Construire un chatbot IA responsable

import openai
import os

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

SYSTEM_PROMPT = """Vous êtes CloudDash Support, un assistant utile pour
CloudDash — un tableau de bord de surveillance cloud. Répondez aux questions sur
les prix, les fonctionnalités, la configuration et le dépannage. Soyez concis et précis.
Si vous ne savez pas quelque chose, dites-le."""


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("Quels plans tarifaires proposez-vous ?")
print(reply)

from rail_score_sdk import RailScoreClient
import os

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

reply = chat("Quels plans tarifaires proposez-vous ?")

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

print(f"Score global : {result.rail_score.score}")
print(f"Confiance :    {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"Global : {result.rail_score.score}")
print()

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