Update app.py

app.py

@@ -84,8 +84,6 @@ class Website:
     def get_contents(self):
         return f"Webpage Title:\n{self.title}\nWebpage Contents:\n{self.text}\n\n"
 
-# ted = Website("https://invoice.2go.com")
-# ted.links
 
 link_system_prompted = "You are to choose the links that are relevant in terms of marketing in this website and then \
                         and then you are to follow through with picking them out. Do not choose privacy link, and anyother irrelevant ones\n"
@@ -93,7 +91,7 @@ link_system_prompted += "Respond in Json"
 link_system_prompted += """Follow this example \
 "links ={type: about us : "https://something/somethinhg"}"""
 
-link_system_prompted
+
 
 def link_user_prompted(website):
     User_prompter = f"I would like to know the relevant link in the {website.url} - "
@@ -101,7 +99,7 @@ def link_user_prompted(website):
     User_prompter +=  "\n" .join(website.links)
     return User_prompter
 
-link_user_prompted(ted)
+
 
 def get_stuff(Url):
     website = Website.url
@@ -116,18 +114,12 @@ def get_stuff(Url):
     result = response.choices[0].message.content
     return json.loads(result)
 
-# ed = Website("https://squeakycleaningservices.co.uk")
-# ed.links
+
 
 """## First step: Have GPT-4o-mini figure out which links are relevant
 
-### Use a call to gpt-4o-mini to read the links on a webpage, and respond in structured JSON.  
-It should decide which links are relevant, and replace relative links such as "/about" with "https://company.com/about".  
-We will use "one shot prompting" in which we provide an example of how it should respond in the prompt.
 
-This is an excellent use case for an LLM, because it requires nuanced understanding. Imagine trying to code this without LLMs by parsing and analyzing the webpage - it would be very hard!
 
-Sidenote: there is a more advanced technique called "Structured Outputs" in which we require the model to respond according to a spec. We cover this technique in Week 8 during our autonomous Agentic AI project.
 """
 
 link_system_prompt = "You are provided with a list of links found on a webpage. \
@@ -153,7 +145,7 @@ Do not include Terms of Service, Privacy, email links.\n"
     user_prompt += "\n".join(website.links)
     return user_prompt
 
-print(get_links_user_prompt(ed))
+
 
 def get_links(url):
     website = Website(url)
@@ -170,11 +162,6 @@ def get_links(url):
 
 # sample
 
-Diamondadverts = Website("https://diamondadverts.com")
-Diamondadverts.links
-
-get_links("https://squeakycleaningservices.co.uk")
-
 
 
 """## Second step: make the pitch deck!
@@ -192,7 +179,8 @@ def get_all_details(url):
         result += Website(link["url"]).get_contents()
     return result
 
-print(get_all_details("https://squeakycleaningservices.co.uk"))
+
+## system prompt updates
 
 # system_prompt = "You are an assistant that analyzes the contents of several relevant pages from a company website \
 # and creates a short pitch deck for the company, so the comapany can use it to apply for mor jobs and clients, investors and recruits. Respond in markdown.\
@@ -220,6 +208,8 @@ Focus on creating a narrative that highlights the company's strengths, unique po
 # and creates a short humorous, entertaining, jokey brochure about the company for prospective customers, investors and recruits. Respond in markdown.\
 # Include details of company culture, customers and careers/jobs if you have the information."
 
+#end
+
 def get_pitch_user_prompt(company_name, url):
     user_prompt = f"You are looking at a company called: {company_name}\n"
     user_prompt += f"Here are the contents of its landing page and other relevant pages; use this information to build a short pitch deck for the company, of the company in markdown.\n"
@@ -240,7 +230,7 @@ def pitch_deck(company_name, url):
     result = response.choices[0].message.content
     display(Markdown(result))
 
-pitch_deck("Squeaky Cleaning Services", "https://squeakycleaningservices.co.uk")
+
 
 """## Finally - a minor improvement