feat: add embedding parameter to Context.add() (#31)

Exposes the embedding field so users can store vectors for semantic search.

Author: dcfocus

python/python/lance_context/api.py

@@ -236,13 +236,14 @@ def add(
         content: Any,
         content_type: str | None = None,
         data_type: str | None = None,
+        embedding: list[float] | None = None,
     ) -> None:
         if content_type is not None and data_type is not None:
             raise ValueError("Specify only one of content_type or data_type")
         if content_type is None:
             content_type = data_type
         payload, resolved_type = _normalize_content(content, content_type)
-        self._inner.add(role, payload, resolved_type)
+        self._inner.add(role, payload, resolved_type, embedding)
 
     def snapshot(self, label: str | None = None) -> str:
         return self._inner.snapshot(label)

python/src/lib.rs

@@ -153,13 +153,14 @@ impl Context {
         self.store.version()
     }
 
-    #[pyo3(signature = (role, content, data_type = None))]
+    #[pyo3(signature = (role, content, data_type = None, embedding = None))]
     fn add(
         &mut self,
         py: Python<'_>,
         role: &str,
         content: &Bound<'_, PyAny>,
         data_type: Option<&str>,
+        embedding: Option<Vec<f32>>,
     ) -> PyResult<()> {
         let (content_type, text_payload, binary_payload, inner_content) =
             match content.extract::<&[u8]>() {
@@ -190,7 +191,7 @@ impl Context {
             content_type,
             text_payload,
             binary_payload,
-            embedding: None,
+            embedding,
         };
 
         let add_res = py.allow_threads(|| {

python/tests/test_search.py

@@ -1,4 +1,5 @@
 from datetime import datetime
+from typing import Any
 
 import pytest
 from lance_context.api import Context, _coerce_vector, _normalize_record, _normalize_search_hit
@@ -8,6 +9,10 @@ class DummyInner:
     def __init__(self) -> None:
         self.search_calls: list[tuple[list[float], int | None]] = []
         self.list_calls: list[tuple[int | None, int | None]] = []
+        self.add_calls: list[tuple[str, Any, str | None, list[float] | None]] = []
+
+    def add(self, role: str, content: Any, data_type: str | None, embedding: list[float] | None):
+        self.add_calls.append((role, content, data_type, embedding))
 
     def search(self, vector: list[float], limit: int | None):
         self.search_calls.append((vector, limit))
@@ -140,3 +145,48 @@ def test_context_list_default_args():
     ctx.list()
 
     assert dummy.list_calls == [(None, None)]
+
+
+def test_context_add_with_embedding():
+    ctx = Context.__new__(Context)
+    dummy = DummyInner()
+    ctx._inner = dummy  # type: ignore[attr-defined]
+
+    embedding = [0.1, 0.2, 0.3]
+    ctx.add("user", "hello", embedding=embedding)
+
+    assert len(dummy.add_calls) == 1
+    role, content, data_type, passed_embedding = dummy.add_calls[0]
+    assert role == "user"
+    assert content == "hello"
+    assert data_type is None
+    assert passed_embedding == [0.1, 0.2, 0.3]
+
+
+def test_context_add_without_embedding():
+    ctx = Context.__new__(Context)
+    dummy = DummyInner()
+    ctx._inner = dummy  # type: ignore[attr-defined]
+
+    ctx.add("assistant", "world")
+
+    assert len(dummy.add_calls) == 1
+    role, content, data_type, passed_embedding = dummy.add_calls[0]
+    assert role == "assistant"
+    assert content == "world"
+    assert passed_embedding is None
+
+
+def test_context_add_with_content_type_and_embedding():
+    ctx = Context.__new__(Context)
+    dummy = DummyInner()
+    ctx._inner = dummy  # type: ignore[attr-defined]
+
+    embedding = [0.5, 0.6]
+    ctx.add("system", "prompt", content_type="text/markdown", embedding=embedding)
+
+    assert len(dummy.add_calls) == 1
+    role, content, data_type, passed_embedding = dummy.add_calls[0]
+    assert role == "system"
+    assert data_type == "text/markdown"
+    assert passed_embedding == [0.5, 0.6]