === "submitted") {
setThinkingPhrase(getRandomPhrase());
}
}, [status]);
const lastMessage = messages[messages.length - 1];
const lastAssistantHasVisibleContent =
lastMessage?.role === "assistant" &&
lastMessage.parts.some(
(p) =>
(p.type === "text" && p.text.trim().length > 0) ||
p.type.startsWith("tool-"),
);
// Determine if something is visibly "in-flight" in the last assistant message:
// - Text is actively streaming (last part is non-empty text)
// - A tool call is pending (state is input-streaming or input-available)
const hasInflight = (() => {
if (lastMessage?.role !== "assistant") return false;
const parts = lastMessage.parts;
if (parts.length === 0) return false;
const lastPart = parts[parts.length - 1];
// Text is actively being written
if (lastPart.type === "text" && lastPart.text.trim().length > 0)
return true;
// A tool call is still pending (no output yet)
if (
lastPart.type.startsWith("tool-") &&
"state" in lastPart &&
(lastPart.state === "input-streaming" ||
lastPart.state === "input-available")
)
return true;
return false;
})();
const showThinking =
status === "submitted" ||
(status === "streaming" && !lastAssistantHasVisibleContent);
status === "submitted" || (status === "streaming" && !hasInflight);
useEffect(() => {
if (showThinking) {
setThinkingPhrase(getRandomPhrase());
}
}, [showThinking]);
return (
<Conversation className="min-h-0 flex-1">
@@ -182,11 +252,6 @@ export const ChatMessagesContainer = ({
const isLastAssistant =
messageIndex === messages.length - 1 &&
message.role === "assistant";
const messageHasVisibleContent = message.parts.some(
(p) =>
(p.type === "text" && p.text.trim().length > 0) ||
p.type.startsWith("tool-"),
);
return (
<Message from={message.role} key={message.id}>
@@ -199,15 +264,41 @@ export const ChatMessagesContainer = ({
>
{message.parts.map((part, i) => {
switch (part.type) {
case "text":
case "text": {
// Check for special markers (error, system)
const { markerType, markerText, cleanText } =
parseSpecialMarkers(part.text);
if (markerType === "error") {
return (
<ErrorCard
key={`${message.id}-${i}`}
responseError={{ message: markerText }}
context="execution"
/>
);
}
if (markerType === "system") {
return (
<div
key={`${message.id}-${i}`}
className="my-2 rounded-lg bg-neutral-100 px-3 py-2 text-sm italic text-neutral-600"
>
{markerText}
</div>
);
}
return (
<MessageResponse
key={`${message.id}-${i}`}
components={STREAMDOWN_COMPONENTS}
>
{resolveWorkspaceUrls(part.text)}
{resolveWorkspaceUrls(cleanText)}
</MessageResponse>
);
}
case "tool-find_block":
return (
<FindBlocksTool
@@ -295,13 +386,11 @@ export const ChatMessagesContainer = ({
return null;
}
})}
{isLastAssistant &&
!messageHasVisibleContent &&
showThinking && (
<span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
{thinkingPhrase}
</span>
)}
{isLastAssistant && showThinking && (
<span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
{thinkingPhrase}
</span>
)}
</MessageContent>
</Message>
);

16
autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx
View File

@@ -16,6 +16,10 @@ import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
import { ClarificationQuestionsCard } from "./components/ClarificationQuestionsCard";
import { MiniGame } from "../../components/MiniGame/MiniGame";
import { SuggestedGoalCard } from "./components/SuggestedGoalCard";
import {
buildClarificationAnswersMessage,
normalizeClarifyingQuestions,
} from "../clarifying-questions";
import {
AccordionIcon,
formatMaybeJson,
@@ -28,7 +32,6 @@ import {
isSuggestedGoalOutput,
ToolIcon,
truncateText,
normalizeClarifyingQuestions,
type CreateAgentToolOutput,
} from "./helpers";
@@ -110,16 +113,7 @@ export function CreateAgentTool({ part }: Props) {
? (output.questions ?? [])
: [];
const contextMessage = questions
.map((q) => {
const answer = answers[q.keyword] || "";
return `> ${q.question}\n\n${answer}`;
})
.join("\n\n");
onSend(
`**Here are my answers:**\n\n${contextMessage}\n\nPlease proceed with creating the agent.`,
);
onSend(buildClarificationAnswersMessage(answers, questions, "create"));
}
return (

8
autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/ClarificationQuestionsCard.tsx
View File

@@ -7,7 +7,7 @@ import { Text } from "@/components/atoms/Text/Text";
import { cn } from "@/lib/utils";
import { ChatTeardropDotsIcon, CheckCircleIcon } from "@phosphor-icons/react";
import { useEffect, useRef, useState } from "react";
import type { ClarifyingQuestion } from "../helpers";
import type { ClarifyingQuestion } from "../../clarifying-questions";
interface Props {
questions: ClarifyingQuestion[];
@@ -149,20 +149,20 @@ export function ClarificationQuestionsCard({
<div className="space-y-6">
{questions.map((q, index) => {
const isAnswered = !!answers[q.keyword]?.trim();
const hasAnswer = !!answers[q.keyword]?.trim();
return (
<div
key={`${q.keyword}-${index}`}
className={cn(
"relative rounded-lg border border-dotted p-3",
isAnswered
hasAnswer
? "border-green-500 bg-green-50/50"
: "border-slate-100 bg-slate-50/50",
)}
>
<div className="mb-2 flex items-start gap-2">
{isAnswered ? (
{hasAnswer ? (
<CheckCircleIcon
size={20}
className="mt-0.5 text-green-500"

38
autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/helpers.tsx
View File

@@ -157,41 +157,3 @@ export function truncateText(text: string, maxChars: number): string {
if (trimmed.length <= maxChars) return trimmed;
return `${trimmed.slice(0, maxChars).trimEnd()}…`;
}
export interface ClarifyingQuestion {
question: string;
keyword: string;
example?: string;
}
export function normalizeClarifyingQuestions(
questions: Array<{ question: string; keyword: string; example?: unknown }>,
): ClarifyingQuestion[] {
const seen = new Set<string>();
return questions.map((q, index) => {
let keyword = q.keyword?.trim().toLowerCase() || "";
if (!keyword) {
keyword = `question-${index}`;
}
let unique = keyword;
let suffix = 1;
while (seen.has(unique)) {
unique = `${keyword}-${suffix}`;
suffix++;
}
seen.add(unique);
const item: ClarifyingQuestion = {
question: q.question,
keyword: unique,
};
const example =
typeof q.example === "string" && q.example.trim()
? q.example.trim()
: null;
if (example) item.example = example;
return item;
});
}

16
autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/EditAgent.tsx
View File

@@ -14,8 +14,11 @@ import {
ContentMessage,
} from "../../components/ToolAccordion/AccordionContent";
import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
import {
buildClarificationAnswersMessage,
normalizeClarifyingQuestions,
} from "../clarifying-questions";
import { ClarificationQuestionsCard } from "../CreateAgent/components/ClarificationQuestionsCard";
import { normalizeClarifyingQuestions } from "../CreateAgent/helpers";
import {
AccordionIcon,
formatMaybeJson,
@@ -99,16 +102,7 @@ export function EditAgentTool({ part }: Props) {
? (output.questions ?? [])
: [];
const contextMessage = questions
.map((q) => {
const answer = answers[q.keyword] || "";
return `> ${q.question}\n\n${answer}`;
})
.join("\n\n");
onSend(
`**Here are my answers:**\n\n${contextMessage}\n\nPlease proceed with editing the agent.`,
);
onSend(buildClarificationAnswersMessage(answers, questions, "edit"));
}
return (

10
autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/AgentDetailsCard.tsx
View File

@@ -3,7 +3,7 @@
import type { AgentDetailsResponse } from "@/app/api/__generated__/models/agentDetailsResponse";
import { Button } from "@/components/atoms/Button/Button";
import { FormRenderer } from "@/components/renderers/InputRenderer/FormRenderer";
import { useState } from "react";
import { useEffect, useState } from "react";
import { useCopilotChatActions } from "../../../../components/CopilotChatActionsProvider/useCopilotChatActions";
import { ContentMessage } from "../../../../components/ToolAccordion/AccordionContent";
import { buildInputSchema, extractDefaults, isFormValid } from "./helpers";
@@ -24,6 +24,14 @@ export function AgentDetailsCard({ output }: Props) {
schema ? isFormValid(schema, defaults) : false,
);
// Reset form state when the agent changes (e.g. during mid-conversation switches)
useEffect(() => {
const newSchema = buildInputSchema(output.agent.inputs);
const newDefaults = newSchema ? extractDefaults(newSchema) : {};
setInputValues(newDefaults);
setValid(newSchema ? isFormValid(newSchema, newDefaults) : false);
}, [output.agent.id]);
function handleChange(v: { formData?: Record<string, unknown> }) {
const data = v.formData ?? {};
setInputValues(data);

106
autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/helpers.test.ts Normal file
View File

@@ -0,0 +1,106 @@
import type { RJSFSchema } from "@rjsf/utils";
import { describe, expect, it } from "vitest";
import { buildInputSchema, extractDefaults, isFormValid } from "./helpers";
describe("buildInputSchema", () => {
it("returns null for falsy input", () => {
expect(buildInputSchema(null)).toBeNull();
expect(buildInputSchema(undefined)).toBeNull();
expect(buildInputSchema("")).toBeNull();
});
it("returns null for empty properties object", () => {
expect(buildInputSchema({})).toBeNull();
});
it("returns the schema when properties exist", () => {
const schema = { name: { type: "string" as const } };
expect(buildInputSchema(schema)).toBe(schema);
});
});
describe("extractDefaults", () => {
it("returns an empty object when no properties exist", () => {
expect(extractDefaults({})).toEqual({});
expect(extractDefaults({ properties: null as never })).toEqual({});
});
it("extracts default values from property definitions", () => {
const schema: RJSFSchema = {
properties: {
name: { type: "string", default: "Alice" },
age: { type: "number", default: 30 },
},
};
expect(extractDefaults(schema)).toEqual({ name: "Alice", age: 30 });
});
it("falls back to the first example when no default is defined", () => {
const schema: RJSFSchema = {
properties: {
query: { type: "string", examples: ["hello", "world"] },
},
};
expect(extractDefaults(schema)).toEqual({ query: "hello" });
});
it("prefers default over examples", () => {
const schema: RJSFSchema = {
properties: {
value: { type: "string", default: "def", examples: ["ex"] },
},
};
expect(extractDefaults(schema)).toEqual({ value: "def" });
});
it("skips properties without default or examples", () => {
const schema: RJSFSchema = {
properties: {
name: { type: "string" },
title: { type: "string", default: "Mr." },
},
};
expect(extractDefaults(schema)).toEqual({ title: "Mr." });
});
it("skips properties that are not objects", () => {
const schema: RJSFSchema = {
properties: {
bad: true,
alsobad: false,
},
};
expect(extractDefaults(schema)).toEqual({});
});
});
describe("isFormValid", () => {
it("returns true for a valid form", () => {
const schema: RJSFSchema = {
type: "object",
properties: {
name: { type: "string" },
},
};
expect(isFormValid(schema, { name: "Alice" })).toBe(true);
});
it("returns false when required fields are missing", () => {
const schema: RJSFSchema = {
type: "object",
required: ["name"],
properties: {
name: { type: "string" },
},
};
expect(isFormValid(schema, {})).toBe(false);
});
it("returns true for empty schema with empty data", () => {
const schema: RJSFSchema = {
type: "object",
properties: {},
};
expect(isFormValid(schema, {})).toBe(true);
});
});

93
autogpt_platform/frontend/src/app/(platform)/copilot/tools/clarifying-questions.test.ts Normal file
View File

@@ -0,0 +1,93 @@
import { describe, expect, it } from "vitest";
import {
buildClarificationAnswersMessage,
normalizeClarifyingQuestions,
} from "./clarifying-questions";
describe("normalizeClarifyingQuestions", () => {
it("returns normalized questions with trimmed lowercase keywords", () => {
const result = normalizeClarifyingQuestions([
{ question: "What is your goal?", keyword: " Goal ", example: "test" },
]);
expect(result).toEqual([
{ question: "What is your goal?", keyword: "goal", example: "test" },
]);
});
it("deduplicates keywords by appending a numeric suffix", () => {
const result = normalizeClarifyingQuestions([
{ question: "Q1", keyword: "topic" },
{ question: "Q2", keyword: "topic" },
{ question: "Q3", keyword: "topic" },
]);
expect(result.map((q) => q.keyword)).toEqual([
"topic",
"topic-1",
"topic-2",
]);
});
it("falls back to question-{index} when keyword is empty", () => {
const result = normalizeClarifyingQuestions([
{ question: "First?", keyword: "" },
{ question: "Second?", keyword: " " },
]);
expect(result[0].keyword).toBe("question-0");
expect(result[1].keyword).toBe("question-1");
});
it("coerces non-string examples to undefined", () => {
const result = normalizeClarifyingQuestions([
{ question: "Q1", keyword: "k1", example: 42 },
{ question: "Q2", keyword: "k2", example: null },
{ question: "Q3", keyword: "k3", example: { nested: true } },
]);
expect(result[0].example).toBeUndefined();
expect(result[1].example).toBeUndefined();
expect(result[2].example).toBeUndefined();
});
it("trims string examples and omits empty ones", () => {
const result = normalizeClarifyingQuestions([
{ question: "Q1", keyword: "k1", example: " valid " },
{ question: "Q2", keyword: "k2", example: " " },
]);
expect(result[0].example).toBe("valid");
expect(result[1].example).toBeUndefined();
});
it("returns an empty array for empty input", () => {
expect(normalizeClarifyingQuestions([])).toEqual([]);
});
});
describe("buildClarificationAnswersMessage", () => {
it("formats answers with create mode", () => {
const result = buildClarificationAnswersMessage(
{ goal: "automate tasks" },
[{ question: "What is your goal?", keyword: "goal" }],
"create",
);
expect(result).toContain("> What is your goal?");
expect(result).toContain("automate tasks");
expect(result).toContain("Please proceed with creating the agent.");
});
it("formats answers with edit mode", () => {
const result = buildClarificationAnswersMessage(
{ goal: "fix bugs" },
[{ question: "What should change?", keyword: "goal" }],
"edit",
);
expect(result).toContain("Please proceed with editing the agent.");
});
it("uses empty string for missing answers", () => {
const result = buildClarificationAnswersMessage(
{},
[{ question: "Q?", keyword: "missing" }],
"create",
);
expect(result).toContain("> Q?\n\n");
});
});

56
autogpt_platform/frontend/src/app/(platform)/copilot/tools/clarifying-questions.ts Normal file
View File

@@ -0,0 +1,56 @@
export interface ClarifyingQuestion {
question: string;
keyword: string;
example?: string;
}
export function normalizeClarifyingQuestions(
questions: Array<{ question: string; keyword: string; example?: unknown }>,
): ClarifyingQuestion[] {
const seen = new Set<string>();
return questions.map((q, index) => {
let keyword = q.keyword?.trim().toLowerCase() || "";
if (!keyword) {
keyword = `question-${index}`;
}
let unique = keyword;
let suffix = 1;
while (seen.has(unique)) {
unique = `${keyword}-${suffix}`;
suffix++;
}
seen.add(unique);
const item: ClarifyingQuestion = {
question: q.question,
keyword: unique,
};
const example =
typeof q.example === "string" && q.example.trim()
? q.example.trim()
: null;
if (example) item.example = example;
return item;
});
}
/**
* Formats clarification answers as a context message and sends it via onSend.
*/
export function buildClarificationAnswersMessage(
answers: Record<string, string>,
rawQuestions: Array<{ question: string; keyword: string }>,
mode: "create" | "edit",
): string {
const contextMessage = rawQuestions
.map((q) => {
const answer = answers[q.keyword] || "";
return `> ${q.question}\n\n${answer}`;
})
.join("\n\n");
const action = mode === "create" ? "creating" : "editing";
return `**Here are my answers:**\n\n${contextMessage}\n\nPlease proceed with ${action} the agent.`;
}

5
autogpt_platform/frontend/src/app/(platform)/copilot/useChatSession.ts
View File

@@ -18,7 +18,7 @@ export function useChatSession() {
const sessionQuery = useGetV2GetSession(sessionId ?? "", {
query: {
enabled: !!sessionId,
staleTime: Infinity,
staleTime: Infinity, // Manual invalidation on session switch
refetchOnWindowFocus: false,
refetchOnReconnect: true,
refetchOnMount: true,
@@ -47,7 +47,7 @@ export function useChatSession() {
const hasActiveStream = useMemo(() => {
if (sessionQuery.data?.status !== 200) return false;
return !!sessionQuery.data.data.active_stream;
}, [sessionQuery.data]);
}, [sessionQuery.data, sessionId]);
// Memoize so the effect in useCopilotPage doesn't infinite-loop on a new
// array reference every render. Re-derives only when query data changes.
@@ -119,5 +119,6 @@ export function useChatSession() {
isSessionError: sessionQuery.isError,
createSession,
isCreatingSession,
refetchSession: sessionQuery.refetch,
};
}

168
autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts
View File

@@ -15,7 +15,9 @@ import type { UIMessage } from "ai";
import { useCallback, useEffect, useMemo, useRef, useState } from "react";
import { useChatSession } from "./useChatSession";
const STREAM_START_TIMEOUT_MS = 12_000;
const RECONNECT_BASE_DELAY_MS = 1_000;
const RECONNECT_MAX_DELAY_MS = 30_000;
const RECONNECT_MAX_ATTEMPTS = 5;
/** Mark any in-progress tool parts as completed/errored so spinners stop. */
function resolveInProgressTools(
@@ -35,42 +37,12 @@ function resolveInProgressTools(
}));
}
/** Build a fingerprint from a message's role + text/tool content for cross-boundary dedup. */
function messageFingerprint(msg: UIMessage): string {
const fragments = msg.parts.map((p) => {
if ("text" in p && typeof p.text === "string") return p.text;
if ("toolCallId" in p && typeof p.toolCallId === "string")
return `tool:${p.toolCallId}`;
return "";
});
return `${msg.role}::${fragments.join("\n")}`;
}
/**
* Deduplicate messages by ID *and* by content fingerprint.
* ID-based dedup catches duplicates within the same source (e.g. two
* identical stream events). Fingerprint-based dedup catches duplicates
* across the hydration/stream boundary where IDs differ (synthetic
* `${sessionId}-${index}` vs AI SDK nanoid).
*
* NOTE: Fingerprint dedup only applies to assistant messages, not user messages.
* Users should be able to send the same message multiple times.
*/
/** Simple ID-based deduplication - trust backend for correctness */
function deduplicateMessages(messages: UIMessage[]): UIMessage[] {
const seenIds = new Set<string>();
const seenFingerprints = new Set<string>();
return messages.filter((msg) => {
if (seenIds.has(msg.id)) return false;
seenIds.add(msg.id);
// Only apply fingerprint deduplication to assistant messages
// User messages should allow duplicates (same text sent multiple times)
if (msg.role === "assistant") {
const fp = messageFingerprint(msg);
if (fp !== "::" && seenFingerprints.has(fp)) return false;
seenFingerprints.add(fp);
}
return true;
});
}
@@ -94,6 +66,7 @@ export function useCopilotPage() {
isSessionError,
createSession,
isCreatingSession,
refetchSession,
} = useChatSession();
const { mutate: deleteSessionMutation, isPending: isDeleting } =
@@ -153,6 +126,48 @@ export function useCopilotPage() {
[sessionId],
);
// Reconnect state
const [reconnectAttempts, setReconnectAttempts] = useState(0);
const [isReconnectScheduled, setIsReconnectScheduled] = useState(false);
const reconnectTimerRef = useRef<ReturnType<typeof setTimeout>>();
const hasShownDisconnectToast = useRef(false);
// Consolidated reconnect logic
function handleReconnect(sid: string) {
if (isReconnectScheduled || !sid) return;
const nextAttempt = reconnectAttempts + 1;
if (nextAttempt > RECONNECT_MAX_ATTEMPTS) {
toast({
title: "Connection lost",
description: "Unable to reconnect. Please refresh the page.",
variant: "destructive",
});
return;
}
setIsReconnectScheduled(true);
setReconnectAttempts(nextAttempt);
if (!hasShownDisconnectToast.current) {
hasShownDisconnectToast.current = true;
toast({
title: "Connection lost",
description: "Reconnecting...",
});
}
const delay = Math.min(
RECONNECT_BASE_DELAY_MS * 2 ** reconnectAttempts,
RECONNECT_MAX_DELAY_MS,
);
reconnectTimerRef.current = setTimeout(() => {
setIsReconnectScheduled(false);
resumeStream();
}, delay);
}
const {
messages: rawMessages,
sendMessage,
@@ -164,9 +179,32 @@ export function useCopilotPage() {
} = useChat({
id: sessionId ?? undefined,
transport: transport ?? undefined,
// Don't use resume: true — it fires before hydration completes, causing
// the hydrated messages to overwrite the resumed stream. Instead we
// call resumeStream() manually after hydration + active_stream detection.
onFinish: async ({ isDisconnect, isAbort }) => {
if (isAbort || !sessionId) return;
if (isDisconnect) {
handleReconnect(sessionId);
return;
}
// Check if backend executor is still running after clean close
const result = await refetchSession();
const backendActive =
result.data?.status === 200 && !!result.data.data.active_stream;
if (backendActive) {
handleReconnect(sessionId);
}
},
onError: (error) => {
if (!sessionId) return;
// Only reconnect on network errors (not HTTP errors)
const isNetworkError =
error.name === "TypeError" || error.name === "AbortError";
if (isNetworkError) {
handleReconnect(sessionId);
}
},
});
// Deduplicate messages continuously to prevent duplicates when resuming streams
@@ -205,44 +243,31 @@ export function useCopilotPage() {
}
}
// Abort the stream if the backend doesn't start sending data within 12s.
const stopRef = useRef(stop);
stopRef.current = stop;
useEffect(() => {
if (status !== "submitted") return;
const timer = setTimeout(() => {
stopRef.current();
toast({
title: "Stream timed out",
description: "The server took too long to respond. Please try again.",
variant: "destructive",
});
}, STREAM_START_TIMEOUT_MS);
return () => clearTimeout(timer);
}, [status]);
// Hydrate messages from the REST session endpoint.
// Skip hydration while streaming to avoid overwriting the live stream.
// Hydrate messages from REST API when not actively streaming
useEffect(() => {
if (!hydratedMessages || hydratedMessages.length === 0) return;
if (status === "streaming" || status === "submitted") return;
if (isReconnectScheduled) return;
setMessages((prev) => {
if (prev.length >= hydratedMessages.length) return prev;
// Deduplicate to handle rare cases where duplicate streams might occur
return deduplicateMessages(hydratedMessages);
});
}, [hydratedMessages, setMessages, status]);
}, [hydratedMessages, setMessages, status, isReconnectScheduled]);
// Ref: tracks whether we've already resumed for a given session.
// Format: Map<sessionId, hasResumed>
// Track resume state per session
const hasResumedRef = useRef<Map<string, boolean>>(new Map());
// When the stream ends (or drops), invalidate the session cache so the
// next hydration fetches fresh messages from the backend. Without this,
// staleTime: Infinity means the cache keeps the pre-stream data forever,
// and any messages added during streaming are lost on remount/navigation.
// Clean up reconnect state on session switch
useEffect(() => {
clearTimeout(reconnectTimerRef.current);
reconnectTimerRef.current = undefined;
setReconnectAttempts(0);
setIsReconnectScheduled(false);
hasShownDisconnectToast.current = false;
prevStatusRef.current = status; // Reset to avoid cross-session state bleeding
}, [sessionId, status]);
// Invalidate session cache when stream completes
const prevStatusRef = useRef(status);
useEffect(() => {
const prev = prevStatusRef.current;
@@ -250,12 +275,17 @@ export function useCopilotPage() {
const wasActive = prev === "streaming" || prev === "submitted";
const isIdle = status === "ready" || status === "error";
if (wasActive && isIdle && sessionId) {
if (wasActive && isIdle && sessionId && !isReconnectScheduled) {
queryClient.invalidateQueries({
queryKey: getGetV2GetSessionQueryKey(sessionId),
});
if (status === "ready") {
setReconnectAttempts(0);
hasShownDisconnectToast.current = false;
}
}
}, [status, sessionId, queryClient]);
}, [status, sessionId, queryClient, isReconnectScheduled]);
// Resume an active stream AFTER hydration completes.
// IMPORTANT: Only runs when page loads with existing active stream (reconnection).
@@ -352,16 +382,16 @@ export function useCopilotPage() {
}
}, [isDeleting]);
// True while we know the backend has an active stream but haven't
// reconnected yet. Used to disable the send button and show stop UI.
// True while reconnecting or backend has active stream but we haven't connected yet
const isReconnecting =
hasActiveStream && status !== "streaming" && status !== "submitted";
isReconnectScheduled ||
(hasActiveStream && status !== "streaming" && status !== "submitted");
return {
sessionId,
messages,
status,
error,
error: isReconnecting ? undefined : error,
stop,
isReconnecting,
isLoadingSession,

16
autogpt_platform/frontend/src/app/api/chat/sessions/[sessionId]/stream/route.ts
View File

@@ -3,6 +3,20 @@ import { getServerAuthToken } from "@/lib/autogpt-server-api/helpers";
import { NextRequest } from "next/server";
import { normalizeSSEStream, SSE_HEADERS } from "../../../sse-helpers";
export const maxDuration = 800;
const DEBUG_SSE_TIMEOUT_MS = process.env.NEXT_PUBLIC_SSE_TIMEOUT_MS
? Number(process.env.NEXT_PUBLIC_SSE_TIMEOUT_MS)
: undefined;
function debugSignal(): AbortSignal | undefined {
if (!DEBUG_SSE_TIMEOUT_MS) return undefined;
console.warn(
`[SSE_DEBUG] Simulating proxy timeout in ${DEBUG_SSE_TIMEOUT_MS}ms`,
);
return AbortSignal.timeout(DEBUG_SSE_TIMEOUT_MS);
}
export async function POST(
request: NextRequest,
{ params }: { params: Promise<{ sessionId: string }> },
@@ -47,6 +61,7 @@ export async function POST(
is_user_message: is_user_message ?? true,
context: context || null,
}),
signal: debugSignal(),
});
if (!response.ok) {
@@ -110,6 +125,7 @@ export async function GET(
const response = await fetch(streamUrl.toString(), {
method: "GET",
headers,
signal: debugSignal(),
});
if (response.status === 204) {

2
autogpt_platform/frontend/src/app/api/openapi.json
View File

@@ -7573,9 +7573,11 @@
"IDENTITY",
"EXECUTE_GRAPH",
"READ_GRAPH",
"WRITE_GRAPH",
"EXECUTE_BLOCK",
"READ_BLOCK",
"READ_STORE",
"WRITE_LIBRARY",
"USE_TOOLS",
"MANAGE_INTEGRATIONS",
"READ_INTEGRATIONS",

5
autogpt_platform/frontend/src/app/globals.css
View File

@@ -181,6 +181,11 @@ body[data-google-picker-open="true"] [data-dialog-content] {
pointer-events: none !important;
}
/* Streamdown external link dialog: "Open link" button */
[data-streamdown="link-safety-modal"] button:last-of-type {
color: black;
}
/* CoPilot chat table styling — remove left/right borders, increase padding */
[data-streamdown="table-wrapper"] table {
border-left: none;

10
autogpt_platform/frontend/src/components/ai-elements/conversation.tsx
View File

@@ -61,15 +61,11 @@ export const ConversationEmptyState = ({
>
{children ?? (
<>
{icon && (
<div className="text-neutral-500 dark:text-neutral-400">{icon}</div>
)}
{icon && <div className="text-neutral-500">{icon}</div>}
<div className="space-y-1">
<h3 className="text-sm font-medium">{title}</h3>
{description && (
<p className="text-sm text-neutral-500 dark:text-neutral-400">
{description}
</p>
<p className="text-sm text-neutral-500">{description}</p>
)}
</div>
</>
@@ -93,7 +89,7 @@ export const ConversationScrollButton = ({
!isAtBottom && (
<Button
className={cn(
"absolute bottom-4 left-[50%] translate-x-[-50%] rounded-full dark:bg-white dark:dark:bg-neutral-950 dark:dark:hover:bg-neutral-800 dark:hover:bg-neutral-100",
"absolute bottom-4 left-[50%] translate-x-[-50%] rounded-full",
className,
)}
onClick={handleScrollToBottom}

110
autogpt_platform/frontend/src/components/ai-elements/message.stories.tsx Normal file
View File

@@ -0,0 +1,110 @@
import type { Meta, StoryObj } from "@storybook/nextjs";
import { Message, MessageContent, MessageResponse } from "./message";
const meta: Meta<typeof Message> = {
title: "AI Elements/Message",
component: Message,
parameters: {
layout: "padded",
},
};
export default meta;
type Story = StoryObj<typeof Message>;
type MessageStoryProps = { children: string };
function AssistantMessage({ children }: MessageStoryProps) {
return (
<Message from="assistant">
<MessageContent>
<MessageResponse>{children}</MessageResponse>
</MessageContent>
</Message>
);
}
function UserMessage({ children }: MessageStoryProps) {
return (
<Message from="user">
<MessageContent>
<MessageResponse>{children}</MessageResponse>
</MessageContent>
</Message>
);
}
export const Default: Story = {
render: () => (
<div className="flex flex-col gap-4">
<AssistantMessage>
{
"Here is a response with **bold text**, *italic text*, and `inline code`."
}
</AssistantMessage>
</div>
),
};
export const UserMessageStory: Story = {
name: "User Message",
render: () => (
<div className="flex flex-col gap-4">
<UserMessage>{"How do I download my workspace files?"}</UserMessage>
</div>
),
};
export const WithLinks: Story = {
name: "With Links (Internal & External)",
render: () => (
<div className="flex flex-col gap-4">
<AssistantMessage>
{[
"Here are some links:\n\n",
"- Internal link: [Download file](/api/proxy/api/v1/workspace/files/download/abc123)\n",
"- External link: [GitHub](https://github.com/Significant-Gravitas/AutoGPT)\n",
"- Another external: [Documentation](https://docs.agpt.co)\n\n",
"Internal links should open directly. External links should show a safety modal.\n\n",
"**Try clicking each link to verify behavior.**",
].join("")}
</AssistantMessage>
</div>
),
};
export const LinkSafetyModal: Story = {
name: "LinkSafetyModal",
render: () => (
<div className="flex flex-col gap-4">
<p className="text-sm text-muted-foreground">
Click the external link below to trigger the link safety modal. Verify
that both &quot;Copy link&quot; and &quot;Open link&quot; buttons are
visible.
</p>
<AssistantMessage>
{
"Click this external link to see the safety modal: [Example Site](https://example.com)"
}
</AssistantMessage>
</div>
),
};
export const Conversation: Story = {
render: () => (
<div className="flex flex-col gap-4">
<UserMessage>{"Can you help me with my workspace files?"}</UserMessage>
<AssistantMessage>
{[
"Sure! Here's how to manage your workspace files:\n\n",
"1. Upload files using the attachment button\n",
"2. Download files by clicking the link in chat\n",
"3. View all files in the [workspace panel](/workspace)\n\n",
"For more details, check the [documentation](https://docs.agpt.co/workspace).",
].join("")}
</AssistantMessage>
</div>
),
};

19
autogpt_platform/frontend/src/components/ai-elements/message.tsx
View File

@@ -45,8 +45,8 @@ export const MessageContent = ({
className={cn(
"is-user:dark flex w-full min-w-0 max-w-full flex-col gap-2 overflow-hidden text-sm",
"group-[.is-user]:w-fit",
"group-[.is-user]:ml-auto group-[.is-user]:rounded-lg group-[.is-user]:bg-neutral-100 group-[.is-user]:px-4 group-[.is-user]:py-3 group-[.is-user]:text-neutral-950 dark:group-[.is-user]:bg-neutral-800 dark:group-[.is-user]:text-neutral-50",
"group-[.is-assistant]:text-neutral-950 dark:group-[.is-assistant]:text-neutral-50",
"group-[.is-user]:ml-auto group-[.is-user]:rounded-lg group-[.is-user]:bg-neutral-100 group-[.is-user]:px-4 group-[.is-user]:py-3 group-[.is-user]:text-neutral-950",
"group-[.is-assistant]:text-neutral-950",
className,
)}
{...props}
@@ -291,7 +291,7 @@ export const MessageBranchPage = ({
return (
<ButtonGroupText
className={cn(
"border-none bg-transparent text-neutral-500 shadow-none dark:text-neutral-400",
"border-none bg-transparent text-neutral-500 shadow-none",
className,
)}
{...props}
@@ -303,6 +303,15 @@ export const MessageBranchPage = ({
export type MessageResponseProps = ComponentProps<typeof Streamdown>;
function isSameOriginLink(url: string): boolean {
try {
const parsed = new URL(url, window.location.origin);
return parsed.origin === window.location.origin;
} catch {
return false;
}
}
export const MessageResponse = memo(
({ className, ...props }: MessageResponseProps) => (
<Streamdown
@@ -311,6 +320,10 @@ export const MessageResponse = memo(
className,
)}
plugins={{ code, mermaid, math, cjk }}
linkSafety={{
enabled: true,
onLinkCheck: isSameOriginLink,
}}
{...props}
/>
),

345
autogpt_platform/frontend/src/components/ai-elements/prompt-input.tsx Normal file
View File

@@ -0,0 +1,345 @@
"use client";
/**
* Adapted from AI SDK Elements `prompt-input` component.
* @see https://elements.ai-sdk.dev/components/prompt-input
*
* Stripped down to only the sub-components used by the copilot ChatInput:
* PromptInput, PromptInputBody, PromptInputTextarea, PromptInputFooter,
* PromptInputTools, PromptInputButton, PromptInputSubmit.
*/
import type { ChatStatus } from "ai";
import type {
ComponentProps,
FormEvent,
FormEventHandler,
HTMLAttributes,
KeyboardEventHandler,
ReactNode,
} from "react";
import {
InputGroup,
InputGroupAddon,
InputGroupButton,
InputGroupTextarea,
} from "@/components/ui/input-group";
import { Spinner } from "@/components/ui/spinner";
import {
Tooltip,
TooltipContent,
TooltipTrigger,
} from "@/components/ui/tooltip";
import { cn } from "@/lib/utils";
import {
ArrowUp as ArrowUpIcon,
Stop as StopIcon,
} from "@phosphor-icons/react";
import { Children, useCallback, useEffect, useRef, useState } from "react";
// ============================================================================
// PromptInput — form wrapper
// ============================================================================
export type PromptInputProps = Omit<
HTMLAttributes<HTMLFormElement>,
"onSubmit"
> & {
onSubmit: (
text: string,
event: FormEvent<HTMLFormElement>,
) => void | Promise<void>;
};
export function PromptInput({
className,
onSubmit,
children,
...props
}: PromptInputProps) {
const formRef = useRef<HTMLFormElement | null>(null);
const handleSubmit: FormEventHandler<HTMLFormElement> = useCallback(
async (event) => {
event.preventDefault();
const form = event.currentTarget;
const formData = new FormData(form);
const text = (formData.get("message") as string) || "";
const result = onSubmit(text, event);
if (result instanceof Promise) {
await result;
}
},
[onSubmit],
);
return (
<form
className={cn("w-full", className)}
onSubmit={handleSubmit}
ref={formRef}
{...props}
>
<InputGroup className="overflow-hidden">{children}</InputGroup>
</form>
);
}
// ============================================================================
// PromptInputBody — content wrapper
// ============================================================================
export type PromptInputBodyProps = HTMLAttributes<HTMLDivElement>;
export function PromptInputBody({ className, ...props }: PromptInputBodyProps) {
return <div className={cn("contents", className)} {...props} />;
}
// ============================================================================
// PromptInputTextarea — auto-resize textarea with Enter-to-submit
// ============================================================================
export type PromptInputTextareaProps = ComponentProps<
typeof InputGroupTextarea
>;
export function PromptInputTextarea({
onKeyDown,
onChange,
className,
placeholder = "Type your message...",
value,
...props
}: PromptInputTextareaProps) {
const [isComposing, setIsComposing] = useState(false);
const textareaRef = useRef<HTMLTextAreaElement | null>(null);
function autoResize(el: HTMLTextAreaElement) {
el.style.height = "auto";
el.style.height = `${el.scrollHeight}px`;
}
// Resize when value changes externally (e.g. cleared after send)
useEffect(() => {
if (textareaRef.current) autoResize(textareaRef.current);
}, [value]);
const handleChange = useCallback(
(e: React.ChangeEvent<HTMLTextAreaElement>) => {
autoResize(e.currentTarget);
onChange?.(e);
},
[onChange],
);
const handleKeyDown: KeyboardEventHandler<HTMLTextAreaElement> = useCallback(
(e) => {
// Call external handler first
onKeyDown?.(e);
if (e.defaultPrevented) return;
if (e.key === "Enter") {
if (isComposing || e.nativeEvent.isComposing) return;
if (e.shiftKey) return;
e.preventDefault();
const { form } = e.currentTarget;
const submitButton = form?.querySelector(
'button[type="submit"]',
) as HTMLButtonElement | null;
if (submitButton?.disabled) return;
form?.requestSubmit();
}
},
[onKeyDown, isComposing],
);
const handleCompositionEnd = useCallback(() => setIsComposing(false), []);
const handleCompositionStart = useCallback(() => setIsComposing(true), []);
return (
<InputGroupTextarea
ref={textareaRef}
rows={1}
className={cn(
"max-h-48 min-h-0 text-base leading-6 md:text-base",
className,
)}
name="message"
value={value}
onChange={handleChange}
onCompositionEnd={handleCompositionEnd}
onCompositionStart={handleCompositionStart}
onKeyDown={handleKeyDown}
placeholder={placeholder}
{...props}
/>
);
}
// ============================================================================
// PromptInputFooter — bottom bar
// ============================================================================
export type PromptInputFooterProps = Omit<
ComponentProps<typeof InputGroupAddon>,
"align"
>;
export function PromptInputFooter({
className,
...props
}: PromptInputFooterProps) {
return (
<InputGroupAddon
align="block-end"
className={cn("justify-between gap-1", className)}
{...props}
/>
);
}
// ============================================================================
// PromptInputTools — left-side button group
// ============================================================================
export type PromptInputToolsProps = HTMLAttributes<HTMLDivElement>;
export function PromptInputTools({
className,
...props
}: PromptInputToolsProps) {
return (
<div
className={cn("flex min-w-0 items-center gap-1", className)}
{...props}
/>
);
}
// ============================================================================
// PromptInputButton — tool button with optional tooltip
// ============================================================================
export type PromptInputButtonTooltip =
| string
| {
content: ReactNode;
shortcut?: string;
side?: ComponentProps<typeof TooltipContent>["side"];
};
export type PromptInputButtonProps = ComponentProps<typeof InputGroupButton> & {
tooltip?: PromptInputButtonTooltip;
};
export function PromptInputButton({
variant = "ghost",
className,
size,
tooltip,
...props
}: PromptInputButtonProps) {
const newSize =
size ?? (Children.count(props.children) > 1 ? "sm" : "icon-sm");
const button = (
<InputGroupButton
className={cn(className)}
size={newSize}
type="button"
variant={variant}
{...props}
/>
);
if (!tooltip) return button;
const tooltipContent =
typeof tooltip === "string" ? tooltip : tooltip.content;
const shortcut = typeof tooltip === "string" ? undefined : tooltip.shortcut;
const side = typeof tooltip === "string" ? "top" : (tooltip.side ?? "top");
return (
<Tooltip>
<TooltipTrigger asChild>{button}</TooltipTrigger>
<TooltipContent side={side}>
{tooltipContent}
{shortcut && (
<span className="ml-2 text-muted-foreground">{shortcut}</span>
)}
</TooltipContent>
</Tooltip>
);
}
// ============================================================================
// PromptInputSubmit — send / stop button
// ============================================================================
export type PromptInputSubmitProps = ComponentProps<typeof InputGroupButton> & {
status?: ChatStatus;
onStop?: () => void;
};
export function PromptInputSubmit({
className,
variant = "default",
size = "icon-sm",
status,
onStop,
onClick,
disabled,
children,
...props
}: PromptInputSubmitProps) {
const isGenerating = status === "submitted" || status === "streaming";
const canStop = isGenerating && Boolean(onStop);
const isDisabled = Boolean(disabled) || (isGenerating && !canStop);
let Icon = <ArrowUpIcon className="size-4" weight="bold" />;
if (status === "submitted") {
Icon = <Spinner />;
} else if (status === "streaming") {
Icon = <StopIcon className="size-4" weight="bold" />;
}
const handleClick = useCallback(
(e: React.MouseEvent<HTMLButtonElement>) => {
if (canStop && onStop) {
e.preventDefault();
onStop();
return;
}
if (isGenerating) {
e.preventDefault();
return;
}
onClick?.(e);
},
[canStop, isGenerating, onStop, onClick],
);
return (
<InputGroupButton
aria-label={canStop ? "Stop" : "Submit"}
className={cn(
"size-[2.625rem] rounded-full border-zinc-800 bg-zinc-800 text-white hover:border-zinc-900 hover:bg-zinc-900 disabled:border-zinc-200 disabled:bg-zinc-200 disabled:text-white disabled:opacity-100",
className,
)}
disabled={isDisabled}
onClick={handleClick}
size={size}
type={canStop ? "button" : "submit"}
variant={variant}
{...props}
>
{children ?? Icon}
</InputGroupButton>
);
}

129
autogpt_platform/frontend/src/components/ui/input-group.tsx Normal file
View File

@@ -0,0 +1,129 @@
"use client";
import * as React from "react";
import { cva, type VariantProps } from "class-variance-authority";
import { cn } from "@/lib/utils";
import { Button } from "@/components/ui/button";
import { Textarea } from "@/components/ui/textarea";
function InputGroup({ className, ...props }: React.ComponentProps<"div">) {
return (
<div
data-slot="input-group"
role="group"
className={cn(
"group/input-group relative flex w-full items-center rounded-xlarge border border-neutral-200 bg-white shadow-sm outline-none transition-[color,box-shadow]",
"min-w-0 has-[>textarea]:h-auto",
// Variants based on alignment.
"has-[>[data-align=block-start]]:h-auto has-[>[data-align=block-start]]:flex-col",
"has-[>[data-align=block-end]]:h-auto has-[>[data-align=block-end]]:flex-col",
// Focus state.
"has-[[data-slot=input-group-control]:focus-visible]:border-zinc-400 has-[[data-slot=input-group-control]:focus-visible]:ring-1 has-[[data-slot=input-group-control]:focus-visible]:ring-zinc-400",
className,
)}
{...props}
/>
);
}
const inputGroupAddonVariants = cva(
"text-muted-foreground flex h-auto cursor-text items-center justify-center gap-2 py-1.5 text-sm font-medium select-none group-data-[disabled=true]/input-group:opacity-50",
{
variants: {
align: {
"inline-start": "order-first pl-3",
"inline-end": "order-last pr-3",
"block-start": "order-first w-full justify-start px-3 pt-3",
"block-end": "order-last w-full justify-start px-3 pb-3",
},
},
defaultVariants: {
align: "inline-start",
},
},
);
function InputGroupAddon({
className,
align = "inline-start",
onClick,
...props
}: React.ComponentProps<"div"> & VariantProps<typeof inputGroupAddonVariants>) {
return (
<div
role="group"
data-slot="input-group-addon"
data-align={align}
className={cn(inputGroupAddonVariants({ align }), className)}
onClick={(e) => {
onClick?.(e);
if (e.defaultPrevented) return;
if ((e.target as HTMLElement).closest("button")) {
return;
}
e.currentTarget.parentElement?.querySelector("textarea")?.focus();
}}
{...props}
/>
);
}
const inputGroupButtonVariants = cva(
"text-sm shadow-none flex min-w-0 gap-2 items-center",
{
variants: {
size: {
xs: "h-6 gap-1 px-2 rounded-md has-[>svg]:px-2",
sm: "h-8 px-2.5 gap-1.5 rounded-md has-[>svg]:px-2.5",
"icon-xs": "size-6 rounded-md p-0 has-[>svg]:p-0",
"icon-sm": "size-8 rounded-md p-0 has-[>svg]:p-0",
},
},
defaultVariants: {
size: "xs",
},
},
);
function InputGroupButton({
className,
type = "button",
variant = "ghost",
size = "xs",
...props
}: Omit<React.ComponentProps<typeof Button>, "size"> &
VariantProps<typeof inputGroupButtonVariants>) {
return (
<Button
type={type}
data-size={size}
variant={variant}
className={cn(inputGroupButtonVariants({ size }), className)}
{...props}
/>
);
}
const InputGroupTextarea = React.forwardRef<
HTMLTextAreaElement,
React.ComponentProps<"textarea">
>(({ className, ...props }, ref) => {
return (
<Textarea
ref={ref}
data-slot="input-group-control"
className={cn(
"flex-1 resize-none rounded-none border-0 bg-transparent py-3 shadow-none focus-visible:ring-0",
className,
)}
{...props}
/>
);
});
InputGroupTextarea.displayName = "InputGroupTextarea";
export { InputGroup, InputGroupAddon, InputGroupButton, InputGroupTextarea };

16
autogpt_platform/frontend/src/components/ui/spinner.tsx Normal file
View File

@@ -0,0 +1,16 @@
import { CircleNotch as CircleNotchIcon } from "@phosphor-icons/react";
import { cn } from "@/lib/utils";
function Spinner({ className, ...props }: React.ComponentProps<"svg">) {
return (
<CircleNotchIcon
role="status"
aria-label="Loading"
className={cn("size-4 animate-spin", className)}
{...(props as Record<string, unknown>)}
/>
);
}
export { Spinner };

22
autogpt_platform/frontend/src/components/ui/textarea.tsx Normal file
View File

@@ -0,0 +1,22 @@
import * as React from "react";
import { cn } from "@/lib/utils";
const Textarea = React.forwardRef<
HTMLTextAreaElement,
React.ComponentProps<"textarea">
>(({ className, ...props }, ref) => {
return (
<textarea
className={cn(
"flex min-h-[60px] w-full rounded-md border border-neutral-200 bg-transparent px-3 py-2 text-base shadow-sm placeholder:text-neutral-500 focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-neutral-950 disabled:cursor-not-allowed disabled:opacity-50 dark:border-neutral-800 dark:placeholder:text-neutral-400 dark:focus-visible:ring-neutral-300 md:text-sm",
className,
)}
ref={ref}
{...props}
/>
);
});
Textarea.displayName = "Textarea";
export { Textarea };

2
autogpt_platform/frontend/src/hooks/useCredits.ts
View File

@@ -41,7 +41,7 @@ export default function useCredits({
const fetchCredits = useCallback(async () => {
const response = await api.getUserCredit();
setCredits(response.credits);
setCredits(response.credits ?? null);
}, [api]);
useEffect(() => {

37
autogpt_platform/frontend/src/lib/autogpt-server-api/client.ts
View File

@@ -72,6 +72,18 @@ import type {
const isClient = environment.isClientSide();
/**
* Thrown when a request fails because the user is logging out.
* Callers can catch this specifically to silently ignore logout-related failures,
* rather than receiving null and crashing on property access.
*/
export class LogoutInterruptError extends Error {
constructor(message: string) {
super(message);
this.name = "LogoutInterruptError";
}
}
export default class BackendAPI {
private baseUrl: string;
private wsUrl: string;
@@ -128,11 +140,15 @@ export default class BackendAPI {
/////////////// CREDITS ////////////////
////////////////////////////////////////
getUserCredit(): Promise<{ credits: number }> {
async getUserCredit(): Promise<{ credits: number }> {
try {
return this._get("/credits");
} catch {
return Promise.resolve({ credits: 0 });
const response = await this._get("/credits");
return response ?? { credits: 0 };
} catch (error) {
if (!(error instanceof LogoutInterruptError)) {
Sentry.captureException(error);
}
return { credits: 0 };
}
}
@@ -433,13 +449,14 @@ export default class BackendAPI {
///////////// V2 STORE API /////////////
////////////////////////////////////////
getStoreProfile(): Promise<ProfileDetails | null> {
async getStoreProfile(): Promise<ProfileDetails | null> {
try {
const result = this._get("/store/profile");
return result;
return await this._get("/store/profile");
} catch (error) {
console.error("Error fetching store profile:", error);
return Promise.resolve(null);
if (!(error instanceof LogoutInterruptError)) {
Sentry.captureException(error);
}
return null;
}
}
@@ -1040,7 +1057,7 @@ export default class BackendAPI {
"Authentication request failed during logout, ignoring:",
error.message,
);
return null;
throw new LogoutInterruptError("Request cancelled: logout in progress");
}
throw error;
}

94
autogpt_platform/frontend/src/lib/autogpt-server-api/helpers.test.ts
View File

@@ -1,94 +0,0 @@
/**
* Unit tests for helpers.ts
*
* These tests validate the error handling in handleFetchError, specifically
* the fix for the issue where calling response.json() on non-JSON responses
* would throw: "Failed to execute 'json' on 'Response': Unexpected token 'A',
* "A server e"... is not valid JSON"
*
* To run these tests, you'll need to set up a unit test framework like Jest or Vitest.
*
* Test cases to cover:
*
* 1. JSON error responses should be parsed correctly
* - Given: Response with content-type: application/json
* - When: handleFetchError is called
* - Then: Should parse JSON and return ApiError with parsed response
*
* 2. Non-JSON error responses (e.g., HTML) should be handled gracefully
* - Given: Response with content-type: text/html
* - When: handleFetchError is called
* - Then: Should read as text and return ApiError with text response
*
* 3. Response without content-type header should be handled
* - Given: Response without content-type header
* - When: handleFetchError is called
* - Then: Should default to reading as text
*
* 4. JSON parsing errors should not throw
* - Given: Response with content-type: application/json but HTML body
* - When: handleFetchError is called and json() throws
* - Then: Should catch error, log warning, and return ApiError with null response
*
* 5. Specific validation for the fixed bug
* - Given: 502 Bad Gateway with content-type: application/json but HTML body
* - When: response.json() throws "Unexpected token 'A'" error
* - Then: Should NOT propagate the error, should return ApiError with null response
*/
import { handleFetchError } from "./helpers";
// Manual test function - can be run in browser console or Node
export async function testHandleFetchError() {
console.log("Testing handleFetchError...");
// Test 1: JSON response
const jsonResponse = new Response(
JSON.stringify({ error: "Internal server error" }),
{
status: 500,
headers: { "content-type": "application/json" },
},
);
const error1 = await handleFetchError(jsonResponse);
console.assert(
error1.status === 500 && error1.response?.error === "Internal server error",
"Test 1 failed: JSON response",
);
// Test 2: HTML response
const htmlResponse = new Response("<html><body>Server Error</body></html>", {
status: 502,
headers: { "content-type": "text/html" },
});
const error2 = await handleFetchError(htmlResponse);
console.assert(
error2.status === 502 &&
typeof error2.response === "string" &&
error2.response.includes("Server Error"),
"Test 2 failed: HTML response",
);
// Test 3: Mismatched content-type (claims JSON but is HTML)
// This simulates the bug that was fixed
const mismatchedResponse = new Response(
"<html><body>A server error occurred</body></html>",
{
status: 502,
headers: { "content-type": "application/json" }, // Claims JSON but isn't
},
);
try {
const error3 = await handleFetchError(mismatchedResponse);
console.assert(
error3.status === 502 && error3.response === null,
"Test 3 failed: Mismatched content-type should return null response",
);
console.log("✓ All tests passed!");
} catch (e) {
console.error("✗ Test 3 failed: Should not throw error", e);
}
}
// Uncomment to run manual tests
// testHandleFetchError();

2
autogpt_platform/frontend/tailwind.config.ts
View File

@@ -5,7 +5,7 @@ import { colors } from "./src/components/styles/colors";
const config = {
darkMode: ["class", ".dark-mode"], // ignore dark: prefix classes for now until we fully support dark mode
content: ["./src/**/*.{ts,tsx}"],
content: ["./src/**/*.{ts,tsx}", "./node_modules/streamdown/dist/**/*.js"],
prefix: "",
theme: {
container: {

2
autogpt_platform/frontend/vitest.config.mts
View File

@@ -6,7 +6,7 @@ export default defineConfig({
plugins: [tsconfigPaths(), react()],
test: {
environment: "happy-dom",
include: ["src/**/*.test.tsx"],
include: ["src/**/*.test.tsx", "src/**/*.test.ts"],
setupFiles: ["./src/tests/integrations/vitest.setup.tsx"],
},
});

165
plans/SECRT-1950-claude-ci-optimizations.md
View File

@@ -1,165 +0,0 @@
# Implementation Plan: SECRT-1950 - Apply E2E CI Optimizations to Claude Code Workflows
## Ticket
[SECRT-1950](https://linear.app/autogpt/issue/SECRT-1950)
## Summary
Apply Pwuts's CI performance optimizations from PR #12090 to Claude Code workflows.
## Reference PR
https://github.com/Significant-Gravitas/AutoGPT/pull/12090
---
## Analysis
### Current State (claude.yml)
**pnpm caching (lines 104-118):**
```yaml
- name: Set up Node.js
uses: actions/setup-node@v6
with:
node-version: "22"
- name: Enable corepack
run: corepack enable
- name: Set pnpm store directory
run: |
pnpm config set store-dir ~/.pnpm-store
echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
- name: Cache frontend dependencies
uses: actions/cache@v5
with:
path: ~/.pnpm-store
key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
restore-keys: |
${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
${{ runner.os }}-pnpm-
```
**Docker setup (lines 134-165):**
- Uses `docker-buildx-action@v3`
- Has manual Docker image caching via `actions/cache`
- Runs `docker compose up` without buildx bake optimization
### Pwuts's Optimizations (PR #12090)
1. **Simplified pnpm caching** - Use `setup-node` built-in cache:
```yaml
- name: Enable corepack
run: corepack enable
- name: Set up Node
uses: actions/setup-node@v6
with:
node-version: "22.18.0"
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
```
2. **Docker build caching via buildx bake**:
```yaml
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
with:
driver: docker-container
driver-opts: network=host
- name: Expose GHA cache to docker buildx CLI
uses: crazy-max/ghaction-github-runtime@v3
- name: Build Docker images (with cache)
run: |
pip install pyyaml
docker compose -f docker-compose.yml config > docker-compose.resolved.yml
python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
--source docker-compose.resolved.yml \
--cache-from "type=gha" \
--cache-to "type=gha,mode=max" \
...
docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
```
---
## Proposed Changes
### 1. Update pnpm caching in `claude.yml`
**Before:**
- Manual cache key generation
- Separate `actions/cache` step
- Manual pnpm store directory config
**After:**
- Use `setup-node` built-in `cache: "pnpm"` option
- Remove manual cache step
- Keep `corepack enable` before `setup-node`
### 2. Update Docker build in `claude.yml`
**Before:**
- Manual Docker layer caching via `actions/cache` with `/tmp/.buildx-cache`
- Simple `docker compose build`
**After:**
- Use `crazy-max/ghaction-github-runtime@v3` to expose GHA cache
- Use `docker-ci-fix-compose-build-cache.py` script
- Build with `docker buildx bake`
### 3. Apply same changes to other Claude workflows
- `claude-dependabot.yml` - Check if it has similar patterns
- `claude-ci-failure-auto-fix.yml` - Check if it has similar patterns
- `copilot-setup-steps.yml` - Reusable workflow, may be the source of truth
---
## Files to Modify
1. `.github/workflows/claude.yml`
2. `.github/workflows/claude-dependabot.yml` (if applicable)
3. `.github/workflows/claude-ci-failure-auto-fix.yml` (if applicable)
## Dependencies
- PR #12090 must be merged first (provides the `docker-ci-fix-compose-build-cache.py` script)
- Backend Dockerfile optimizations (already in PR #12090)
---
## Test Plan
1. Create PR with changes
2. Trigger Claude workflow manually or via `@claude` mention on a test issue
3. Compare CI runtime before/after
4. Verify Claude agent still works correctly (can checkout, build, run tests)
---
## Risk Assessment
**Low risk:**
- These are CI infrastructure changes, not code changes
- If caching fails, builds fall back to uncached (slower but works)
- Changes mirror proven patterns from PR #12090
---
## Questions for Reviewer
1. Should we wait for PR #12090 to merge before creating this PR?
2. Does `copilot-setup-steps.yml` need updating, or is it a separate concern?
3. Any concerns about cache key collisions between frontend E2E and Claude workflows?
---
## Verified
- ✅ **`claude-dependabot.yml`**: Has same pnpm caching pattern as `claude.yml` (manual `actions/cache`) — NEEDS UPDATE
- ✅ **`claude-ci-failure-auto-fix.yml`**: Simple workflow with no pnpm or Docker caching — NO CHANGES NEEDED
- ✅ **Script path**: `docker-ci-fix-compose-build-cache.py` will be at `.github/workflows/scripts/` after PR #12090 merges
- ✅ **Test seed caching**: NOT APPLICABLE — Claude workflows spin up a dev environment but don't run E2E tests with pre-seeded data. The seed caching in PR #12090 is specific to the frontend E2E test suite which needs consistent test data. Claude just needs the services running.