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January 14, 2026 05:12
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News sentiment analysis with GPT-5.2
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| import os | |
| import json | |
| from typing import List, Literal | |
| from pydantic import BaseModel | |
| from openai import OpenAI | |
| NEWSAPI_KEY = "NEWSAPI_KEY" | |
| class AnalysisResult(BaseModel): | |
| article: str | |
| sentiment: Literal["Positive", "Negative"] | |
| signal: Literal["Buy", "Sell"] | |
| impact: Literal["low", "medium", "high"] | |
| class NewsResponse(BaseModel): | |
| results: List[AnalysisResult] | |
| client = OpenAI(api_key="OPENAI_KEY") | |
| def analyze_articles(article_texts: List[str]): | |
| combined_content = "\n\n".join(article_texts) | |
| response = client.beta.chat.completions.parse( | |
| model="gpt-5.2" | |
| messages=[ | |
| {"role": "system", "content": "You are a financial analyst. Analyze the following articles and provide a structured sentiment analysis."}, | |
| {"role": "user", "content": f"Analyze these articles:\n{combined_content}"} | |
| ], | |
| response_format=NewsResponse, | |
| ) | |
| return response.choices[0].message.parsed | |
| if __name__ == "__main__": | |
| url = f"https://newsapi.org/v2/everything?q={ticker}&from={from_date}&to={to_date}&sortBy=publishedAt&language=en&apiKey={NEWSAPI_KEY}" | |
| response = requests.get(url) | |
| response.raise_for_status() | |
| data = response.json() | |
| if data['status'] != 'ok' or data['totalResults'] == 0: | |
| return pd.DataFrame() | |
| articles = [] | |
| for article in data['articles']: | |
| articles.append({ | |
| 'title': article['title'], | |
| 'source': article['source']['name'], | |
| 'published_at': datetime.strptime(article['publishedAt'], '%Y-%m-%dT%H:%M:%SZ'), | |
| 'url': article['url'], | |
| 'description': article['description'][:200] + "..." if article['description'] and len(article['description']) > 200 else article['description'] | |
| }) | |
| structured_data = analyze_articles(articles) | |
| print(json.dumps(structured_data.dict(), indent=2)) |
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