In the third part of this series, we’ll create a quote generator by leveraging Astra DB’s vector search capabilities and the generative power of an LLM (Large Language Model) like OpenAI’s GPT-3.
Key Steps:
Prompt Engineering:
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- Craft a prompt that guides the LLM in generating text in the style of a specific philosopher or philosophical movement.
- Consider using keywords or phrases from the search results to provide context.
- Example prompt: “Generate a philosophical quote in the style of Socrates about the nature of knowledge.”
LLM Processing:
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- Send the prompt to the LLM.
- The LLM processes the prompt and generates text based on its training data and the provided context. 1
- 1. All You Need To Know About LLM Text Generation | by Javaid
Filtering and Refinement:
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- Filter the generated text to ensure it aligns with philosophical principles and the desired style.
- Consider using techniques like temperature tuning to control the creativity and randomness of the generated text.
Output and Presentation:
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- Present the generated quote in a user-friendly format, such as a web page or a mobile app.
- Include information about the philosopher or philosophical movement associated with the quote.
Code Example (Using Python and OpenAI):
Python import open # … (other imports and setup) def generate_quote(prompt, model=”text-DaVinci-003″): response = openai.Completion. create( engine=model, prompt=prompt, max_tokens=100, n=1, stop=None, temperature=0.7, ) return response.choices[0].text.strip() # Example usage:
search_query = “the meaning of life” similar_quotes = search_quotes(search_query) prompt = f”Generate a philosophical quote in the style of Nietzsche, inspired by the following: {similar_quotes}”
generated_quote = generate_quote(prompt) print(generated_quote)
Additional Considerations:
- Ethical Implications: Consider the moral implications of generating philosophical content. Avoid creating misleading or harmful content.
- User Feedback: Incorporate user feedback to improve the quality and relevance of generated quotes.
- Continuous Learning: Update the model with new data and refine the prompt engineering techniques.
By combining the power of vector search and generative AI, you can create a compelling and innovative philosophy quote generator that can inspire and entertain users.
