Merge branch 'dev' into hackathon/copilot

autogpt_platform/backend/backend/api/rest_api.py

@@ -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():

autogpt_platform/backend/backend/blocks/ai_condition.py

@@ -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,

autogpt_platform/backend/backend/blocks/llm.py

@@ -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,

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -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,
         )

autogpt_platform/backend/backend/blocks/test/test_blocks_dos_vulnerability.py

@@ -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."""

autogpt_platform/backend/backend/blocks/test/test_llm.py

@@ -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
         )
 

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker.py

@@ -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
         )

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dynamic_fields.py

@@ -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,
                 )

autogpt_platform/backend/backend/blocks/xml_parser.py

@@ -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

autogpt_platform/backend/backend/blocks/youtube.py

@@ -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(

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -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.O3_MINI: 2,
-    LlmModel.O1: 16,  # $15 / $60
+    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,

autogpt_platform/backend/poetry.lock

@@ -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-0.1.4-py3-none-any.whl", hash = "sha256:671a18b11d3d8a0e270c6a80c72cd058458b18d5ef7560d00010e962ab1bca74"},
-    {file = "gravitasml-0.1.3.tar.gz", hash = "sha256:04d240b9fa35878252d57a36032130b6516487468847fcdced1022c032a20f57"},
+    {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"

autogpt_platform/backend/pyproject.toml

@@ -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"

autogpt_platform/backend/test/blocks/test_google_docs_format_text_color.py

@@ -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()

autogpt_platform/backend/test/blocks/test_youtube.py

@@ -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."""

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

@@ -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);
 

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

@@ -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)),
     },