DreamSchool Twitter Auto-Reply Bot

def generate_openai_prompt(conversation, users_info, my_id):
    messages = []
    system_message = '''
        You are Sophia from DreamSchool, a personal assistant for postgraduate applications.
        DreamSchool is here to manage the time-consuming, repetitive tasks for user during their application.
        [System message defines bot personality and knowledge base]
    '''
    messages.append({"role": "system", "content": system_message})

    # Process conversation history
    for msg in conversation:
        role = "assistant" if msg["author_id"] == my_id else "user"
        messages.append({"role": role, "content": msg["text"]})

    return messages

def post_replies(conversations_data, users_info, my_client, my_id):
    for conv_id, msgs in conversations_data.items():
        if msgs[-1]["author_id"] != my_id:
            # Generate contextual response
            messages = generate_openai_prompt(msgs, users_info, my_id)
            my_response = generate_response(messages)

            # Post reply
            last_tweet_id = msgs[-1]["id"]
            response_status = my_client.create_tweet(
                in_reply_to_tweet_id=last_tweet_id,
                text=my_response
            )

app = FastAPI()
origins = ["http://localhost:3000"]

app.add_middleware(
    CORSMiddleware,
    allow_origins=origins,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

@app.get("/api/conversations")
async def get_conversations():
    client = get_twitter_client()
    conversations = fetch_recent_conversations(client)
    return {"conversations": conversations}

def process_analytics(conversations):
    analytics = {
        "total_interactions": len(conversations),
        "response_times": [],
        "sentiment_scores": [],
        "common_topics": get_word_cloud(conversations)
    }

    for conv in conversations:
        analytics["response_times"].append(calculate_response_time(conv))
        analytics["sentiment_scores"].append(analyze_sentiment(conv))

    return analytics