mirror of
https://github.com/Significant-Gravitas/AutoGPT.git
synced 2026-01-30 09:28:19 -05:00
Merge branch 'dev' into feat/sub-agent-support
This commit is contained in:
Zamil Majdy
@@ -8,7 +8,7 @@ from backend.api.features.library import model as library_model
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from backend.api.features.store import db as store_db
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from backend.data import graph as graph_db
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from backend.data.graph import GraphModel
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from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
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from backend.data.model import Credentials, CredentialsFieldInfo, CredentialsMetaInput
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from backend.integrations.creds_manager import IntegrationCredentialsManager
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from backend.util.exceptions import NotFoundError
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@@ -266,13 +266,14 @@ async def match_user_credentials_to_graph(
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credential_requirements,
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_node_fields,
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) in aggregated_creds.items():
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# Find first matching credential by provider and type
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# Find first matching credential by provider, type, and scopes
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matching_cred = next(
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(
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cred
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for cred in available_creds
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if cred.provider in credential_requirements.provider
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and cred.type in credential_requirements.supported_types
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and _credential_has_required_scopes(cred, credential_requirements)
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),
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None,
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)
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@@ -296,10 +297,17 @@ async def match_user_credentials_to_graph(
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f"{credential_field_name} (validation failed: {e})"
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)
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else:
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# Build a helpful error message including scope requirements
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error_parts = [
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f"provider in {list(credential_requirements.provider)}",
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f"type in {list(credential_requirements.supported_types)}",
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]
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if credential_requirements.required_scopes:
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error_parts.append(
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f"scopes including {list(credential_requirements.required_scopes)}"
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)
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missing_creds.append(
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f"{credential_field_name} "
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f"(requires provider in {list(credential_requirements.provider)}, "
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f"type in {list(credential_requirements.supported_types)})"
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f"{credential_field_name} (requires {', '.join(error_parts)})"
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)
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logger.info(
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@@ -309,6 +317,28 @@ async def match_user_credentials_to_graph(
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return graph_credentials_inputs, missing_creds
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def _credential_has_required_scopes(
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credential: Credentials,
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requirements: CredentialsFieldInfo,
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) -> bool:
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"""
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Check if a credential has all the scopes required by the block.
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For OAuth2 credentials, verifies that the credential's scopes are a superset
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of the required scopes. For other credential types, returns True (no scope check).
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"""
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# Only OAuth2 credentials have scopes to check
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if credential.type != "oauth2":
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return True
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# If no scopes are required, any credential matches
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if not requirements.required_scopes:
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return True
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# Check that credential scopes are a superset of required scopes
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return set(credential.scopes).issuperset(requirements.required_scopes)
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async def check_user_has_required_credentials(
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user_id: str,
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required_credentials: list[CredentialsMetaInput],
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@@ -115,7 +115,6 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
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CLAUDE_4_5_OPUS = "claude-opus-4-5-20251101"
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CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
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CLAUDE_4_5_HAIKU = "claude-haiku-4-5-20251001"
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CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
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CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
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# AI/ML API models
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AIML_API_QWEN2_5_72B = "Qwen/Qwen2.5-72B-Instruct-Turbo"
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@@ -280,9 +279,6 @@ MODEL_METADATA = {
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LlmModel.CLAUDE_4_5_HAIKU: ModelMetadata(
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"anthropic", 200000, 64000, "Claude Haiku 4.5", "Anthropic", "Anthropic", 2
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), # claude-haiku-4-5-20251001
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LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
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"anthropic", 200000, 64000, "Claude 3.7 Sonnet", "Anthropic", "Anthropic", 2
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), # claude-3-7-sonnet-20250219
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LlmModel.CLAUDE_3_HAIKU: ModelMetadata(
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"anthropic", 200000, 4096, "Claude 3 Haiku", "Anthropic", "Anthropic", 1
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), # claude-3-haiku-20240307
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@@ -83,7 +83,7 @@ class StagehandRecommendedLlmModel(str, Enum):
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GPT41_MINI = "gpt-4.1-mini-2025-04-14"
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# Anthropic
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CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
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CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
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@property
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def provider_name(self) -> str:
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@@ -137,7 +137,7 @@ class StagehandObserveBlock(Block):
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model: StagehandRecommendedLlmModel = SchemaField(
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title="LLM Model",
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description="LLM to use for Stagehand (provider is inferred)",
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default=StagehandRecommendedLlmModel.CLAUDE_3_7_SONNET,
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default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
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advanced=False,
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)
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model_credentials: AICredentials = AICredentialsField()
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@@ -230,7 +230,7 @@ class StagehandActBlock(Block):
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model: StagehandRecommendedLlmModel = SchemaField(
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title="LLM Model",
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description="LLM to use for Stagehand (provider is inferred)",
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default=StagehandRecommendedLlmModel.CLAUDE_3_7_SONNET,
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default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
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advanced=False,
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)
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model_credentials: AICredentials = AICredentialsField()
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@@ -330,7 +330,7 @@ class StagehandExtractBlock(Block):
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model: StagehandRecommendedLlmModel = SchemaField(
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title="LLM Model",
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description="LLM to use for Stagehand (provider is inferred)",
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default=StagehandRecommendedLlmModel.CLAUDE_3_7_SONNET,
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default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
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advanced=False,
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)
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model_credentials: AICredentials = AICredentialsField()
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@@ -81,7 +81,6 @@ MODEL_COST: dict[LlmModel, int] = {
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LlmModel.CLAUDE_4_5_HAIKU: 4,
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LlmModel.CLAUDE_4_5_OPUS: 14,
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LlmModel.CLAUDE_4_5_SONNET: 9,
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LlmModel.CLAUDE_3_7_SONNET: 5,
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LlmModel.CLAUDE_3_HAIKU: 1,
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LlmModel.AIML_API_QWEN2_5_72B: 1,
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LlmModel.AIML_API_LLAMA3_1_70B: 1,
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@@ -666,10 +666,16 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
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if not (self.discriminator and self.discriminator_mapping):
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return self
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try:
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provider = self.discriminator_mapping[discriminator_value]
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except KeyError:
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raise ValueError(
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f"Model '{discriminator_value}' is not supported. "
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"It may have been deprecated. Please update your agent configuration."
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)
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return CredentialsFieldInfo(
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credentials_provider=frozenset(
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[self.discriminator_mapping[discriminator_value]]
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),
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credentials_provider=frozenset([provider]),
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credentials_types=self.supported_types,
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credentials_scopes=self.required_scopes,
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discriminator=self.discriminator,
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@@ -0,0 +1,22 @@
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-- Migrate Claude 3.7 Sonnet to Claude 4.5 Sonnet
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-- This updates all AgentNode blocks that use the deprecated Claude 3.7 Sonnet model
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-- Anthropic is retiring claude-3-7-sonnet-20250219 on February 19, 2026
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-- Update AgentNode constant inputs
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UPDATE "AgentNode"
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SET "constantInput" = JSONB_SET(
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"constantInput"::jsonb,
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'{model}',
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'"claude-sonnet-4-5-20250929"'::jsonb
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)
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WHERE "constantInput"::jsonb->>'model' = 'claude-3-7-sonnet-20250219';
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-- Update AgentPreset input overrides (stored in AgentNodeExecutionInputOutput)
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UPDATE "AgentNodeExecutionInputOutput"
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SET "data" = JSONB_SET(
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"data"::jsonb,
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'{model}',
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'"claude-sonnet-4-5-20250929"'::jsonb
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)
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WHERE "agentPresetId" IS NOT NULL
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AND "data"::jsonb->>'model' = 'claude-3-7-sonnet-20250219';
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@@ -43,19 +43,24 @@ faker = Faker()
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# Constants for data generation limits (reduced for E2E tests)
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NUM_USERS = 15
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NUM_AGENT_BLOCKS = 30
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MIN_GRAPHS_PER_USER = 15
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MAX_GRAPHS_PER_USER = 15
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MIN_GRAPHS_PER_USER = 25
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MAX_GRAPHS_PER_USER = 25
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MIN_NODES_PER_GRAPH = 3
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MAX_NODES_PER_GRAPH = 6
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MIN_PRESETS_PER_USER = 2
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MAX_PRESETS_PER_USER = 3
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MIN_AGENTS_PER_USER = 15
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MAX_AGENTS_PER_USER = 15
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MIN_AGENTS_PER_USER = 25
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MAX_AGENTS_PER_USER = 25
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MIN_EXECUTIONS_PER_GRAPH = 2
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MAX_EXECUTIONS_PER_GRAPH = 8
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MIN_REVIEWS_PER_VERSION = 2
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MAX_REVIEWS_PER_VERSION = 5
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# Guaranteed minimums for marketplace tests (deterministic)
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GUARANTEED_FEATURED_AGENTS = 8
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GUARANTEED_FEATURED_CREATORS = 5
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GUARANTEED_TOP_AGENTS = 10
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def get_image():
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"""Generate a consistent image URL using picsum.photos service."""
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@@ -385,7 +390,7 @@ class TestDataCreator:
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library_agents = []
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for user in self.users:
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num_agents = 10 # Create exactly 10 agents per user
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num_agents = random.randint(MIN_AGENTS_PER_USER, MAX_AGENTS_PER_USER)
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# Get available graphs for this user
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user_graphs = [
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@@ -507,14 +512,17 @@ class TestDataCreator:
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existing_profiles, min(num_creators, len(existing_profiles))
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)
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# Mark about 50% of creators as featured (more for testing)
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num_featured = max(2, int(num_creators * 0.5))
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# Guarantee at least GUARANTEED_FEATURED_CREATORS featured creators
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num_featured = max(GUARANTEED_FEATURED_CREATORS, int(num_creators * 0.5))
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num_featured = min(
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num_featured, len(selected_profiles)
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) # Don't exceed available profiles
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featured_profile_ids = set(
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random.sample([p.id for p in selected_profiles], num_featured)
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)
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print(
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f"🎯 Creating {num_featured} featured creators (min: {GUARANTEED_FEATURED_CREATORS})"
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)
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for profile in selected_profiles:
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try:
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@@ -545,21 +553,25 @@ class TestDataCreator:
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return profiles
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async def create_test_store_submissions(self) -> List[Dict[str, Any]]:
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"""Create test store submissions using the API function."""
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"""Create test store submissions using the API function.
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DETERMINISTIC: Guarantees minimum featured agents for E2E tests.
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"""
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print("Creating test store submissions...")
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submissions = []
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approved_submissions = []
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featured_count = 0
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submission_counter = 0
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# Create a special test submission for test123@gmail.com
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# Create a special test submission for test123@gmail.com (ALWAYS approved + featured)
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test_user = next(
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(user for user in self.users if user["email"] == "test123@gmail.com"), None
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)
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if test_user:
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# Special test data for consistent testing
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if test_user and self.agent_graphs:
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test_submission_data = {
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"user_id": test_user["id"],
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"agent_id": self.agent_graphs[0]["id"], # Use first available graph
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"agent_id": self.agent_graphs[0]["id"],
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"agent_version": 1,
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"slug": "test-agent-submission",
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"name": "Test Agent Submission",
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@@ -580,37 +592,24 @@ class TestDataCreator:
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submissions.append(test_submission.model_dump())
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print("✅ Created special test store submission for test123@gmail.com")
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# Randomly approve, reject, or leave pending the test submission
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# ALWAYS approve and feature the test submission
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if test_submission.store_listing_version_id:
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random_value = random.random()
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if random_value < 0.4: # 40% chance to approve
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approved_submission = await review_store_submission(
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store_listing_version_id=test_submission.store_listing_version_id,
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is_approved=True,
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external_comments="Test submission approved",
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internal_comments="Auto-approved test submission",
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reviewer_id=test_user["id"],
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)
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approved_submissions.append(approved_submission.model_dump())
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print("✅ Approved test store submission")
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approved_submission = await review_store_submission(
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store_listing_version_id=test_submission.store_listing_version_id,
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is_approved=True,
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external_comments="Test submission approved",
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internal_comments="Auto-approved test submission",
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reviewer_id=test_user["id"],
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)
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approved_submissions.append(approved_submission.model_dump())
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print("✅ Approved test store submission")
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# Mark approved submission as featured
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await prisma.storelistingversion.update(
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where={"id": test_submission.store_listing_version_id},
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data={"isFeatured": True},
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)
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print("🌟 Marked test agent as FEATURED")
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elif random_value < 0.7: # 30% chance to reject (40% to 70%)
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await review_store_submission(
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store_listing_version_id=test_submission.store_listing_version_id,
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is_approved=False,
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external_comments="Test submission rejected - needs improvements",
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internal_comments="Auto-rejected test submission for E2E testing",
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reviewer_id=test_user["id"],
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)
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print("❌ Rejected test store submission")
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else: # 30% chance to leave pending (70% to 100%)
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print("⏳ Left test submission pending for review")
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await prisma.storelistingversion.update(
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where={"id": test_submission.store_listing_version_id},
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data={"isFeatured": True},
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)
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featured_count += 1
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print("🌟 Marked test agent as FEATURED")
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|
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except Exception as e:
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print(f"Error creating test store submission: {e}")
|
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@@ -620,7 +619,6 @@ class TestDataCreator:
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# Create regular submissions for all users
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for user in self.users:
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# Get available graphs for this specific user
|
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user_graphs = [
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g for g in self.agent_graphs if g.get("userId") == user["id"]
|
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]
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@@ -631,18 +629,17 @@ class TestDataCreator:
|
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)
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continue
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# Create exactly 4 store submissions per user
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for submission_index in range(4):
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graph = random.choice(user_graphs)
|
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submission_counter += 1
|
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|
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try:
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print(
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f"Creating store submission for user {user['id']} with graph {graph['id']} (owner: {graph.get('userId')})"
|
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f"Creating store submission for user {user['id']} with graph {graph['id']}"
|
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)
|
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|
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# Use the API function to create store submission with correct parameters
|
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submission = await create_store_submission(
|
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user_id=user["id"], # Must match graph's userId
|
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user_id=user["id"],
|
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agent_id=graph["id"],
|
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agent_version=graph.get("version", 1),
|
||||
slug=faker.slug(),
|
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@@ -651,22 +648,24 @@ class TestDataCreator:
|
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video_url=get_video_url() if random.random() < 0.3 else None,
|
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image_urls=[get_image() for _ in range(3)],
|
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description=faker.text(),
|
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categories=[
|
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get_category()
|
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], # Single category from predefined list
|
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categories=[get_category()],
|
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changes_summary="Initial E2E test submission",
|
||||
)
|
||||
submissions.append(submission.model_dump())
|
||||
print(f"✅ Created store submission: {submission.name}")
|
||||
|
||||
# Randomly approve, reject, or leave pending the submission
|
||||
if submission.store_listing_version_id:
|
||||
random_value = random.random()
|
||||
if random_value < 0.4: # 40% chance to approve
|
||||
try:
|
||||
# Pick a random user as the reviewer (admin)
|
||||
reviewer_id = random.choice(self.users)["id"]
|
||||
# DETERMINISTIC: First N submissions are always approved
|
||||
# First GUARANTEED_FEATURED_AGENTS of those are always featured
|
||||
should_approve = (
|
||||
submission_counter <= GUARANTEED_TOP_AGENTS
|
||||
or random.random() < 0.4
|
||||
)
|
||||
should_feature = featured_count < GUARANTEED_FEATURED_AGENTS
|
||||
|
||||
if should_approve:
|
||||
try:
|
||||
reviewer_id = random.choice(self.users)["id"]
|
||||
approved_submission = await review_store_submission(
|
||||
store_listing_version_id=submission.store_listing_version_id,
|
||||
is_approved=True,
|
||||
@@ -681,16 +680,7 @@ class TestDataCreator:
|
||||
f"✅ Approved store submission: {submission.name}"
|
||||
)
|
||||
|
||||
# Mark some agents as featured during creation (30% chance)
|
||||
# More likely for creators and first submissions
|
||||
is_creator = user["id"] in [
|
||||
p.get("userId") for p in self.profiles
|
||||
]
|
||||
feature_chance = (
|
||||
0.5 if is_creator else 0.2
|
||||
) # 50% for creators, 20% for others
|
||||
|
||||
if random.random() < feature_chance:
|
||||
if should_feature:
|
||||
try:
|
||||
await prisma.storelistingversion.update(
|
||||
where={
|
||||
@@ -698,8 +688,25 @@ class TestDataCreator:
|
||||
},
|
||||
data={"isFeatured": True},
|
||||
)
|
||||
featured_count += 1
|
||||
print(
|
||||
f"🌟 Marked agent as FEATURED: {submission.name}"
|
||||
f"🌟 Marked agent as FEATURED ({featured_count}/{GUARANTEED_FEATURED_AGENTS}): {submission.name}"
|
||||
)
|
||||
except Exception as e:
|
||||
print(
|
||||
f"Warning: Could not mark submission as featured: {e}"
|
||||
)
|
||||
elif random.random() < 0.2:
|
||||
try:
|
||||
await prisma.storelistingversion.update(
|
||||
where={
|
||||
"id": submission.store_listing_version_id
|
||||
},
|
||||
data={"isFeatured": True},
|
||||
)
|
||||
featured_count += 1
|
||||
print(
|
||||
f"🌟 Marked agent as FEATURED (bonus): {submission.name}"
|
||||
)
|
||||
except Exception as e:
|
||||
print(
|
||||
@@ -710,11 +717,9 @@ class TestDataCreator:
|
||||
print(
|
||||
f"Warning: Could not approve submission {submission.name}: {e}"
|
||||
)
|
||||
elif random_value < 0.7: # 30% chance to reject (40% to 70%)
|
||||
elif random.random() < 0.5:
|
||||
try:
|
||||
# Pick a random user as the reviewer (admin)
|
||||
reviewer_id = random.choice(self.users)["id"]
|
||||
|
||||
await review_store_submission(
|
||||
store_listing_version_id=submission.store_listing_version_id,
|
||||
is_approved=False,
|
||||
@@ -729,7 +734,7 @@ class TestDataCreator:
|
||||
print(
|
||||
f"Warning: Could not reject submission {submission.name}: {e}"
|
||||
)
|
||||
else: # 30% chance to leave pending (70% to 100%)
|
||||
else:
|
||||
print(
|
||||
f"⏳ Left submission pending for review: {submission.name}"
|
||||
)
|
||||
@@ -743,9 +748,13 @@ class TestDataCreator:
|
||||
traceback.print_exc()
|
||||
continue
|
||||
|
||||
print("\n📊 Store Submissions Summary:")
|
||||
print(f" Created: {len(submissions)}")
|
||||
print(f" Approved: {len(approved_submissions)}")
|
||||
print(
|
||||
f"Created {len(submissions)} store submissions, approved {len(approved_submissions)}"
|
||||
f" Featured: {featured_count} (guaranteed min: {GUARANTEED_FEATURED_AGENTS})"
|
||||
)
|
||||
|
||||
self.store_submissions = submissions
|
||||
return submissions
|
||||
|
||||
@@ -825,12 +834,15 @@ class TestDataCreator:
|
||||
print(f"✅ Agent blocks available: {len(self.agent_blocks)}")
|
||||
print(f"✅ Agent graphs created: {len(self.agent_graphs)}")
|
||||
print(f"✅ Library agents created: {len(self.library_agents)}")
|
||||
print(f"✅ Creator profiles updated: {len(self.profiles)} (some featured)")
|
||||
print(
|
||||
f"✅ Store submissions created: {len(self.store_submissions)} (some marked as featured during creation)"
|
||||
)
|
||||
print(f"✅ Creator profiles updated: {len(self.profiles)}")
|
||||
print(f"✅ Store submissions created: {len(self.store_submissions)}")
|
||||
print(f"✅ API keys created: {len(self.api_keys)}")
|
||||
print(f"✅ Presets created: {len(self.presets)}")
|
||||
print("\n🎯 Deterministic Guarantees:")
|
||||
print(f" • Featured agents: >= {GUARANTEED_FEATURED_AGENTS}")
|
||||
print(f" • Featured creators: >= {GUARANTEED_FEATURED_CREATORS}")
|
||||
print(f" • Top agents (approved): >= {GUARANTEED_TOP_AGENTS}")
|
||||
print(f" • Library agents per user: >= {MIN_AGENTS_PER_USER}")
|
||||
print("\n🚀 Your E2E test database is ready to use!")
|
||||
|
||||
|
||||
|
||||
@@ -57,6 +57,7 @@ export function ChatInput({
|
||||
isStreaming,
|
||||
value,
|
||||
baseHandleKeyDown,
|
||||
inputId,
|
||||
});
|
||||
|
||||
return (
|
||||
|
||||
@@ -15,6 +15,7 @@ interface Args {
|
||||
isStreaming?: boolean;
|
||||
value: string;
|
||||
baseHandleKeyDown: (event: KeyboardEvent<HTMLTextAreaElement>) => void;
|
||||
inputId?: string;
|
||||
}
|
||||
|
||||
export function useVoiceRecording({
|
||||
@@ -23,6 +24,7 @@ export function useVoiceRecording({
|
||||
isStreaming = false,
|
||||
value,
|
||||
baseHandleKeyDown,
|
||||
inputId,
|
||||
}: Args) {
|
||||
const [isRecording, setIsRecording] = useState(false);
|
||||
const [isTranscribing, setIsTranscribing] = useState(false);
|
||||
@@ -103,7 +105,7 @@ export function useVoiceRecording({
|
||||
setIsTranscribing(false);
|
||||
}
|
||||
},
|
||||
[handleTranscription],
|
||||
[handleTranscription, inputId],
|
||||
);
|
||||
|
||||
const stopRecording = useCallback(() => {
|
||||
@@ -201,6 +203,15 @@ export function useVoiceRecording({
|
||||
}
|
||||
}, [error, toast]);
|
||||
|
||||
useEffect(() => {
|
||||
if (!isTranscribing && inputId) {
|
||||
const inputElement = document.getElementById(inputId);
|
||||
if (inputElement) {
|
||||
inputElement.focus();
|
||||
}
|
||||
}
|
||||
}, [isTranscribing, inputId]);
|
||||
|
||||
const handleKeyDown = useCallback(
|
||||
(event: KeyboardEvent<HTMLTextAreaElement>) => {
|
||||
if (event.key === " " && !value.trim() && !isTranscribing) {
|
||||
|
||||
@@ -59,12 +59,13 @@ test.describe("Library", () => {
|
||||
});
|
||||
|
||||
test("pagination works correctly", async ({ page }, testInfo) => {
|
||||
test.setTimeout(testInfo.timeout * 3); // Increase timeout for pagination operations
|
||||
test.setTimeout(testInfo.timeout * 3);
|
||||
await page.goto("/library");
|
||||
|
||||
const PAGE_SIZE = 20;
|
||||
const paginationResult = await libraryPage.testPagination();
|
||||
|
||||
if (paginationResult.initialCount >= 10) {
|
||||
if (paginationResult.initialCount >= PAGE_SIZE) {
|
||||
expect(paginationResult.finalCount).toBeGreaterThanOrEqual(
|
||||
paginationResult.initialCount,
|
||||
);
|
||||
@@ -133,7 +134,10 @@ test.describe("Library", () => {
|
||||
test.expect(clearedSearchValue).toBe("");
|
||||
});
|
||||
|
||||
test("pagination while searching works correctly", async ({ page }) => {
|
||||
test("pagination while searching works correctly", async ({
|
||||
page,
|
||||
}, testInfo) => {
|
||||
test.setTimeout(testInfo.timeout * 3);
|
||||
await page.goto("/library");
|
||||
|
||||
const allAgents = await libraryPage.getAgents();
|
||||
@@ -152,9 +156,10 @@ test.describe("Library", () => {
|
||||
);
|
||||
expect(matchingResults.length).toEqual(initialSearchResults.length);
|
||||
|
||||
const PAGE_SIZE = 20;
|
||||
const searchPaginationResult = await libraryPage.testPagination();
|
||||
|
||||
if (searchPaginationResult.initialCount >= 10) {
|
||||
if (searchPaginationResult.initialCount >= PAGE_SIZE) {
|
||||
expect(searchPaginationResult.finalCount).toBeGreaterThanOrEqual(
|
||||
searchPaginationResult.initialCount,
|
||||
);
|
||||
|
||||
@@ -69,9 +69,12 @@ test.describe("Marketplace Creator Page – Basic Functionality", () => {
|
||||
await marketplacePage.getFirstCreatorProfile(page);
|
||||
await firstCreatorProfile.click();
|
||||
await page.waitForURL("**/marketplace/creator/**");
|
||||
await page.waitForLoadState("networkidle").catch(() => {});
|
||||
|
||||
const firstAgent = page
|
||||
.locator('[data-testid="store-card"]:visible')
|
||||
.first();
|
||||
await firstAgent.waitFor({ state: "visible", timeout: 30000 });
|
||||
|
||||
await firstAgent.click();
|
||||
await page.waitForURL("**/marketplace/agent/**");
|
||||
|
||||
@@ -77,7 +77,6 @@ test.describe("Marketplace – Basic Functionality", () => {
|
||||
|
||||
const firstFeaturedAgent =
|
||||
await marketplacePage.getFirstFeaturedAgent(page);
|
||||
await firstFeaturedAgent.waitFor({ state: "visible" });
|
||||
await firstFeaturedAgent.click();
|
||||
await page.waitForURL("**/marketplace/agent/**");
|
||||
await matchesUrl(page, /\/marketplace\/agent\/.+/);
|
||||
@@ -116,7 +115,15 @@ test.describe("Marketplace – Basic Functionality", () => {
|
||||
const searchTerm = page.getByText("DummyInput").first();
|
||||
await isVisible(searchTerm);
|
||||
|
||||
await page.waitForTimeout(10000);
|
||||
await page.waitForLoadState("networkidle").catch(() => {});
|
||||
|
||||
await page
|
||||
.waitForFunction(
|
||||
() =>
|
||||
document.querySelectorAll('[data-testid="store-card"]').length > 0,
|
||||
{ timeout: 15000 },
|
||||
)
|
||||
.catch(() => console.log("No search results appeared within timeout"));
|
||||
|
||||
const results = await marketplacePage.getSearchResultsCount(page);
|
||||
expect(results).toBeGreaterThan(0);
|
||||
|
||||
@@ -300,21 +300,27 @@ export class LibraryPage extends BasePage {
|
||||
async scrollToLoadMore(): Promise<void> {
|
||||
console.log(`scrolling to load more agents`);
|
||||
|
||||
// Get initial agent count
|
||||
const initialCount = await this.getAgentCount();
|
||||
console.log(`Initial agent count: ${initialCount}`);
|
||||
const initialCount = await this.getAgentCountByListLength();
|
||||
console.log(`Initial agent count (DOM cards): ${initialCount}`);
|
||||
|
||||
// Scroll down to trigger pagination
|
||||
await this.scrollToBottom();
|
||||
|
||||
// Wait for potential new agents to load
|
||||
await this.page.waitForTimeout(2000);
|
||||
await this.page
|
||||
.waitForLoadState("networkidle", { timeout: 10000 })
|
||||
.catch(() => console.log("Network idle timeout, continuing..."));
|
||||
|
||||
// Check if more agents loaded
|
||||
const newCount = await this.getAgentCount();
|
||||
console.log(`New agent count after scroll: ${newCount}`);
|
||||
await this.page
|
||||
.waitForFunction(
|
||||
(prevCount) =>
|
||||
document.querySelectorAll('[data-testid="library-agent-card"]')
|
||||
.length > prevCount,
|
||||
initialCount,
|
||||
{ timeout: 5000 },
|
||||
)
|
||||
.catch(() => {});
|
||||
|
||||
return;
|
||||
const newCount = await this.getAgentCountByListLength();
|
||||
console.log(`New agent count after scroll (DOM cards): ${newCount}`);
|
||||
}
|
||||
|
||||
async testPagination(): Promise<{
|
||||
|
||||
@@ -9,6 +9,7 @@ export class MarketplacePage extends BasePage {
|
||||
|
||||
async goto(page: Page) {
|
||||
await page.goto("/marketplace");
|
||||
await page.waitForLoadState("networkidle").catch(() => {});
|
||||
}
|
||||
|
||||
async getMarketplaceTitle(page: Page) {
|
||||
@@ -109,16 +110,24 @@ export class MarketplacePage extends BasePage {
|
||||
|
||||
async getFirstFeaturedAgent(page: Page) {
|
||||
const { getId } = getSelectors(page);
|
||||
return getId("featured-store-card").first();
|
||||
const card = getId("featured-store-card").first();
|
||||
await card.waitFor({ state: "visible", timeout: 30000 });
|
||||
return card;
|
||||
}
|
||||
|
||||
async getFirstTopAgent() {
|
||||
return this.page.locator('[data-testid="store-card"]:visible').first();
|
||||
const card = this.page
|
||||
.locator('[data-testid="store-card"]:visible')
|
||||
.first();
|
||||
await card.waitFor({ state: "visible", timeout: 30000 });
|
||||
return card;
|
||||
}
|
||||
|
||||
async getFirstCreatorProfile(page: Page) {
|
||||
const { getId } = getSelectors(page);
|
||||
return getId("creator-card").first();
|
||||
const card = getId("creator-card").first();
|
||||
await card.waitFor({ state: "visible", timeout: 30000 });
|
||||
return card;
|
||||
}
|
||||
|
||||
async getSearchResultsCount(page: Page) {
|
||||
|
||||
@@ -65,7 +65,7 @@ The result routes data to yes_output or no_output, enabling intelligent branchin
|
||||
| condition | A plaintext English description of the condition to evaluate | str | Yes |
|
||||
| yes_value | (Optional) Value to output if the condition is true. If not provided, input_value will be used. | Yes Value | No |
|
||||
| no_value | (Optional) Value to output if the condition is false. If not provided, input_value will be used. | No Value | No |
|
||||
| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
|
||||
### Outputs
|
||||
|
||||
@@ -103,7 +103,7 @@ The block sends the entire conversation history to the chosen LLM, including sys
|
||||
|-------|-------------|------|----------|
|
||||
| prompt | The prompt to send to the language model. | str | No |
|
||||
| messages | List of messages in the conversation. | List[Any] | Yes |
|
||||
| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
|
||||
| ollama_host | Ollama host for local models | str | No |
|
||||
|
||||
@@ -257,7 +257,7 @@ The block formulates a prompt based on the given focus or source data, sends it
|
||||
|-------|-------------|------|----------|
|
||||
| focus | The focus of the list to generate. | str | No |
|
||||
| source_data | The data to generate the list from. | str | No |
|
||||
| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| max_retries | Maximum number of retries for generating a valid list. | int | No |
|
||||
| force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
|
||||
| max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
|
||||
@@ -424,7 +424,7 @@ The block sends the input prompt to a chosen LLM, along with any system prompts
|
||||
| prompt | The prompt to send to the language model. | str | Yes |
|
||||
| expected_format | Expected format of the response. If provided, the response will be validated against this format. The keys should be the expected fields in the response, and the values should be the description of the field. | Dict[str, str] | Yes |
|
||||
| list_result | Whether the response should be a list of objects in the expected format. | bool | No |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
|
||||
| sys_prompt | The system prompt to provide additional context to the model. | str | No |
|
||||
| conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
|
||||
@@ -464,7 +464,7 @@ The block sends the input prompt to a chosen LLM, processes the response, and re
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| prompt | The prompt to send to the language model. You can use any of the {keys} from Prompt Values to fill in the prompt with values from the prompt values dictionary by putting them in curly braces. | str | Yes |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| sys_prompt | The system prompt to provide additional context to the model. | str | No |
|
||||
| retry | Number of times to retry the LLM call if the response does not match the expected format. | int | No |
|
||||
| prompt_values | Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}. | Dict[str, str] | No |
|
||||
@@ -501,7 +501,7 @@ The block splits the input text into smaller chunks, sends each chunk to an LLM
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| text | The text to summarize. | str | Yes |
|
||||
| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| focus | The topic to focus on in the summary | str | No |
|
||||
| style | The style of the summary to generate. | "concise" \| "detailed" \| "bullet points" \| "numbered list" | No |
|
||||
| max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
|
||||
@@ -763,7 +763,7 @@ Configure agent_mode_max_iterations to control loop behavior: 0 for single decis
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| prompt | The prompt to send to the language model. | str | Yes |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| multiple_tool_calls | Whether to allow multiple tool calls in a single response. | bool | No |
|
||||
| sys_prompt | The system prompt to provide additional context to the model. | str | No |
|
||||
| conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
|
||||
|
||||
@@ -20,7 +20,7 @@ Configure timeouts for DOM settlement and page loading. Variables can be passed
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| browserbase_project_id | Browserbase project ID (required if using Browserbase) | str | Yes |
|
||||
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-3-7-sonnet-20250219" | No |
|
||||
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" | No |
|
||||
| url | URL to navigate to. | str | Yes |
|
||||
| action | Action to perform. Suggested actions are: click, fill, type, press, scroll, select from dropdown. For multi-step actions, add an entry for each step. | List[str] | Yes |
|
||||
| variables | Variables to use in the action. Variables contains data you want the action to use. | Dict[str, str] | No |
|
||||
@@ -65,7 +65,7 @@ Supports searching within iframes and configurable timeouts for dynamic content
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| browserbase_project_id | Browserbase project ID (required if using Browserbase) | str | Yes |
|
||||
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-3-7-sonnet-20250219" | No |
|
||||
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" | No |
|
||||
| url | URL to navigate to. | str | Yes |
|
||||
| instruction | Natural language description of elements or actions to discover. | str | Yes |
|
||||
| iframes | Whether to search within iframes. If True, Stagehand will search for actions within iframes. | bool | No |
|
||||
@@ -106,7 +106,7 @@ Use this to explore a page's interactive elements before building automated work
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| browserbase_project_id | Browserbase project ID (required if using Browserbase) | str | Yes |
|
||||
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-3-7-sonnet-20250219" | No |
|
||||
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" | No |
|
||||
| url | URL to navigate to. | str | Yes |
|
||||
| instruction | Natural language description of elements or actions to discover. | str | Yes |
|
||||
| iframes | Whether to search within iframes. If True, Stagehand will search for actions within iframes. | bool | No |
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Reference in New Issue
Block a user