| |
| from utils.llm_client import llm_client, llm_so_client |
| from pydantic import BaseModel, Field |
|
|
| class Score(BaseModel): |
| score: int |
|
|
| def assign_certainty_score(st): |
| print(f"\nassign certainty score: {st.session_state.state.discrepancies}\n") |
| text = "## A. Certainty Score\n" |
| index = 0 |
| |
| for item in st.session_state.state.discrepancies: |
| index += 1 |
| |
| system_prompt = "You are a compliance analyst." |
| |
| user_messages = ( |
| f"Assess the following discrepancy and assign a certainty score from 0 to 100 indicating how certain you are that this is a real issue.\n\n" |
| f"**Discrepancy:**\n{item['discrepancy']}\n\n" |
| "Provide the certainty score as a single number." |
| ) |
| item['certainty_score'] = llm_so_client(system_prompt, user_messages, responseModel=Score) |
|
|
| text += f"1. System prompt:\n```\n{system_prompt}\n```\n" |
| text += f"2. User message:\n```\n{user_messages}\n```\n" |
| text += f"3. Score:\n```\n {item['certainty_score']}\n```\n" |
| return text |
|
|
|
|
| def assign_severity_score(st): |
| print(f"\nassign severity score: {st.session_state.state.discrepancies}\n") |
| text = "## B. Severity Score\n" |
| |
| index = 0 |
| for item in st.session_state.state.discrepancies: |
| index += 1 |
| system_prompt = "You are a risk assessment expert." |
|
|
| user_messages = ( |
| f"Given the following discrepancy, assign a severity score from 0 to 100 where 0 is not severe and 100 is very severe.\n\n" |
| f"**Discrepancy:**\n{item['discrepancy']}\n\n" |
| "Provide the severity score as a single number." |
| ) |
| |
| item['severity_score'] = llm_so_client(system_prompt, user_messages, responseModel=Score) |
| |
| text += f"### DISCREPANCIE {index}\n" |
| text += f"1. System prompt:\n```\n{system_prompt}\n```\n" |
| text += f"2. User message:\n```\n{user_messages}\n```\n" |
| text += f"3. Score:\n```\n {item['certainty_score']}\n```\n" |
| return text |
