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+# Search and Vector Building Blocks
+
+Author: Mike Nguyen - @mikeee (hey@mike.ee)
+
+## Overview
+
+This is a proposal surrounding the implementation of two new specialised state stores without bringing into
+scope the deep integrations planned on implementation of these building blocks. Whilst the two building 
+blocks share almost the same envelope, the method of requesting the records can vary significantly and should
+be kept distinct shapes.
+
+## Background
+
+The current implementations of state stores do not accomodate the necessity to access data not only by 
+key-value but an extended querying layer. New 'specialised' building blocks facilitate rapid development.
+
+There is a specific need from AI workloads to not only query by key but also by 'relevant' records returned
+through lexical/structured matching or geometric proximity for example.
+
+## Providers in scope
+
+| Provider | Lexical Search | Vector Search |
+|----------|---|---|
+| Meilisearch | ✓ | ✓ |
+| Elasticsearch | ✓ | ✓ |
+| Chroma | ✓ | ✓ |
+
+Other providers with existing component implementations may be leveraged.
+
+## HTTP API / Protos
+
+A HTTP api will be exposed mirroring the below.
+
+### Search
+
+```protobuf
+rpc IndexDocumentsAlpha1(IndexDocumentsRequestAlpha1) returns (IndexDocumentsResponseAlpha1) {}
+rpc DeleteDocumentsAlpha1(DeleteDocumentsRequestAlpha1) returns (google.protobuf.Empty) {}
+rpc SearchAlpha1(SearchRequestAlpha1) returns (SearchResponseAlpha1) {}
+
+message SearchDocument {
+  string id = 1;
+  bytes content = 2;
+  map<string, string> metadata = 3;
+}
+
+message SearchHit {
+  SearchDocument document = 1;
+  double score = 2;
+  map<string, string> highlights = 3;
+}
+
+enum SortOrder {
+  SORT_ORDER_UNSPECIFIED = 0;
+  SORT_ORDER_ASC = 1;
+  SORT_ORDER_DESC = 2;
+}
+
+message SortClause {
+  string field = 1;
+  SortOrder order = 2;
+}
+
+enum IndexAck {
+  INDEX_ACK_UNSPECIFIED = 0;
+  INDEX_ACK_QUEUED = 1;
+  INDEX_ACK_DURABLE = 2;
+}
+
+message IndexDocumentsRequestAlpha1 {
+  string store_name = 1;
+  string index = 2;
+  repeated SearchDocument documents = 3;
+  map<string, string> metadata = 10;
+}
+
+message IndexDocumentsResponseAlpha1 {
+  repeated string failed_ids = 1;
+  IndexAck ack = 2;
+}
+
+message DeleteDocumentsRequestAlpha1 {
+  string store_name = 1;
+  string index = 2;
+  repeated string ids = 3;
+  map<string, string> metadata = 10;
+}
+
+message SearchRequestAlpha1 {
+  string store_name = 1;
+  string index = 2;
+
+  oneof query {
+    string text = 3;
+    google.protobuf.Struct native = 4;
+  }
+
+  google.protobuf.Struct filter = 5;
+  uint32 top_k = 6;
+  uint32 offset = 7;
+  repeated string return_fields = 8;
+  bool include_content = 9;
+  map<string, string> metadata = 10;
+  repeated string search_fields = 11;
+  repeated SortClause sort = 12;
+  repeated string highlight_fields = 13;
+
+  reserved 14, 15, 16;
+}
+
+message SearchResponseAlpha1 {
+  repeated SearchHit hits = 1;
+  uint64 total_hits = 2;
+  string continuation_token = 3;
+}
+```
+
+### Vector
+
+```protobuf
+rpc UpsertVectorsAlpha1(UpsertVectorsRequestAlpha1) returns (UpsertVectorsResponseAlpha1) {}
+rpc DeleteVectorsAlpha1(DeleteVectorsRequestAlpha1) returns (google.protobuf.Empty) {}
+rpc GetVectorsAlpha1(GetVectorsRequestAlpha1) returns (GetVectorsResponseAlpha1) {}
+rpc QueryVectorsAlpha1(QueryVectorsRequestAlpha1) returns (QueryVectorsResponseAlpha1) {}
+rpc BatchQueryVectorsAlpha1(BatchQueryVectorsRequestAlpha1) returns (BatchQueryVectorsResponseAlpha1) {}
+
+enum DistanceMetric {
+  DISTANCE_METRIC_UNSPECIFIED = 0;
+  DISTANCE_METRIC_COSINE = 1;
+  DISTANCE_METRIC_DOT_PRODUCT = 2;
+  DISTANCE_METRIC_EUCLIDEAN = 3;
+}
+
+message SparseVector {
+  repeated uint32 indices = 1;
+  repeated float values = 2;
+}
+
+message NamedVector {
+  repeated float values = 1;
+  SparseVector sparse_values = 2;
+}
+
+message VectorRecord {
+  string id = 1;
+  repeated float values = 2;
+  bytes payload = 3;
+  map<string, string> metadata = 4;
+  SparseVector sparse_values = 5;
+  map<string, NamedVector> named_vectors = 6;
+}
+
+message VectorMatch {
+  VectorRecord record = 1;
+  double score = 2;
+}
+
+message UpsertVectorsRequestAlpha1 {
+  string store_name = 1;
+  string collection = 2;
+  repeated VectorRecord records = 3;
+  map<string, string> metadata = 10;
+}
+
+message UpsertVectorsResponseAlpha1 {
+  repeated string failed_ids = 1;
+}
+
+message DeleteVectorsRequestAlpha1 {
+  string store_name = 1;
+  string collection = 2;
+  repeated string ids = 3;
+  map<string, string> metadata = 10;
+}
+
+message GetVectorsRequestAlpha1 {
+  string store_name = 1;
+  string collection = 2;
+  repeated string ids = 3;
+  bool include_values = 4;
+  map<string, string> metadata = 10;
+}
+
+message GetVectorsResponseAlpha1 {
+  repeated VectorRecord records = 1;
+}
+
+message QueryVectorsRequestAlpha1 {
+  string store_name = 1;
+  string collection = 2;
+
+  oneof query {
+    VectorRecord vector = 3;
+    string by_id = 4;
+  }
+
+  uint32 top_k = 5;
+  google.protobuf.Struct filter = 6;
+  bool include_values = 7;
+  bool include_payload = 8;
+  DistanceMetric metric = 9;
+  map<string, string> metadata = 10;
+  SparseVector sparse_query = 11;
+  optional float alpha = 12;
+  optional string vector_name = 13;
+  optional float score_threshold = 14;
+}
+
+message QueryVectorsResponseAlpha1 {
+  repeated VectorMatch matches = 1;
+}
+
+message BatchQueryVectorsRequestAlpha1 {
+  string store_name = 1;
+  string collection = 2;
+  repeated QueryVectorsRequestAlpha1 queries = 3;
+  map<string, string> metadata = 10;
+}
+
+message BatchQueryVectorsResponseAlpha1 {
+  repeated QueryVectorsResponseAlpha1 results = 1;
+}
+```
+
+## Consumption Examples (Go)
+
+```go
+// Search
+hits, err := client.SearchAlpha1(ctx, &client.SearchRequestAlpha1{
+    StoreName: "meili-products",
+    Index:         "products",
+    Query:         &client.SearchRequestAlpha1Text{Text: "wireless headphones"},
+    SearchFields:  []string{"title", "description"},
+    TopK:          10,
+})
+
+// Vector query
+matches, err := client.QueryVectorsAlpha1(ctx, &client.QueryVectorsRequestAlpha1{
+    StoreName: "meili-docs",
+    Collection:    "manuals",
+    Query: &client.QueryVectorsRequestAlpha1_Vector{
+        Vector: &client.VectorRecord{Values: dense},
+    },
+    SparseQuery:    &client.SparseVector{Indices: sparseIdx, Values: sparseVal},
+    Alpha:          proto.Float32(0.7),
+    TopK:           5,
+    IncludePayload: true,
+    ScoreThreshold: proto.Float32(0.6),
+})
+
+// Batch query
+batch, err := client.BatchQueryVectorsAlpha1(ctx, &client.BatchQueryVectorsRequestAlpha1{
+    StoreName: "meili-docs",
+    Collection:    "manuals",
+    Queries: []*client.QueryVectorsRequestAlpha1{
+        {Query: &client.QueryVectorsRequestAlpha1_Vector{Vector: &client.VectorRecord{Values: q1}}, TopK: 5},
+        {Query: &client.QueryVectorsRequestAlpha1_Vector{Vector: &client.VectorRecord{Values: q2}}, TopK: 5},
+    },
+})
+```
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