Update app.py

app.py

@@ -19,7 +19,6 @@ also take this data and absorb your knowledge, you dont need use now what dont m
 
 import requests
 from bs4 import BeautifulSoup
-from SearchResult import SearchResult
 
 headers = {
 	"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36"
@@ -38,51 +37,27 @@ def search_ddg(question: str):
 	data = response.text
 	soup = BeautifulSoup(data, "html.parser")
 
-	did_you_mean = soup.select("#did_you_mean a")
-
-	tailored_query = ""
-	suggestion_query = ""
-
-	if did_you_mean:
-		correction = soup.find(id="did_you_mean")
-		if correction:
-			correction_hyperlink = correction.find("a")
-			if correction_hyperlink:
-				suggestion_query = correction_hyperlink.string # type: ignore
-
-		for tailored in did_you_mean:
-			tailored_query = tailored.string
-			break
-
-	result_links = soup.find_all("a")
-	filtered_urls = [
-		link["href"]
-		for link in result_links
-		if link.get("href") and (link["href"].startswith("https://") or link["href"].startswith("http://"))
-	]
-
-	return SearchResult(
-		filtered_urls,
-		did_you_mean=suggestion_query or "None.",
-		tailored_query=tailored_query or "None.",
-		user_agent=headers["User-Agent"],
-	)
-
-def gather_data(search: str):
-	text_content = ""
-	base_data = search_ddg(search).parse_results()
-	for data in base_data:
-		if data:
-			text_content += data.get("text_content") + "\n\n"
+	result_texts = soup.find_all("a", class_="result__snippet")
+	results: list[str] = []
+	output_string: str = ""
+
+	for element in result_texts:
+		if len(results) < 5:
+			text_content = element.get_text()
+			results.append(text_content)
 		else:
-			text_content += ""
-	return text_content
+			continue
+
+	for element in results:
+		output_string += element + '\n'
+
+	return output_string
 
 def generate(instruction):
 	base_prompt = ins.format(instruction)
-	gathered_data = gather_data(instruction)
+	feeding_data = search_ddg("What is KOIT-FM?")
 
-	response = llm(ins.format(base_prompt  + "\n" + gathered_data))
+	response = llm(ins.format(base_prompt  + "\n" + feeding_data))
 	result = response['choices'][0]['text']
 	return result