something I threw together for tracking sentiment of keywords for a company, with the help of ai

sentiment_serp_keyword_tracking_ai.py

import os 
import marvin
from serpapi import Client as SerpApi


serpapi = SerpApi(api_key=os.environ['SERPAPI_API_KEY'])


@marvin.ai_fn
def get_suggested_keywords(org_name: str) -> list[str]:
    """
    Given an `org_name`, returns a list of suggested keywords to rank / track for SEO for that organization.
    """



@marvin.ai_fn
def sentiment_score(texts: list[str]) -> list[float]:
    """
    Given a list of `texts`, returns a list of numbers between 1 (positive) and
    -1 (negative) indicating their respective sentiment scores.
    """

def get_keyword_serp(keyword: str, with_snippet_sentiment=False) -> dict:
    s = serpapi.search(
        engine="google",
        q=keyword
    )

    if with_snippet_sentiment:
        return score_serp_descriptions(s)
    
    return s.as_dict()



def score_serp_descriptions(serp: dict) -> dict:
    scores = [sentiment_score([result['snippet']]) for result in serp['organic_results']]
    
    for i, score in enumerate(scores):
        serp['organic_results'][i]['sentiment-score'] = score

    return serp


# ----

company = "Apple"
print(f"Company name: {company}.")

serp = get_keyword_serp(company)
suggested_keywords = get_suggested_keywords(company)
print(f"Suggested keywords to track: {suggested_keywords}")

for keyword in suggested_keywords:
    print()
    print(f"Getting SERP for {keyword} and scoring snippet sentiment.")

    s = get_keyword_serp(keyword, with_snippet_sentiment=True)
    for result in s['organic_results']:
        print(f"{result['position']}: {result['title']}: {result['sentiment-score']}")

just a neat idea. not too much to see here