Textzusammenfassung und -erweiterung

Prompt-Engineering mit der OpenAI-API

Fouad Trad

Machine Learning Engineer

Textzusammenfassung

Fasst Texte in einem kürzeren Format zusammen
Geschäftsprozessoptimierung
- Finanzbranche -> fasst lange Berichte zusammen
- Marketing -> wandelt Kundenfeedback in nützliche Informationen um
LLMs können Texte mit effektiven Prompts zusammenfassen.

Bild, das zeigt, wie durch Zusammenfassung ein Stapel Bücher in ein Dokument mit einer Zusammenfassung verwandelt wird.

Ineffizienter Prompt

Nur den zusammenzufassenden Text angeben.

text = "I recently purchased your XYZ Smart Watch and wanted to provide some feedback
based on my experience with the product. I must say that I'm impressed with the sleek design 
and build quality of the watch. It feels comfortable on the wrist and looks great with any 
outfit. The touchscreen is responsive and easy to navigate through the various features."


prompt = f"""Summarize the text delimited by triple backticks:
           ```{text}```"""
print(get_response(prompt))

The author purchased the XYZ Smart Watch and is impressed with its sleek design, build 
quality, and comfortable fit on the wrist. They find the touchscreen responsive and 
user-friendly for navigating the watch's features.

Schnelle Verbesserung

Ausgabebeschränkungen
Ausgabestruktur
Fokus der Zusammenfassung

Bild, das eine Person zeigt, die von einer Stufe auf eine höhere steigt, als Zeichen der Verbesserung.

Effektiver Prompt: Ausgabebeschränkungen

Gibt die Anzahl der Sätze, Wörter und Zeichen an.

text = "I recently purchased your XYZ Smart Watch and wanted to provide some feedback
based on my experience with the product. I must say that I'm impressed with the sleek design 
and build quality of the watch. It feels comfortable on the wrist and looks great with any 
outfit. The touchscreen is responsive and easy to navigate through the various features."


prompt = f"""Summarize the text delimited by triple backticks in one sentence:
           ```{text}```"""
print(get_response(prompt))

The customer is impressed with the sleek design, build quality, comfort, and responsiveness 
of the XYZ Smart Watch's touch screen.

Effektiver Prompt: Ausgabestruktur

Gibt die Ausgabestruktur vor

text = "I recently purchased your XYZ Smart Watch and wanted to provide some feedback
based on my experience with the product. I must say that I'm impressed with the sleek design 
and build quality of the watch. It feels comfortable on the wrist and looks great with any 
outfit. The touchscreen is responsive and easy to navigate through the various features."


prompt = f"""Summarize the text delimited by triple backticks, in at most three bullet points.
           ```{text}```"""
print(get_response(prompt))

- The XYZ Smart Watch has a sleek and impressive design with  excellent build quality.
- It feels comfortable on the wrist and complements any outfit.
- The touch screen is responsive and user-friendly for easy navigation through the features.

Effektiver Prompt: Fokus auf Zusammenfassung

Weist das Modell an, sich auf bestimmte Teile des Textes zu konzentrieren.

text = "I recently purchased your XYZ Smart Watch and wanted to provide some feedback
based on my experience with the product. I must say that I'm impressed with the sleek design 
and build quality of the watch. It feels comfortable on the wrist and looks great with any 
outfit. The touchscreen is responsive and easy to navigate through the various features."


prompt = f"""Summarize the review delimited by triple backticks, in three sentences, 
focusing on the key features and user experience:
           ```{text}```"""
print(get_response(prompt))

Effektiver Prompt: Fokus auf Zusammenfassung

The customer purchased the XYZ Smart Watch and was impressed with its sleek design 
and build quality. 
They found it comfortable to wear and versatile enough to match any outfit. 
The touch screen was responsive and user-friendly, making it easy to navigate 
through the watch's features.

Text-Erweiterung

Erstellt Texte aus Ideen oder Stichpunkten.
Steigert die Effizienz und Produktivität.
LLMs können Texte mit gut gemachten Prompts erweitern.

Bild, das erklärt, dass es bei der Text-Erweiterung darum geht, einen ganzen Text aus ein paar kleinen Ideen für Anforderungen zu machen.

Texterweiterungs-Prompts

Weist das Modell an, den Text zu erweitern.
Wichtige Punkte hervorheben
Angabe von: Ton, Länge, Aufbau, Zielgruppe

Symbol, das einen Bleistift zeigt, der in ein Notizbuch schreibt.

Eine Servicebeschreibung erweitern

service_description = """Service: Social XYZ
- Social Media Strategy Development
- Content Creation and Posting 
- Audience Engagement and Community Building
- Increased Brand Visibility
- Enhanced Customer Engagement
- Data-Driven Marketing Decisions"""

prompt = f"""Expand the description for the Social XYZ service delimited by triple 
backticks to provide an overview of its features and benefits, without bypassing 
the limit of two sentences. Use a professional tone.
```{service_description}```"""
print(get_response(prompt))

Eine Servicebeschreibung erweitern

Social XYZ is a comprehensive social media service that offers strategic 
development, content creation, and posting to help businesses effectively engage 
with their target audience and build a strong online community. 

With a focus on increasing brand visibility and enhancing customer engagement, 
Social XYZ enables businesses to make data-driven marketing decisions for optimal 
results.

Lass uns üben!

Prompt-Engineering mit der OpenAI-API