Add support for multi-modal search

.code-samples.meilisearch.yaml

@@ -767,6 +767,25 @@ get_batch_1: |-
   client.get_batch(BATCH_UID)
 get_similar_post_1: |-
   client.index("INDEX_NAME").get_similar_documents({"id": "TARGET_DOCUMENT_ID", "embedder": "default"})
+search_parameter_reference_media_1: |-
+  client.index('movies_fragments').search(
+      "a futuristic space movie",
+      {
+          "media": {
+              "textAndPoster": {
+                  "text": "a futuristic space movie",
+                  "image": {
+                      "mime": "image/jpeg",
+                      "data": "BASE64_ENCODED_IMAGE_DATA"
+                  }
+              }
+          },
+          "hybrid": {
+              "embedder": "multimodal",
+              "semanticRatio": 1.0
+          },
+      }
+  )
 webhooks_get_1: |-
   client.get_webhooks()
 webhooks_get_single_1: |-

docs/conf.py

@@ -58,9 +58,9 @@
 # This value contains a list of modules to be mocked up.
 autodoc_mock_imports = ["camel_converter"]
 
-html_title = 'Meilisearch Python | Documentation'
+html_title = "Meilisearch Python | Documentation"
 
 # Add Fathom analytics script
 html_js_files = [
-    ("https://cdn.usefathom.com/script.js", { "data-site": "QNBPJXIV", "defer": "defer" })
+    ("https://cdn.usefathom.com/script.js", {"data-site": "QNBPJXIV", "defer": "defer"})
 ]

meilisearch/client.py

@@ -1110,3 +1110,41 @@ def _valid_uuid(uuid: str) -> bool:
         )
         match = uuid4hex.match(uuid)
         return bool(match)
+
+    def get_experimental_features(self) -> Dict[str, Any]:
+        """Retrieve the current settings for all experimental features.
+
+        Returns
+        -------
+        features:
+            A dictionary mapping feature names to their enabled/disabled state.
+            For example: {"multimodal": True, "vectorStore": False}
+
+        Raises
+        ------
+        MeilisearchApiError
+            An error containing details about why Meilisearch can't process your request. Meilisearch error codes are described here: https://www.meilisearch.com/docs/reference/errors/error_codes#meilisearch-errors
+        """
+        return self.http.get(self.config.paths.experimental_features)
+
+    def update_experimental_features(self, features: Dict[str, bool]) -> Dict[str, Any]:
+        """Update one or more experimental features.
+
+        Parameters
+        ----------
+        features:
+            A dictionary mapping feature names to booleans.
+            For example, {"multimodal": True} to enable multimodal,
+            or {"multimodal": True, "vectorStore": False} to update multiple features.
+
+        Returns
+        -------
+        features:
+            The updated experimental features settings as a dictionary.
+
+        Raises
+        ------
+        MeilisearchApiError
+            An error containing details about why Meilisearch can't process your request. Meilisearch error codes are described here: https://www.meilisearch.com/docs/reference/errors/error_codes#meilisearch-errors
+        """
+        return self.http.patch(self.config.paths.experimental_features, body=features)

meilisearch/config.py

@@ -47,6 +47,7 @@ class Paths:
         localized_attributes = "localized-attributes"
         edit = "edit"
         network = "network"
+        experimental_features = "experimental-features"
         webhooks = "webhooks"
 
     def __init__(

meilisearch/models/embedders.py

@@ -167,6 +167,12 @@ class RestEmbedder(CamelBase):
         Template defining the data Meilisearch sends to the embedder
     document_template_max_bytes: Optional[int]
         Maximum allowed size of rendered document template (defaults to 400)
+    indexing_fragments: Optional[Dict[str, Dict[str, Any]]]
+        Defines how to fragment documents for indexing (multi-modal search).
+        Fragments can contain complex nested structures (e.g., lists of objects).
+    search_fragments: Optional[Dict[str, Dict[str, Any]]]
+        Defines how to fragment search queries (multi-modal search).
+        Fragments can contain complex nested structures (e.g., lists of objects).
     request: Dict[str, Any]
         A JSON value representing the request Meilisearch makes to the remote embedder
     response: Dict[str, Any]
@@ -185,6 +191,8 @@ class RestEmbedder(CamelBase):
     dimensions: Optional[int] = None
     document_template: Optional[str] = None
     document_template_max_bytes: Optional[int] = None
+    indexing_fragments: Optional[Dict[str, Dict[str, Any]]] = None
+    search_fragments: Optional[Dict[str, Dict[str, Any]]] = None
     request: Dict[str, Any]
     response: Dict[str, Any]
     headers: Optional[Dict[str, str]] = None

tests/client/test_experimental_features.py

@@ -0,0 +1,22 @@
+"""Tests for experimental features API."""
+
+
+def test_get_experimental_features(client):
+    """Test getting experimental features."""
+    response = client.get_experimental_features()
+    assert isinstance(response, dict)
+    # Check that at least one known experimental feature is present
+    assert "multimodal" in response or "vectorStoreSetting" in response
+
+
+def test_update_experimental_features(client):
+    """Test updating experimental features."""
+    # Enable multimodal
+    response = client.update_experimental_features({"multimodal": True})
+    assert isinstance(response, dict)
+    assert response.get("multimodal") is True
+
+    # Disable multimodal
+    response = client.update_experimental_features({"multimodal": False})
+    assert isinstance(response, dict)
+    assert response.get("multimodal") is False