Building a Responsible AI Chatbot

import openai
import os

openai_client = openai.OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

SYSTEM_PROMPT = """You are CloudDash Support, a helpful assistant for
CloudDash — a cloud monitoring dashboard. Answer questions about
pricing, features, setup, and troubleshooting. Be concise and accurate.
If you don't know something, say so."""


def chat(user_message: str, history: list[dict] = None) -> str:
    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
    if history:
        messages.extend(history)
    messages.append({"role": "user", "content": user_message})

    response = openai_client.chat.completions.create(
        model="gpt-4o",
        messages=messages,
        temperature=0.3,
    )
    return response.choices[0].message.content


reply = chat("What pricing plans do you offer?")
print(reply)

from rail_score_sdk import RailScoreClient
import os

rail = RailScoreClient(api_key=os.getenv("RAIL_API_KEY"))

reply = chat("What pricing plans do you offer?")

result = rail.eval(content=reply, mode="basic")

print(f"Overall Score: {result.rail_score.score}")
print(f"Confidence:    {result.rail_score.confidence}")
print()
for dim_name, dim_score in result.dimension_scores.items():
    print(f"  {dim_name:15s} {dim_score.score}")

result = rail.eval(content=reply, mode="deep")

print(f"Overall: {result.rail_score.score}")
print()

for dim_name, detail in result.dimension_scores.items():
    print(f"--- {dim_name} (score: {detail.score}) ---")
    print(f"  Explanation: {detail.explanation}")
    if detail.issues:
        print(f"  Issues: {', '.join(detail.issues)}")
    if detail.suggestions:
        print(f"  Suggestion: {detail.suggestions[0]}")
    print()