Working on Prompt rework

chatsky/conditions/llm.py

@@ -9,7 +9,7 @@
 from chatsky.core import BaseCondition, Context
 from chatsky.core.script_function import AnyResponse
 from chatsky.llm.methods import BaseMethod
-from chatsky.llm.utils import context_to_history, message_to_langchain
+from chatsky.llm.langchain_context import context_to_history, message_to_langchain
 from chatsky.llm.filters import BaseHistoryFilter, DefaultFilter
 
 

chatsky/llm/utils.py → chatsky/llm/langchain_context.py

@@ -12,6 +12,7 @@
 from chatsky.core.script_function import ConstResponse
 from chatsky.llm._langchain_imports import HumanMessage, SystemMessage, AIMessage, check_langchain_available
 from chatsky.llm.filters import BaseHistoryFilter
+from chatsky.llm.prompt import Prompt, DesaultPositionConfig
 
 
 async def message_to_langchain(
@@ -80,3 +81,15 @@ async def context_to_history(
         history.append(await message_to_langchain(req, ctx=ctx, max_size=max_size))
         history.append(await message_to_langchain(resp, ctx=ctx, source="ai", max_size=max_size))
     return history
+
+# get a list of messages to pass to LLM from context and prompts
+# called in LLM_API
+def get_langchain_context(
+        system_prompt: Prompt,
+        ctx: Context,
+        call_prompt,
+        prompt_misc_filter: str=r"prompt",  # r"prompt" -> extract misc prompts
+        postition_config: DesaultPositionConfig=DesaultPositionConfig,
+        **history_args,
+    ):
+        history = context_to_history(ctx, history_args)

chatsky/llm/prompt.py

@@ -0,0 +1,32 @@
+from typing import Optional, Union
+from pydantic import BaseModel, model_validator
+from chatsky.core import BaseResponse, BasePriority, AnyPriority, AnyResponse, MessageInitTypes, Message
+
+
+class DesaultPositionConfig(BaseModel):
+    system_prompt: float = 0
+    history: float = 1
+    misc_prompt: float = 2
+    call_prompt: float = 3
+    last_response: float = 4
+
+
+class Prompt(BaseModel):
+    prompt: AnyResponse
+    position: Optional[AnyPriority] = None
+
+    def __init__(
+        self,
+        prompt: Union[MessageInitTypes, BaseResponse],
+        position: Optional[Union[float, BasePriority]] = None
+    ):
+        super().__init__(prompt=prompt, position=position)
+
+    @model_validator(mode="before")
+    @classmethod
+    def validate_from_message(cls, data):
+            # MISC: {"prompt": "message", "prompt": Message("text"), "prompt": FilledTemplate(), "prompt": Prompt(prompt=FilledTemplate(), position=-2)
+            # Prompt.model_validate
+        if isinstance(data, (str, Message, BaseResponse)):
+            return {"prompt": data}
+        return data

chatsky/responses/llm.py

@@ -11,7 +11,7 @@
 
 from chatsky.core.message import Message
 from chatsky.core.context import Context
-from chatsky.llm.utils import message_to_langchain, context_to_history
+from chatsky.llm.langchain_context import message_to_langchain, context_to_history
 from chatsky.llm._langchain_imports import check_langchain_available
 from chatsky.llm.filters import BaseHistoryFilter, DefaultFilter
 from chatsky.core.script_function import BaseResponse, AnyResponse

tests/llm/test_llm.py

@@ -7,7 +7,7 @@
 from chatsky.conditions.llm import LLMCondition
 from chatsky.slots.llm import LLMSlot, LLMGroupSlot
 from chatsky.slots.slots import SlotNotExtracted, ExtractedGroupSlot
-from chatsky.llm.utils import message_to_langchain, context_to_history
+from chatsky.llm.langchain_context import message_to_langchain, context_to_history
 from chatsky.llm.filters import IsImportant, FromModel
 from chatsky.llm.methods import Contains, LogProb, BaseMethod
 from chatsky.core.message import Message