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expand input types #25

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89 changes: 57 additions & 32 deletions graphcore/graph.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,9 +14,14 @@
# along with this program. If not, see <https://www.gnu.org/licenses/>.

import logging
from typing import Optional, List, Annotated, Literal, TypeVar, Type, Protocol, cast, Any, Tuple, NotRequired, Iterable, Generic, Callable, Generator, Awaitable, Coroutine
from typing import (
Optional, List, Annotated, Literal, TypeVar, Type, Protocol, cast,
Any, Tuple, NotRequired, Iterable, Generic, Callable, Generator, Awaitable, Coroutine
)
from typing_extensions import TypedDict
from langchain_core.messages import ToolMessage, AnyMessage, SystemMessage, HumanMessage, BaseMessage, AIMessage, RemoveMessage
from langchain_core.messages import (
ToolMessage, AnyMessage, SystemMessage, HumanMessage, BaseMessage, AIMessage, RemoveMessage
)
from langchain_core.tools import InjectedToolCallId, BaseTool
from langchain_core.language_models.base import LanguageModelInput
from langchain_core.language_models.chat_models import BaseChatModel
Expand Down Expand Up @@ -154,6 +159,9 @@ class AsyncNodeFunction(Protocol[InputType, OutputType]):
def __call__(self, state: InputType) -> Coroutine[Any, Any, OutputType]:
...

type MessagePayloadType = str | list[str | dict] | dict
type RawMessageType = str | dict

type ChatNodeFunction[InputType] = NodeFunction[InputType, dict[str, list[BaseMessage]]]
type AsyncChatNodeFunction[InputType] = AsyncNodeFunction[InputType, dict[str, list[BaseMessage]]]
type AnyChatNodeFunction[StateT] = AsyncChatNodeFunction[StateT] | ChatNodeFunction[StateT]
Expand Down Expand Up @@ -268,8 +276,8 @@ def __call__(
...

def _get_summarizer_pure(
system_prompt: str,
initial_prompt: str | dict,
system_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
state_type: type[StateT],
context: SummaryConfig[StateT]
) -> PureFunction:
Expand All @@ -289,11 +297,11 @@ def to_return(state: StateT) -> PureFunctionGenerator:
resume_message = config.get_resume_prompt(state, summary)
config.on_summary(state, summary, resume_message)
# Handle initial_prompt as either str or dict (with cache_control)
initial_content: list[str | dict] = [initial_prompt]
initial_content: list[str | dict] = _normalize_list(initial_prompt)
return {
"messages": [
RemoveMessage(id="__remove_all__"),
SystemMessage(content=system_prompt),
SystemMessage(content=_normalize(system_prompt)),
HumanMessage(content=initial_content, display_tag="initial_prompt"),
HumanMessage(content=resume_message, display_tag="resume"),
]
Expand All @@ -318,11 +326,28 @@ def _default_conversation_node(state: MessagesState) -> dict[str, list[BaseMessa
I = TypeVar("I", bound=FlowInput)
O = TypeVar("O")

def _normalize(
s: MessagePayloadType
) -> str | list[str | dict]:
if isinstance(s, dict):
return [s]
else:
return s

def _normalize_list(
s: MessagePayloadType
) -> list[RawMessageType]:
if isinstance(s, dict) or isinstance(s, str):
return [s]
else:
return s.copy()


def _get_initial_pure(
t: Type[I],
output_state: Type[O],
sys_prompt: str,
initial_prompt: str | dict,
sys_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
) -> PureFunction[I, O]:
def impl(
state: I
Expand All @@ -333,15 +358,15 @@ def impl(
"""
initial_messages : List[AnyMessage] = [
SystemMessage(
sys_prompt
_normalize(sys_prompt)
)
]
front = state.get("front_matter", None)
if front is not None:
app = cast(List[HumanMessage], front)
app = cast(list[HumanMessage], front)
initial_messages.extend(app)

prompt_and_input_message: List[str | dict] = [initial_prompt]
prompt_and_input_message: list[str | dict] = _normalize_list(initial_prompt)
prompt_and_input_message.extend(state["input"])

initial_messages.append(
Expand Down Expand Up @@ -371,8 +396,8 @@ def impl(

def get_summarizer(
llm: LLM,
system_prompt: str,
initial_prompt: str | dict,
system_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
state_type: type[StateT],
context: SummaryConfig[StateT]
) -> ChatNodeFunction[StateT]:
Expand All @@ -383,8 +408,8 @@ def get_summarizer(

def get_async_summarizer(
llm: LLM,
system_prompt: str,
initial_prompt: str | dict,
system_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
state_type: type[StateT],
context: SummaryConfig[StateT]
) -> AsyncChatNodeFunction[StateT]:
Expand All @@ -397,8 +422,8 @@ class _SummarizerFact(Protocol):
def __call__(
self,
llm: LLM,
system_prompt: str,
initial_prompt: str | dict,
system_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
state_type: type[StateT],
context: SummaryConfig[StateT]
) -> AnyChatNodeFunction[StateT]:
Expand All @@ -407,8 +432,8 @@ def __call__(
def initial_node(
t: Type[InputState],
output_state: Type[StateT],
sys_prompt: str,
initial_prompt: str | dict,
sys_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
llm: LLM
) -> NodeFunction[InputState, StateT]:
return _stitch_sync_impl(
Expand All @@ -419,8 +444,8 @@ def initial_node(
def async_initial_node(
t: Type[InputState],
output_state: Type[StateT],
sys_prompt: str,
initial_prompt: str | dict,
sys_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
llm: LLM
) -> AsyncNodeFunction[InputState, StateT]:
return _stitch_async_impl(
Expand All @@ -433,8 +458,8 @@ def __call__(
self,
t: Type[InputState],
output_state: Type[StateT],
sys_prompt: str,
initial_prompt: str | dict,
sys_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
llm: LLM
) -> AnyNodeFunction[InputState, StateT]:
...
Expand Down Expand Up @@ -467,8 +492,8 @@ class Builder(
Generic[_BStateT, _BContextT, _BInputT]
):
def __init__(self):
self._initial_prompt : str | None = None
self._sys_prompt : str | None = None
self._initial_prompt : MessagePayloadType | None = None
self._sys_prompt : MessagePayloadType | None = None

self._summary_config : SummaryConfig[_BStateT] | None = None
self._unbound_llm : BaseChatModel | None = None
Expand Down Expand Up @@ -539,7 +564,7 @@ def with_input(self, t: type[_BInputTBind]) -> "Builder[_BStateT, _BContextT, _B
to_ret._conversation_handler = self._conversation_handler
return to_ret

def with_initial_prompt(self, prompt: str) -> "Builder[_BStateT, _BContextT, _BInputT]":
def with_initial_prompt(self, prompt: MessagePayloadType) -> "Builder[_BStateT, _BContextT, _BInputT]":
to_ret: "Builder[_BStateT, _BContextT, _BInputT]" = Builder()
self._copy_untyped_to_(to_ret)
self._copy_typed_to(to_ret)
Expand Down Expand Up @@ -677,8 +702,8 @@ def build_workflow(
state_class: Type[StateT],
input_type: Type[InputState],
tools_list: Iterable[BaseTool | SplitTool],
sys_prompt: str,
initial_prompt: str | dict,
sys_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
output_key: str,
unbound_llm: BaseChatModel,
output_schema: Optional[Type[OutputT]] = None,
Expand Down Expand Up @@ -706,8 +731,8 @@ def build_async_workflow(
state_class: Type[StateT],
input_type: Type[InputState],
tools_list: Iterable[BaseTool | SplitTool],
sys_prompt: str,
initial_prompt: str | dict,
sys_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
output_key: str,
unbound_llm: BaseChatModel,
output_schema: Optional[Type[OutputT]] = None,
Expand All @@ -734,8 +759,8 @@ def _build_workflow(
state_class: Type[StateT],
input_type: Type[InputState],
tools_list: Iterable[BaseTool | SplitTool],
sys_prompt: str,
initial_prompt: str | dict,
sys_prompt: MessagePayloadType,
initial_prompt: MessagePayloadType,
output_key: str,
unbound_llm: BaseChatModel,
output_schema: Optional[Type[OutputT]],
Expand Down
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