refactor transformation, add graph and admin

open_notebook/graphs/prompt.py

@@ -0,0 +1,46 @@
+from typing import Any, Optional
+
+from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_core.runnables import (
+    RunnableConfig,
+)
+from langgraph.graph import END, START, StateGraph
+from loguru import logger
+from typing_extensions import TypedDict
+
+from open_notebook.graphs.utils import provision_langchain_model
+from open_notebook.prompter import Prompter
+
+
+class PatternChainState(TypedDict):
+    prompt: str
+    parser: Optional[Any]
+    input_text: str
+    output: str
+
+
+def call_model(state: dict, config: RunnableConfig) -> dict:
+    content = state["input_text"]
+    system_prompt = Prompter(
+        prompt_text=state["prompt"], parser=state.get("parser")
+    ).render(data=state)
+    logger.warning(content)
+    payload = [SystemMessage(content=system_prompt)] + [HumanMessage(content=content)]
+    chain = provision_langchain_model(
+        str(payload),
+        config.get("configurable", {}).get("model_id"),
+        "transformation",
+        max_tokens=5000,
+    )
+
+    response = chain.invoke(payload)
+
+    return {"output": response.content}
+
+
+agent_state = StateGraph(PatternChainState)
+agent_state.add_node("agent", call_model)
+agent_state.add_edge(START, "agent")
+agent_state.add_edge("agent", END)
+
+graph = agent_state.compile()