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import inspect
from abc import ABC, abstractmethod
from enum import Enum
from typing import (
Any,
ClassVar,
Generator,
Generic,
Optional,
Type,
TypeVar,
cast,
get_origin,
)
import jsonref
import jsonschema
from prisma.models import AgentBlock
from pydantic import BaseModel
from backend.util import json
from backend.util.settings import Config
from .model import (
CREDENTIALS_FIELD_NAME,
ContributorDetails,
Credentials,
CredentialsMetaInput,
)
app_config = Config()
BlockData = tuple[str, Any] # Input & Output data should be a tuple of (name, data).
BlockInput = dict[str, Any] # Input: 1 input pin consumes 1 data.
BlockOutput = Generator[BlockData, None, None] # Output: 1 output pin produces n data.
CompletedBlockOutput = dict[str, list[Any]] # Completed stream, collected as a dict.
class BlockType(Enum):
STANDARD = "Standard"
INPUT = "Input"
OUTPUT = "Output"
NOTE = "Note"
WEBHOOK = "Webhook"
WEBHOOK_MANUAL = "Webhook (manual)"
AGENT = "Agent"
class BlockCategory(Enum):
AI = "Block that leverages AI to perform a task."
SOCIAL = "Block that interacts with social media platforms."
TEXT = "Block that processes text data."
SEARCH = "Block that searches or extracts information from the internet."
BASIC = "Block that performs basic operations."
INPUT = "Block that interacts with input of the graph."
OUTPUT = "Block that interacts with output of the graph."
LOGIC = "Programming logic to control the flow of your agent"
COMMUNICATION = "Block that interacts with communication platforms."
DEVELOPER_TOOLS = "Developer tools such as GitHub blocks."
DATA = "Block that interacts with structured data."
HARDWARE = "Block that interacts with hardware."
AGENT = "Block that interacts with other agents."
CRM = "Block that interacts with CRM services."
def dict(self) -> dict[str, str]:
return {"category": self.name, "description": self.value}
class BlockSchema(BaseModel):
cached_jsonschema: ClassVar[dict[str, Any]]
@classmethod
def jsonschema(cls) -> dict[str, Any]:
if cls.cached_jsonschema:
return cls.cached_jsonschema
model = jsonref.replace_refs(cls.model_json_schema(), merge_props=True)
def ref_to_dict(obj):
if isinstance(obj, dict):
# OpenAPI <3.1 does not support sibling fields that has a $ref key
# So sometimes, the schema has an "allOf"/"anyOf"/"oneOf" with 1 item.
keys = {"allOf", "anyOf", "oneOf"}
one_key = next((k for k in keys if k in obj and len(obj[k]) == 1), None)
if one_key:
obj.update(obj[one_key][0])
return {
key: ref_to_dict(value)
for key, value in obj.items()
if not key.startswith("$") and key != one_key
}
elif isinstance(obj, list):
return [ref_to_dict(item) for item in obj]
return obj
cls.cached_jsonschema = cast(dict[str, Any], ref_to_dict(model))
# Set default properties values
for field in cls.cached_jsonschema.get("properties", {}).values():
if isinstance(field, dict) and "advanced" not in field:
field["advanced"] = True
return cls.cached_jsonschema
@classmethod
def validate_data(cls, data: BlockInput) -> str | None:
return json.validate_with_jsonschema(schema=cls.jsonschema(), data=data)
@classmethod
def validate_field(cls, field_name: str, data: BlockInput) -> str | None:
"""
Validate the data against a specific property (one of the input/output name).
Returns the validation error message if the data does not match the schema.
"""
model_schema = cls.jsonschema().get("properties", {})
if not model_schema:
return f"Invalid model schema {cls}"
property_schema = model_schema.get(field_name)
if not property_schema:
return f"Invalid property name {field_name}"
try:
jsonschema.validate(json.to_dict(data), property_schema)
return None
except jsonschema.ValidationError as e:
return str(e)
@classmethod
def get_fields(cls) -> set[str]:
return set(cls.model_fields.keys())
@classmethod
def get_required_fields(cls) -> set[str]:
return {
field
for field, field_info in cls.model_fields.items()
if field_info.is_required()
}
@classmethod
def __pydantic_init_subclass__(cls, **kwargs):
"""Validates the schema definition. Rules:
- Only one `CredentialsMetaInput` field may be present.
- This field MUST be called `credentials`.
- A field that is called `credentials` MUST be a `CredentialsMetaInput`.
"""
super().__pydantic_init_subclass__(**kwargs)
# Reset cached JSON schema to prevent inheriting it from parent class
cls.cached_jsonschema = {}
credentials_fields = [
field_name
for field_name, info in cls.model_fields.items()
if (
inspect.isclass(info.annotation)
and issubclass(
get_origin(info.annotation) or info.annotation,
CredentialsMetaInput,
)
)
]
if len(credentials_fields) > 1:
raise ValueError(
f"{cls.__qualname__} can only have one CredentialsMetaInput field"
)
elif (
len(credentials_fields) == 1
and credentials_fields[0] != CREDENTIALS_FIELD_NAME
):
raise ValueError(
f"CredentialsMetaInput field on {cls.__qualname__} "
"must be named 'credentials'"
)
elif (
len(credentials_fields) == 0
and CREDENTIALS_FIELD_NAME in cls.model_fields.keys()
):
raise TypeError(
f"Field 'credentials' on {cls.__qualname__} "
f"must be of type {CredentialsMetaInput.__name__}"
)
if credentials_field := cls.model_fields.get(CREDENTIALS_FIELD_NAME):
credentials_input_type = cast(
CredentialsMetaInput, credentials_field.annotation
)
credentials_input_type.validate_credentials_field_schema(cls)
BlockSchemaInputType = TypeVar("BlockSchemaInputType", bound=BlockSchema)
BlockSchemaOutputType = TypeVar("BlockSchemaOutputType", bound=BlockSchema)
class EmptySchema(BlockSchema):
pass
# --8<-- [start:BlockWebhookConfig]
class BlockManualWebhookConfig(BaseModel):
"""
Configuration model for webhook-triggered blocks on which
the user has to manually set up the webhook at the provider.
"""
provider: str
"""The service provider that the webhook connects to"""
webhook_type: str
"""
Identifier for the webhook type. E.g. GitHub has repo and organization level hooks.
Only for use in the corresponding `WebhooksManager`.
"""
event_filter_input: str = ""
"""
Name of the block's event filter input.
Leave empty if the corresponding webhook doesn't have distinct event/payload types.
"""
event_format: str = "{event}"
"""
Template string for the event(s) that a block instance subscribes to.
Applied individually to each event selected in the event filter input.
Example: `"pull_request.{event}"` -> `"pull_request.opened"`
"""
class BlockWebhookConfig(BlockManualWebhookConfig):
"""
Configuration model for webhook-triggered blocks for which
the webhook can be automatically set up through the provider's API.
"""
resource_format: str
"""
Template string for the resource that a block instance subscribes to.
Fields will be filled from the block's inputs (except `payload`).
Example: `f"{repo}/pull_requests"` (note: not how it's actually implemented)
Only for use in the corresponding `WebhooksManager`.
"""
# --8<-- [end:BlockWebhookConfig]
class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
def __init__(
self,
id: str = "",
description: str = "",
contributors: list[ContributorDetails] = [],
categories: set[BlockCategory] | None = None,
input_schema: Type[BlockSchemaInputType] = EmptySchema,
output_schema: Type[BlockSchemaOutputType] = EmptySchema,
test_input: BlockInput | list[BlockInput] | None = None,
test_output: BlockData | list[BlockData] | None = None,
test_mock: dict[str, Any] | None = None,
test_credentials: Optional[Credentials] = None,
disabled: bool = False,
static_output: bool = False,
block_type: BlockType = BlockType.STANDARD,
webhook_config: Optional[BlockWebhookConfig | BlockManualWebhookConfig] = None,
):
"""
Initialize the block with the given schema.
Args:
id: The unique identifier for the block, this value will be persisted in the
DB. So it should be a unique and constant across the application run.
Use the UUID format for the ID.
description: The description of the block, explaining what the block does.
contributors: The list of contributors who contributed to the block.
input_schema: The schema, defined as a Pydantic model, for the input data.
output_schema: The schema, defined as a Pydantic model, for the output data.
test_input: The list or single sample input data for the block, for testing.
test_output: The list or single expected output if the test_input is run.
test_mock: function names on the block implementation to mock on test run.
disabled: If the block is disabled, it will not be available for execution.
static_output: Whether the output links of the block are static by default.
"""
self.id = id
self.input_schema = input_schema
self.output_schema = output_schema
self.test_input = test_input
self.test_output = test_output
self.test_mock = test_mock
self.test_credentials = test_credentials
self.description = description
self.categories = categories or set()
self.contributors = contributors or set()
self.disabled = disabled
self.static_output = static_output
self.block_type = block_type
self.webhook_config = webhook_config
self.execution_stats = {}
if self.webhook_config:
if isinstance(self.webhook_config, BlockWebhookConfig):
# Enforce presence of credentials field on auto-setup webhook blocks
if CREDENTIALS_FIELD_NAME not in self.input_schema.model_fields:
raise TypeError(
"credentials field is required on auto-setup webhook blocks"
)
self.block_type = BlockType.WEBHOOK
else:
self.block_type = BlockType.WEBHOOK_MANUAL
# Enforce shape of webhook event filter, if present
if self.webhook_config.event_filter_input:
event_filter_field = self.input_schema.model_fields[
self.webhook_config.event_filter_input
]
if not (
isinstance(event_filter_field.annotation, type)
and issubclass(event_filter_field.annotation, BaseModel)
and all(
field.annotation is bool
for field in event_filter_field.annotation.model_fields.values()
)
):
raise NotImplementedError(
f"{self.name} has an invalid webhook event selector: "
"field must be a BaseModel and all its fields must be boolean"
)
# Enforce presence of 'payload' input
if "payload" not in self.input_schema.model_fields:
raise TypeError(
f"{self.name} is webhook-triggered but has no 'payload' input"
)
# Disable webhook-triggered block if webhook functionality not available
if not app_config.platform_base_url:
self.disabled = True
@classmethod
def create(cls: Type["Block"]) -> "Block":
return cls()
@abstractmethod
def run(self, input_data: BlockSchemaInputType, **kwargs) -> BlockOutput:
"""
Run the block with the given input data.
Args:
input_data: The input data with the structure of input_schema.
Returns:
A Generator that yields (output_name, output_data).
output_name: One of the output name defined in Block's output_schema.
output_data: The data for the output_name, matching the defined schema.
"""
pass
def run_once(self, input_data: BlockSchemaInputType, output: str, **kwargs) -> Any:
for name, data in self.run(input_data, **kwargs):
if name == output:
return data
raise ValueError(f"{self.name} did not produce any output for {output}")
def merge_stats(self, stats: dict[str, Any]) -> dict[str, Any]:
for key, value in stats.items():
if isinstance(value, dict):
self.execution_stats.setdefault(key, {}).update(value)
elif isinstance(value, (int, float)):
self.execution_stats.setdefault(key, 0)
self.execution_stats[key] += value
elif isinstance(value, list):
self.execution_stats.setdefault(key, [])
self.execution_stats[key].extend(value)
else:
self.execution_stats[key] = value
return self.execution_stats
@property
def name(self):
return self.__class__.__name__
def to_dict(self):
return {
"id": self.id,
"name": self.name,
"inputSchema": self.input_schema.jsonschema(),
"outputSchema": self.output_schema.jsonschema(),
"description": self.description,
"categories": [category.dict() for category in self.categories],
"contributors": [
contributor.model_dump() for contributor in self.contributors
],
"staticOutput": self.static_output,
"uiType": self.block_type.value,
}
def execute(self, input_data: BlockInput, **kwargs) -> BlockOutput:
if error := self.input_schema.validate_data(input_data):
raise ValueError(
f"Unable to execute block with invalid input data: {error}"
)
for output_name, output_data in self.run(
self.input_schema(**input_data), **kwargs
):
if output_name == "error":
raise RuntimeError(output_data)
if self.block_type == BlockType.STANDARD and (
error := self.output_schema.validate_field(output_name, output_data)
):
raise ValueError(f"Block produced an invalid output data: {error}")
yield output_name, output_data
# ======================= Block Helper Functions ======================= #
def get_blocks() -> dict[str, Type[Block]]:
from backend.blocks import AVAILABLE_BLOCKS # noqa: E402
return AVAILABLE_BLOCKS
async def initialize_blocks() -> None:
for cls in get_blocks().values():
block = cls()
existing_block = await AgentBlock.prisma().find_first(
where={"OR": [{"id": block.id}, {"name": block.name}]}
)
if not existing_block:
await AgentBlock.prisma().create(
data={
"id": block.id,
"name": block.name,
"inputSchema": json.dumps(block.input_schema.jsonschema()),
"outputSchema": json.dumps(block.output_schema.jsonschema()),
}
)
continue
input_schema = json.dumps(block.input_schema.jsonschema())
output_schema = json.dumps(block.output_schema.jsonschema())
if (
block.id != existing_block.id
or block.name != existing_block.name
or input_schema != existing_block.inputSchema
or output_schema != existing_block.outputSchema
):
await AgentBlock.prisma().update(
where={"id": existing_block.id},
data={
"id": block.id,
"name": block.name,
"inputSchema": input_schema,
"outputSchema": output_schema,
},
)
def get_block(block_id: str) -> Block | None:
cls = get_blocks().get(block_id)
return cls() if cls else None