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Author SHA1 Message Date
Otto
b739f36826 fix(binary-processor): add virus scanning + tests for offset loop
Security fix: Add scan_content_safe() call before writing files to prevent
bypass of ClamAV scanning infrastructure. Malicious base64-encoded content
matching a supported magic number would previously be saved without scanning.

Test coverage:
- Add tests for 4-byte aligned offset loop (handles marker bleed-in)
- Add tests for PDF_BASE64_START/END marker expansion
- Add tests verifying virus scanner integration
- Mock virus scanner in existing process_binary_outputs tests

Addresses review feedback from Claude sub-agents and ntindle.
2026-02-05 23:29:57 +00:00
Toran Bruce Richards
4e75279ea3 Merge branch 'dev' into otto/secrt-1887-content-based-detection 2026-02-05 23:50:58 +01:00
Otto
cbf3f16792 fix(binary-processor): handle marker text bleeding into base64 match
When markers like PDF_BASE64_START are concatenated directly with base64
content (no delimiter), the regex matches both together. This corrupts
the decode because 'START' becomes part of the base64 string.

Fix: Try decoding from multiple 4-byte aligned offsets (0, 4, 8, ... 32)
until we find valid magic numbers. Also add PDF_BASE64_START/END to the
marker patterns for cleanup.

Tested with: PDF_BASE64_STARTJVBERi0... (no delimiter case)
2026-02-05 22:46:15 +00:00
Otto
950f950985 style: Address review nits
- Remove redundant extension from filename (was: block_png_uuid.png, now: block_uuid.png)
- Use lazy logging format instead of f-string
2026-02-05 20:26:36 +00:00
Otto
4fe74d8e7f fix: Correct test position calculation for marker expansion
The test had wrong indices - ABCDEF starts at position 26, not 27.
2026-02-05 20:25:42 +00:00
Otto
513ec16357 fix: Handle RFC 2045 line-wrapped base64 in embedded detection
Sentry correctly identified that the regex and decode would fail on
line-wrapped base64. Fixed by:
- Updated regex to allow whitespace in base64 chunks
- Strip whitespace before decoding with validate=True
- Added test for line-wrapped base64
2026-02-05 20:00:09 +00:00
Toran Bruce Richards
8cbf07ce40 Merge branch 'dev' into otto/secrt-1887-content-based-detection 2026-02-05 20:53:18 +01:00
Otto
9914d0ef2d refactor: Focus binary detection on embedded base64 in stdout_logs
Previous implementation detected data URIs and pure base64 strings,
but these cases already worked in CoPilot. The actual problem was
code execution printing base64 to stdout with markers.

Changes:
- Remove data URI detection (no user-facing impact)
- Remove pure base64 detection (covered by embedded detection)
- Add embedded base64 pattern matching within text strings
- Handle marker patterns (---BASE64_START---/---BASE64_END---)
- Replace base64 + markers with workspace:// reference

This now solves the actual problem: ExecuteCodeBlock stdout_logs
containing embedded base64 that would otherwise cost 17k+ output
tokens for the LLM to re-type.
2026-02-05 19:52:14 +00:00
Otto
c32c7fb959 fix: Handle RFC 2045 line-wrapped base64 in binary detection
- Strip whitespace before base64 decoding (encoders often add line breaks)
- Update regex comment to clarify whitespace handling
- Add test case for line-wrapped base64

Addresses CodeRabbit review feedback.
2026-02-05 19:11:56 +00:00
Otto
dcb3550910 feat(copilot): Auto-save binary block outputs using content-based detection
When CoPilot executes blocks that produce binary outputs (images, PDFs),
the data is now automatically detected and saved to the user's workspace,
replacing raw base64 data with workspace:// references.

Uses content-based detection (not field-name based) because:
- Code execution blocks return base64 in stdout_logs, not structured fields
- The png/jpeg/pdf fields only populate from Jupyter display mechanisms
- Other blocks use various field names (image, result, output, etc.)

Detection strategy:
1. Data URI detection with mimetype whitelist
2. Raw base64 with magic number validation (PNG, JPEG, PDF, GIF, WebP)
3. Size threshold > 1KB to filter tokens/hashes

Features:
- Scans ALL string values recursively, regardless of field name
- Content deduplication within single block execution via SHA-256 hash
- Graceful degradation (original value preserved on save failure)
- ~97% token reduction observed (17k -> 500 tokens for PDF generation)

Closes SECRT-1887
2026-02-05 18:39:31 +00:00
39 changed files with 1297 additions and 1921 deletions

View File

@@ -27,20 +27,11 @@ jobs:
runs-on: ubuntu-latest
outputs:
cache-key: ${{ steps.cache-key.outputs.key }}
components-changed: ${{ steps.filter.outputs.components }}
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Check for component changes
uses: dorny/paths-filter@v3
id: filter
with:
filters: |
components:
- 'autogpt_platform/frontend/src/components/**'
- name: Set up Node.js
uses: actions/setup-node@v4
with:
@@ -99,11 +90,8 @@ jobs:
chromatic:
runs-on: ubuntu-latest
needs: setup
# Disabled: to re-enable, remove 'false &&' from the condition below
if: >-
false
&& (github.ref == 'refs/heads/dev' || github.base_ref == 'dev')
&& needs.setup.outputs.components-changed == 'true'
# Only run on dev branch pushes or PRs targeting dev
if: github.ref == 'refs/heads/dev' || github.base_ref == 'dev'
steps:
- name: Checkout repository

View File

@@ -0,0 +1,251 @@
"""
Detect and save embedded binary data in block outputs.
Scans stdout_logs and other string outputs for embedded base64 patterns,
saves detected binary content to workspace, and replaces the base64 with
workspace:// references. This reduces LLM output token usage by ~97% for
file generation tasks.
Primary use case: ExecuteCodeBlock prints base64 to stdout, which appears
in stdout_logs. Without this processor, the LLM would re-type the entire
base64 string when saving files.
"""
import base64
import binascii
import hashlib
import logging
import re
import uuid
from typing import Any, Optional
from backend.util.file import sanitize_filename
from backend.util.virus_scanner import scan_content_safe
from backend.util.workspace import WorkspaceManager
logger = logging.getLogger(__name__)
# Minimum decoded size to process (filters out small base64 strings)
MIN_DECODED_SIZE = 1024 # 1KB
# Pattern to find base64 chunks in text (at least 100 chars to be worth checking)
# Matches continuous base64 characters (with optional whitespace for line wrapping),
# optionally ending with = padding
EMBEDDED_BASE64_PATTERN = re.compile(r"[A-Za-z0-9+/\s]{100,}={0,2}")
# Magic numbers for binary file detection
MAGIC_SIGNATURES = [
(b"\x89PNG\r\n\x1a\n", "png"),
(b"\xff\xd8\xff", "jpg"),
(b"%PDF-", "pdf"),
(b"GIF87a", "gif"),
(b"GIF89a", "gif"),
(b"RIFF", "webp"), # Also check content[8:12] == b'WEBP'
]
async def process_binary_outputs(
outputs: dict[str, list[Any]],
workspace_manager: WorkspaceManager,
block_name: str,
) -> dict[str, list[Any]]:
"""
Scan all string values in outputs for embedded base64 binary content.
Save detected binaries to workspace and replace with references.
Args:
outputs: Block execution outputs (dict of output_name -> list of values)
workspace_manager: WorkspaceManager instance with session scoping
block_name: Name of the block (used in generated filenames)
Returns:
Processed outputs with embedded base64 replaced by workspace references
"""
cache: dict[str, str] = {} # content_hash -> workspace_ref
processed: dict[str, list[Any]] = {}
for name, items in outputs.items():
processed_items = []
for item in items:
processed_items.append(
await _process_value(item, workspace_manager, block_name, cache)
)
processed[name] = processed_items
return processed
async def _process_value(
value: Any,
wm: WorkspaceManager,
block: str,
cache: dict[str, str],
) -> Any:
"""Recursively process a value, detecting embedded base64 in strings."""
if isinstance(value, dict):
result = {}
for k, v in value.items():
result[k] = await _process_value(v, wm, block, cache)
return result
if isinstance(value, list):
return [await _process_value(v, wm, block, cache) for v in value]
if isinstance(value, str) and len(value) > MIN_DECODED_SIZE:
return await _extract_and_replace_base64(value, wm, block, cache)
return value
async def _extract_and_replace_base64(
text: str,
wm: WorkspaceManager,
block: str,
cache: dict[str, str],
) -> str:
"""
Find embedded base64 in text, save binaries, replace with references.
Scans for base64 patterns, validates each as binary via magic numbers,
saves valid binaries to workspace, and replaces the base64 portion
(plus any surrounding markers) with the workspace reference.
"""
result = text
offset = 0
for match in EMBEDDED_BASE64_PATTERN.finditer(text):
b64_str = match.group(0)
# Try to decode and validate
detection = _decode_and_validate(b64_str)
if detection is None:
continue
content, ext = detection
# Save to workspace
ref = await _save_binary(content, ext, wm, block, cache)
if ref is None:
continue
# Calculate replacement bounds (include surrounding markers if present)
start, end = match.start(), match.end()
start, end = _expand_to_markers(text, start, end)
# Apply replacement with offset adjustment
adj_start = start + offset
adj_end = end + offset
result = result[:adj_start] + ref + result[adj_end:]
offset += len(ref) - (end - start)
return result
def _decode_and_validate(b64_str: str) -> Optional[tuple[bytes, str]]:
"""
Decode base64 and validate it's a known binary format.
Tries multiple 4-byte aligned offsets to handle cases where marker text
(e.g., "START" from "PDF_BASE64_START") bleeds into the regex match.
Base64 works in 4-char chunks, so we only check aligned offsets.
Returns (content, extension) if valid binary, None otherwise.
"""
# Strip whitespace for RFC 2045 line-wrapped base64
normalized = re.sub(r"\s+", "", b64_str)
# Try offsets 0, 4, 8, ... up to 32 chars (handles markers up to ~24 chars)
# This handles cases like "STARTJVBERi0..." where "START" bleeds into match
for char_offset in range(0, min(33, len(normalized)), 4):
candidate = normalized[char_offset:]
try:
content = base64.b64decode(candidate, validate=True)
except (ValueError, binascii.Error):
continue
# Must meet minimum size
if len(content) < MIN_DECODED_SIZE:
continue
# Check magic numbers
for magic, ext in MAGIC_SIGNATURES:
if content.startswith(magic):
# Special case for WebP: RIFF container, verify "WEBP" at offset 8
if magic == b"RIFF":
if len(content) < 12 or content[8:12] != b"WEBP":
continue
return content, ext
return None
def _expand_to_markers(text: str, start: int, end: int) -> tuple[int, int]:
"""
Expand replacement bounds to include surrounding markers if present.
Handles patterns like:
- ---BASE64_START---\\n{base64}\\n---BASE64_END---
- [BASE64]{base64}[/BASE64]
- Or just the raw base64
"""
# Common marker patterns to strip (order matters - check longer patterns first)
start_markers = [
"PDF_BASE64_START",
"---BASE64_START---\n",
"---BASE64_START---",
"[BASE64]\n",
"[BASE64]",
]
end_markers = [
"PDF_BASE64_END",
"\n---BASE64_END---",
"---BASE64_END---",
"\n[/BASE64]",
"[/BASE64]",
]
# Check for start markers
for marker in start_markers:
marker_start = start - len(marker)
if marker_start >= 0 and text[marker_start:start] == marker:
start = marker_start
break
# Check for end markers
for marker in end_markers:
marker_end = end + len(marker)
if marker_end <= len(text) and text[end:marker_end] == marker:
end = marker_end
break
return start, end
async def _save_binary(
content: bytes,
ext: str,
wm: WorkspaceManager,
block: str,
cache: dict[str, str],
) -> Optional[str]:
"""
Save binary content to workspace with deduplication.
Returns workspace://file-id reference, or None on failure.
"""
content_hash = hashlib.sha256(content).hexdigest()
if content_hash in cache:
return cache[content_hash]
try:
safe_block = sanitize_filename(block)[:20].lower()
filename = f"{safe_block}_{uuid.uuid4().hex[:12]}.{ext}"
# Scan for viruses before saving
await scan_content_safe(content, filename=filename)
file = await wm.write_file(content, filename)
ref = f"workspace://{file.id}"
cache[content_hash] = ref
return ref
except Exception as e:
logger.warning("Failed to save binary output: %s", e)
return None

View File

@@ -14,8 +14,10 @@ from backend.data.model import CredentialsMetaInput
from backend.data.workspace import get_or_create_workspace
from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.util.exceptions import BlockError
from backend.util.workspace import WorkspaceManager
from .base import BaseTool
from .binary_output_processor import process_binary_outputs
from .models import (
BlockOutputResponse,
ErrorResponse,
@@ -321,6 +323,16 @@ class RunBlockTool(BaseTool):
):
outputs[output_name].append(output_data)
# Post-process outputs to save binary content to workspace
workspace_manager = WorkspaceManager(
user_id=user_id,
workspace_id=workspace.id,
session_id=session.session_id,
)
outputs = await process_binary_outputs(
dict(outputs), workspace_manager, block.name
)
return BlockOutputResponse(
message=f"Block '{block.name}' executed successfully",
block_id=block_id,

View File

@@ -0,0 +1,518 @@
"""Tests for embedded binary detection in block outputs."""
import base64
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from .binary_output_processor import (
_decode_and_validate,
_expand_to_markers,
process_binary_outputs,
)
@pytest.fixture
def mock_workspace_manager():
"""Create a mock workspace manager that returns predictable file IDs."""
wm = MagicMock()
async def mock_write_file(content, filename):
file = MagicMock()
file.id = f"file-{filename[:10]}"
return file
wm.write_file = AsyncMock(side_effect=mock_write_file)
return wm
def _make_pdf_base64(size: int = 2000) -> str:
"""Create a valid PDF base64 string of specified size."""
pdf_content = b"%PDF-1.4 " + b"x" * size
return base64.b64encode(pdf_content).decode()
def _make_png_base64(size: int = 2000) -> str:
"""Create a valid PNG base64 string of specified size."""
png_content = b"\x89PNG\r\n\x1a\n" + b"\x00" * size
return base64.b64encode(png_content).decode()
# =============================================================================
# Decode and Validate Tests
# =============================================================================
class TestDecodeAndValidate:
"""Tests for _decode_and_validate function."""
def test_detects_pdf_magic_number(self):
"""Should detect valid PDF by magic number."""
pdf_b64 = _make_pdf_base64()
result = _decode_and_validate(pdf_b64)
assert result is not None
content, ext = result
assert ext == "pdf"
assert content.startswith(b"%PDF-")
def test_detects_png_magic_number(self):
"""Should detect valid PNG by magic number."""
png_b64 = _make_png_base64()
result = _decode_and_validate(png_b64)
assert result is not None
content, ext = result
assert ext == "png"
def test_detects_jpeg_magic_number(self):
"""Should detect valid JPEG by magic number."""
jpeg_content = b"\xff\xd8\xff\xe0" + b"\x00" * 2000
jpeg_b64 = base64.b64encode(jpeg_content).decode()
result = _decode_and_validate(jpeg_b64)
assert result is not None
_, ext = result
assert ext == "jpg"
def test_detects_gif_magic_number(self):
"""Should detect valid GIF by magic number."""
gif_content = b"GIF89a" + b"\x00" * 2000
gif_b64 = base64.b64encode(gif_content).decode()
result = _decode_and_validate(gif_b64)
assert result is not None
_, ext = result
assert ext == "gif"
def test_detects_webp_magic_number(self):
"""Should detect valid WebP by magic number."""
webp_content = b"RIFF\x00\x00\x00\x00WEBP" + b"\x00" * 2000
webp_b64 = base64.b64encode(webp_content).decode()
result = _decode_and_validate(webp_b64)
assert result is not None
_, ext = result
assert ext == "webp"
def test_rejects_small_content(self):
"""Should reject content smaller than threshold."""
small_pdf = b"%PDF-1.4 small"
small_b64 = base64.b64encode(small_pdf).decode()
result = _decode_and_validate(small_b64)
assert result is None
def test_rejects_no_magic_number(self):
"""Should reject content without recognized magic number."""
random_content = b"This is just random text" * 100
random_b64 = base64.b64encode(random_content).decode()
result = _decode_and_validate(random_b64)
assert result is None
def test_rejects_invalid_base64(self):
"""Should reject invalid base64."""
result = _decode_and_validate("not-valid-base64!!!")
assert result is None
def test_rejects_riff_without_webp(self):
"""Should reject RIFF files that aren't WebP (e.g., WAV)."""
wav_content = b"RIFF\x00\x00\x00\x00WAVE" + b"\x00" * 2000
wav_b64 = base64.b64encode(wav_content).decode()
result = _decode_and_validate(wav_b64)
assert result is None
def test_handles_line_wrapped_base64(self):
"""Should handle RFC 2045 line-wrapped base64."""
pdf_content = b"%PDF-1.4 " + b"x" * 2000
pdf_b64 = base64.b64encode(pdf_content).decode()
# Simulate line wrapping at 76 chars
wrapped = "\n".join(pdf_b64[i : i + 76] for i in range(0, len(pdf_b64), 76))
result = _decode_and_validate(wrapped)
assert result is not None
content, ext = result
assert ext == "pdf"
assert content == pdf_content
# =============================================================================
# Marker Expansion Tests
# =============================================================================
class TestExpandToMarkers:
"""Tests for _expand_to_markers function."""
def test_expands_base64_start_end_markers(self):
"""Should expand to include ---BASE64_START--- and ---BASE64_END---."""
text = "prefix\n---BASE64_START---\nABCDEF\n---BASE64_END---\nsuffix"
# Base64 "ABCDEF" is at position 26-32
start, end = _expand_to_markers(text, 26, 32)
assert text[start:end] == "---BASE64_START---\nABCDEF\n---BASE64_END---"
def test_expands_bracket_markers(self):
"""Should expand to include [BASE64] and [/BASE64] markers."""
text = "prefix[BASE64]ABCDEF[/BASE64]suffix"
# Base64 is at position 14-20
start, end = _expand_to_markers(text, 14, 20)
assert text[start:end] == "[BASE64]ABCDEF[/BASE64]"
def test_no_expansion_without_markers(self):
"""Should not expand if no markers present."""
text = "prefix ABCDEF suffix"
start, end = _expand_to_markers(text, 7, 13)
assert start == 7
assert end == 13
# =============================================================================
# Process Binary Outputs Tests
# =============================================================================
@pytest.fixture
def mock_scan():
"""Patch virus scanner for tests."""
with patch(
"backend.api.features.chat.tools.binary_output_processor.scan_content_safe",
new_callable=AsyncMock,
) as mock:
yield mock
class TestProcessBinaryOutputs:
"""Tests for process_binary_outputs function."""
@pytest.mark.asyncio
async def test_detects_embedded_pdf_in_stdout_logs(
self, mock_workspace_manager, mock_scan
):
"""Should detect and replace embedded PDF in stdout_logs."""
pdf_b64 = _make_pdf_base64()
stdout = f"PDF generated!\n---BASE64_START---\n{pdf_b64}\n---BASE64_END---\n"
outputs = {"stdout_logs": [stdout]}
result = await process_binary_outputs(
outputs, mock_workspace_manager, "ExecuteCodeBlock"
)
# Should contain workspace reference, not base64
assert "workspace://" in result["stdout_logs"][0]
assert pdf_b64 not in result["stdout_logs"][0]
assert "PDF generated!" in result["stdout_logs"][0]
mock_workspace_manager.write_file.assert_called_once()
@pytest.mark.asyncio
async def test_detects_embedded_png_without_markers(
self, mock_workspace_manager, mock_scan
):
"""Should detect embedded PNG even without markers."""
png_b64 = _make_png_base64()
stdout = f"Image created: {png_b64} done"
outputs = {"stdout_logs": [stdout]}
result = await process_binary_outputs(
outputs, mock_workspace_manager, "ExecuteCodeBlock"
)
assert "workspace://" in result["stdout_logs"][0]
assert "Image created:" in result["stdout_logs"][0]
assert "done" in result["stdout_logs"][0]
@pytest.mark.asyncio
async def test_preserves_small_strings(self, mock_workspace_manager, mock_scan):
"""Should not process small strings."""
outputs = {"stdout_logs": ["small output"]}
result = await process_binary_outputs(
outputs, mock_workspace_manager, "TestBlock"
)
assert result["stdout_logs"][0] == "small output"
mock_workspace_manager.write_file.assert_not_called()
@pytest.mark.asyncio
async def test_preserves_non_binary_large_strings(
self, mock_workspace_manager, mock_scan
):
"""Should preserve large strings that don't contain valid binary."""
large_text = "A" * 5000 # Large string - decodes to nulls, no magic number
outputs = {"stdout_logs": [large_text]}
result = await process_binary_outputs(
outputs, mock_workspace_manager, "TestBlock"
)
assert result["stdout_logs"][0] == large_text
mock_workspace_manager.write_file.assert_not_called()
@pytest.mark.asyncio
async def test_deduplicates_identical_content(
self, mock_workspace_manager, mock_scan
):
"""Should save identical content only once."""
pdf_b64 = _make_pdf_base64()
stdout1 = f"First: {pdf_b64}"
stdout2 = f"Second: {pdf_b64}"
outputs = {"stdout_logs": [stdout1, stdout2]}
result = await process_binary_outputs(
outputs, mock_workspace_manager, "TestBlock"
)
# Both should have references
assert "workspace://" in result["stdout_logs"][0]
assert "workspace://" in result["stdout_logs"][1]
# But only one write
assert mock_workspace_manager.write_file.call_count == 1
@pytest.mark.asyncio
async def test_handles_multiple_binaries_in_one_string(
self, mock_workspace_manager, mock_scan
):
"""Should handle multiple embedded binaries in a single string."""
pdf_b64 = _make_pdf_base64()
png_b64 = _make_png_base64()
stdout = f"PDF: {pdf_b64}\nPNG: {png_b64}"
outputs = {"stdout_logs": [stdout]}
result = await process_binary_outputs(
outputs, mock_workspace_manager, "TestBlock"
)
# Should have two workspace references
assert result["stdout_logs"][0].count("workspace://") == 2
assert mock_workspace_manager.write_file.call_count == 2
@pytest.mark.asyncio
async def test_processes_nested_structures(self, mock_workspace_manager, mock_scan):
"""Should recursively process nested dicts and lists."""
pdf_b64 = _make_pdf_base64()
outputs = {"result": [{"nested": {"deep": f"data: {pdf_b64}"}}]}
result = await process_binary_outputs(
outputs, mock_workspace_manager, "TestBlock"
)
assert "workspace://" in result["result"][0]["nested"]["deep"]
@pytest.mark.asyncio
async def test_graceful_degradation_on_save_failure(
self, mock_workspace_manager, mock_scan
):
"""Should preserve original on save failure."""
mock_workspace_manager.write_file = AsyncMock(
side_effect=Exception("Storage error")
)
pdf_b64 = _make_pdf_base64()
stdout = f"PDF: {pdf_b64}"
outputs = {"stdout_logs": [stdout]}
result = await process_binary_outputs(
outputs, mock_workspace_manager, "TestBlock"
)
# Should keep original since save failed
assert pdf_b64 in result["stdout_logs"][0]
# =============================================================================
# Offset Loop Tests (handling marker bleed-in)
# =============================================================================
class TestOffsetLoopHandling:
"""Tests for the offset-aligned decoding that handles marker bleed-in."""
def test_handles_4char_aligned_prefix(self):
"""Should detect base64 when a 4-char aligned prefix bleeds into match.
When 'TEST' (4 chars, aligned) bleeds in, offset 4 finds valid base64.
"""
pdf_content = b"%PDF-1.4 " + b"x" * 2000
pdf_b64 = base64.b64encode(pdf_content).decode()
# 4-char prefix (aligned)
with_prefix = f"TEST{pdf_b64}"
result = _decode_and_validate(with_prefix)
assert result is not None
content, ext = result
assert ext == "pdf"
assert content == pdf_content
def test_handles_8char_aligned_prefix(self):
"""Should detect base64 when an 8-char prefix bleeds into match."""
pdf_content = b"%PDF-1.4 " + b"x" * 2000
pdf_b64 = base64.b64encode(pdf_content).decode()
# 8-char prefix (aligned)
with_prefix = f"TESTTEST{pdf_b64}"
result = _decode_and_validate(with_prefix)
assert result is not None
content, ext = result
assert ext == "pdf"
def test_handles_misaligned_prefix(self):
"""Should handle misaligned prefix by finding a valid aligned offset.
'START' is 5 chars (misaligned). The loop tries offsets 0, 4, 8...
Since characters 0-4 include 'START' which is invalid base64 on its own,
we need the full PDF base64 to eventually decode correctly at some offset.
"""
pdf_content = b"%PDF-1.4 " + b"x" * 2000
pdf_b64 = base64.b64encode(pdf_content).decode()
# 5-char prefix - misaligned, but offset 4 should start mid-'START'
# and offset 8 will be past the prefix
with_prefix = f"START{pdf_b64}"
result = _decode_and_validate(with_prefix)
# Should find valid PDF at some offset (8 in this case)
assert result is not None
_, ext = result
assert ext == "pdf"
def test_handles_pdf_base64_start_marker_bleed(self):
"""Should handle PDF_BASE64_START marker bleeding into regex match.
This is the real-world case: regex matches 'STARTJVBERi0...' because
'START' chars are in the base64 alphabet. Offset loop skips past it.
PDF_BASE64_START is 16 chars (4-aligned), so offset 16 finds valid base64.
"""
pdf_content = b"%PDF-1.4 " + b"x" * 2000
pdf_b64 = base64.b64encode(pdf_content).decode()
# Simulate regex capturing 'PDF_BASE64_START' + base64 together
# This happens when there's no delimiter between marker and content
with_full_marker = f"PDF_BASE64_START{pdf_b64}"
result = _decode_and_validate(with_full_marker)
assert result is not None
_, ext = result
assert ext == "pdf"
def test_clean_base64_works_at_offset_zero(self):
"""Should detect clean base64 at offset 0 without issues."""
pdf_content = b"%PDF-1.4 " + b"x" * 2000
pdf_b64 = base64.b64encode(pdf_content).decode()
result = _decode_and_validate(pdf_b64)
assert result is not None
content, ext = result
assert ext == "pdf"
assert content == pdf_content
# =============================================================================
# PDF Marker Tests
# =============================================================================
class TestPdfMarkerExpansion:
"""Tests for PDF_BASE64_START/END marker handling."""
def test_expands_pdf_base64_start_marker(self):
"""Should expand to include PDF_BASE64_START marker."""
text = "prefixPDF_BASE64_STARTABCDEF"
# Base64 'ABCDEF' is at position 22-28
start, end = _expand_to_markers(text, 22, 28)
assert text[start:end] == "PDF_BASE64_STARTABCDEF"
def test_expands_pdf_base64_end_marker(self):
"""Should expand to include PDF_BASE64_END marker."""
text = "ABCDEFPDF_BASE64_ENDsuffix"
# Base64 'ABCDEF' is at position 0-6
start, end = _expand_to_markers(text, 0, 6)
assert text[start:end] == "ABCDEFPDF_BASE64_END"
def test_expands_both_pdf_markers(self):
"""Should expand to include both PDF_BASE64_START and END."""
text = "xPDF_BASE64_STARTABCDEFPDF_BASE64_ENDy"
# Base64 'ABCDEF' is at position 17-23
start, end = _expand_to_markers(text, 17, 23)
assert text[start:end] == "PDF_BASE64_STARTABCDEFPDF_BASE64_END"
def test_partial_marker_not_expanded(self):
"""Should not expand if only partial marker present."""
text = "BASE64_STARTABCDEF" # Missing 'PDF_' prefix
start, end = _expand_to_markers(text, 12, 18)
# Should not expand since it's not the full marker
assert start == 12
assert end == 18
@pytest.mark.asyncio
async def test_full_pipeline_with_pdf_markers(self, mock_workspace_manager):
"""Test full pipeline with PDF_BASE64_START/END markers."""
pdf_b64 = _make_pdf_base64()
stdout = f"Output: PDF_BASE64_START{pdf_b64}PDF_BASE64_END done"
outputs = {"stdout_logs": [stdout]}
with patch(
"backend.api.features.chat.tools.binary_output_processor.scan_content_safe",
new_callable=AsyncMock,
):
result = await process_binary_outputs(
outputs, mock_workspace_manager, "TestBlock"
)
# Should have workspace reference
assert "workspace://" in result["stdout_logs"][0]
# Markers should be consumed along with base64
assert "PDF_BASE64_START" not in result["stdout_logs"][0]
assert "PDF_BASE64_END" not in result["stdout_logs"][0]
# Surrounding text preserved
assert "Output:" in result["stdout_logs"][0]
assert "done" in result["stdout_logs"][0]
# =============================================================================
# Virus Scanning Tests
# =============================================================================
class TestVirusScanning:
"""Tests for virus scanning integration."""
@pytest.mark.asyncio
async def test_calls_virus_scanner_before_save(self, mock_workspace_manager):
"""Should call scan_content_safe before writing file."""
pdf_b64 = _make_pdf_base64()
stdout = f"PDF: {pdf_b64}"
outputs = {"stdout_logs": [stdout]}
with patch(
"backend.api.features.chat.tools.binary_output_processor.scan_content_safe",
new_callable=AsyncMock,
) as mock_scan:
result = await process_binary_outputs(
outputs, mock_workspace_manager, "TestBlock"
)
# Verify scanner was called
mock_scan.assert_called_once()
# Verify file was written after scan
mock_workspace_manager.write_file.assert_called_once()
# Verify result has workspace reference
assert "workspace://" in result["stdout_logs"][0]
@pytest.mark.asyncio
async def test_virus_scan_failure_preserves_original(self, mock_workspace_manager):
"""Should preserve original if virus scan fails."""
pdf_b64 = _make_pdf_base64()
stdout = f"PDF: {pdf_b64}"
outputs = {"stdout_logs": [stdout]}
with patch(
"backend.api.features.chat.tools.binary_output_processor.scan_content_safe",
new_callable=AsyncMock,
side_effect=Exception("Virus detected"),
):
result = await process_binary_outputs(
outputs, mock_workspace_manager, "TestBlock"
)
# Should keep original since scan failed
assert pdf_b64 in result["stdout_logs"][0]
# File should not have been written
mock_workspace_manager.write_file.assert_not_called()

View File

@@ -6,6 +6,7 @@ from typing import Any
from backend.api.features.library import db as library_db
from backend.api.features.library import model as library_model
from backend.api.features.store import db as store_db
from backend.data import graph as graph_db
from backend.data.graph import GraphModel
from backend.data.model import (
CredentialsFieldInfo,
@@ -43,8 +44,14 @@ async def fetch_graph_from_store_slug(
return None, None
# Get the graph from store listing version
graph = await store_db.get_available_graph(
store_agent.store_listing_version_id, hide_nodes=False
graph_meta = await store_db.get_available_graph(
store_agent.store_listing_version_id
)
graph = await graph_db.get_graph(
graph_id=graph_meta.id,
version=graph_meta.version,
user_id=None, # Public access
include_subgraphs=True,
)
return graph, store_agent
@@ -117,11 +124,11 @@ def build_missing_credentials_from_graph(
preserving all supported credential types for each field.
"""
matched_keys = set(matched_credentials.keys()) if matched_credentials else set()
aggregated_fields = graph.regular_credentials_inputs
aggregated_fields = graph.aggregate_credentials_inputs()
return {
field_key: _serialize_missing_credential(field_key, field_info)
for field_key, (field_info, _, _) in aggregated_fields.items()
for field_key, (field_info, _node_fields) in aggregated_fields.items()
if field_key not in matched_keys
}
@@ -244,7 +251,7 @@ async def match_user_credentials_to_graph(
missing_creds: list[str] = []
# Get aggregated credentials requirements from the graph
aggregated_creds = graph.regular_credentials_inputs
aggregated_creds = graph.aggregate_credentials_inputs()
logger.debug(
f"Matching credentials for graph {graph.id}: {len(aggregated_creds)} required"
)
@@ -262,8 +269,7 @@ async def match_user_credentials_to_graph(
# provider is in the set of acceptable providers.
for credential_field_name, (
credential_requirements,
_,
_,
_node_fields,
) in aggregated_creds.items():
# Find first matching credential by provider, type, and scopes
matching_cred = next(

View File

@@ -1,78 +0,0 @@
"""Tests for chat tools utility functions."""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from backend.data.model import CredentialsFieldInfo
def _make_regular_field() -> CredentialsFieldInfo:
return CredentialsFieldInfo.model_validate(
{
"credentials_provider": ["github"],
"credentials_types": ["api_key"],
"is_auto_credential": False,
},
by_alias=True,
)
def test_build_missing_credentials_excludes_auto_creds():
"""
build_missing_credentials_from_graph() should use regular_credentials_inputs
and thus exclude auto_credentials from the "missing" set.
"""
from backend.api.features.chat.tools.utils import (
build_missing_credentials_from_graph,
)
regular_field = _make_regular_field()
mock_graph = MagicMock()
# regular_credentials_inputs should only return the non-auto field
mock_graph.regular_credentials_inputs = {
"github_api_key": (regular_field, {("node-1", "credentials")}, True),
}
result = build_missing_credentials_from_graph(mock_graph, matched_credentials=None)
# Should include the regular credential
assert "github_api_key" in result
# Should NOT include the auto_credential (not in regular_credentials_inputs)
assert "google_oauth2" not in result
@pytest.mark.asyncio
async def test_match_user_credentials_excludes_auto_creds():
"""
match_user_credentials_to_graph() should use regular_credentials_inputs
and thus exclude auto_credentials from matching.
"""
from backend.api.features.chat.tools.utils import match_user_credentials_to_graph
regular_field = _make_regular_field()
mock_graph = MagicMock()
mock_graph.id = "test-graph"
# regular_credentials_inputs returns only non-auto fields
mock_graph.regular_credentials_inputs = {
"github_api_key": (regular_field, {("node-1", "credentials")}, True),
}
# Mock the credentials manager to return no credentials
with patch(
"backend.api.features.chat.tools.utils.IntegrationCredentialsManager"
) as MockCredsMgr:
mock_store = AsyncMock()
mock_store.get_all_creds.return_value = []
MockCredsMgr.return_value.store = mock_store
matched, missing = await match_user_credentials_to_graph(
user_id="test-user", graph=mock_graph
)
# No credentials available, so github should be missing
assert len(matched) == 0
assert len(missing) == 1
assert "github_api_key" in missing[0]

View File

@@ -374,7 +374,7 @@ async def get_library_agent_by_graph_id(
async def add_generated_agent_image(
graph: graph_db.GraphBaseMeta,
graph: graph_db.BaseGraph,
user_id: str,
library_agent_id: str,
) -> Optional[prisma.models.LibraryAgent]:
@@ -1103,7 +1103,7 @@ async def create_preset_from_graph_execution(
raise NotFoundError(
f"Graph #{graph_execution.graph_id} not found or accessible"
)
elif len(graph.regular_credentials_inputs) > 0:
elif len(graph.aggregate_credentials_inputs()) > 0:
raise ValueError(
f"Graph execution #{graph_exec_id} can't be turned into a preset "
"because it was run before this feature existed "

View File

@@ -1,7 +1,7 @@
import asyncio
import logging
from datetime import datetime, timezone
from typing import Any, Literal, overload
from typing import Any, Literal
import fastapi
import prisma.enums
@@ -11,8 +11,8 @@ import prisma.types
from backend.data.db import transaction
from backend.data.graph import (
GraphMeta,
GraphModel,
GraphModelWithoutNodes,
get_graph,
get_graph_as_admin,
get_sub_graphs,
@@ -334,22 +334,7 @@ async def get_store_agent_details(
raise DatabaseError("Failed to fetch agent details") from e
@overload
async def get_available_graph(
store_listing_version_id: str, hide_nodes: Literal[False]
) -> GraphModel: ...
@overload
async def get_available_graph(
store_listing_version_id: str, hide_nodes: Literal[True] = True
) -> GraphModelWithoutNodes: ...
async def get_available_graph(
store_listing_version_id: str,
hide_nodes: bool = True,
) -> GraphModelWithoutNodes | GraphModel:
async def get_available_graph(store_listing_version_id: str) -> GraphMeta:
try:
# Get avaialble, non-deleted store listing version
store_listing_version = (
@@ -359,7 +344,7 @@ async def get_available_graph(
"isAvailable": True,
"isDeleted": False,
},
include={"AgentGraph": {"include": AGENT_GRAPH_INCLUDE}},
include={"AgentGraph": {"include": {"Nodes": True}}},
)
)
@@ -369,9 +354,7 @@ async def get_available_graph(
detail=f"Store listing version {store_listing_version_id} not found",
)
return (GraphModelWithoutNodes if hide_nodes else GraphModel).from_db(
store_listing_version.AgentGraph
)
return GraphModel.from_db(store_listing_version.AgentGraph).meta()
except Exception as e:
logger.error(f"Error getting agent: {e}")

View File

@@ -16,7 +16,7 @@ from backend.blocks.ideogram import (
StyleType,
UpscaleOption,
)
from backend.data.graph import GraphBaseMeta
from backend.data.graph import BaseGraph
from backend.data.model import CredentialsMetaInput, ProviderName
from backend.integrations.credentials_store import ideogram_credentials
from backend.util.request import Requests
@@ -34,14 +34,14 @@ class ImageStyle(str, Enum):
DIGITAL_ART = "digital art"
async def generate_agent_image(agent: GraphBaseMeta | AgentGraph) -> io.BytesIO:
async def generate_agent_image(agent: BaseGraph | AgentGraph) -> io.BytesIO:
if settings.config.use_agent_image_generation_v2:
return await generate_agent_image_v2(graph=agent)
else:
return await generate_agent_image_v1(agent=agent)
async def generate_agent_image_v2(graph: GraphBaseMeta | AgentGraph) -> io.BytesIO:
async def generate_agent_image_v2(graph: BaseGraph | AgentGraph) -> io.BytesIO:
"""
Generate an image for an agent using Ideogram model.
Returns:
@@ -54,17 +54,14 @@ async def generate_agent_image_v2(graph: GraphBaseMeta | AgentGraph) -> io.Bytes
description = f"{name} ({graph.description})" if graph.description else name
prompt = (
"Create a visually striking retro-futuristic vector pop art illustration "
f'prominently featuring "{name}" in bold typography. The image clearly and '
f"literally depicts a {description}, along with recognizable objects directly "
f"associated with the primary function of a {name}. "
f"Ensure the imagery is concrete, intuitive, and immediately understandable, "
f"clearly conveying the purpose of a {name}. "
"Maintain vibrant, limited-palette colors, sharp vector lines, "
"geometric shapes, flat illustration techniques, and solid colors "
"without gradients or shading. Preserve a retro-futuristic aesthetic "
"influenced by mid-century futurism and 1960s psychedelia, "
"prioritizing clear visual storytelling and thematic clarity above all else."
f"Create a visually striking retro-futuristic vector pop art illustration prominently featuring "
f'"{name}" in bold typography. The image clearly and literally depicts a {description}, '
f"along with recognizable objects directly associated with the primary function of a {name}. "
f"Ensure the imagery is concrete, intuitive, and immediately understandable, clearly conveying the "
f"purpose of a {name}. Maintain vibrant, limited-palette colors, sharp vector lines, geometric "
f"shapes, flat illustration techniques, and solid colors without gradients or shading. Preserve a "
f"retro-futuristic aesthetic influenced by mid-century futurism and 1960s psychedelia, "
f"prioritizing clear visual storytelling and thematic clarity above all else."
)
custom_colors = [
@@ -102,12 +99,12 @@ async def generate_agent_image_v2(graph: GraphBaseMeta | AgentGraph) -> io.Bytes
return io.BytesIO(response.content)
async def generate_agent_image_v1(agent: GraphBaseMeta | AgentGraph) -> io.BytesIO:
async def generate_agent_image_v1(agent: BaseGraph | AgentGraph) -> io.BytesIO:
"""
Generate an image for an agent using Flux model via Replicate API.
Args:
agent (GraphBaseMeta | AgentGraph): The agent to generate an image for
agent (Graph): The agent to generate an image for
Returns:
io.BytesIO: The generated image as bytes
@@ -117,13 +114,7 @@ async def generate_agent_image_v1(agent: GraphBaseMeta | AgentGraph) -> io.Bytes
raise ValueError("Missing Replicate API key in settings")
# Construct prompt from agent details
prompt = (
"Create a visually engaging app store thumbnail for the AI agent "
"that highlights what it does in a clear and captivating way:\n"
f"- **Name**: {agent.name}\n"
f"- **Description**: {agent.description}\n"
f"Focus on showcasing its core functionality with an appealing design."
)
prompt = f"Create a visually engaging app store thumbnail for the AI agent that highlights what it does in a clear and captivating way:\n- **Name**: {agent.name}\n- **Description**: {agent.description}\nFocus on showcasing its core functionality with an appealing design."
# Set up Replicate client
client = ReplicateClient(api_token=settings.secrets.replicate_api_key)

View File

@@ -278,7 +278,7 @@ async def get_agent(
)
async def get_graph_meta_by_store_listing_version_id(
store_listing_version_id: str,
) -> backend.data.graph.GraphModelWithoutNodes:
) -> backend.data.graph.GraphMeta:
"""
Get Agent Graph from Store Listing Version ID.
"""

View File

@@ -246,9 +246,7 @@ class BlockSchema(BaseModel):
f"is not of type {CredentialsMetaInput.__name__}"
)
CredentialsMetaInput.validate_credentials_field_schema(
cls.get_field_schema(field_name), field_name
)
credentials_fields[field_name].validate_credentials_field_schema(cls)
elif field_name in credentials_fields:
raise KeyError(
@@ -319,8 +317,6 @@ class BlockSchema(BaseModel):
"credentials_provider": [config.get("provider", "google")],
"credentials_types": [config.get("type", "oauth2")],
"credentials_scopes": config.get("scopes"),
"is_auto_credential": True,
"input_field_name": info["field_name"],
}
result[kwarg_name] = CredentialsFieldInfo.model_validate(
auto_schema, by_alias=True

View File

@@ -3,7 +3,7 @@ import logging
import uuid
from collections import defaultdict
from datetime import datetime, timezone
from typing import TYPE_CHECKING, Annotated, Any, Literal, Optional, Self, cast
from typing import TYPE_CHECKING, Annotated, Any, Literal, Optional, cast
from prisma.enums import SubmissionStatus
from prisma.models import (
@@ -20,7 +20,7 @@ from prisma.types import (
AgentNodeLinkCreateInput,
StoreListingVersionWhereInput,
)
from pydantic import BaseModel, BeforeValidator, Field
from pydantic import BaseModel, BeforeValidator, Field, create_model
from pydantic.fields import computed_field
from backend.blocks.agent import AgentExecutorBlock
@@ -30,6 +30,7 @@ from backend.data.db import prisma as db
from backend.data.dynamic_fields import is_tool_pin, sanitize_pin_name
from backend.data.includes import MAX_GRAPH_VERSIONS_FETCH
from backend.data.model import (
CredentialsField,
CredentialsFieldInfo,
CredentialsMetaInput,
is_credentials_field_name,
@@ -44,6 +45,7 @@ from .block import (
AnyBlockSchema,
Block,
BlockInput,
BlockSchema,
BlockType,
EmptySchema,
get_block,
@@ -111,12 +113,10 @@ class Link(BaseDbModel):
class Node(BaseDbModel):
block_id: str
input_default: BlockInput = Field( # dict[input_name, default_value]
default_factory=dict
)
metadata: dict[str, Any] = Field(default_factory=dict)
input_links: list[Link] = Field(default_factory=list)
output_links: list[Link] = Field(default_factory=list)
input_default: BlockInput = {} # dict[input_name, default_value]
metadata: dict[str, Any] = {}
input_links: list[Link] = []
output_links: list[Link] = []
@property
def credentials_optional(self) -> bool:
@@ -221,33 +221,18 @@ class NodeModel(Node):
return result
class GraphBaseMeta(BaseDbModel):
"""
Shared base for `GraphMeta` and `BaseGraph`, with core graph metadata fields.
"""
class BaseGraph(BaseDbModel):
version: int = 1
is_active: bool = True
name: str
description: str
instructions: str | None = None
recommended_schedule_cron: str | None = None
nodes: list[Node] = []
links: list[Link] = []
forked_from_id: str | None = None
forked_from_version: int | None = None
class BaseGraph(GraphBaseMeta):
"""
Graph with nodes, links, and computed I/O schema fields.
Used to represent sub-graphs within a `Graph`. Contains the full graph
structure including nodes and links, plus computed fields for schemas
and trigger info. Does NOT include user_id or created_at (see GraphModel).
"""
nodes: list[Node] = Field(default_factory=list)
links: list[Link] = Field(default_factory=list)
@computed_field
@property
def input_schema(self) -> dict[str, Any]:
@@ -376,78 +361,44 @@ class GraphTriggerInfo(BaseModel):
class Graph(BaseGraph):
"""Creatable graph model used in API create/update endpoints."""
sub_graphs: list[BaseGraph] = Field(default_factory=list) # Flattened sub-graphs
class GraphMeta(GraphBaseMeta):
"""
Lightweight graph metadata model representing an existing graph from the database,
for use in listings and summaries.
Lacks `GraphModel`'s nodes, links, and expensive computed fields.
Use for list endpoints where full graph data is not needed and performance matters.
"""
id: str # type: ignore
version: int # type: ignore
user_id: str
created_at: datetime
@classmethod
def from_db(cls, graph: "AgentGraph") -> Self:
return cls(
id=graph.id,
version=graph.version,
is_active=graph.isActive,
name=graph.name or "",
description=graph.description or "",
instructions=graph.instructions,
recommended_schedule_cron=graph.recommendedScheduleCron,
forked_from_id=graph.forkedFromId,
forked_from_version=graph.forkedFromVersion,
user_id=graph.userId,
created_at=graph.createdAt,
)
class GraphModel(Graph, GraphMeta):
"""
Full graph model representing an existing graph from the database.
This is the primary model for working with persisted graphs. Includes all
graph data (nodes, links, sub_graphs) plus user ownership and timestamps.
Provides computed fields (input_schema, output_schema, etc.) used during
set-up (frontend) and execution (backend).
Inherits from:
- `Graph`: provides structure (nodes, links, sub_graphs) and computed schemas
- `GraphMeta`: provides user_id, created_at for database records
"""
nodes: list[NodeModel] = Field(default_factory=list) # type: ignore
@property
def starting_nodes(self) -> list[NodeModel]:
outbound_nodes = {link.sink_id for link in self.links}
input_nodes = {
node.id for node in self.nodes if node.block.block_type == BlockType.INPUT
}
return [
node
for node in self.nodes
if node.id not in outbound_nodes or node.id in input_nodes
]
@property
def webhook_input_node(self) -> NodeModel | None: # type: ignore
return cast(NodeModel, super().webhook_input_node)
sub_graphs: list[BaseGraph] = [] # Flattened sub-graphs
@computed_field
@property
def credentials_input_schema(self) -> dict[str, Any]:
graph_credentials_inputs = self.regular_credentials_inputs
schema = self._credentials_input_schema.jsonschema()
# Determine which credential fields are required based on credentials_optional metadata
graph_credentials_inputs = self.aggregate_credentials_inputs()
required_fields = []
# Build a map of node_id -> node for quick lookup
all_nodes = {node.id: node for node in self.nodes}
for sub_graph in self.sub_graphs:
for node in sub_graph.nodes:
all_nodes[node.id] = node
for field_key, (
_field_info,
node_field_pairs,
) in graph_credentials_inputs.items():
# A field is required if ANY node using it has credentials_optional=False
is_required = False
for node_id, _field_name in node_field_pairs:
node = all_nodes.get(node_id)
if node and not node.credentials_optional:
is_required = True
break
if is_required:
required_fields.append(field_key)
schema["required"] = required_fields
return schema
@property
def _credentials_input_schema(self) -> type[BlockSchema]:
graph_credentials_inputs = self.aggregate_credentials_inputs()
logger.debug(
f"Combined credentials input fields for graph #{self.id} ({self.name}): "
f"{graph_credentials_inputs}"
@@ -455,8 +406,8 @@ class GraphModel(Graph, GraphMeta):
# Warn if same-provider credentials inputs can't be combined (= bad UX)
graph_cred_fields = list(graph_credentials_inputs.values())
for i, (field, keys, _) in enumerate(graph_cred_fields):
for other_field, other_keys, _ in list(graph_cred_fields)[i + 1 :]:
for i, (field, keys) in enumerate(graph_cred_fields):
for other_field, other_keys in list(graph_cred_fields)[i + 1 :]:
if field.provider != other_field.provider:
continue
if ProviderName.HTTP in field.provider:
@@ -472,78 +423,31 @@ class GraphModel(Graph, GraphMeta):
f"keys: {keys} <> {other_keys}."
)
# Build JSON schema directly to avoid expensive create_model + validation overhead
properties = {}
required_fields = []
for agg_field_key, (
field_info,
_,
is_required,
) in graph_credentials_inputs.items():
providers = list(field_info.provider)
cred_types = list(field_info.supported_types)
field_schema: dict[str, Any] = {
"credentials_provider": providers,
"credentials_types": cred_types,
"type": "object",
"properties": {
"id": {"title": "Id", "type": "string"},
"title": {
"anyOf": [{"type": "string"}, {"type": "null"}],
"default": None,
"title": "Title",
},
"provider": {
"title": "Provider",
"type": "string",
**(
{"enum": providers}
if len(providers) > 1
else {"const": providers[0]}
),
},
"type": {
"title": "Type",
"type": "string",
**(
{"enum": cred_types}
if len(cred_types) > 1
else {"const": cred_types[0]}
),
},
},
"required": ["id", "provider", "type"],
}
# Add other (optional) field info items
field_schema.update(
field_info.model_dump(
by_alias=True,
exclude_defaults=True,
exclude={"provider", "supported_types"}, # already included above
)
fields: dict[str, tuple[type[CredentialsMetaInput], CredentialsMetaInput]] = {
agg_field_key: (
CredentialsMetaInput[
Literal[tuple(field_info.provider)], # type: ignore
Literal[tuple(field_info.supported_types)], # type: ignore
],
CredentialsField(
required_scopes=set(field_info.required_scopes or []),
discriminator=field_info.discriminator,
discriminator_mapping=field_info.discriminator_mapping,
discriminator_values=field_info.discriminator_values,
),
)
# Ensure field schema is well-formed
CredentialsMetaInput.validate_credentials_field_schema(
field_schema, agg_field_key
)
properties[agg_field_key] = field_schema
if is_required:
required_fields.append(agg_field_key)
return {
"type": "object",
"properties": properties,
"required": required_fields,
for agg_field_key, (field_info, _) in graph_credentials_inputs.items()
}
return create_model(
self.name.replace(" ", "") + "CredentialsInputSchema",
__base__=BlockSchema,
**fields, # type: ignore
)
def aggregate_credentials_inputs(
self,
) -> dict[str, tuple[CredentialsFieldInfo, set[tuple[str, str]], bool]]:
) -> dict[str, tuple[CredentialsFieldInfo, set[tuple[str, str]]]]:
"""
Returns:
dict[aggregated_field_key, tuple(
@@ -551,19 +455,13 @@ class GraphModel(Graph, GraphMeta):
(now includes discriminator_values from matching nodes)
set[(node_id, field_name)]: Node credentials fields that are
compatible with this aggregated field spec
bool: True if the field is required (any node has credentials_optional=False)
)]
"""
# First collect all credential field data with input defaults
# Track (field_info, (node_id, field_name), is_required) for each credential field
node_credential_data: list[tuple[CredentialsFieldInfo, tuple[str, str]]] = []
node_required_map: dict[str, bool] = {} # node_id -> is_required
node_credential_data = []
for graph in [self] + self.sub_graphs:
for node in graph.nodes:
# Track if this node requires credentials (credentials_optional=False means required)
node_required_map[node.id] = not node.credentials_optional
for (
field_name,
field_info,
@@ -587,43 +485,37 @@ class GraphModel(Graph, GraphMeta):
)
# Combine credential field info (this will merge discriminator_values automatically)
combined = CredentialsFieldInfo.combine(*node_credential_data)
return CredentialsFieldInfo.combine(*node_credential_data)
# Add is_required flag to each aggregated field
# A field is required if ANY node using it has credentials_optional=False
return {
key: (
field_info,
node_field_pairs,
any(
node_required_map.get(node_id, True)
for node_id, _ in node_field_pairs
),
)
for key, (field_info, node_field_pairs) in combined.items()
}
class GraphModel(Graph):
user_id: str
nodes: list[NodeModel] = [] # type: ignore
created_at: datetime
@property
def regular_credentials_inputs(
self,
) -> dict[str, tuple[CredentialsFieldInfo, set[tuple[str, str]], bool]]:
"""Credentials that need explicit user mapping (CredentialsMetaInput fields)."""
return {
k: v
for k, v in self.aggregate_credentials_inputs().items()
if not v[0].is_auto_credential
def starting_nodes(self) -> list[NodeModel]:
outbound_nodes = {link.sink_id for link in self.links}
input_nodes = {
node.id for node in self.nodes if node.block.block_type == BlockType.INPUT
}
return [
node
for node in self.nodes
if node.id not in outbound_nodes or node.id in input_nodes
]
@property
def auto_credentials_inputs(
self,
) -> dict[str, tuple[CredentialsFieldInfo, set[tuple[str, str]], bool]]:
"""Credentials embedded in file fields (_credentials_id), resolved at execution time."""
return {
k: v
for k, v in self.aggregate_credentials_inputs().items()
if v[0].is_auto_credential
}
def webhook_input_node(self) -> NodeModel | None: # type: ignore
return cast(NodeModel, super().webhook_input_node)
def meta(self) -> "GraphMeta":
"""
Returns a GraphMeta object with metadata about the graph.
This is used to return metadata about the graph without exposing nodes and links.
"""
return GraphMeta.from_graph(self)
def reassign_ids(self, user_id: str, reassign_graph_id: bool = False):
"""
@@ -675,16 +567,6 @@ class GraphModel(Graph, GraphMeta):
) and graph_id in graph_id_map:
node.input_default["graph_id"] = graph_id_map[graph_id]
# Clear auto-credentials references (e.g., _credentials_id in
# GoogleDriveFile fields) so the new user must re-authenticate
# with their own account
for node in graph.nodes:
if not node.input_default:
continue
for key, value in node.input_default.items():
if isinstance(value, dict) and "_credentials_id" in value:
del value["_credentials_id"]
def validate_graph(
self,
for_run: bool = False,
@@ -917,14 +799,13 @@ class GraphModel(Graph, GraphMeta):
if is_static_output_block(link.source_id):
link.is_static = True # Each value block output should be static.
@classmethod
def from_db( # type: ignore[reportIncompatibleMethodOverride]
cls,
@staticmethod
def from_db(
graph: AgentGraph,
for_export: bool = False,
sub_graphs: list[AgentGraph] | None = None,
) -> Self:
return cls(
) -> "GraphModel":
return GraphModel(
id=graph.id,
user_id=graph.userId if not for_export else "",
version=graph.version,
@@ -950,28 +831,17 @@ class GraphModel(Graph, GraphMeta):
],
)
def hide_nodes(self) -> "GraphModelWithoutNodes":
"""
Returns a copy of the `GraphModel` with nodes, links, and sub-graphs hidden
(excluded from serialization). They are still present in the model instance
so all computed fields (e.g. `credentials_input_schema`) still work.
"""
return GraphModelWithoutNodes.model_validate(self, from_attributes=True)
class GraphMeta(Graph):
user_id: str
class GraphModelWithoutNodes(GraphModel):
"""
GraphModel variant that excludes nodes, links, and sub-graphs from serialization.
# Easy work-around to prevent exposing nodes and links in the API response
nodes: list[NodeModel] = Field(default=[], exclude=True) # type: ignore
links: list[Link] = Field(default=[], exclude=True)
Used in contexts like the store where exposing internal graph structure
is not desired. Inherits all computed fields from GraphModel but marks
nodes and links as excluded from JSON output.
"""
nodes: list[NodeModel] = Field(default_factory=list, exclude=True)
links: list[Link] = Field(default_factory=list, exclude=True)
sub_graphs: list[BaseGraph] = Field(default_factory=list, exclude=True)
@staticmethod
def from_graph(graph: GraphModel) -> "GraphMeta":
return GraphMeta(**graph.model_dump())
class GraphsPaginated(BaseModel):
@@ -1042,11 +912,21 @@ async def list_graphs_paginated(
where=where_clause,
distinct=["id"],
order={"version": "desc"},
include=AGENT_GRAPH_INCLUDE,
skip=offset,
take=page_size,
)
graph_models = [GraphMeta.from_db(graph) for graph in graphs]
graph_models: list[GraphMeta] = []
for graph in graphs:
try:
graph_meta = GraphModel.from_db(graph).meta()
# Trigger serialization to validate that the graph is well formed
graph_meta.model_dump()
graph_models.append(graph_meta)
except Exception as e:
logger.error(f"Error processing graph {graph.id}: {e}")
continue
return GraphsPaginated(
graphs=graph_models,

View File

@@ -463,328 +463,3 @@ def test_node_credentials_optional_with_other_metadata():
assert node.credentials_optional is True
assert node.metadata["position"] == {"x": 100, "y": 200}
assert node.metadata["customized_name"] == "My Custom Node"
# ============================================================================
# Tests for _reassign_ids credential clearing (Fix 3: SECRT-1772)
def test_combine_preserves_is_auto_credential_flag():
"""
CredentialsFieldInfo.combine() must propagate is_auto_credential and
input_field_name to the combined result. Regression test for reviewer
finding that combine() dropped these fields.
"""
from backend.data.model import CredentialsFieldInfo
auto_field = CredentialsFieldInfo.model_validate(
{
"credentials_provider": ["google"],
"credentials_types": ["oauth2"],
"credentials_scopes": ["drive.readonly"],
"is_auto_credential": True,
"input_field_name": "spreadsheet",
},
by_alias=True,
)
# combine() takes *args of (field_info, key) tuples
combined = CredentialsFieldInfo.combine(
(auto_field, ("node-1", "credentials")),
(auto_field, ("node-2", "credentials")),
)
assert len(combined) == 1
group_key = next(iter(combined))
combined_info, combined_keys = combined[group_key]
assert combined_info.is_auto_credential is True
assert combined_info.input_field_name == "spreadsheet"
assert combined_keys == {("node-1", "credentials"), ("node-2", "credentials")}
def test_combine_preserves_regular_credential_defaults():
"""Regular credentials should have is_auto_credential=False after combine()."""
from backend.data.model import CredentialsFieldInfo
regular_field = CredentialsFieldInfo.model_validate(
{
"credentials_provider": ["github"],
"credentials_types": ["api_key"],
"is_auto_credential": False,
},
by_alias=True,
)
combined = CredentialsFieldInfo.combine(
(regular_field, ("node-1", "credentials")),
)
group_key = next(iter(combined))
combined_info, _ = combined[group_key]
assert combined_info.is_auto_credential is False
assert combined_info.input_field_name is None
# ============================================================================
def test_reassign_ids_clears_credentials_id():
"""
[SECRT-1772] _reassign_ids should clear _credentials_id from
GoogleDriveFile-style input_default fields so forked agents
don't retain the original creator's credential references.
"""
from backend.data.graph import GraphModel
node = Node(
id="node-1",
block_id=StoreValueBlock().id,
input_default={
"spreadsheet": {
"_credentials_id": "original-cred-id",
"id": "file-123",
"name": "test.xlsx",
"mimeType": "application/vnd.google-apps.spreadsheet",
"url": "https://docs.google.com/spreadsheets/d/file-123",
},
},
)
graph = Graph(
id="test-graph",
name="Test",
description="Test",
nodes=[node],
links=[],
)
GraphModel._reassign_ids(graph, user_id="new-user", graph_id_map={})
# _credentials_id key should be removed (not set to None) so that
# _acquire_auto_credentials correctly errors instead of treating it as chained data
assert "_credentials_id" not in graph.nodes[0].input_default["spreadsheet"]
def test_reassign_ids_preserves_non_credential_fields():
"""
Regression guard: _reassign_ids should NOT modify non-credential fields
like name, mimeType, id, url.
"""
from backend.data.graph import GraphModel
node = Node(
id="node-1",
block_id=StoreValueBlock().id,
input_default={
"spreadsheet": {
"_credentials_id": "cred-abc",
"id": "file-123",
"name": "test.xlsx",
"mimeType": "application/vnd.google-apps.spreadsheet",
"url": "https://docs.google.com/spreadsheets/d/file-123",
},
},
)
graph = Graph(
id="test-graph",
name="Test",
description="Test",
nodes=[node],
links=[],
)
GraphModel._reassign_ids(graph, user_id="new-user", graph_id_map={})
field = graph.nodes[0].input_default["spreadsheet"]
assert field["id"] == "file-123"
assert field["name"] == "test.xlsx"
assert field["mimeType"] == "application/vnd.google-apps.spreadsheet"
assert field["url"] == "https://docs.google.com/spreadsheets/d/file-123"
def test_reassign_ids_handles_no_credentials():
"""
Regression guard: _reassign_ids should not error when input_default
has no dict fields with _credentials_id.
"""
from backend.data.graph import GraphModel
node = Node(
id="node-1",
block_id=StoreValueBlock().id,
input_default={
"input": "some value",
"another_input": 42,
},
)
graph = Graph(
id="test-graph",
name="Test",
description="Test",
nodes=[node],
links=[],
)
GraphModel._reassign_ids(graph, user_id="new-user", graph_id_map={})
# Should not error, fields unchanged
assert graph.nodes[0].input_default["input"] == "some value"
assert graph.nodes[0].input_default["another_input"] == 42
def test_reassign_ids_handles_multiple_credential_fields():
"""
[SECRT-1772] When a node has multiple dict fields with _credentials_id,
ALL of them should be cleared.
"""
from backend.data.graph import GraphModel
node = Node(
id="node-1",
block_id=StoreValueBlock().id,
input_default={
"spreadsheet": {
"_credentials_id": "cred-1",
"id": "file-1",
"name": "file1.xlsx",
},
"doc_file": {
"_credentials_id": "cred-2",
"id": "file-2",
"name": "file2.docx",
},
"plain_input": "not a dict",
},
)
graph = Graph(
id="test-graph",
name="Test",
description="Test",
nodes=[node],
links=[],
)
GraphModel._reassign_ids(graph, user_id="new-user", graph_id_map={})
assert "_credentials_id" not in graph.nodes[0].input_default["spreadsheet"]
assert "_credentials_id" not in graph.nodes[0].input_default["doc_file"]
assert graph.nodes[0].input_default["plain_input"] == "not a dict"
# ============================================================================
# Tests for discriminate() field propagation
def test_discriminate_preserves_is_auto_credential_flag():
"""
CredentialsFieldInfo.discriminate() must propagate is_auto_credential and
input_field_name to the discriminated result. Regression test for
discriminate() dropping these fields (same class of bug as combine()).
"""
from backend.data.model import CredentialsFieldInfo
auto_field = CredentialsFieldInfo.model_validate(
{
"credentials_provider": ["google", "openai"],
"credentials_types": ["oauth2"],
"credentials_scopes": ["drive.readonly"],
"is_auto_credential": True,
"input_field_name": "spreadsheet",
"discriminator": "model",
"discriminator_mapping": {"gpt-4": "openai", "gemini": "google"},
},
by_alias=True,
)
discriminated = auto_field.discriminate("gemini")
assert discriminated.is_auto_credential is True
assert discriminated.input_field_name == "spreadsheet"
assert discriminated.provider == frozenset(["google"])
def test_discriminate_preserves_regular_credential_defaults():
"""Regular credentials should have is_auto_credential=False after discriminate()."""
from backend.data.model import CredentialsFieldInfo
regular_field = CredentialsFieldInfo.model_validate(
{
"credentials_provider": ["google", "openai"],
"credentials_types": ["api_key"],
"is_auto_credential": False,
"discriminator": "model",
"discriminator_mapping": {"gpt-4": "openai", "gemini": "google"},
},
by_alias=True,
)
discriminated = regular_field.discriminate("gpt-4")
assert discriminated.is_auto_credential is False
assert discriminated.input_field_name is None
assert discriminated.provider == frozenset(["openai"])
# ============================================================================
# Tests for credentials_input_schema excluding auto_credentials
def test_credentials_input_schema_excludes_auto_creds():
"""
GraphModel.credentials_input_schema should exclude auto_credentials
(is_auto_credential=True) from the schema. Auto_credentials are
transparently resolved at execution time via file picker data.
"""
from datetime import datetime, timezone
from unittest.mock import PropertyMock, patch
from backend.data.graph import GraphModel, NodeModel
from backend.data.model import CredentialsFieldInfo
regular_field_info = CredentialsFieldInfo.model_validate(
{
"credentials_provider": ["github"],
"credentials_types": ["api_key"],
"is_auto_credential": False,
},
by_alias=True,
)
graph = GraphModel(
id="test-graph",
version=1,
name="Test",
description="Test",
user_id="test-user",
created_at=datetime.now(timezone.utc),
nodes=[
NodeModel(
id="node-1",
block_id=StoreValueBlock().id,
input_default={},
graph_id="test-graph",
graph_version=1,
),
],
links=[],
)
# Mock regular_credentials_inputs to return only the non-auto field (3-tuple)
regular_only = {
"github_credentials": (
regular_field_info,
{("node-1", "credentials")},
True,
),
}
with patch.object(
type(graph),
"regular_credentials_inputs",
new_callable=PropertyMock,
return_value=regular_only,
):
schema = graph.credentials_input_schema
field_names = set(schema.get("properties", {}).keys())
# Should include regular credential but NOT auto_credential
assert "github_credentials" in field_names
assert "google_credentials" not in field_names

View File

@@ -163,6 +163,7 @@ class User(BaseModel):
if TYPE_CHECKING:
from prisma.models import User as PrismaUser
from backend.data.block import BlockSchema
T = TypeVar("T")
logger = logging.getLogger(__name__)
@@ -507,13 +508,15 @@ class CredentialsMetaInput(BaseModel, Generic[CP, CT]):
def allowed_cred_types(cls) -> tuple[CredentialsType, ...]:
return get_args(cls.model_fields["type"].annotation)
@staticmethod
def validate_credentials_field_schema(
field_schema: dict[str, Any], field_name: str
):
@classmethod
def validate_credentials_field_schema(cls, model: type["BlockSchema"]):
"""Validates the schema of a credentials input field"""
field_name = next(
name for name, type in model.get_credentials_fields().items() if type is cls
)
field_schema = model.jsonschema()["properties"][field_name]
try:
field_info = CredentialsFieldInfo[CP, CT].model_validate(field_schema)
schema_extra = CredentialsFieldInfo[CP, CT].model_validate(field_schema)
except ValidationError as e:
if "Field required [type=missing" not in str(e):
raise
@@ -523,11 +526,11 @@ class CredentialsMetaInput(BaseModel, Generic[CP, CT]):
f"{field_schema}"
) from e
providers = field_info.provider
providers = cls.allowed_providers()
if (
providers is not None
and len(providers) > 1
and not field_info.discriminator
and not schema_extra.discriminator
):
raise TypeError(
f"Multi-provider CredentialsField '{field_name}' "
@@ -571,8 +574,6 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
discriminator: Optional[str] = None
discriminator_mapping: Optional[dict[str, CP]] = None
discriminator_values: set[Any] = Field(default_factory=set)
is_auto_credential: bool = False
input_field_name: Optional[str] = None
@classmethod
def combine(
@@ -653,9 +654,6 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
+ "_credentials"
)
# Propagate is_auto_credential from the combined field.
# All fields in a group should share the same is_auto_credential
# value since auto and regular credentials serve different purposes.
result[group_key] = (
CredentialsFieldInfo[CP, CT](
credentials_provider=combined.provider,
@@ -664,8 +662,6 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
discriminator=combined.discriminator,
discriminator_mapping=combined.discriminator_mapping,
discriminator_values=set(all_discriminator_values),
is_auto_credential=combined.is_auto_credential,
input_field_name=combined.input_field_name,
),
combined_keys,
)
@@ -691,8 +687,6 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
discriminator=self.discriminator,
discriminator_mapping=self.discriminator_mapping,
discriminator_values=self.discriminator_values,
is_auto_credential=self.is_auto_credential,
input_field_name=self.input_field_name,
)

View File

@@ -172,81 +172,6 @@ def execute_graph(
T = TypeVar("T")
async def _acquire_auto_credentials(
input_model: type[BlockSchema],
input_data: dict[str, Any],
creds_manager: "IntegrationCredentialsManager",
user_id: str,
) -> tuple[dict[str, Any], list[AsyncRedisLock]]:
"""
Resolve auto_credentials from GoogleDriveFileField-style inputs.
Returns:
(extra_exec_kwargs, locks): kwargs to inject into block execution, and
credential locks to release after execution completes.
"""
extra_exec_kwargs: dict[str, Any] = {}
locks: list[AsyncRedisLock] = []
# NOTE: If a block ever has multiple auto-credential fields, a ValueError
# on a later field will strand locks acquired for earlier fields. They'll
# auto-expire via Redis TTL, but add a try/except to release partial locks
# if that becomes a real scenario.
for kwarg_name, info in input_model.get_auto_credentials_fields().items():
field_name = info["field_name"]
field_data = input_data.get(field_name)
if field_data and isinstance(field_data, dict):
# Check if _credentials_id key exists in the field data
if "_credentials_id" in field_data:
cred_id = field_data["_credentials_id"]
if cred_id:
# Credential ID provided - acquire credentials
provider = info.get("config", {}).get(
"provider", "external service"
)
file_name = field_data.get("name", "selected file")
try:
credentials, lock = await creds_manager.acquire(
user_id, cred_id
)
locks.append(lock)
extra_exec_kwargs[kwarg_name] = credentials
except ValueError:
raise ValueError(
f"{provider.capitalize()} credentials for "
f"'{file_name}' in field '{field_name}' are not "
f"available in your account. "
f"This can happen if the agent was created by another "
f"user or the credentials were deleted. "
f"Please open the agent in the builder and re-select "
f"the file to authenticate with your own account."
)
# else: _credentials_id is explicitly None, skip (chained data)
else:
# _credentials_id key missing entirely - this is an error
provider = info.get("config", {}).get("provider", "external service")
file_name = field_data.get("name", "selected file")
raise ValueError(
f"Authentication missing for '{file_name}' in field "
f"'{field_name}'. Please re-select the file to authenticate "
f"with {provider.capitalize()}."
)
elif field_data is None and field_name not in input_data:
# Field not in input_data at all = connected from upstream block, skip
pass
else:
# field_data is None/empty but key IS in input_data = user didn't select
provider = info.get("config", {}).get("provider", "external service")
raise ValueError(
f"No file selected for '{field_name}'. "
f"Please select a file to provide "
f"{provider.capitalize()} authentication."
)
return extra_exec_kwargs, locks
async def execute_node(
node: Node,
data: NodeExecutionEntry,
@@ -346,14 +271,41 @@ async def execute_node(
extra_exec_kwargs[field_name] = credentials
# Handle auto-generated credentials (e.g., from GoogleDriveFileInput)
auto_extra_kwargs, auto_locks = await _acquire_auto_credentials(
input_model=input_model,
input_data=input_data,
creds_manager=creds_manager,
user_id=user_id,
)
extra_exec_kwargs.update(auto_extra_kwargs)
creds_locks.extend(auto_locks)
for kwarg_name, info in input_model.get_auto_credentials_fields().items():
field_name = info["field_name"]
field_data = input_data.get(field_name)
if field_data and isinstance(field_data, dict):
# Check if _credentials_id key exists in the field data
if "_credentials_id" in field_data:
cred_id = field_data["_credentials_id"]
if cred_id:
# Credential ID provided - acquire credentials
provider = info.get("config", {}).get(
"provider", "external service"
)
file_name = field_data.get("name", "selected file")
try:
credentials, lock = await creds_manager.acquire(
user_id, cred_id
)
creds_locks.append(lock)
extra_exec_kwargs[kwarg_name] = credentials
except ValueError:
# Credential was deleted or doesn't exist
raise ValueError(
f"Authentication expired for '{file_name}' in field '{field_name}'. "
f"The saved {provider.capitalize()} credentials no longer exist. "
f"Please re-select the file to re-authenticate."
)
# else: _credentials_id is explicitly None, skip credentials (for chained data)
else:
# _credentials_id key missing entirely - this is an error
provider = info.get("config", {}).get("provider", "external service")
file_name = field_data.get("name", "selected file")
raise ValueError(
f"Authentication missing for '{file_name}' in field '{field_name}'. "
f"Please re-select the file to authenticate with {provider.capitalize()}."
)
output_size = 0

View File

@@ -1,320 +0,0 @@
"""
Tests for auto_credentials handling in execute_node().
These test the _acquire_auto_credentials() helper function extracted from
execute_node() (manager.py lines 273-308).
"""
import pytest
from pytest_mock import MockerFixture
@pytest.fixture
def google_drive_file_data():
return {
"valid": {
"_credentials_id": "cred-id-123",
"id": "file-123",
"name": "test.xlsx",
"mimeType": "application/vnd.google-apps.spreadsheet",
},
"chained": {
"_credentials_id": None,
"id": "file-456",
"name": "chained.xlsx",
"mimeType": "application/vnd.google-apps.spreadsheet",
},
"missing_key": {
"id": "file-789",
"name": "bad.xlsx",
"mimeType": "application/vnd.google-apps.spreadsheet",
},
}
@pytest.fixture
def mock_input_model(mocker: MockerFixture):
"""Create a mock input model with get_auto_credentials_fields() returning one field."""
input_model = mocker.MagicMock()
input_model.get_auto_credentials_fields.return_value = {
"credentials": {
"field_name": "spreadsheet",
"config": {
"provider": "google",
"type": "oauth2",
"scopes": ["https://www.googleapis.com/auth/drive.readonly"],
},
}
}
return input_model
@pytest.fixture
def mock_creds_manager(mocker: MockerFixture):
manager = mocker.AsyncMock()
mock_lock = mocker.AsyncMock()
mock_creds = mocker.MagicMock()
mock_creds.id = "cred-id-123"
mock_creds.provider = "google"
manager.acquire.return_value = (mock_creds, mock_lock)
return manager, mock_creds, mock_lock
@pytest.mark.asyncio
async def test_auto_credentials_happy_path(
mocker: MockerFixture,
google_drive_file_data,
mock_input_model,
mock_creds_manager,
):
"""When field_data has a valid _credentials_id, credentials should be acquired."""
from backend.executor.manager import _acquire_auto_credentials
manager, mock_creds, mock_lock = mock_creds_manager
input_data = {"spreadsheet": google_drive_file_data["valid"]}
extra_kwargs, locks = await _acquire_auto_credentials(
input_model=mock_input_model,
input_data=input_data,
creds_manager=manager,
user_id="user-1",
)
manager.acquire.assert_called_once_with("user-1", "cred-id-123")
assert extra_kwargs["credentials"] == mock_creds
assert mock_lock in locks
@pytest.mark.asyncio
async def test_auto_credentials_field_none_static_raises(
mocker: MockerFixture,
mock_input_model,
mock_creds_manager,
):
"""
[THE BUG FIX TEST — OPEN-2895]
When field_data is None and the key IS in input_data (user didn't select a file),
should raise ValueError instead of silently skipping.
"""
from backend.executor.manager import _acquire_auto_credentials
manager, _, _ = mock_creds_manager
# Key is present but value is None = user didn't select a file
input_data = {"spreadsheet": None}
with pytest.raises(ValueError, match="No file selected"):
await _acquire_auto_credentials(
input_model=mock_input_model,
input_data=input_data,
creds_manager=manager,
user_id="user-1",
)
@pytest.mark.asyncio
async def test_auto_credentials_field_absent_skips(
mocker: MockerFixture,
mock_input_model,
mock_creds_manager,
):
"""
When the field key is NOT in input_data at all (upstream connection),
should skip without error.
"""
from backend.executor.manager import _acquire_auto_credentials
manager, _, _ = mock_creds_manager
# Key not present = connected from upstream block
input_data = {}
extra_kwargs, locks = await _acquire_auto_credentials(
input_model=mock_input_model,
input_data=input_data,
creds_manager=manager,
user_id="user-1",
)
manager.acquire.assert_not_called()
assert "credentials" not in extra_kwargs
assert locks == []
@pytest.mark.asyncio
async def test_auto_credentials_chained_cred_id_none(
mocker: MockerFixture,
google_drive_file_data,
mock_input_model,
mock_creds_manager,
):
"""
When _credentials_id is explicitly None (chained data from upstream),
should skip credential acquisition.
"""
from backend.executor.manager import _acquire_auto_credentials
manager, _, _ = mock_creds_manager
input_data = {"spreadsheet": google_drive_file_data["chained"]}
extra_kwargs, locks = await _acquire_auto_credentials(
input_model=mock_input_model,
input_data=input_data,
creds_manager=manager,
user_id="user-1",
)
manager.acquire.assert_not_called()
assert "credentials" not in extra_kwargs
@pytest.mark.asyncio
async def test_auto_credentials_missing_cred_id_key_raises(
mocker: MockerFixture,
google_drive_file_data,
mock_input_model,
mock_creds_manager,
):
"""
When _credentials_id key is missing entirely from field_data dict,
should raise ValueError.
"""
from backend.executor.manager import _acquire_auto_credentials
manager, _, _ = mock_creds_manager
input_data = {"spreadsheet": google_drive_file_data["missing_key"]}
with pytest.raises(ValueError, match="Authentication missing"):
await _acquire_auto_credentials(
input_model=mock_input_model,
input_data=input_data,
creds_manager=manager,
user_id="user-1",
)
@pytest.mark.asyncio
async def test_auto_credentials_ownership_mismatch_error(
mocker: MockerFixture,
google_drive_file_data,
mock_input_model,
mock_creds_manager,
):
"""
[SECRT-1772] When acquire() raises ValueError (credential belongs to another user),
the error message should mention 'not available' (not 'expired').
"""
from backend.executor.manager import _acquire_auto_credentials
manager, _, _ = mock_creds_manager
manager.acquire.side_effect = ValueError(
"Credentials #cred-id-123 for user #user-2 not found"
)
input_data = {"spreadsheet": google_drive_file_data["valid"]}
with pytest.raises(ValueError, match="not available in your account"):
await _acquire_auto_credentials(
input_model=mock_input_model,
input_data=input_data,
creds_manager=manager,
user_id="user-2",
)
@pytest.mark.asyncio
async def test_auto_credentials_deleted_credential_error(
mocker: MockerFixture,
google_drive_file_data,
mock_input_model,
mock_creds_manager,
):
"""
[SECRT-1772] When acquire() raises ValueError (credential was deleted),
the error message should mention 'not available' (not 'expired').
"""
from backend.executor.manager import _acquire_auto_credentials
manager, _, _ = mock_creds_manager
manager.acquire.side_effect = ValueError(
"Credentials #cred-id-123 for user #user-1 not found"
)
input_data = {"spreadsheet": google_drive_file_data["valid"]}
with pytest.raises(ValueError, match="not available in your account"):
await _acquire_auto_credentials(
input_model=mock_input_model,
input_data=input_data,
creds_manager=manager,
user_id="user-1",
)
@pytest.mark.asyncio
async def test_auto_credentials_lock_appended(
mocker: MockerFixture,
google_drive_file_data,
mock_input_model,
mock_creds_manager,
):
"""Lock from acquire() should be included in returned locks list."""
from backend.executor.manager import _acquire_auto_credentials
manager, _, mock_lock = mock_creds_manager
input_data = {"spreadsheet": google_drive_file_data["valid"]}
extra_kwargs, locks = await _acquire_auto_credentials(
input_model=mock_input_model,
input_data=input_data,
creds_manager=manager,
user_id="user-1",
)
assert len(locks) == 1
assert locks[0] is mock_lock
@pytest.mark.asyncio
async def test_auto_credentials_multiple_fields(
mocker: MockerFixture,
mock_creds_manager,
):
"""When there are multiple auto_credentials fields, only valid ones should acquire."""
from backend.executor.manager import _acquire_auto_credentials
manager, mock_creds, mock_lock = mock_creds_manager
input_model = mocker.MagicMock()
input_model.get_auto_credentials_fields.return_value = {
"credentials": {
"field_name": "spreadsheet",
"config": {"provider": "google", "type": "oauth2"},
},
"credentials2": {
"field_name": "doc_file",
"config": {"provider": "google", "type": "oauth2"},
},
}
input_data = {
"spreadsheet": {
"_credentials_id": "cred-id-123",
"id": "file-1",
"name": "file1.xlsx",
},
"doc_file": {
"_credentials_id": None,
"id": "file-2",
"name": "chained.doc",
},
}
extra_kwargs, locks = await _acquire_auto_credentials(
input_model=input_model,
input_data=input_data,
creds_manager=manager,
user_id="user-1",
)
# Only the first field should have acquired credentials
manager.acquire.assert_called_once_with("user-1", "cred-id-123")
assert "credentials" in extra_kwargs
assert "credentials2" not in extra_kwargs
assert len(locks) == 1

View File

@@ -259,8 +259,7 @@ async def _validate_node_input_credentials(
# Find any fields of type CredentialsMetaInput
credentials_fields = block.input_schema.get_credentials_fields()
auto_credentials_fields = block.input_schema.get_auto_credentials_fields()
if not credentials_fields and not auto_credentials_fields:
if not credentials_fields:
continue
# Track if any credential field is missing for this node
@@ -340,47 +339,6 @@ async def _validate_node_input_credentials(
] = "Invalid credentials: type/provider mismatch"
continue
# Validate auto-credentials (GoogleDriveFileField-based)
# These have _credentials_id embedded in the file field data
if auto_credentials_fields:
for _kwarg_name, info in auto_credentials_fields.items():
field_name = info["field_name"]
# Check input_default and nodes_input_masks for the field value
field_value = node.input_default.get(field_name)
if nodes_input_masks and node.id in nodes_input_masks:
field_value = nodes_input_masks[node.id].get(
field_name, field_value
)
if field_value and isinstance(field_value, dict):
if "_credentials_id" not in field_value:
# Key removed (e.g., on fork) — needs re-auth
has_missing_credentials = True
credential_errors[node.id][field_name] = (
"Authentication missing for the selected file. "
"Please re-select the file to authenticate with "
"your own account."
)
continue
cred_id = field_value.get("_credentials_id")
if cred_id and isinstance(cred_id, str):
try:
creds_store = get_integration_credentials_store()
creds = await creds_store.get_creds_by_id(user_id, cred_id)
except Exception as e:
has_missing_credentials = True
credential_errors[node.id][
field_name
] = f"Credentials not available: {e}"
continue
if not creds:
has_missing_credentials = True
credential_errors[node.id][field_name] = (
"The saved credentials are not available "
"for your account. Please re-select the file to "
"authenticate with your own account."
)
# If node has optional credentials and any are missing, mark for skipping
# But only if there are no other errors for this node
if (
@@ -412,11 +370,10 @@ def make_node_credentials_input_map(
"""
result: dict[str, dict[str, JsonValue]] = {}
# Only map regular credentials (not auto_credentials, which are resolved
# at execution time from _credentials_id in file field data)
graph_cred_inputs = graph.regular_credentials_inputs
# Get aggregated credentials fields for the graph
graph_cred_inputs = graph.aggregate_credentials_inputs()
for graph_input_name, (_, compatible_node_fields, _) in graph_cred_inputs.items():
for graph_input_name, (_, compatible_node_fields) in graph_cred_inputs.items():
# Best-effort map: skip missing items
if graph_input_name not in graph_credentials_input:
continue

View File

@@ -907,335 +907,3 @@ async def test_stop_graph_execution_cascades_to_child_with_reviews(
# Verify both parent and child status updates
assert mock_execution_db.update_graph_execution_stats.call_count >= 1
# ============================================================================
# Tests for auto_credentials validation in _validate_node_input_credentials
# (Fix 3: SECRT-1772 + Fix 4: Path 4)
# ============================================================================
@pytest.mark.asyncio
async def test_validate_node_input_credentials_auto_creds_valid(
mocker: MockerFixture,
):
"""
[SECRT-1772] When a node has auto_credentials with a valid _credentials_id
that exists in the store, validation should pass without errors.
"""
from backend.executor.utils import _validate_node_input_credentials
mock_node = mocker.MagicMock()
mock_node.id = "node-with-auto-creds"
mock_node.credentials_optional = False
mock_node.input_default = {
"spreadsheet": {
"_credentials_id": "valid-cred-id",
"id": "file-123",
"name": "test.xlsx",
}
}
mock_block = mocker.MagicMock()
# No regular credentials fields
mock_block.input_schema.get_credentials_fields.return_value = {}
# Has auto_credentials fields
mock_block.input_schema.get_auto_credentials_fields.return_value = {
"credentials": {
"field_name": "spreadsheet",
"config": {"provider": "google", "type": "oauth2"},
}
}
mock_node.block = mock_block
mock_graph = mocker.MagicMock()
mock_graph.nodes = [mock_node]
# Mock the credentials store to return valid credentials
mock_store = mocker.MagicMock()
mock_creds = mocker.MagicMock()
mock_creds.id = "valid-cred-id"
mock_store.get_creds_by_id = mocker.AsyncMock(return_value=mock_creds)
mocker.patch(
"backend.executor.utils.get_integration_credentials_store",
return_value=mock_store,
)
errors, nodes_to_skip = await _validate_node_input_credentials(
graph=mock_graph,
user_id="test-user",
nodes_input_masks=None,
)
assert mock_node.id not in errors
assert mock_node.id not in nodes_to_skip
@pytest.mark.asyncio
async def test_validate_node_input_credentials_auto_creds_missing(
mocker: MockerFixture,
):
"""
[SECRT-1772] When a node has auto_credentials with a _credentials_id
that doesn't exist for the current user, validation should report an error.
"""
from backend.executor.utils import _validate_node_input_credentials
mock_node = mocker.MagicMock()
mock_node.id = "node-with-bad-auto-creds"
mock_node.credentials_optional = False
mock_node.input_default = {
"spreadsheet": {
"_credentials_id": "other-users-cred-id",
"id": "file-123",
"name": "test.xlsx",
}
}
mock_block = mocker.MagicMock()
mock_block.input_schema.get_credentials_fields.return_value = {}
mock_block.input_schema.get_auto_credentials_fields.return_value = {
"credentials": {
"field_name": "spreadsheet",
"config": {"provider": "google", "type": "oauth2"},
}
}
mock_node.block = mock_block
mock_graph = mocker.MagicMock()
mock_graph.nodes = [mock_node]
# Mock the credentials store to return None (cred not found for this user)
mock_store = mocker.MagicMock()
mock_store.get_creds_by_id = mocker.AsyncMock(return_value=None)
mocker.patch(
"backend.executor.utils.get_integration_credentials_store",
return_value=mock_store,
)
errors, nodes_to_skip = await _validate_node_input_credentials(
graph=mock_graph,
user_id="different-user",
nodes_input_masks=None,
)
assert mock_node.id in errors
assert "spreadsheet" in errors[mock_node.id]
assert "not available" in errors[mock_node.id]["spreadsheet"].lower()
@pytest.mark.asyncio
async def test_validate_node_input_credentials_both_regular_and_auto(
mocker: MockerFixture,
):
"""
[SECRT-1772] A node that has BOTH regular credentials AND auto_credentials
should have both validated.
"""
from backend.executor.utils import _validate_node_input_credentials
mock_node = mocker.MagicMock()
mock_node.id = "node-with-both-creds"
mock_node.credentials_optional = False
mock_node.input_default = {
"credentials": {
"id": "regular-cred-id",
"provider": "github",
"type": "api_key",
},
"spreadsheet": {
"_credentials_id": "auto-cred-id",
"id": "file-123",
"name": "test.xlsx",
},
}
mock_credentials_field_type = mocker.MagicMock()
mock_credentials_meta = mocker.MagicMock()
mock_credentials_meta.id = "regular-cred-id"
mock_credentials_meta.provider = "github"
mock_credentials_meta.type = "api_key"
mock_credentials_field_type.model_validate.return_value = mock_credentials_meta
mock_block = mocker.MagicMock()
# Regular credentials field
mock_block.input_schema.get_credentials_fields.return_value = {
"credentials": mock_credentials_field_type,
}
# Auto-credentials field
mock_block.input_schema.get_auto_credentials_fields.return_value = {
"auto_credentials": {
"field_name": "spreadsheet",
"config": {"provider": "google", "type": "oauth2"},
}
}
mock_node.block = mock_block
mock_graph = mocker.MagicMock()
mock_graph.nodes = [mock_node]
# Mock the credentials store to return valid credentials for both
mock_store = mocker.MagicMock()
mock_regular_creds = mocker.MagicMock()
mock_regular_creds.id = "regular-cred-id"
mock_regular_creds.provider = "github"
mock_regular_creds.type = "api_key"
mock_auto_creds = mocker.MagicMock()
mock_auto_creds.id = "auto-cred-id"
def get_creds_side_effect(user_id, cred_id):
if cred_id == "regular-cred-id":
return mock_regular_creds
elif cred_id == "auto-cred-id":
return mock_auto_creds
return None
mock_store.get_creds_by_id = mocker.AsyncMock(side_effect=get_creds_side_effect)
mocker.patch(
"backend.executor.utils.get_integration_credentials_store",
return_value=mock_store,
)
errors, nodes_to_skip = await _validate_node_input_credentials(
graph=mock_graph,
user_id="test-user",
nodes_input_masks=None,
)
# Both should validate successfully - no errors
assert mock_node.id not in errors
assert mock_node.id not in nodes_to_skip
@pytest.mark.asyncio
async def test_validate_node_input_credentials_auto_creds_skipped_when_none(
mocker: MockerFixture,
):
"""
When a node has auto_credentials but the field value has _credentials_id=None
(e.g., from upstream connection), validation should skip it without error.
"""
from backend.executor.utils import _validate_node_input_credentials
mock_node = mocker.MagicMock()
mock_node.id = "node-with-chained-auto-creds"
mock_node.credentials_optional = False
mock_node.input_default = {
"spreadsheet": {
"_credentials_id": None,
"id": "file-123",
"name": "test.xlsx",
}
}
mock_block = mocker.MagicMock()
mock_block.input_schema.get_credentials_fields.return_value = {}
mock_block.input_schema.get_auto_credentials_fields.return_value = {
"credentials": {
"field_name": "spreadsheet",
"config": {"provider": "google", "type": "oauth2"},
}
}
mock_node.block = mock_block
mock_graph = mocker.MagicMock()
mock_graph.nodes = [mock_node]
errors, nodes_to_skip = await _validate_node_input_credentials(
graph=mock_graph,
user_id="test-user",
nodes_input_masks=None,
)
# No error - chained data with None cred_id is valid
assert mock_node.id not in errors
# ============================================================================
# Tests for CredentialsFieldInfo auto_credential tag (Fix 4: Path 4)
# ============================================================================
def test_credentials_field_info_auto_credential_tag():
"""
[Path 4] CredentialsFieldInfo should support is_auto_credential and
input_field_name fields for distinguishing auto from regular credentials.
"""
from backend.data.model import CredentialsFieldInfo
# Regular credential should have is_auto_credential=False by default
regular = CredentialsFieldInfo.model_validate(
{
"credentials_provider": ["github"],
"credentials_types": ["api_key"],
},
by_alias=True,
)
assert regular.is_auto_credential is False
assert regular.input_field_name is None
# Auto credential should have is_auto_credential=True
auto = CredentialsFieldInfo.model_validate(
{
"credentials_provider": ["google"],
"credentials_types": ["oauth2"],
"is_auto_credential": True,
"input_field_name": "spreadsheet",
},
by_alias=True,
)
assert auto.is_auto_credential is True
assert auto.input_field_name == "spreadsheet"
def test_make_node_credentials_input_map_excludes_auto_creds(
mocker: MockerFixture,
):
"""
[Path 4] make_node_credentials_input_map should only include regular credentials,
not auto_credentials (which are resolved at execution time).
"""
from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
from backend.executor.utils import make_node_credentials_input_map
from backend.integrations.providers import ProviderName
# Create a mock graph with aggregate_credentials_inputs that returns
# both regular and auto credentials
mock_graph = mocker.MagicMock()
regular_field_info = CredentialsFieldInfo.model_validate(
{
"credentials_provider": ["github"],
"credentials_types": ["api_key"],
"is_auto_credential": False,
},
by_alias=True,
)
# Mock regular_credentials_inputs property (auto_credentials are excluded)
mock_graph.regular_credentials_inputs = {
"github_creds": (regular_field_info, {("node-1", "credentials")}, True),
}
graph_credentials_input = {
"github_creds": CredentialsMetaInput(
id="cred-123",
provider=ProviderName("github"),
type="api_key",
),
}
result = make_node_credentials_input_map(mock_graph, graph_credentials_input)
# Regular credentials should be mapped
assert "node-1" in result
assert "credentials" in result["node-1"]
# Auto credentials should NOT appear in the result
# (they would have been mapped to the kwarg_name "credentials" not "spreadsheet")
for node_id, fields in result.items():
for field_name, value in fields.items():
# Verify no auto-credential phantom entries
if isinstance(value, dict):
assert "_credentials_id" not in value

View File

@@ -22,7 +22,6 @@ from backend.data.workspace import (
soft_delete_workspace_file,
)
from backend.util.settings import Config
from backend.util.virus_scanner import scan_content_safe
from backend.util.workspace_storage import compute_file_checksum, get_workspace_storage
logger = logging.getLogger(__name__)
@@ -188,9 +187,6 @@ class WorkspaceManager:
f"{Config().max_file_size_mb}MB limit"
)
# Virus scan content before persisting (defense in depth)
await scan_content_safe(content, filename=filename)
# Determine path with session scoping
if path is None:
path = f"/{filename}"

View File

@@ -3,6 +3,7 @@
"credentials_input_schema": {
"properties": {},
"required": [],
"title": "TestGraphCredentialsInputSchema",
"type": "object"
},
"description": "A test graph",

View File

@@ -1,14 +1,34 @@
[
{
"created_at": "2025-09-04T13:37:00",
"credentials_input_schema": {
"properties": {},
"required": [],
"title": "TestGraphCredentialsInputSchema",
"type": "object"
},
"description": "A test graph",
"forked_from_id": null,
"forked_from_version": null,
"has_external_trigger": false,
"has_human_in_the_loop": false,
"has_sensitive_action": false,
"id": "graph-123",
"input_schema": {
"properties": {},
"required": [],
"type": "object"
},
"instructions": null,
"is_active": true,
"name": "Test Graph",
"output_schema": {
"properties": {},
"required": [],
"type": "object"
},
"recommended_schedule_cron": null,
"sub_graphs": [],
"trigger_setup_info": null,
"user_id": "3e53486c-cf57-477e-ba2a-cb02dc828e1a",
"version": 1
}

View File

@@ -1,5 +1,5 @@
import { CredentialsMetaInput } from "@/app/api/__generated__/models/credentialsMetaInput";
import { GraphModel } from "@/app/api/__generated__/models/graphModel";
import { GraphMeta } from "@/app/api/__generated__/models/graphMeta";
import { CredentialsInput } from "@/components/contextual/CredentialsInput/CredentialsInput";
import { useState } from "react";
import { getSchemaDefaultCredentials } from "../../helpers";
@@ -9,7 +9,7 @@ type Credential = CredentialsMetaInput | undefined;
type Credentials = Record<string, Credential>;
type Props = {
agent: GraphModel | null;
agent: GraphMeta | null;
siblingInputs?: Record<string, any>;
onCredentialsChange: (
credentials: Record<string, CredentialsMetaInput>,

View File

@@ -1,9 +1,9 @@
import { CredentialsMetaInput } from "@/app/api/__generated__/models/credentialsMetaInput";
import { GraphModel } from "@/app/api/__generated__/models/graphModel";
import { GraphMeta } from "@/app/api/__generated__/models/graphMeta";
import { BlockIOCredentialsSubSchema } from "@/lib/autogpt-server-api/types";
export function getCredentialFields(
agent: GraphModel | null,
agent: GraphMeta | null,
): AgentCredentialsFields {
if (!agent) return {};

View File

@@ -3,10 +3,10 @@ import type {
CredentialsMetaInput,
} from "@/lib/autogpt-server-api/types";
import type { InputValues } from "./types";
import { GraphModel } from "@/app/api/__generated__/models/graphModel";
import { GraphMeta } from "@/app/api/__generated__/models/graphMeta";
export function computeInitialAgentInputs(
agent: GraphModel | null,
agent: GraphMeta | null,
existingInputs?: InputValues | null,
): InputValues {
const properties = agent?.input_schema?.properties || {};
@@ -29,7 +29,7 @@ export function computeInitialAgentInputs(
}
type IsRunDisabledParams = {
agent: GraphModel | null;
agent: GraphMeta | null;
isRunning: boolean;
agentInputs: InputValues | null | undefined;
};

View File

@@ -30,8 +30,6 @@ import {
} from "@/components/atoms/Tooltip/BaseTooltip";
import { GraphMeta } from "@/lib/autogpt-server-api";
import jaro from "jaro-winkler";
import { getV1GetSpecificGraph } from "@/app/api/__generated__/endpoints/graphs/graphs";
import { okData } from "@/app/api/helpers";
type _Block = Omit<Block, "inputSchema" | "outputSchema"> & {
uiKey?: string;
@@ -109,8 +107,6 @@ export function BlocksControl({
.filter((b) => b.uiType !== BlockUIType.AGENT)
.sort((a, b) => a.name.localeCompare(b.name));
// Agent blocks are created from GraphMeta which doesn't include schemas.
// Schemas will be fetched on-demand when the block is actually added.
const agentBlockList = flows
.map((flow): _Block => {
return {
@@ -120,9 +116,8 @@ export function BlocksControl({
`Ver.${flow.version}` +
(flow.description ? ` | ${flow.description}` : ""),
categories: [{ category: "AGENT", description: "" }],
// Empty schemas - will be populated when block is added
inputSchema: { type: "object", properties: {} },
outputSchema: { type: "object", properties: {} },
inputSchema: flow.input_schema,
outputSchema: flow.output_schema,
staticOutput: false,
uiType: BlockUIType.AGENT,
costs: [],
@@ -130,7 +125,8 @@ export function BlocksControl({
hardcodedValues: {
graph_id: flow.id,
graph_version: flow.version,
// Schemas will be fetched on-demand when block is added
input_schema: flow.input_schema,
output_schema: flow.output_schema,
},
};
})
@@ -186,37 +182,6 @@ export function BlocksControl({
setSelectedCategory(null);
}, []);
// Handler to add a block, fetching graph data on-demand for agent blocks
const handleAddBlock = useCallback(
async (block: _Block & { notAvailable: string | null }) => {
if (block.notAvailable) return;
// For agent blocks, fetch the full graph to get schemas
if (block.uiType === BlockUIType.AGENT && block.hardcodedValues) {
const graphID = block.hardcodedValues.graph_id as string;
const graphVersion = block.hardcodedValues.graph_version as number;
const graphData = okData(
await getV1GetSpecificGraph(graphID, { version: graphVersion }),
);
if (graphData) {
addBlock(block.id, block.name, {
...block.hardcodedValues,
input_schema: graphData.input_schema,
output_schema: graphData.output_schema,
});
} else {
// Fallback: add without schemas (will be incomplete)
console.error("Failed to fetch graph data for agent block");
addBlock(block.id, block.name, block.hardcodedValues || {});
}
} else {
addBlock(block.id, block.name, block.hardcodedValues || {});
}
},
[addBlock],
);
// Extract unique categories from blocks
const categories = useMemo(() => {
return Array.from(
@@ -338,7 +303,10 @@ export function BlocksControl({
}),
);
}}
onClick={() => handleAddBlock(block)}
onClick={() =>
!block.notAvailable &&
addBlock(block.id, block.name, block?.hardcodedValues || {})
}
title={block.notAvailable ?? undefined}
>
<div

View File

@@ -29,17 +29,13 @@ import "@xyflow/react/dist/style.css";
import { ConnectedEdge, CustomNode } from "../CustomNode/CustomNode";
import "./flow.css";
import {
BlockIORootSchema,
BlockUIType,
formatEdgeID,
GraphExecutionID,
GraphID,
GraphMeta,
LibraryAgent,
SpecialBlockID,
} from "@/lib/autogpt-server-api";
import { getV1GetSpecificGraph } from "@/app/api/__generated__/endpoints/graphs/graphs";
import { okData } from "@/app/api/helpers";
import { IncompatibilityInfo } from "../../../hooks/useSubAgentUpdate/types";
import { Key, storage } from "@/services/storage/local-storage";
import { findNewlyAddedBlockCoordinates, getTypeColor } from "@/lib/utils";
@@ -691,94 +687,8 @@ const FlowEditor: React.FC<{
[getNode, updateNode, nodes],
);
/* Shared helper to create and add a node */
const createAndAddNode = useCallback(
async (
blockID: string,
blockName: string,
hardcodedValues: Record<string, any>,
position: { x: number; y: number },
): Promise<CustomNode | null> => {
const nodeSchema = availableBlocks.find((node) => node.id === blockID);
if (!nodeSchema) {
console.error(`Schema not found for block ID: ${blockID}`);
return null;
}
// For agent blocks, fetch the full graph to get schemas
let inputSchema: BlockIORootSchema = nodeSchema.inputSchema;
let outputSchema: BlockIORootSchema = nodeSchema.outputSchema;
let finalHardcodedValues = hardcodedValues;
if (blockID === SpecialBlockID.AGENT) {
const graphID = hardcodedValues.graph_id as string;
const graphVersion = hardcodedValues.graph_version as number;
const graphData = okData(
await getV1GetSpecificGraph(graphID, { version: graphVersion }),
);
if (graphData) {
inputSchema = graphData.input_schema as BlockIORootSchema;
outputSchema = graphData.output_schema as BlockIORootSchema;
finalHardcodedValues = {
...hardcodedValues,
input_schema: graphData.input_schema,
output_schema: graphData.output_schema,
};
} else {
console.error("Failed to fetch graph data for agent block");
}
}
const newNode: CustomNode = {
id: nodeId.toString(),
type: "custom",
position,
data: {
blockType: blockName,
blockCosts: nodeSchema.costs || [],
title: `${blockName} ${nodeId}`,
description: nodeSchema.description,
categories: nodeSchema.categories,
inputSchema: inputSchema,
outputSchema: outputSchema,
hardcodedValues: finalHardcodedValues,
connections: [],
isOutputOpen: false,
block_id: blockID,
isOutputStatic: nodeSchema.staticOutput,
uiType: nodeSchema.uiType,
},
};
addNodes(newNode);
setNodeId((prevId) => prevId + 1);
clearNodesStatusAndOutput();
history.push({
type: "ADD_NODE",
payload: { node: { ...newNode, ...newNode.data } },
undo: () => deleteElements({ nodes: [{ id: newNode.id }] }),
redo: () => addNodes(newNode),
});
return newNode;
},
[
availableBlocks,
nodeId,
addNodes,
deleteElements,
clearNodesStatusAndOutput,
],
);
const addNode = useCallback(
async (
blockId: string,
nodeType: string,
hardcodedValues: Record<string, any> = {},
) => {
(blockId: string, nodeType: string, hardcodedValues: any = {}) => {
const nodeSchema = availableBlocks.find((node) => node.id === blockId);
if (!nodeSchema) {
console.error(`Schema not found for block ID: ${blockId}`);
@@ -797,42 +707,73 @@ const FlowEditor: React.FC<{
// Alternative: We could also use D3 force, Intersection for this (React flow Pro examples)
const { x, y } = getViewport();
const position =
const viewportCoordinates =
nodeDimensions && Object.keys(nodeDimensions).length > 0
? findNewlyAddedBlockCoordinates(
? // we will get all the dimension of nodes, then store
findNewlyAddedBlockCoordinates(
nodeDimensions,
nodeSchema.uiType == BlockUIType.NOTE ? 300 : 500,
60,
1.0,
)
: {
: // we will get all the dimension of nodes, then store
{
x: window.innerWidth / 2 - x,
y: window.innerHeight / 2 - y,
};
const newNode = await createAndAddNode(
blockId,
nodeType,
hardcodedValues,
position,
);
if (!newNode) return;
const newNode: CustomNode = {
id: nodeId.toString(),
type: "custom",
position: viewportCoordinates, // Set the position to the calculated viewport center
data: {
blockType: nodeType,
blockCosts: nodeSchema.costs,
title: `${nodeType} ${nodeId}`,
description: nodeSchema.description,
categories: nodeSchema.categories,
inputSchema: nodeSchema.inputSchema,
outputSchema: nodeSchema.outputSchema,
hardcodedValues: hardcodedValues,
connections: [],
isOutputOpen: false,
block_id: blockId,
isOutputStatic: nodeSchema.staticOutput,
uiType: nodeSchema.uiType,
},
};
addNodes(newNode);
setNodeId((prevId) => prevId + 1);
clearNodesStatusAndOutput(); // Clear status and output when a new node is added
setViewport(
{
x: -position.x * 0.8 + (window.innerWidth - 0.0) / 2,
y: -position.y * 0.8 + (window.innerHeight - 400) / 2,
// Rough estimate of the dimension of the node is: 500x400px.
// Though we skip shifting the X, considering the block menu side-bar.
x: -viewportCoordinates.x * 0.8 + (window.innerWidth - 0.0) / 2,
y: -viewportCoordinates.y * 0.8 + (window.innerHeight - 400) / 2,
zoom: 0.8,
},
{ duration: 500 },
);
history.push({
type: "ADD_NODE",
payload: { node: { ...newNode, ...newNode.data } },
undo: () => deleteElements({ nodes: [{ id: newNode.id }] }),
redo: () => addNodes(newNode),
});
},
[
nodeId,
getViewport,
setViewport,
availableBlocks,
addNodes,
nodeDimensions,
createAndAddNode,
deleteElements,
clearNodesStatusAndOutput,
],
);
@@ -979,7 +920,7 @@ const FlowEditor: React.FC<{
}, []);
const onDrop = useCallback(
async (event: React.DragEvent) => {
(event: React.DragEvent) => {
event.preventDefault();
const blockData = event.dataTransfer.getData("application/reactflow");
@@ -994,17 +935,62 @@ const FlowEditor: React.FC<{
y: event.clientY,
});
await createAndAddNode(
blockId,
blockName,
hardcodedValues || {},
// Find the block schema
const nodeSchema = availableBlocks.find((node) => node.id === blockId);
if (!nodeSchema) {
console.error(`Schema not found for block ID: ${blockId}`);
return;
}
// Create the new node at the drop position
const newNode: CustomNode = {
id: nodeId.toString(),
type: "custom",
position,
);
data: {
blockType: blockName,
blockCosts: nodeSchema.costs || [],
title: `${blockName} ${nodeId}`,
description: nodeSchema.description,
categories: nodeSchema.categories,
inputSchema: nodeSchema.inputSchema,
outputSchema: nodeSchema.outputSchema,
hardcodedValues: hardcodedValues,
connections: [],
isOutputOpen: false,
block_id: blockId,
uiType: nodeSchema.uiType,
},
};
history.push({
type: "ADD_NODE",
payload: { node: { ...newNode, ...newNode.data } },
undo: () => {
deleteElements({ nodes: [{ id: newNode.id } as any], edges: [] });
},
redo: () => {
addNodes([newNode]);
},
});
addNodes([newNode]);
clearNodesStatusAndOutput();
setNodeId((prevId) => prevId + 1);
} catch (error) {
console.error("Failed to drop block:", error);
}
},
[screenToFlowPosition, createAndAddNode],
[
nodeId,
availableBlocks,
nodes,
edges,
addNodes,
screenToFlowPosition,
deleteElements,
clearNodesStatusAndOutput,
],
);
const buildContextValue: BuilderContextType = useMemo(

View File

@@ -4,13 +4,13 @@ import { AgentRunDraftView } from "@/app/(platform)/library/agents/[id]/componen
import { Dialog } from "@/components/molecules/Dialog/Dialog";
import type {
CredentialsMetaInput,
Graph,
GraphMeta,
} from "@/lib/autogpt-server-api/types";
interface RunInputDialogProps {
isOpen: boolean;
doClose: () => void;
graph: Graph;
graph: GraphMeta;
doRun?: (
inputs: Record<string, any>,
credentialsInputs: Record<string, CredentialsMetaInput>,

View File

@@ -9,13 +9,13 @@ import { CustomNodeData } from "@/app/(platform)/build/components/legacy-builder
import {
BlockUIType,
CredentialsMetaInput,
Graph,
GraphMeta,
} from "@/lib/autogpt-server-api/types";
import RunnerOutputUI, { OutputNodeInfo } from "./RunnerOutputUI";
import { RunnerInputDialog } from "./RunnerInputUI";
interface RunnerUIWrapperProps {
graph: Graph;
graph: GraphMeta;
nodes: Node<CustomNodeData>[];
graphExecutionError?: string | null;
saveAndRun: (

View File

@@ -1,5 +1,5 @@
import { GraphInputSchema } from "@/lib/autogpt-server-api";
import { GraphLike, IncompatibilityInfo } from "./types";
import { GraphMetaLike, IncompatibilityInfo } from "./types";
// Helper type for schema properties - the generated types are too loose
type SchemaProperties = Record<string, GraphInputSchema["properties"][string]>;
@@ -36,7 +36,7 @@ export function getSchemaRequired(schema: unknown): SchemaRequired {
*/
export function createUpdatedAgentNodeInputs(
currentInputs: Record<string, unknown>,
latestSubGraphVersion: GraphLike,
latestSubGraphVersion: GraphMetaLike,
): Record<string, unknown> {
return {
...currentInputs,

View File

@@ -1,11 +1,7 @@
import type {
Graph as LegacyGraph,
GraphMeta as LegacyGraphMeta,
} from "@/lib/autogpt-server-api";
import type { GraphModel as GeneratedGraph } from "@/app/api/__generated__/models/graphModel";
import type { GraphMeta as LegacyGraphMeta } from "@/lib/autogpt-server-api";
import type { GraphMeta as GeneratedGraphMeta } from "@/app/api/__generated__/models/graphMeta";
export type SubAgentUpdateInfo<T extends GraphLike = GraphLike> = {
export type SubAgentUpdateInfo<T extends GraphMetaLike = GraphMetaLike> = {
hasUpdate: boolean;
currentVersion: number;
latestVersion: number;
@@ -14,10 +10,7 @@ export type SubAgentUpdateInfo<T extends GraphLike = GraphLike> = {
incompatibilities: IncompatibilityInfo | null;
};
// Union type for Graph (with schemas) that works with both legacy and new builder
export type GraphLike = LegacyGraph | GeneratedGraph;
// Union type for GraphMeta (without schemas) for version detection
// Union type for GraphMeta that works with both legacy and new builder
export type GraphMetaLike = LegacyGraphMeta | GeneratedGraphMeta;
export type IncompatibilityInfo = {

View File

@@ -1,11 +1,5 @@
import { useMemo } from "react";
import type {
GraphInputSchema,
GraphOutputSchema,
} from "@/lib/autogpt-server-api";
import type { GraphModel } from "@/app/api/__generated__/models/graphModel";
import { useGetV1GetSpecificGraph } from "@/app/api/__generated__/endpoints/graphs/graphs";
import { okData } from "@/app/api/helpers";
import { GraphInputSchema, GraphOutputSchema } from "@/lib/autogpt-server-api";
import { getEffectiveType } from "@/lib/utils";
import { EdgeLike, getSchemaProperties, getSchemaRequired } from "./helpers";
import {
@@ -17,38 +11,26 @@ import {
/**
* Checks if a newer version of a sub-agent is available and determines compatibility
*/
export function useSubAgentUpdate(
export function useSubAgentUpdate<T extends GraphMetaLike>(
nodeID: string,
graphID: string | undefined,
graphVersion: number | undefined,
currentInputSchema: GraphInputSchema | undefined,
currentOutputSchema: GraphOutputSchema | undefined,
connections: EdgeLike[],
availableGraphs: GraphMetaLike[],
): SubAgentUpdateInfo<GraphModel> {
availableGraphs: T[],
): SubAgentUpdateInfo<T> {
// Find the latest version of the same graph
const latestGraphInfo = useMemo(() => {
const latestGraph = useMemo(() => {
if (!graphID) return null;
return availableGraphs.find((graph) => graph.id === graphID) || null;
}, [graphID, availableGraphs]);
// Check if there's a newer version available
// Check if there's an update available
const hasUpdate = useMemo(() => {
if (!latestGraphInfo || graphVersion === undefined) return false;
return latestGraphInfo.version! > graphVersion;
}, [latestGraphInfo, graphVersion]);
// Fetch full graph IF an update is detected
const { data: latestGraph } = useGetV1GetSpecificGraph(
graphID ?? "",
{ version: latestGraphInfo?.version },
{
query: {
enabled: hasUpdate && !!graphID && !!latestGraphInfo?.version,
select: okData,
},
},
);
if (!latestGraph || graphVersion === undefined) return false;
return latestGraph.version! > graphVersion;
}, [latestGraph, graphVersion]);
// Get connected input and output handles for this specific node
const connectedHandles = useMemo(() => {
@@ -170,8 +152,8 @@ export function useSubAgentUpdate(
return {
hasUpdate,
currentVersion: graphVersion || 0,
latestVersion: latestGraphInfo?.version || 0,
latestGraph: latestGraph || null,
latestVersion: latestGraph?.version || 0,
latestGraph,
isCompatible: compatibilityResult.isCompatible,
incompatibilities: compatibilityResult.incompatibilities,
};

View File

@@ -18,7 +18,7 @@ interface GraphStore {
outputSchema: Record<string, any> | null,
) => void;
// Available graphs; used for sub-graph updated version detection
// Available graphs; used for sub-graph updates
availableSubGraphs: GraphMeta[];
setAvailableSubGraphs: (graphs: GraphMeta[]) => void;

View File

@@ -10,8 +10,8 @@ import React, {
import {
CredentialsMetaInput,
CredentialsType,
Graph,
GraphExecutionID,
GraphMeta,
LibraryAgentPreset,
LibraryAgentPresetID,
LibraryAgentPresetUpdatable,
@@ -69,7 +69,7 @@ export function AgentRunDraftView({
className,
recommendedScheduleCron,
}: {
graph: Graph;
graph: GraphMeta;
agentActions?: ButtonAction[];
recommendedScheduleCron?: string | null;
doRun?: (

View File

@@ -2,8 +2,8 @@
import React, { useCallback, useMemo } from "react";
import {
Graph,
GraphExecutionID,
GraphMeta,
Schedule,
ScheduleID,
} from "@/lib/autogpt-server-api";
@@ -35,7 +35,7 @@ export function AgentScheduleDetailsView({
onForcedRun,
doDeleteSchedule,
}: {
graph: Graph;
graph: GraphMeta;
schedule: Schedule;
agentActions: ButtonAction[];
onForcedRun: (runID: GraphExecutionID) => void;

View File

@@ -5629,9 +5629,7 @@
"description": "Successful Response",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/GraphModelWithoutNodes"
}
"schema": { "$ref": "#/components/schemas/GraphMeta" }
}
}
},
@@ -6497,6 +6495,18 @@
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Recommended Schedule Cron"
},
"nodes": {
"items": { "$ref": "#/components/schemas/Node" },
"type": "array",
"title": "Nodes",
"default": []
},
"links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Links",
"default": []
},
"forked_from_id": {
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Forked From Id"
@@ -6504,22 +6514,11 @@
"forked_from_version": {
"anyOf": [{ "type": "integer" }, { "type": "null" }],
"title": "Forked From Version"
},
"nodes": {
"items": { "$ref": "#/components/schemas/Node" },
"type": "array",
"title": "Nodes"
},
"links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Links"
}
},
"type": "object",
"required": ["name", "description"],
"title": "BaseGraph",
"description": "Graph with nodes, links, and computed I/O schema fields.\n\nUsed to represent sub-graphs within a `Graph`. Contains the full graph\nstructure including nodes and links, plus computed fields for schemas\nand trigger info. Does NOT include user_id or created_at (see GraphModel)."
"title": "BaseGraph"
},
"BaseGraph-Output": {
"properties": {
@@ -6540,6 +6539,18 @@
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Recommended Schedule Cron"
},
"nodes": {
"items": { "$ref": "#/components/schemas/Node" },
"type": "array",
"title": "Nodes",
"default": []
},
"links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Links",
"default": []
},
"forked_from_id": {
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Forked From Id"
@@ -6548,16 +6559,6 @@
"anyOf": [{ "type": "integer" }, { "type": "null" }],
"title": "Forked From Version"
},
"nodes": {
"items": { "$ref": "#/components/schemas/Node" },
"type": "array",
"title": "Nodes"
},
"links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Links"
},
"input_schema": {
"additionalProperties": true,
"type": "object",
@@ -6604,8 +6605,7 @@
"has_sensitive_action",
"trigger_setup_info"
],
"title": "BaseGraph",
"description": "Graph with nodes, links, and computed I/O schema fields.\n\nUsed to represent sub-graphs within a `Graph`. Contains the full graph\nstructure including nodes and links, plus computed fields for schemas\nand trigger info. Does NOT include user_id or created_at (see GraphModel)."
"title": "BaseGraph"
},
"BlockCategoryResponse": {
"properties": {
@@ -7399,6 +7399,18 @@
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Recommended Schedule Cron"
},
"nodes": {
"items": { "$ref": "#/components/schemas/Node" },
"type": "array",
"title": "Nodes",
"default": []
},
"links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Links",
"default": []
},
"forked_from_id": {
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Forked From Id"
@@ -7407,26 +7419,16 @@
"anyOf": [{ "type": "integer" }, { "type": "null" }],
"title": "Forked From Version"
},
"nodes": {
"items": { "$ref": "#/components/schemas/Node" },
"type": "array",
"title": "Nodes"
},
"links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Links"
},
"sub_graphs": {
"items": { "$ref": "#/components/schemas/BaseGraph-Input" },
"type": "array",
"title": "Sub Graphs"
"title": "Sub Graphs",
"default": []
}
},
"type": "object",
"required": ["name", "description"],
"title": "Graph",
"description": "Creatable graph model used in API create/update endpoints."
"title": "Graph"
},
"GraphExecution": {
"properties": {
@@ -7778,7 +7780,7 @@
"GraphMeta": {
"properties": {
"id": { "type": "string", "title": "Id" },
"version": { "type": "integer", "title": "Version" },
"version": { "type": "integer", "title": "Version", "default": 1 },
"is_active": {
"type": "boolean",
"title": "Is Active",
@@ -7802,24 +7804,68 @@
"anyOf": [{ "type": "integer" }, { "type": "null" }],
"title": "Forked From Version"
},
"sub_graphs": {
"items": { "$ref": "#/components/schemas/BaseGraph-Output" },
"type": "array",
"title": "Sub Graphs",
"default": []
},
"user_id": { "type": "string", "title": "User Id" },
"created_at": {
"type": "string",
"format": "date-time",
"title": "Created At"
"input_schema": {
"additionalProperties": true,
"type": "object",
"title": "Input Schema",
"readOnly": true
},
"output_schema": {
"additionalProperties": true,
"type": "object",
"title": "Output Schema",
"readOnly": true
},
"has_external_trigger": {
"type": "boolean",
"title": "Has External Trigger",
"readOnly": true
},
"has_human_in_the_loop": {
"type": "boolean",
"title": "Has Human In The Loop",
"readOnly": true
},
"has_sensitive_action": {
"type": "boolean",
"title": "Has Sensitive Action",
"readOnly": true
},
"trigger_setup_info": {
"anyOf": [
{ "$ref": "#/components/schemas/GraphTriggerInfo" },
{ "type": "null" }
],
"readOnly": true
},
"credentials_input_schema": {
"additionalProperties": true,
"type": "object",
"title": "Credentials Input Schema",
"readOnly": true
}
},
"type": "object",
"required": [
"id",
"version",
"name",
"description",
"user_id",
"created_at"
"input_schema",
"output_schema",
"has_external_trigger",
"has_human_in_the_loop",
"has_sensitive_action",
"trigger_setup_info",
"credentials_input_schema"
],
"title": "GraphMeta",
"description": "Lightweight graph metadata model representing an existing graph from the database,\nfor use in listings and summaries.\n\nLacks `GraphModel`'s nodes, links, and expensive computed fields.\nUse for list endpoints where full graph data is not needed and performance matters."
"title": "GraphMeta"
},
"GraphModel": {
"properties": {
@@ -7840,111 +7886,17 @@
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Recommended Schedule Cron"
},
"forked_from_id": {
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Forked From Id"
},
"forked_from_version": {
"anyOf": [{ "type": "integer" }, { "type": "null" }],
"title": "Forked From Version"
},
"user_id": { "type": "string", "title": "User Id" },
"created_at": {
"type": "string",
"format": "date-time",
"title": "Created At"
},
"nodes": {
"items": { "$ref": "#/components/schemas/NodeModel" },
"type": "array",
"title": "Nodes"
"title": "Nodes",
"default": []
},
"links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Links"
},
"sub_graphs": {
"items": { "$ref": "#/components/schemas/BaseGraph-Output" },
"type": "array",
"title": "Sub Graphs"
},
"input_schema": {
"additionalProperties": true,
"type": "object",
"title": "Input Schema",
"readOnly": true
},
"output_schema": {
"additionalProperties": true,
"type": "object",
"title": "Output Schema",
"readOnly": true
},
"has_external_trigger": {
"type": "boolean",
"title": "Has External Trigger",
"readOnly": true
},
"has_human_in_the_loop": {
"type": "boolean",
"title": "Has Human In The Loop",
"readOnly": true
},
"has_sensitive_action": {
"type": "boolean",
"title": "Has Sensitive Action",
"readOnly": true
},
"trigger_setup_info": {
"anyOf": [
{ "$ref": "#/components/schemas/GraphTriggerInfo" },
{ "type": "null" }
],
"readOnly": true
},
"credentials_input_schema": {
"additionalProperties": true,
"type": "object",
"title": "Credentials Input Schema",
"readOnly": true
}
},
"type": "object",
"required": [
"name",
"description",
"user_id",
"created_at",
"input_schema",
"output_schema",
"has_external_trigger",
"has_human_in_the_loop",
"has_sensitive_action",
"trigger_setup_info",
"credentials_input_schema"
],
"title": "GraphModel",
"description": "Full graph model representing an existing graph from the database.\n\nThis is the primary model for working with persisted graphs. Includes all\ngraph data (nodes, links, sub_graphs) plus user ownership and timestamps.\nProvides computed fields (input_schema, output_schema, etc.) used during\nset-up (frontend) and execution (backend).\n\nInherits from:\n- `Graph`: provides structure (nodes, links, sub_graphs) and computed schemas\n- `GraphMeta`: provides user_id, created_at for database records"
},
"GraphModelWithoutNodes": {
"properties": {
"id": { "type": "string", "title": "Id" },
"version": { "type": "integer", "title": "Version", "default": 1 },
"is_active": {
"type": "boolean",
"title": "Is Active",
"default": true
},
"name": { "type": "string", "title": "Name" },
"description": { "type": "string", "title": "Description" },
"instructions": {
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Instructions"
},
"recommended_schedule_cron": {
"anyOf": [{ "type": "string" }, { "type": "null" }],
"title": "Recommended Schedule Cron"
"title": "Links",
"default": []
},
"forked_from_id": {
"anyOf": [{ "type": "string" }, { "type": "null" }],
@@ -7954,6 +7906,12 @@
"anyOf": [{ "type": "integer" }, { "type": "null" }],
"title": "Forked From Version"
},
"sub_graphs": {
"items": { "$ref": "#/components/schemas/BaseGraph-Output" },
"type": "array",
"title": "Sub Graphs",
"default": []
},
"user_id": { "type": "string", "title": "User Id" },
"created_at": {
"type": "string",
@@ -8015,8 +7973,7 @@
"trigger_setup_info",
"credentials_input_schema"
],
"title": "GraphModelWithoutNodes",
"description": "GraphModel variant that excludes nodes, links, and sub-graphs from serialization.\n\nUsed in contexts like the store where exposing internal graph structure\nis not desired. Inherits all computed fields from GraphModel but marks\nnodes and links as excluded from JSON output."
"title": "GraphModel"
},
"GraphSettings": {
"properties": {
@@ -8656,22 +8613,26 @@
"input_default": {
"additionalProperties": true,
"type": "object",
"title": "Input Default"
"title": "Input Default",
"default": {}
},
"metadata": {
"additionalProperties": true,
"type": "object",
"title": "Metadata"
"title": "Metadata",
"default": {}
},
"input_links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Input Links"
"title": "Input Links",
"default": []
},
"output_links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Output Links"
"title": "Output Links",
"default": []
}
},
"type": "object",
@@ -8751,22 +8712,26 @@
"input_default": {
"additionalProperties": true,
"type": "object",
"title": "Input Default"
"title": "Input Default",
"default": {}
},
"metadata": {
"additionalProperties": true,
"type": "object",
"title": "Metadata"
"title": "Metadata",
"default": {}
},
"input_links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Input Links"
"title": "Input Links",
"default": []
},
"output_links": {
"items": { "$ref": "#/components/schemas/Link" },
"type": "array",
"title": "Output Links"
"title": "Output Links",
"default": []
},
"graph_id": { "type": "string", "title": "Graph Id" },
"graph_version": { "type": "integer", "title": "Graph Version" },

View File

@@ -102,6 +102,18 @@ export function ChatMessage({
}
}
function handleClarificationAnswers(answers: Record<string, string>) {
if (onSendMessage) {
const contextMessage = Object.entries(answers)
.map(([keyword, answer]) => `${keyword}: ${answer}`)
.join("\n");
onSendMessage(
`I have the answers to your questions:\n\n${contextMessage}\n\nPlease proceed with creating the agent.`,
);
}
}
const handleCopy = useCallback(
async function handleCopy() {
if (message.type !== "message") return;
@@ -150,22 +162,6 @@ export function ChatMessage({
.slice(index + 1)
.some((m) => m.type === "message" && m.role === "user");
const handleClarificationAnswers = (answers: Record<string, string>) => {
if (onSendMessage) {
// Iterate over questions (preserves original order) instead of answers
const contextMessage = message.questions
.map((q) => {
const answer = answers[q.keyword] || "";
return `> ${q.question}\n\n${answer}`;
})
.join("\n\n");
onSendMessage(
`**Here are my answers:**\n\n${contextMessage}\n\nPlease proceed with creating the agent.`,
);
}
};
return (
<ClarificationQuestionsWidget
questions={message.questions}

View File

@@ -19,13 +19,13 @@ export function ThinkingMessage({ className }: ThinkingMessageProps) {
if (timerRef.current === null) {
timerRef.current = setTimeout(() => {
setShowSlowLoader(true);
}, 8000);
}, 3000);
}
if (coffeeTimerRef.current === null) {
coffeeTimerRef.current = setTimeout(() => {
setShowCoffeeMessage(true);
}, 10000);
}, 8000);
}
return () => {

View File

@@ -4,9 +4,7 @@ import { loadScript } from "@/services/scripts/scripts";
export async function loadGoogleAPIPicker(): Promise<void> {
validateWindow();
await loadScript("https://apis.google.com/js/api.js", {
referrerPolicy: "no-referrer-when-downgrade",
});
await loadScript("https://apis.google.com/js/api.js");
const googleAPI = window.gapi;
if (!googleAPI) {
@@ -29,9 +27,7 @@ export async function loadGoogleIdentityServices(): Promise<void> {
throw new Error("Google Identity Services cannot load on server");
}
await loadScript("https://accounts.google.com/gsi/client", {
referrerPolicy: "no-referrer-when-downgrade",
});
await loadScript("https://accounts.google.com/gsi/client");
const google = window.google;
if (!google?.accounts?.oauth2) {

View File

@@ -362,14 +362,25 @@ export type GraphMeta = {
user_id: UserID;
version: number;
is_active: boolean;
created_at: Date;
name: string;
description: string;
instructions?: string | null;
recommended_schedule_cron: string | null;
forked_from_id?: GraphID | null;
forked_from_version?: number | null;
};
input_schema: GraphInputSchema;
output_schema: GraphOutputSchema;
credentials_input_schema: CredentialsInputSchema;
} & (
| {
has_external_trigger: true;
trigger_setup_info: GraphTriggerInfo;
}
| {
has_external_trigger: false;
trigger_setup_info: null;
}
);
export type GraphID = Brand<string, "GraphID">;
@@ -436,22 +447,11 @@ export type GraphTriggerInfo = {
/* Mirror of backend/data/graph.py:Graph */
export type Graph = GraphMeta & {
created_at: Date;
nodes: Node[];
links: Link[];
sub_graphs: Omit<Graph, "sub_graphs">[]; // Flattened sub-graphs
input_schema: GraphInputSchema;
output_schema: GraphOutputSchema;
credentials_input_schema: CredentialsInputSchema;
} & (
| {
has_external_trigger: true;
trigger_setup_info: GraphTriggerInfo;
}
| {
has_external_trigger: false;
trigger_setup_info: null;
}
);
};
export type GraphUpdateable = Omit<
Graph,