Quick Rate limiting, Sentiment analysis, Safe AI response in Python for GenAI apps

import time

from functools import wraps

def rate_limit(calls: int, period: float):

    min_interval = period / calls

    last_called = [0.0]

    def decorator(func):

        @wraps(func)

        def wrapper(*args, **kwargs):

            elapsed = time.time() - last_called[0]

            if elapsed < min_interval:

                time.sleep(min_interval - elapsed)

            result = func(*args, **kwargs)

            last_called[0] = time.time()

            return result

        return wrapper

    return decorator

@rate_limit(calls=3, period=1.0)  # 3 calls per second

def rate_limited_ai(state: AgentState) -> AgentState:

    return ai(state)'

from textblob import TextBlob

def analyze_sentiment(text: str) -> float:

    """Returns sentiment score between -1 (negative) and 1 (positive)"""

    return TextBlob(text).sentiment.polarity

def enhanced_ai(state: AgentState) -> AgentState:

    messages = state["messages"]

    last_message = messages[-1].content

    # Analyze user sentiment

    sentiment = analyze_sentiment(last_message)

    # Adjust system prompt based on sentiment

    base_prompt = "You are a helpful AI assistant."

    if sentiment < -0.3:

        system_prompt = f"{base_prompt} Please respond with extra empathy and support."

    elif sentiment > 0.3:

        system_prompt = f"{base_prompt} Match the user's positive energy."

    else:

        system_prompt = base_prompt

    llm = Ollama(base_url="<http://localhost:11434>", model="llama3")

    context = f"{system_prompt}\\\\n\\\\nUser: {last_message}"

    response = llm.invoke(context)

    state["messages"].append(AIMessage(content=response))

    state["next"] = "human"

    return state

 def safe_ai_response(state: AgentState) -> AgentState:

    try:

        return ai(state)

    except Exception as e:

        error_message = f"An error occurred: {str(e)}"

        state["messages"].append(AIMessage(content=error_message))

        state["next"] = "human"

        return state