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Merge branch 'dev' into feat/browsing-capability-copilot

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This commit is contained in:
Zamil Majdy
2026-02-27 20:45:10 +07:00
committed by GitHub
parent a2ca05611e bf6308e87c
commit 1c26799867
24 changed files with 1080 additions and 476 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
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@@ -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

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:

78
autogpt_platform/backend/backend/copilot/sdk/service.py
View File

@@ -83,10 +83,13 @@ COPILOT_SYSTEM_PREFIX = "[COPILOT_SYSTEM]" # Renders as system info message
# 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
@@ -94,9 +97,16 @@ _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.
@@ -122,6 +132,21 @@ 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
@@ -132,6 +157,7 @@ is delivered to the user via a background stream.
All tasks must run in the foreground.
"""
STREAM_LOCK_PREFIX = "copilot:stream:lock:"
@@ -460,14 +486,13 @@ 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(
@@ -490,21 +515,30 @@ 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()
# 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:

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,

97
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"]
files = [
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{file = "fonttools-4.61.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:5fe9fd43882620017add5eabb781ebfbc6998ee49b35bd7f8f79af1f9f99a958"},
{file = "fonttools-4.61.1-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d8db08051fc9e7d8bc622f2112511b8107d8f27cd89e2f64ec45e9825e8288da"},
{file = "fonttools-4.61.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:a76d4cb80f41ba94a6691264be76435e5f72f2cb3cab0b092a6212855f71c2f6"},
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{file = "fonttools-4.61.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b846a1fcf8beadeb9ea4f44ec5bdde393e2f1569e17d700bfc49cd69bde75881"},
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{file = "fonttools-4.61.1-cp310-cp310-win_amd64.whl", hash = "sha256:eff1ac3cc66c2ac7cda1e64b4e2f3ffef474b7335f92fc3833fc632d595fcee6"},
{file = "fonttools-4.61.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:c6604b735bb12fef8e0efd5578c9fb5d3d8532d5001ea13a19cddf295673ee09"},
{file = "fonttools-4.61.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:5ce02f38a754f207f2f06557523cd39a06438ba3aafc0639c477ac409fc64e37"},
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{file = "fonttools-4.61.1-cp314-cp314-macosx_10_15_universal2.whl", hash = "sha256:fff4f534200a04b4a36e7ae3cb74493afe807b517a09e99cb4faa89a34ed6ecd"},
{file = "fonttools-4.61.1-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:d9203500f7c63545b4ce3799319fe4d9feb1a1b89b28d3cb5abd11b9dd64147e"},
{file = "fonttools-4.61.1-cp314-cp314-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:fa646ecec9528bef693415c79a86e733c70a4965dd938e9a226b0fc64c9d2e6c"},
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{file = "fonttools-4.61.1-py3-none-any.whl", hash = "sha256:17d2bf5d541add43822bcf0c43d7d847b160c9bb01d15d5007d84e2217aaa371"},
{file = "fonttools-4.61.1.tar.gz", hash = "sha256:6675329885c44657f826ef01d9e4fb33b9158e9d93c537d84ad8399539bc6f69"},
]
[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 = [
{file = "fpdf2-2.8.6-py3-none-any.whl", hash = "sha256:464658b896c6b0fcbf883abb316b8f0a52d582eb959d71822ba254d6c790bfdd"},
{file = "fpdf2-2.8.6.tar.gz", hash = "sha256:5132f26bbeee69a7ca6a292e4da1eb3241147b5aea9348b35e780ecd02bf5fc2"},
]
[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"
@@ -8530,4 +8625,4 @@ 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 = "3869bc3fb8ea50e7101daffce13edbe563c8af568cb751adfa31fb9bb5c8318a"

1
autogpt_platform/backend/pyproject.toml
View File

@@ -89,6 +89,7 @@ croniter = "^6.0.0"
stagehand = "^0.5.1"
gravitas-md2gdocs = "^0.1.0"
posthog = "^7.6.0"
fpdf2 = "^2.8.6"
[tool.poetry.group.dev.dependencies]
aiohappyeyeballs = "^2.6.1"

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",

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">

6
autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx
View File

@@ -104,11 +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})`;
},
);

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;

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>
),
};

13
autogpt_platform/frontend/src/components/ai-elements/message.tsx
View File

@@ -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}
/>
),

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;
}

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: {

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.