,
Was $199, now $99. Use code SAVE50.
" link: "https://example.com/deal?iref=rss-c142" ``` **Output**: ```json { "title": "Sony Headphones for $99 + free shipping", "summary": "Sony Headphones originally priced at $199, now available for $99 with free shipping. Use promo code SAVE50 at checkout.", "url": "https://example.com/deal" } ``` """ def gpt_parse(soup: str) -> Optional[Dict[str, str]]: """ Parse RSS feed content using GPT to extract title, summary, and URL. Args: soup: Raw RSS feed content (HTML/text) Returns: Dictionary with title, summary, url keys or None if parsing fails """ text_to_summarize = soup if not text_to_summarize: return None try: response = openai.chat.completions.create( model="gpt-4o-mini", temperature=0.2, messages=[ {"role": "system", "content": SYSTEM_PROMPT}, {"role": "user", "content": text_to_summarize}, ], ) res_text = response.choices[0].message.content parsed_data = json.loads(res_text) if all( key in parsed_data and parsed_data[key] for key in ["title", "summary", "url"] ): return { "title": parsed_data["title"], "summary": parsed_data["summary"], "url": parsed_data["url"], } else: print(f"Missing or empty required fields in response: {parsed_data}") return None except json.JSONDecodeError as e: print(f"Error parsing JSON from OpenAI response: {e}") return None except Exception as e: print(f"Error calling OpenAI: {e}") return None class ScrapedDeal: """ A class to represent a Deal retrieved from an RSS feed """ category: str title: str summary: str url: str details: str features: str def __init__(self, entry: Dict[str, str]): """ Populate this instance based on the provided dict """ self.title = entry["title"] self.summary = entry["summary"] self.url = entry["url"] self.details = self.summary self.features = "" def __repr__(self): """ Return a string to describe this deal """ return f"<{self.title}>" def describe(self): """ Return a longer string to describe this deal for use in calling a model """ return f"Title: {self.title}\nDetails: {self.details.strip()}\nFeatures: {self.features.strip()}\nURL: {self.url}" @classmethod def fetch(cls, show_progress: bool = False) -> List[Self]: """ Retrieve all deals from the selected RSS feeds """ deals = [] skipped = 0 feed_iter = tqdm(feeds) if show_progress else feeds for feed_url in feed_iter: feed = feedparser.parse(feed_url) for entry in feed.entries[:10]: try: parsed_deal = gpt_parse(json.dumps(entry)) deals.append(cls(parsed_deal)) deals.append(cls(entry)) time.sleep(0.5) except Exception as e: skipped += 1 print(f"Skipping deal: {str(e)}") continue print(f"Fetched {len(deals)} deals successfully, skipped {skipped}") return deals class Deal(BaseModel): """ A class to Represent a Deal with a summary description """ product_description: str price: float url: str class DealSelection(BaseModel): """ A class to Represent a list of Deals """ deals: List[Deal] class Opportunity(BaseModel): """ A class to represent a possible opportunity: a Deal where we estimate it should cost more than it's being offered """ deal: Deal estimate: float discount: float