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Ask QuestionI'm building a system where users ask questions about their data in natural language, and an LLM generates SQL queries and interprets results. **The problem:** The LLM often "hallucinates" insights t...
Our company wants to use GPT-4 to analyze customer support tickets and suggest responses. Legal and compliance teams are concerned about: 1. **Data retention**: Does OpenAI store our API requests? 2....
I need to extract structured data from unstructured text using GPT-4. I've tried both approaches: **Function Calling:** ```python response = client.chat.completions.create( model="gpt-4", mes...
I want to build a RAG system for our internal documentation, but I'm confused about the embedding strategy. **Current setup:** - 500+ markdown documentation files - Using OpenAI's text-embedding-3-sm...
I'm working on a production system where we use GPT-4 for various tasks. As we iterate on our prompts, I'm concerned about: 1. **Version control**: How do you track prompt changes over time? 2. **A/B...
I'm building a system where users ask questions about their data in natural language, and an LLM generates SQL queries and interprets results. **The problem:** The LLM often "hallucinates" insights t...
Our company wants to use GPT-4 to analyze customer support tickets and suggest responses. Legal and compliance teams are concerned about: 1. **Data retention**: Does OpenAI store our API requests? 2....
I need to extract structured data from unstructured text using GPT-4. I've tried both approaches: **Function Calling:** ```python response = client.chat.completions.create( model="gpt-4", mes...
I want to build a RAG system for our internal documentation, but I'm confused about the embedding strategy. **Current setup:** - 500+ markdown documentation files - Using OpenAI's text-embedding-3-sm...
I'm working on a production system where we use GPT-4 for various tasks. As we iterate on our prompts, I'm concerned about: 1. **Version control**: How do you track prompt changes over time? 2. **A/B...
Our company wants to use GPT-4 to analyze customer support tickets and suggest responses. Legal and compliance teams are concerned about: 1. **Data retention**: Does OpenAI store our API requests? 2....
I'm building a system where users ask questions about their data in natural language, and an LLM generates SQL queries and interprets results. **The problem:** The LLM often "hallucinates" insights t...
I need to extract structured data from unstructured text using GPT-4. I've tried both approaches: **Function Calling:** ```python response = client.chat.completions.create( model="gpt-4", mes...
I want to build a RAG system for our internal documentation, but I'm confused about the embedding strategy. **Current setup:** - 500+ markdown documentation files - Using OpenAI's text-embedding-3-sm...
I'm working on a production system where we use GPT-4 for various tasks. As we iterate on our prompts, I'm concerned about: 1. **Version control**: How do you track prompt changes over time? 2. **A/B...
We want to expand our AI chatbot to support 10+ languages. Questions: 1. Should we use separate prompts for each language or rely on LLM's multilingual capabilities? 2. How to ensure consistent quali...
I've heard a lot about chain-of-thought (CoT) prompting improving LLM reasoning, but I'm not sure how to implement it properly. Can someone explain: 1. What exactly is chain-of-thought prompting? 2. ...
Our AI application is getting expensive with GPT-4 API calls. We're spending $5000/month and growing. What strategies can reduce costs without sacrificing too much quality? Current setup: - 100k API...
I am building a Retrieval-Augmented Generation (RAG) chatbot for internal company documents. Sometimes the LLM makes up information when the retrieved context doesn't contain the answer. What prompti...
I want to fine-tune GPT-4 for medical diagnosis assistance. I have a dataset of 10,000 medical cases with symptoms and diagnoses. What are the best practices for: 1. Preparing the training data 2. Ch...