Embedding Bridge

make clean
make all
make install

# Download the release archive (tar.gz or zip):
#   tar -xzf embedding_bridge-<version>.tar.gz
#   # or
#   unzip embedding_bridge-<version>.zip
#   cd embedding_bridge-<version>

# Create a short-name `embr` launcher in this folder (symlink to the wrapper):
ln -s run_embedding_bridge.sh embr

# Add the release directory to your PATH so you can invoke the launcher:
export PATH="$PWD:$PATH"

# Now run the CLI (the wrapper will set LD_LIBRARY_PATH for you):
embr --help

# Initialize
embr init

# Register a model
embr model register text-embedding-3-small --dimensions 1536 --normalize

# Store an embedding
embr store --embedding vector.bin --dims 1536 document.txt

# Check status
embr status document.txt

# Compare embeddings
embr diff <hash1> <hash2>

# Roll back to previous version
embr rollback <hash> document.txt

# Create and manage sets
embr set create experimental
embr switch experimental

# Register a new model
embr model register <model-name> --dimensions <dims> [--normalize]

# List registered models
embr model list

# Store embedding from binary file
embr store --embedding vector.bin --dims 1536 file.txt

# Store embedding from numpy file
embr store --embedding vector.npy file.txt

# Check embedding status
embr status file.txt
embr status -v file.txt  # verbose output

# Compare embeddings
embr diff <hash1> <hash2>

# Roll back to previous version
embr rollback <hash> file.txt

# View embedding log
embr log file.txt

# Create a new set of embeddings
embr set create <name>

# List available sets
embr set list
embr set list --verbose

# Switch between sets
embr switch <name>

# Show current set status
embr set status

# Compare differences between sets
embr set diff <set1> <set2>

# Delete a set
embr set -d <name> [--force]

# Merge embeddings from one set to another
embr merge <source-set> [<target-set>] [--strategy=<strategy>]

# Add a remote
embr remote add <name> <url>

# List remotes
embr remote list

# Push a set to remote
embr push <remote> [<set>]

# Pull a set from remote
embr pull <remote> [<set>]

# Download a file or directory from a repository
embr get <remote> <path>

# Garbage collect unreferenced embeddings
embr gc [options]
# Example: dry run
enbr gc -n

# Remove embeddings from tracking
embr rm file.txt
embr rm --cached file.txt
embr rm -m openai-3 file.txt