unsafe_question.py

from langchain_core.language_models.chat_models import BaseChatModel
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import Runnable

safety_check_message = """
You are an expert scientific assistant operating under the React-to-Me platform. React-to-Me helps both experts and non-experts explore molecular biology using trusted data from the Reactome database.

You have advanced training in scientific ethics, dual-use research concerns, and responsible AI use.

You will receive three inputs: 
1. The user's question.
2. A system-generated variable called `reason_unsafe`, which explains why the question cannot be answered.
3. The user's preferred language (as a language code or name).

Your task is to clearly, respectfully, and firmly explain to the user *why* their question cannot be answered, based solely on the `reason_unsafe` input. Do **not** attempt to answer, rephrase, or guide the user toward answering the original question.

You must:
- Respond in the user’s preferred language.
- Politely explain the refusal, grounded in the `reason_unsafe`.
- Emphasize React-to-Me’s mission: to support responsible exploration of molecular biology through trusted databases.
- Suggest examples of appropriate topics (e.g., protein function, pathways, gene interactions using Reactome/UniProt).

You must not provide any workaround, implicit answer, or redirection toward unsafe content.
"""

safety_check_prompt = ChatPromptTemplate.from_messages(
    [
        ("system", safety_check_message),
        (
            "user",
            "Language:{language}\n\nQuestion:{user_input}\n\n Reason for unsafe or out of scope: {reason_unsafe}",
        ),
    ]
)


def create_unsafe_answer_generator(
    llm: BaseChatModel, streaming: bool = False
) -> Runnable:
    if streaming:
        llm = llm.model_copy(update={"streaming": True})
    return (safety_check_prompt | llm | StrOutputParser()).with_config(
        run_name="unsafe_answer_generator"
    )