Configure OpenAI as embedding provider for GrepAI. Use this skill for high-quality cloud embeddings.
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
Aspect
Details
✅ Quality
State-of-the-art embeddings
✅ Speed
Fast, no local compute needed
✅ Scalability
Handles any codebase size
⚠️ Privacy
Code sent to OpenAI servers
⚠️ Cost
Pay per token
⚠️ Internet
Requires connection
Prerequisites
OpenAI API key
Billing enabled on OpenAI account
Get your API key at: https://platform.openai.com/api-keys
Configuration
Basic Configuration
# .grepai/config.yaml
embedder:
provider: openai
model: text-embedding-3-small
api_key: ${OPENAI_API_KEY}
Set the environment variable:
export OPENAI_API_KEY="sk-..."
With Parallel Processing
embedder:
provider: openai
model: text-embedding-3-small
api_key: ${OPENAI_API_KEY}
parallelism: 8 # Concurrent requests for speed
Direct API Key (Not Recommended)
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)
Property
Value
Dimensions
1536
Price
$0.00002 / 1K tokens
Quality
Very high
Speed
Fast
Best for: Most use cases, good balance of cost/quality.
embedder:
provider: openai
model: text-embedding-3-small
text-embedding-3-large
Property
Value
Dimensions
3072
Price
$0.00013 / 1K tokens
Quality
Highest
Speed
Fast
Best for: Maximum accuracy, cost not a concern.
embedder:
provider: openai
model: text-embedding-3-large
dimensions: 3072
Dimension Reduction
You can reduce dimensions to save storage:
embedder:
provider: openai
model: text-embedding-3-large
dimensions: 1024 # Reduced from 3072
Model Comparison
Model
Dimensions
Cost/1K tokens
Quality
text-embedding-3-small
1536
$0.00002
⭐⭐⭐⭐
text-embedding-3-large
3072
$0.00013
⭐⭐⭐⭐⭐
Cost Estimation
Approximate costs per 1000 source files:
Codebase Size
Chunks
Small Model
Large 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:
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:
Tier
RPM
TPM
Free
3
150,000
Tier 1
500
1,000,000
Tier 2
5,000
5,000,000
GrepAI handles rate limiting automatically with adaptive backoff.
Environment Variables
Setting the API Key
macOS/Linux:
# In ~/.bashrc, ~/.zshrc, or ~/.profile
export OPENAI_API_KEY="sk-..."
Windows (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:
.env
Azure OpenAI
For Azure-hosted OpenAI:
embedder:
provider: openai
model: your-deployment-name
api_key: ${AZURE_OPENAI_API_KEY}
endpoint: https://your-resource.openai.azure.com
Security Best Practices
Use environment variables: Never hardcode API keys
Add to .gitignore: Exclude .env files
Rotate keys: Regularly rotate API keys
Monitor usage: Check OpenAI dashboard for unexpected usage
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:
echo $OPENAI_API_KEY
❌ Problem: 429 Rate limit exceeded
✅ Solution: Reduce parallelism or upgrade OpenAI tier:
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:
embedder:
parallelism: 8
❌ Problem: Privacy concerns
✅ Solution: Use Ollama for local embeddings instead
Migrating from Ollama to OpenAI
Update configuration:
embedder:
provider: openai
model: text-embedding-3-small
api_key: ${OPENAI_API_KEY}
Delete existing index:
rm .grepai/index.gob
Re-index:
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.don't have the plugin yet? install it then click "run inline in claude" again.