grepai-embeddings-openai

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Translated

Configure OpenAI as embedding provider for GrepAI. Use this skill for high-quality cloud embeddings.

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Sourceyoanbernabeu/grepai-skills
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NPX Install

npx skill4agent add yoanbernabeu/grepai-skills grepai-embeddings-openai

Tags

Translated version includes tags in frontmatter
openai-embeddinggrepai-configurationcloud-embeddingsai-embedding-providercost-optimization

SKILL.md Content

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GrepAI Embeddings with OpenAI

This skill covers using OpenAI's embedding API with GrepAI for high-quality, cloud-based embeddings.

When to Use This Skill

  • Need highest quality embeddings
  • Team environment with shared infrastructure
  • Don't want to manage local embedding server
  • Willing to trade privacy for quality/convenience

Considerations

AspectDetails
✅ QualityState-of-the-art embeddings
✅ SpeedFast, no local compute needed
✅ ScalabilityHandles any codebase size
⚠️ PrivacyCode sent to OpenAI servers
⚠️ CostPay per token
⚠️ InternetRequires connection

Prerequisites

  1. OpenAI API key
  2. Billing enabled on OpenAI account
Get your API key at: https://platform.openai.com/api-keys

Configuration

Basic Configuration

yaml
# .grepai/config.yaml
embedder:
  provider: openai
  model: text-embedding-3-small
  api_key: ${OPENAI_API_KEY}
Set the environment variable:
bash
export OPENAI_API_KEY="sk-..."

With Parallel Processing

yaml
embedder:
  provider: openai
  model: text-embedding-3-small
  api_key: ${OPENAI_API_KEY}
  parallelism: 8  # Concurrent requests for speed

Direct API Key (Not Recommended)

yaml
embedder:
  provider: openai
  model: text-embedding-3-small
  api_key: sk-your-api-key-here  # Avoid committing secrets!
Warning: Never commit API keys to version control.

Available Models

text-embedding-3-small (Recommended)

PropertyValue
Dimensions1536
Price$0.00002 / 1K tokens
QualityVery high
SpeedFast
Best for: Most use cases, good balance of cost/quality.
yaml
embedder:
  provider: openai
  model: text-embedding-3-small

text-embedding-3-large

PropertyValue
Dimensions3072
Price$0.00013 / 1K tokens
QualityHighest
SpeedFast
Best for: Maximum accuracy, cost not a concern.
yaml
embedder:
  provider: openai
  model: text-embedding-3-large
  dimensions: 3072

Dimension Reduction

You can reduce dimensions to save storage:
yaml
embedder:
  provider: openai
  model: text-embedding-3-large
  dimensions: 1024  # Reduced from 3072

Model Comparison

ModelDimensionsCost/1K tokensQuality
text-embedding-3-small
1536$0.00002⭐⭐⭐⭐
text-embedding-3-large
3072$0.00013⭐⭐⭐⭐⭐

Cost Estimation

Approximate costs per 1000 source files:
Codebase SizeChunksSmall ModelLarge Model
Small (100 files)~500$0.01$0.06
Medium (1000 files)~5,000$0.10$0.65
Large (10000 files)~50,000$1.00$6.50
Note: Costs are one-time for initial indexing. Updates only re-embed changed files.

Optimizing for Speed

Parallel Requests

GrepAI v0.24.0+ supports adaptive rate limiting and parallel requests:
yaml
embedder:
  provider: openai
  model: text-embedding-3-small
  api_key: ${OPENAI_API_KEY}
  parallelism: 8  # Adjust based on your rate limit tier
Parallelism recommendations:
  • Tier 1 (Free): 1-2
  • Tier 2: 4-8
  • Tier 3+: 8-16

Batching

GrepAI automatically batches chunks for efficient API usage.

Rate Limits

OpenAI has rate limits based on your account tier:
TierRPMTPM
Free3150,000
Tier 15001,000,000
Tier 25,0005,000,000
GrepAI handles rate limiting automatically with adaptive backoff.

Environment Variables

Setting the API Key

macOS/Linux:
bash
# In ~/.bashrc, ~/.zshrc, or ~/.profile
export OPENAI_API_KEY="sk-..."
Windows (PowerShell):
powershell
$env:OPENAI_API_KEY = "sk-..."
# Or permanently
[System.Environment]::SetEnvironmentVariable('OPENAI_API_KEY', 'sk-...', 'User')

Using .env Files

Create 
.env
in your project root:
OPENAI_API_KEY=sk-...
Add to 
.gitignore
:
gitignore
.env

Azure OpenAI

For Azure-hosted OpenAI:
yaml
embedder:
  provider: openai
  model: your-deployment-name
  api_key: ${AZURE_OPENAI_API_KEY}
  endpoint: https://your-resource.openai.azure.com

Security Best Practices

  1. Use environment variables: Never hardcode API keys
  2. Add to .gitignore: Exclude 
    .env
    files
  3. Rotate keys: Regularly rotate API keys
  4. Monitor usage: Check OpenAI dashboard for unexpected usage
  5. Review code: Ensure sensitive code isn't being indexed

Common Issues

❌ Problem: 
401 Unauthorized
✅ Solution: Check API key is correct and environment variable is set:
bash
echo $OPENAI_API_KEY
❌ Problem: 
429 Rate limit exceeded
✅ Solution: Reduce parallelism or upgrade OpenAI tier:
yaml
embedder:
  parallelism: 2  # Lower value
❌ Problem: High costs ✅ Solutions:
  • Use 
    text-embedding-3-small
    instead of large
  • Reduce dimension size
  • Add more ignore patterns to reduce indexed files
❌ Problem: Slow indexing ✅ Solution: Increase parallelism:
yaml
embedder:
  parallelism: 8
❌ Problem: Privacy concerns ✅ Solution: Use Ollama for local embeddings instead

Migrating from Ollama to OpenAI

  1. Update configuration:
yaml
embedder:
  provider: openai
  model: text-embedding-3-small
  api_key: ${OPENAI_API_KEY}
  1. Delete existing index:
bash
rm .grepai/index.gob
  1. Re-index:
bash
grepai watch
Important: You cannot mix embeddings from different models/providers.

Output Format

Successful OpenAI configuration:
✅ OpenAI Embedding Provider Configured

   Provider: OpenAI
   Model: text-embedding-3-small
   Dimensions: 1536
   Parallelism: 4
   API Key: sk-...xxxx (from environment)

   Estimated cost for this codebase:
   - Files: 245
   - Chunks: ~1,200
   - Cost: ~$0.02

   Note: Code will be sent to OpenAI servers.