Moss - Real-time Semantic Search for Conversational AI

Python
JavaScript
Moss CLI
Portal

v1.1.0

Multi-index query: new query_multi_index(names, query, options) searches across multiple loaded indexes and returns the global top-K, with each result tagged by source index_name.
Bulk index lifecycle: load_indexes(names, ...) (best-effort, returns LoadIndexesResult { loaded, failed }) and unload_indexes(names).
QueryResultDocumentInfo now exposes an index_name field, set on multi-index results.

v1.0.0

First stable release of the moss Python SDK (previously published as inferedge-moss).Import path changed: from moss import MossClient (was from inferedge_moss import ...)

Semantic search with built-in on-device models (moss-minilm, moss-mediumlm); embedding computation runs in Rust for speed; custom embeddings supported via QueryOptions.embedding
Hybrid search with keyword + semantic search and configurable alpha blending
Metadata filtering on locally loaded indexes with rich operators ($eq, $ne, $gt, $gte, $lt, $lte, $in, $nin, $and, $or, $near for geo-distance)
Cloud query fallback: query() automatically falls back to the cloud API when the index is not loaded locally
Hot reload & auto-refresh: load_index() supports auto_refresh with configurable polling interval to detect and reload updated indexes
Async bulk index pipeline: binary upload, server-side build, poll until completion
Index mutations: create_index, add_docs, delete_docs return MutationResult with job_id, index_name, doc_count
Multi-index support for isolated search spaces
Python 3.10 to 3.14 supported

v1.0.0-beta.19

Updated inferedge-moss-core dependency to 0.8.7
Telemetry improvements
Embedding computation for built-in models (moss-minilm, moss-mediumlm) now runs in Rust; custom embeddings continue to be supported via QueryOptions.embedding
Fixed list_indexes() failing when the cloud API returns null for certain IndexInfo fields on indexes created by older SDK versions

v1.0.0-beta.18

Telemetry improvements

v1.0.0-beta.17

Metadata Filtering: query() now accepts an optional filter dict to narrow results by document metadata on locally loaded indexes
- Comparison operators: $eq, $ne, $gt, $gte, $lt, $lte
- Set operators: $in, $nin
- Composable with $and / $or for complex predicates (supports arbitrary nesting)
- Numeric coercion: int and float filter values are automatically converted to strings for consistent matching
Geo-distance filtering: new $near operator filters documents by haversine distance from a "lat,lng,radiusMeters" value
When filter is passed to query() but the index is not loaded locally, a warning is logged and the filter is skipped (cloud query API does not yet support filtering)
Updated inferedge-moss-core dependency to 0.6.0

v1.0.0-beta.16

Bumped inferedge-moss-core dependency to 0.5.0 to support session index telemetry and push_index improvements

v1.0.0-beta.15

All index mutations and reads now go through the Rust ManageClient, replacing the Python HTTP layer
Index creation uses an async bulk pipeline: binary upload → server-side build → poll until completion
load_index supports both V1 and V2 binary formats, with cloud query fallback when index isn’t loaded locally
New return type MutationResult (with job_id, index_name, doc_count) for create_index, add_docs, delete_docs
get_docs takes doc_ids directly instead of wrapping in GetDocumentsOptions

v1.0.0-beta.14

Query latency reduced from ~2,300ms to ~10ms for 100K vectors
Optimized search pipeline reducing memory allocations
Significantly reduced memory overhead for large indexes (100K+ documents) in the context of hybrid search (keyword + semantic)
Enhanced performance across all index sizes

v1.0.0-beta.13

Hot Reload & Auto-Refresh: Indexes can now automatically detect and reload when updated in the cloud.
- load_index() now accepts optional auto_refresh and polling_interval_in_seconds parameters
- When auto_refresh is enabled, the SDK polls for updates at the configured interval (default: 600 seconds)
- To stop auto-refresh, call load_index() again without the auto_refresh option
load_index() now allows reloading an already-loaded index (previously threw an error)
Index management now uses Rust core for improved performance and reliability

v1.0.0-beta.12

Adds partial support for Python 3.14 by disabling local embedding service functionality. Full support coming soon.

v1.0.0-beta.11

Adds support for user-supplied embeddings.
query() now automatically falls back to the cloud API when the index is not loaded locally, enabling queries without requiring load_index() first.
Adds better scoring evaluation for search results

v1.0.0-beta.10

Removes the ‘<2’ upper bound on numpy dependency.

v1.0.0-beta.9

Drops support for Python 3.9 and below.
Bug fix: Keyword search now functions correctly after load_index().
New service endpoint with significant infrastructure upgrades. Management operations are now ~3× faster across most real-world use cases, providing faster index operations while also supporting larger payloads.

v1.0.0-beta.8

Updates inferedge-moss-core dependency to version 0.2.3 for new ARM64 wheel support.

v1.0.0-beta.7

Adds IntelliSense support in all the IDEs

v1.0.0-beta.6

Adds support for keyword search and alpha blending between keyword and semantic search.

v1.0.0-beta.5

Removes Pipecat integration and MossContextRetriever from the SDK. Will be offered as a pipecat extension instead soon.

v1.0.0-beta.4

Performance improvements for query() calls.

v1.0.0-beta.3

MossContextRetriever: Added Pipecat integration for real-time voice AI applications
- Automatically enhances LLM conversations with semantic search results from Moss indexes
- Seamless integration with OpenAI LLM context frames

v1.0.0-beta.1

Initial release of inferedge-moss with core features:

Semantic search using transformer-based embeddings
Lightweight embedding models for edge computing; supports proprietary “moss-minilm” model
API key validation with secure host access
Cloudflare CDN support for fast model loading
Multi-index support for isolated search spaces
Add, update, and remove items across indexes
Query interface with configurable result count
Performance metrics tracking

v1.0.2

Adds prebuilt binaries for x86_64-apple-darwin (Intel Macs).

v1.0.1

Custom authenticator for browser-safe authentication: new MossClient.withAuthenticator() and IndexManager.withAuthenticator() factory methods accept a JS-side token callback.
CLOUD_API_MANAGE_URL replaced by granular constants: CLOUD_API_IDENTITY_URL, CLOUD_API_AUTH_URL, etc.

v1.0.0

First stable release of @moss-dev/moss.Breaking changes

Package renamed from @inferedge/moss to @moss-dev/moss. Update imports accordingly.

Behavior

query() automatically falls back to cloud HTTP when the index is not loaded locally.

v1.0.0-beta.8

Filesystem index caching: loadIndex() accepts an optional cachePath in LoadIndexOptions to cache index binaries and documents to disk (Node.js/Bun only).
- Cache is automatically invalidated when the cloud index is updated.
- Auto-refresh also persists refreshed data to the cache.
- Atomic writes prevent cache corruption from partial/interrupted writes.
- Path traversal protection on index names.
- Graceful fallback to re-download if cached data is corrupted.
Metadata filtering: query() accepts an optional filter in QueryOptions to narrow results by document metadata on locally loaded indexes.
- Comparison operators: $eq, $ne, $gt, $gte, $lt, $lte
- Set operators: $in, $nin
- Composable with $and / $or (supports arbitrary nesting)
- Number values are automatically stringified for consistent matching
Geo-distance filtering: new $near operator filters documents by haversine distance from a "lat,lng,radiusMeters" value.
New exported types: FilterCondition, MetadataFilter.

v1.0.0-beta.7

Async job-based mutations (createIndex, addDocs, deleteDocs) with built-in polling and onProgress callbacks
Large index support - up to 100k documents via presigned upload + server-side build
New binary index format with smaller payloads and faster deserialization; existing indexes using the previous format are still supported

v1.0.0-beta.6

Hot Reload & Auto-Refresh: Indexes can now automatically detect and reload when updated in the cloud.
- loadIndex() now accepts optional LoadIndexOptions with autoRefresh and pollingIntervalInSeconds parameters
- When autoRefresh is enabled, the SDK polls for updates at the configured interval (default: 600 seconds)
- To stop auto-refresh, call loadIndex() again without the autoRefresh option
loadIndex() now allows reloading an already-loaded index (previously threw an error)

v1.0.0-beta.5

Query optimizations for custom-embedding workflow

v1.0.0-beta.4

Fixed ReferenceError: process is not defined crash in browser environments. The SDK now works seamlessly across all JavaScript runtimes including browsers, Node.js, Deno, and Bun.

v1.0.0-beta.3

Added

Support for user-supplied document embeddings during ingestion. The SDK supports optional embedding arrays in DocumentInfo payloads without using the native embedding service from moss.
Query overloads now accept QueryOptions so users can provide a custom embedding alongside query text.
Relaxed modelId requirement when creating indexes. The SDK aligns with the service default of moss-minilm when no explicit model is provided.
query() now automatically falls back to the cloud API when the index is not loaded locally, enabling queries without requiring loadIndex() first.

Enhancements

New service endpoint with significant infrastructure upgrades. Management operations are now ~3× faster across most real-world use cases, providing faster index operations while also supporting larger payloads.

v1.0.0-beta.2

Fixed

Fixed ESM (ES Module) import compatibility issue. The package now correctly exports as an ES module and can be imported using standard ESM syntax.

Upgrade Instructions

Migrate from CommonJS (require) to ES Module syntax (import).

v1.0.0-beta.1

Initial release of @inferedge/moss with core features:

Semantic search using transformer-based embeddings
Lightweight embedding models for edge computing; supports proprietary “moss-minilm” and “moss-mediumlm” models
Multi-index support for isolated search spaces
Add, update, and remove documents across indexes
Blazing fast querying support after loading indexes
TypeScript support with full type definitions

v0.1.1

Added named config profiles to switch between accounts and projects, and an interactive mode for moss query.

Product Updates

Product Updates