base.py•5.55 kB
"""Base classes for FastMCP prompts."""
import inspect
import json
from collections.abc import Callable
from typing import Any, Awaitable, Literal, Sequence
import pydantic_core
from pydantic import BaseModel, Field, TypeAdapter, validate_call
from mcp.types import EmbeddedResource, ImageContent, TextContent
CONTENT_TYPES = TextContent | ImageContent | EmbeddedResource
class Message(BaseModel):
"""Base class for all prompt messages."""
role: Literal["user", "assistant"]
content: CONTENT_TYPES
def __init__(self, content: str | CONTENT_TYPES, **kwargs):
if isinstance(content, str):
content = TextContent(type="text", text=content)
super().__init__(content=content, **kwargs)
class UserMessage(Message):
"""A message from the user."""
role: Literal["user", "assistant"] = "user"
def __init__(self, content: str | CONTENT_TYPES, **kwargs):
super().__init__(content=content, **kwargs)
class AssistantMessage(Message):
"""A message from the assistant."""
role: Literal["user", "assistant"] = "assistant"
def __init__(self, content: str | CONTENT_TYPES, **kwargs):
super().__init__(content=content, **kwargs)
message_validator = TypeAdapter(UserMessage | AssistantMessage)
SyncPromptResult = (
str | Message | dict[str, Any] | Sequence[str | Message | dict[str, Any]]
)
PromptResult = SyncPromptResult | Awaitable[SyncPromptResult]
class PromptArgument(BaseModel):
"""An argument that can be passed to a prompt."""
name: str = Field(description="Name of the argument")
description: str | None = Field(
None, description="Description of what the argument does"
)
required: bool = Field(
default=False, description="Whether the argument is required"
)
class Prompt(BaseModel):
"""A prompt template that can be rendered with parameters."""
name: str = Field(description="Name of the prompt")
description: str | None = Field(
None, description="Description of what the prompt does"
)
arguments: list[PromptArgument] | None = Field(
None, description="Arguments that can be passed to the prompt"
)
fn: Callable = Field(exclude=True)
@classmethod
def from_function(
cls,
fn: Callable[..., PromptResult],
name: str | None = None,
description: str | None = None,
) -> "Prompt":
"""Create a Prompt from a function.
The function can return:
- A string (converted to a message)
- A Message object
- A dict (converted to a message)
- A sequence of any of the above
"""
func_name = name or fn.__name__
if func_name == "<lambda>":
raise ValueError("You must provide a name for lambda functions")
# Get schema from TypeAdapter - will fail if function isn't properly typed
parameters = TypeAdapter(fn).json_schema()
# Convert parameters to PromptArguments
arguments = []
if "properties" in parameters:
for param_name, param in parameters["properties"].items():
required = param_name in parameters.get("required", [])
arguments.append(
PromptArgument(
name=param_name,
description=param.get("description"),
required=required,
)
)
# ensure the arguments are properly cast
fn = validate_call(fn)
return cls(
name=func_name,
description=description or fn.__doc__ or "",
arguments=arguments,
fn=fn,
)
async def render(self, arguments: dict[str, Any] | None = None) -> list[Message]:
"""Render the prompt with arguments."""
# Validate required arguments
if self.arguments:
required = {arg.name for arg in self.arguments if arg.required}
provided = set(arguments or {})
missing = required - provided
if missing:
raise ValueError(f"Missing required arguments: {missing}")
try:
# Call function and check if result is a coroutine
result = self.fn(**(arguments or {}))
if inspect.iscoroutine(result):
result = await result
# Validate messages
if not isinstance(result, (list, tuple)):
result = [result]
# Convert result to messages
messages = []
for msg in result:
try:
if isinstance(msg, Message):
messages.append(msg)
elif isinstance(msg, dict):
msg = message_validator.validate_python(msg)
messages.append(msg)
elif isinstance(msg, str):
messages.append(
UserMessage(content=TextContent(type="text", text=msg))
)
else:
msg = json.dumps(pydantic_core.to_jsonable_python(msg))
messages.append(Message(role="user", content=msg))
except Exception:
raise ValueError(
f"Could not convert prompt result to message: {msg}"
)
return messages
except Exception as e:
raise ValueError(f"Error rendering prompt {self.name}: {e}")