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Merge branch 'dev' into hackathon/copilot

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This commit is contained in:
Zamil Majdy
2026-01-07 03:34:01 +07:00
committed by GitHub
parent 7ee03fb0ec 818de26d24
commit fb87d6536f
18 changed files with 3152 additions and 55 deletions
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4
autogpt_platform/backend/backend/api/rest_api.py
View File

@@ -39,7 +39,7 @@ import backend.data.user
import backend.integrations.webhooks.utils
import backend.util.service
import backend.util.settings
from backend.blocks.llm import LlmModel
from backend.blocks.llm import DEFAULT_LLM_MODEL
from backend.data.model import Credentials
from backend.integrations.providers import ProviderName
from backend.monitoring.instrumentation import instrument_fastapi
@@ -113,7 +113,7 @@ async def lifespan_context(app: fastapi.FastAPI):
await backend.data.user.migrate_and_encrypt_user_integrations()
await backend.data.graph.fix_llm_provider_credentials()
await backend.data.graph.migrate_llm_models(LlmModel.GPT4O)
await backend.data.graph.migrate_llm_models(DEFAULT_LLM_MODEL)
await backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs()
with launch_darkly_context():

5
autogpt_platform/backend/backend/blocks/ai_condition.py
View File

@@ -1,6 +1,7 @@
from typing import Any
from backend.blocks.llm import (
DEFAULT_LLM_MODEL,
TEST_CREDENTIALS,
TEST_CREDENTIALS_INPUT,
AIBlockBase,
@@ -49,7 +50,7 @@ class AIConditionBlock(AIBlockBase):
)
model: LlmModel = SchemaField(
title="LLM Model",
default=LlmModel.GPT4O,
default=DEFAULT_LLM_MODEL,
description="The language model to use for evaluating the condition.",
advanced=False,
)
@@ -81,7 +82,7 @@ class AIConditionBlock(AIBlockBase):
"condition": "the input is an email address",
"yes_value": "Valid email",
"no_value": "Not an email",
"model": LlmModel.GPT4O,
"model": DEFAULT_LLM_MODEL,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_credentials=TEST_CREDENTIALS,

2896
autogpt_platform/backend/backend/blocks/google/docs.py Normal file
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24
autogpt_platform/backend/backend/blocks/llm.py
View File

@@ -92,8 +92,9 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
O1 = "o1"
O1_MINI = "o1-mini"
# GPT-5 models
GPT5 = "gpt-5-2025-08-07"
GPT5_2 = "gpt-5.2-2025-12-11"
GPT5_1 = "gpt-5.1-2025-11-13"
GPT5 = "gpt-5-2025-08-07"
GPT5_MINI = "gpt-5-mini-2025-08-07"
GPT5_NANO = "gpt-5-nano-2025-08-07"
GPT5_CHAT = "gpt-5-chat-latest"
@@ -194,8 +195,9 @@ MODEL_METADATA = {
LlmModel.O1: ModelMetadata("openai", 200000, 100000), # o1-2024-12-17
LlmModel.O1_MINI: ModelMetadata("openai", 128000, 65536), # o1-mini-2024-09-12
# GPT-5 models
LlmModel.GPT5: ModelMetadata("openai", 400000, 128000),
LlmModel.GPT5_2: ModelMetadata("openai", 400000, 128000),
LlmModel.GPT5_1: ModelMetadata("openai", 400000, 128000),
LlmModel.GPT5: ModelMetadata("openai", 400000, 128000),
LlmModel.GPT5_MINI: ModelMetadata("openai", 400000, 128000),
LlmModel.GPT5_NANO: ModelMetadata("openai", 400000, 128000),
LlmModel.GPT5_CHAT: ModelMetadata("openai", 400000, 16384),
@@ -303,6 +305,8 @@ MODEL_METADATA = {
LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000),
}
DEFAULT_LLM_MODEL = LlmModel.GPT5_2
for model in LlmModel:
if model not in MODEL_METADATA:
raise ValueError(f"Missing MODEL_METADATA metadata for model: {model}")
@@ -790,7 +794,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
)
model: LlmModel = SchemaField(
title="LLM Model",
default=LlmModel.GPT4O,
default=DEFAULT_LLM_MODEL,
description="The language model to use for answering the prompt.",
advanced=False,
)
@@ -855,7 +859,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
input_schema=AIStructuredResponseGeneratorBlock.Input,
output_schema=AIStructuredResponseGeneratorBlock.Output,
test_input={
"model": LlmModel.GPT4O,
"model": DEFAULT_LLM_MODEL,
"credentials": TEST_CREDENTIALS_INPUT,
"expected_format": {
"key1": "value1",
@@ -1221,7 +1225,7 @@ class AITextGeneratorBlock(AIBlockBase):
)
model: LlmModel = SchemaField(
title="LLM Model",
default=LlmModel.GPT4O,
default=DEFAULT_LLM_MODEL,
description="The language model to use for answering the prompt.",
advanced=False,
)
@@ -1317,7 +1321,7 @@ class AITextSummarizerBlock(AIBlockBase):
)
model: LlmModel = SchemaField(
title="LLM Model",
default=LlmModel.GPT4O,
default=DEFAULT_LLM_MODEL,
description="The language model to use for summarizing the text.",
)
focus: str = SchemaField(
@@ -1534,7 +1538,7 @@ class AIConversationBlock(AIBlockBase):
)
model: LlmModel = SchemaField(
title="LLM Model",
default=LlmModel.GPT4O,
default=DEFAULT_LLM_MODEL,
description="The language model to use for the conversation.",
)
credentials: AICredentials = AICredentialsField()
@@ -1572,7 +1576,7 @@ class AIConversationBlock(AIBlockBase):
},
{"role": "user", "content": "Where was it played?"},
],
"model": LlmModel.GPT4O,
"model": DEFAULT_LLM_MODEL,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_credentials=TEST_CREDENTIALS,
@@ -1635,7 +1639,7 @@ class AIListGeneratorBlock(AIBlockBase):
)
model: LlmModel = SchemaField(
title="LLM Model",
default=LlmModel.GPT4O,
default=DEFAULT_LLM_MODEL,
description="The language model to use for generating the list.",
advanced=True,
)
@@ -1692,7 +1696,7 @@ class AIListGeneratorBlock(AIBlockBase):
"drawing explorers to uncover its mysteries. Each planet showcases the limitless possibilities of "
"fictional worlds."
),
"model": LlmModel.GPT4O,
"model": DEFAULT_LLM_MODEL,
"credentials": TEST_CREDENTIALS_INPUT,
"max_retries": 3,
"force_json_output": False,

2
autogpt_platform/backend/backend/blocks/smart_decision_maker.py
View File

@@ -226,7 +226,7 @@ class SmartDecisionMakerBlock(Block):
)
model: llm.LlmModel = SchemaField(
title="LLM Model",
default=llm.LlmModel.GPT4O,
default=llm.DEFAULT_LLM_MODEL,
description="The language model to use for answering the prompt.",
advanced=False,
)

9
autogpt_platform/backend/backend/blocks/test/test_blocks_dos_vulnerability.py
View File

@@ -196,6 +196,15 @@ class TestXMLParserBlockSecurity:
async for _ in block.run(XMLParserBlock.Input(input_xml=large_xml)):
pass
async def test_rejects_text_outside_root(self):
"""Ensure parser surfaces readable errors for invalid root text."""
block = XMLParserBlock()
invalid_xml = "<root><child>value</child></root> trailing"
with pytest.raises(ValueError, match="text outside the root element"):
async for _ in block.run(XMLParserBlock.Input(input_xml=invalid_xml)):
pass
class TestStoreMediaFileSecurity:
"""Test file storage security limits."""

28
autogpt_platform/backend/backend/blocks/test/test_llm.py
View File

@@ -28,7 +28,7 @@ class TestLLMStatsTracking:
response = await llm.llm_call(
credentials=llm.TEST_CREDENTIALS,
llm_model=llm.LlmModel.GPT4O,
llm_model=llm.DEFAULT_LLM_MODEL,
prompt=[{"role": "user", "content": "Hello"}],
max_tokens=100,
)
@@ -65,7 +65,7 @@ class TestLLMStatsTracking:
input_data = llm.AIStructuredResponseGeneratorBlock.Input(
prompt="Test prompt",
expected_format={"key1": "desc1", "key2": "desc2"},
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore # type: ignore
)
@@ -109,7 +109,7 @@ class TestLLMStatsTracking:
# Run the block
input_data = llm.AITextGeneratorBlock.Input(
prompt="Generate text",
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
)
@@ -170,7 +170,7 @@ class TestLLMStatsTracking:
input_data = llm.AIStructuredResponseGeneratorBlock.Input(
prompt="Test prompt",
expected_format={"key1": "desc1", "key2": "desc2"},
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
retry=2,
)
@@ -228,7 +228,7 @@ class TestLLMStatsTracking:
input_data = llm.AITextSummarizerBlock.Input(
text=long_text,
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
max_tokens=100, # Small chunks
chunk_overlap=10,
@@ -299,7 +299,7 @@ class TestLLMStatsTracking:
# Test with very short text (should only need 1 chunk + 1 final summary)
input_data = llm.AITextSummarizerBlock.Input(
text="This is a short text.",
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
max_tokens=1000, # Large enough to avoid chunking
)
@@ -346,7 +346,7 @@ class TestLLMStatsTracking:
{"role": "assistant", "content": "Hi there!"},
{"role": "user", "content": "How are you?"},
],
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
)
@@ -387,7 +387,7 @@ class TestLLMStatsTracking:
# Run the block
input_data = llm.AIListGeneratorBlock.Input(
focus="test items",
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
max_retries=3,
)
@@ -469,7 +469,7 @@ class TestLLMStatsTracking:
input_data = llm.AIStructuredResponseGeneratorBlock.Input(
prompt="Test",
expected_format={"result": "desc"},
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
)
@@ -513,7 +513,7 @@ class TestAITextSummarizerValidation:
# Create input data
input_data = llm.AITextSummarizerBlock.Input(
text="Some text to summarize",
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
style=llm.SummaryStyle.BULLET_POINTS,
)
@@ -558,7 +558,7 @@ class TestAITextSummarizerValidation:
# Create input data
input_data = llm.AITextSummarizerBlock.Input(
text="Some text to summarize",
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
style=llm.SummaryStyle.BULLET_POINTS,
max_tokens=1000,
@@ -593,7 +593,7 @@ class TestAITextSummarizerValidation:
# Create input data
input_data = llm.AITextSummarizerBlock.Input(
text="Some text to summarize",
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
)
@@ -623,7 +623,7 @@ class TestAITextSummarizerValidation:
# Create input data
input_data = llm.AITextSummarizerBlock.Input(
text="Some text to summarize",
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
max_tokens=1000,
)
@@ -654,7 +654,7 @@ class TestAITextSummarizerValidation:
# Create input data
input_data = llm.AITextSummarizerBlock.Input(
text="Some text to summarize",
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
credentials=llm.TEST_CREDENTIALS_INPUT, # type: ignore
)

20
autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker.py
View File

@@ -233,7 +233,7 @@ async def test_smart_decision_maker_tracks_llm_stats():
# Create test input
input_data = SmartDecisionMakerBlock.Input(
prompt="Should I continue with this task?",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
agent_mode_max_iterations=0,
)
@@ -335,7 +335,7 @@ async def test_smart_decision_maker_parameter_validation():
input_data = SmartDecisionMakerBlock.Input(
prompt="Search for keywords",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
retry=2, # Set retry to 2 for testing
agent_mode_max_iterations=0,
@@ -402,7 +402,7 @@ async def test_smart_decision_maker_parameter_validation():
input_data = SmartDecisionMakerBlock.Input(
prompt="Search for keywords",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
agent_mode_max_iterations=0,
)
@@ -462,7 +462,7 @@ async def test_smart_decision_maker_parameter_validation():
input_data = SmartDecisionMakerBlock.Input(
prompt="Search for keywords",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
agent_mode_max_iterations=0,
)
@@ -526,7 +526,7 @@ async def test_smart_decision_maker_parameter_validation():
input_data = SmartDecisionMakerBlock.Input(
prompt="Search for keywords",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
agent_mode_max_iterations=0,
)
@@ -648,7 +648,7 @@ async def test_smart_decision_maker_raw_response_conversion():
input_data = SmartDecisionMakerBlock.Input(
prompt="Test prompt",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
retry=2,
agent_mode_max_iterations=0,
@@ -722,7 +722,7 @@ async def test_smart_decision_maker_raw_response_conversion():
):
input_data = SmartDecisionMakerBlock.Input(
prompt="Simple prompt",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
agent_mode_max_iterations=0,
)
@@ -778,7 +778,7 @@ async def test_smart_decision_maker_raw_response_conversion():
):
input_data = SmartDecisionMakerBlock.Input(
prompt="Another test",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
agent_mode_max_iterations=0,
)
@@ -931,7 +931,7 @@ async def test_smart_decision_maker_agent_mode():
# Test agent mode with max_iterations = 3
input_data = SmartDecisionMakerBlock.Input(
prompt="Complete this task using tools",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
agent_mode_max_iterations=3, # Enable agent mode with 3 max iterations
)
@@ -1020,7 +1020,7 @@ async def test_smart_decision_maker_traditional_mode_default():
# Test default behavior (traditional mode)
input_data = SmartDecisionMakerBlock.Input(
prompt="Test prompt",
model=llm_module.LlmModel.GPT4O,
model=llm_module.DEFAULT_LLM_MODEL,
credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore
agent_mode_max_iterations=0, # Traditional mode
)

4
autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dynamic_fields.py
View File

@@ -373,7 +373,7 @@ async def test_output_yielding_with_dynamic_fields():
input_data = block.input_schema(
prompt="Create a user dictionary",
credentials=llm.TEST_CREDENTIALS_INPUT,
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
agent_mode_max_iterations=0, # Use traditional mode to test output yielding
)
@@ -594,7 +594,7 @@ async def test_validation_errors_dont_pollute_conversation():
input_data = block.input_schema(
prompt="Test prompt",
credentials=llm.TEST_CREDENTIALS_INPUT,
model=llm.LlmModel.GPT4O,
model=llm.DEFAULT_LLM_MODEL,
retry=3, # Allow retries
agent_mode_max_iterations=1,
)

38
autogpt_platform/backend/backend/blocks/xml_parser.py
View File

@@ -1,5 +1,5 @@
from gravitasml.parser import Parser
from gravitasml.token import tokenize
from gravitasml.token import Token, tokenize
from backend.data.block import Block, BlockOutput, BlockSchemaInput, BlockSchemaOutput
from backend.data.model import SchemaField
@@ -25,6 +25,38 @@ class XMLParserBlock(Block):
],
)
@staticmethod
def _validate_tokens(tokens: list[Token]) -> None:
"""Ensure the XML has a single root element and no stray text."""
if not tokens:
raise ValueError("XML input is empty.")
depth = 0
root_seen = False
for token in tokens:
if token.type == "TAG_OPEN":
if depth == 0 and root_seen:
raise ValueError("XML must have a single root element.")
depth += 1
if depth == 1:
root_seen = True
elif token.type == "TAG_CLOSE":
depth -= 1
if depth < 0:
raise SyntaxError("Unexpected closing tag in XML input.")
elif token.type in {"TEXT", "ESCAPE"}:
if depth == 0 and token.value:
raise ValueError(
"XML contains text outside the root element; "
"wrap content in a single root tag."
)
if depth != 0:
raise SyntaxError("Unclosed tag detected in XML input.")
if not root_seen:
raise ValueError("XML must include a root element.")
async def run(self, input_data: Input, **kwargs) -> BlockOutput:
# Security fix: Add size limits to prevent XML bomb attacks
MAX_XML_SIZE = 10 * 1024 * 1024 # 10MB limit for XML input
@@ -35,7 +67,9 @@ class XMLParserBlock(Block):
)
try:
tokens = tokenize(input_data.input_xml)
tokens = list(tokenize(input_data.input_xml))
self._validate_tokens(tokens)
parser = Parser(tokens)
parsed_result = parser.parse()
yield "parsed_xml", parsed_result

2
autogpt_platform/backend/backend/blocks/youtube.py
View File

@@ -111,6 +111,8 @@ class TranscribeYoutubeVideoBlock(Block):
return parsed_url.path.split("/")[2]
if parsed_url.path[:3] == "/v/":
return parsed_url.path.split("/")[2]
if parsed_url.path.startswith("/shorts/"):
return parsed_url.path.split("/")[2]
raise ValueError(f"Invalid YouTube URL: {url}")
def get_transcript(

9
autogpt_platform/backend/backend/data/block_cost_config.py
View File

@@ -59,12 +59,13 @@ from backend.integrations.credentials_store import (
MODEL_COST: dict[LlmModel, int] = {
LlmModel.O3: 4,
LlmModel.O3_MINI: 2, # $1.10 / $4.40
LlmModel.O1: 16, # $15 / $60
LlmModel.O3_MINI: 2,
LlmModel.O1: 16,
LlmModel.O1_MINI: 4,
# GPT-5 models
LlmModel.GPT5: 2,
LlmModel.GPT5_2: 6,
LlmModel.GPT5_1: 5,
LlmModel.GPT5: 2,
LlmModel.GPT5_MINI: 1,
LlmModel.GPT5_NANO: 1,
LlmModel.GPT5_CHAT: 5,
@@ -87,7 +88,7 @@ MODEL_COST: dict[LlmModel, int] = {
LlmModel.AIML_API_LLAMA3_3_70B: 1,
LlmModel.AIML_API_META_LLAMA_3_1_70B: 1,
LlmModel.AIML_API_LLAMA_3_2_3B: 1,
LlmModel.LLAMA3_3_70B: 1, # $0.59 / $0.79
LlmModel.LLAMA3_3_70B: 1,
LlmModel.LLAMA3_1_8B: 1,
LlmModel.OLLAMA_LLAMA3_3: 1,
LlmModel.OLLAMA_LLAMA3_2: 1,

24
autogpt_platform/backend/poetry.lock generated
View File

@@ -1906,16 +1906,32 @@ httpx = {version = ">=0.26,<0.29", extras = ["http2"]}
pydantic = ">=1.10,<3"
pyjwt = ">=2.10.1,<3.0.0"
[[package]]
name = "gravitas-md2gdocs"
version = "0.1.0"
description = "Convert Markdown to Google Docs API requests"
optional = false
python-versions = ">=3.10"
groups = ["main"]
files = [
{file = "gravitas_md2gdocs-0.1.0-py3-none-any.whl", hash = "sha256:0cb0627779fdd65c1604818af4142eea1b25d055060183363de1bae4d9e46508"},
{file = "gravitas_md2gdocs-0.1.0.tar.gz", hash = "sha256:bb3122fe9fa35c528f3f00b785d3f1398d350082d5d03f60f56c895bdcc68033"},
]
[package.extras]
dev = ["google-auth-oauthlib (>=1.0.0)", "pytest (>=7.0.0)", "pytest-cov (>=4.0.0)", "python-dotenv (>=1.0.0)", "ruff (>=0.1.0)"]
google = ["google-api-python-client (>=2.0.0)", "google-auth (>=2.0.0)"]
[[package]]
name = "gravitasml"
version = "0.1.3"
version = "0.1.4"
description = ""
optional = false
python-versions = "<4.0,>=3.10"
groups = ["main"]
files = [
{file = "gravitasml-0.1.3-py3-none-any.whl", hash = "sha256:51ff98b4564b7a61f7796f18d5f2558b919d30b3722579296089645b7bc18b85"},
{file = "gravitasml-0.1.3.tar.gz", hash = "sha256:04d240b9fa35878252d57a36032130b6516487468847fcdced1022c032a20f57"},
{file = "gravitasml-0.1.4-py3-none-any.whl", hash = "sha256:671a18b11d3d8a0e270c6a80c72cd058458b18d5ef7560d00010e962ab1bca74"},
{file = "gravitasml-0.1.4.tar.gz", hash = "sha256:35d0d9fec7431817482d53d9c976e375557c3e041d1eb6928e809324a8c866e3"},
]
[package.dependencies]
@@ -7279,4 +7295,4 @@ cffi = ["cffi (>=1.11)"]
[metadata]
lock-version = "2.1"
python-versions = ">=3.10,<3.14"
content-hash = "13b191b2a1989d3321ff713c66ff6f5f4f3b82d15df4d407e0e5dbf87d7522c4"
content-hash = "a93ba0cea3b465cb6ec3e3f258b383b09f84ea352ccfdbfa112902cde5653fc6"

3
autogpt_platform/backend/pyproject.toml
View File

@@ -27,7 +27,7 @@ google-api-python-client = "^2.177.0"
google-auth-oauthlib = "^1.2.2"
google-cloud-storage = "^3.2.0"
googlemaps = "^4.10.0"
gravitasml = "^0.1.3"
gravitasml = "^0.1.4"
groq = "^0.30.0"
html2text = "^2024.2.26"
jinja2 = "^3.1.6"
@@ -82,6 +82,7 @@ firecrawl-py = "^4.3.6"
exa-py = "^1.14.20"
croniter = "^6.0.0"
stagehand = "^0.5.1"
gravitas-md2gdocs = "^0.1.0"
[tool.poetry.group.dev.dependencies]
aiohappyeyeballs = "^2.6.1"

113
autogpt_platform/backend/test/blocks/test_google_docs_format_text_color.py Normal file
View File

@@ -0,0 +1,113 @@
from unittest.mock import Mock
from backend.blocks.google.docs import GoogleDocsFormatTextBlock
def _make_mock_docs_service() -> Mock:
service = Mock()
# Ensure chained call exists: service.documents().batchUpdate(...).execute()
service.documents.return_value.batchUpdate.return_value.execute.return_value = {}
return service
def test_format_text_parses_shorthand_hex_color():
block = GoogleDocsFormatTextBlock()
service = _make_mock_docs_service()
result = block._format_text(
service,
document_id="doc_1",
start_index=1,
end_index=2,
bold=False,
italic=False,
underline=False,
font_size=0,
foreground_color="#FFF",
)
assert result["success"] is True
# Verify request body contains correct rgbColor for white.
_, kwargs = service.documents.return_value.batchUpdate.call_args
requests = kwargs["body"]["requests"]
rgb = requests[0]["updateTextStyle"]["textStyle"]["foregroundColor"]["color"][
"rgbColor"
]
assert rgb == {"red": 1.0, "green": 1.0, "blue": 1.0}
def test_format_text_parses_full_hex_color():
block = GoogleDocsFormatTextBlock()
service = _make_mock_docs_service()
result = block._format_text(
service,
document_id="doc_1",
start_index=1,
end_index=2,
bold=False,
italic=False,
underline=False,
font_size=0,
foreground_color="#FF0000",
)
assert result["success"] is True
_, kwargs = service.documents.return_value.batchUpdate.call_args
requests = kwargs["body"]["requests"]
rgb = requests[0]["updateTextStyle"]["textStyle"]["foregroundColor"]["color"][
"rgbColor"
]
assert rgb == {"red": 1.0, "green": 0.0, "blue": 0.0}
def test_format_text_ignores_invalid_color_when_other_fields_present():
block = GoogleDocsFormatTextBlock()
service = _make_mock_docs_service()
result = block._format_text(
service,
document_id="doc_1",
start_index=1,
end_index=2,
bold=True,
italic=False,
underline=False,
font_size=0,
foreground_color="#GGG",
)
assert result["success"] is True
assert "warning" in result
# Should still apply bold, but should NOT include foregroundColor in textStyle.
_, kwargs = service.documents.return_value.batchUpdate.call_args
requests = kwargs["body"]["requests"]
text_style = requests[0]["updateTextStyle"]["textStyle"]
fields = requests[0]["updateTextStyle"]["fields"]
assert text_style == {"bold": True}
assert fields == "bold"
def test_format_text_invalid_color_only_does_not_call_api():
block = GoogleDocsFormatTextBlock()
service = _make_mock_docs_service()
result = block._format_text(
service,
document_id="doc_1",
start_index=1,
end_index=2,
bold=False,
italic=False,
underline=False,
font_size=0,
foreground_color="#F",
)
assert result["success"] is False
assert "Invalid foreground_color" in result["message"]
service.documents.return_value.batchUpdate.assert_not_called()

12
autogpt_platform/backend/test/blocks/test_youtube.py
View File

@@ -37,6 +37,18 @@ class TestTranscribeYoutubeVideoBlock:
video_id = self.youtube_block.extract_video_id(url)
assert video_id == "dQw4w9WgXcQ"
def test_extract_video_id_shorts_url(self):
"""Test extracting video ID from YouTube Shorts URL."""
url = "https://www.youtube.com/shorts/dtUqwMu3e-g"
video_id = self.youtube_block.extract_video_id(url)
assert video_id == "dtUqwMu3e-g"
def test_extract_video_id_shorts_url_with_params(self):
"""Test extracting video ID from YouTube Shorts URL with query parameters."""
url = "https://www.youtube.com/shorts/dtUqwMu3e-g?feature=share"
video_id = self.youtube_block.extract_video_id(url)
assert video_id == "dtUqwMu3e-g"
@patch("backend.blocks.youtube.YouTubeTranscriptApi")
def test_get_transcript_english_available(self, mock_api_class):
"""Test getting transcript when English is available."""

12
autogpt_platform/frontend/src/components/renderers/input-renderer/fields/AnyOfField/useAnyOfField.tsx
View File

@@ -64,7 +64,9 @@ export const useAnyOfField = (
const [selectedType, setSelectedType] = useState<string>(initialSelectedType);
const isEnabled = formData !== null && formData !== undefined;
// Only check for explicit null (set by toggle off), not undefined (empty input)
// This allows users to clear number inputs without the field disappearing
const isEnabled = formData !== null;
const handleTypeChange = (t: string) => {
setSelectedType(t);
@@ -79,7 +81,13 @@ export const useAnyOfField = (
}
};
const handleValueChange = (value: any) => onChange(value);
const handleValueChange = (value: any) => {
if (isNullableType && value === null) {
onChange(undefined);
return;
}
onChange(value);
};
const currentTypeOption = typeOptions.find((o) => o.type === selectedType);

2
autogpt_platform/frontend/src/components/renderers/input-renderer/widgets/TextInputWidget/TextInputWidget.tsx
View File

@@ -51,7 +51,7 @@ export const TextInputWidget = (props: WidgetProps) => {
handleChange: (v: string) => (v === "" ? undefined : Number(v)),
},
[InputType.INTEGER]: {
htmlType: "account",
htmlType: "number",
placeholder: "Enter integer value...",
handleChange: (v: string) => (v === "" ? undefined : Number(v)),
},