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Msingh openai rag with vision #1561
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Added Kevin as reviewer |
" `PINECONE_API_KEY=your-api-key-here`. \n", | ||
" 2. Install `pip install python-dotenv` to read the API Key from the .env file. \n", | ||
"\n", | ||
"**Creat2 the Pinecone Index** \n", |
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Should be "Create"
alwell-kevin
approved these changes
Nov 13, 2024
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LGTM! 🚢
Notes that I generally agree with from AI Collaboration below.
• Title and Introduction: Simplify title; consider breaking up dense introductory text.
• Structure: Well-organized steps, but consistent labeling (e.g., Step 1, Step 2) would improve navigation.
• Code Clarity: Functions are clear; add brief in-line comments on key parameters, e.g., get_vision_response.
• Error Handling: Good use of error handling in key functions; add API error output for improved debugging.
• Visual Output: Include sample visual interpretations to verify fidelity; mention limitations for complex visuals especially tabular data.
• Performance Notes: Add early guidance on cost and latency for vision modality use.
• Grammar: Minor typo in markdown, e.g., “Creat2” instead of “Create”.
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Summary
Cookbook that demonstrates setup and implementation of a Pinecone RAG solution for questing and answering using GPR-4o vision modality.
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