pip uninstall numpy==2.0.2

!pip install numpy==1.26.4

Restart kernel

!pip install gensim openai==1.12.0 requests

import requests

import gensim.downloader as api

import re

model = api.load('word2vec-google-news-300')

similar_words = [word for word, _ in model.most_similar('happy', topn=5)]

original_prompt = "What makes a person truly happy?"

enriched_prompt = f"What are the factors that make a person feel {'/'.join(similar_words)}?"

openrouter_api_key = "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"

openrouter_url = "https://openrouter.ai/api/v1/chat/completions"

def get_openrouter_response(prompt):

    headers = {

        "Authorization": f"Bearer {openrouter_api_key}",

        "Content-Type": "application/json"

    }

    data = {

        "model": "openai/gpt-3.5-turbo",

        "messages": [{"role": "user", "content": prompt}],

        "max_tokens": 300

    }

    response = requests.post(openrouter_url, headers=headers, json=data)

    if response.status_code == 200:

        return response.json()["choices"][0]["message"]["content"].strip()

    else:

        return f"Error: {response.text}"

response_original = get_openrouter_response(original_prompt)

response_enriched = get_openrouter_response(enriched_prompt)

print(response_original)

print(response_enriched)

def count_sentences(text):

    sentences = re.split(r'[.!?]|\n-', text)

    sentences = [s.strip() for s in sentences if s.strip()]

    return len(sentences)

print("\nComparison of Responses:")

print("\nOriginal Prompt Response Length:", len(response_original))

print("Enriched Prompt Response Length:", len(response_enriched))

print("\nOriginal Prompt Response Detail:", count_sentences(response_original))

print("Enriched Prompt Response Detail:", count_sentences(response_enriched))