modify reference

docs/docs.trychroma.com/pages/getting-started.md

@@ -143,12 +143,23 @@ const collection = await client.createCollection({
 
 ### 4. Add some text documents to the collection
 
-Chroma will store your text and handle embedding and indexing automatically. You can also customize the embedding model.
+Chroma will store your text and handle embedding and indexing automatically. You can also customize the embedding model. When you add documents, IDs are optional. If you don't provide `ids`, Chroma will automatically generate `ids` using uuid v4 for you.
 
 {% tabs group="code-lang" hideTabs=true %}
 {% tab label="Python" %}
 
 ```python
+# Add docs without IDs
+result = collection.add(
+    documents=[
+        "This is a document about pineapple",
+        "This is a document about oranges"
+    ]
+)
+
+ids = result["ids"]
+
+# Add docs with IDs
 collection.add(
     documents=[
         "This is a document about pineapple",
@@ -162,6 +173,17 @@ collection.add(
 {% tab label="Javascript" %}
 
 ```js
+// Add docs without Ids
+result = await client.addRecords(collection, {
+  documents: [
+    "This is a document about pineapple",
+    "This is a document about oranges",
+  ]
+});
+
+ids = result.ids
+
+// Add docs with Ids
 await client.addRecords(collection, {
   documents: [
     "This is a document about pineapple",

docs/docs.trychroma.com/pages/guides/index.md

@@ -112,8 +112,7 @@ async def main():
     collection = await client.create_collection(name="my_collection")
 
     await collection.add(
-        documents=["hello world"],
-        ids=["id1"]
+        documents=["hello world"]
     )
 
 asyncio.run(main())
@@ -358,8 +357,7 @@ Raw documents:
 ```python
 collection.add(
     documents=["lorem ipsum...", "doc2", "doc3", ...],
-    metadatas=[{"chapter": "3", "verse": "16"}, {"chapter": "3", "verse": "5"}, {"chapter": "29", "verse": "11"}, ...],
-    ids=["id1", "id2", "id3", ...]
+    metadatas=[{"chapter": "3", "verse": "16"}, {"chapter": "3", "verse": "5"}, {"chapter": "29", "verse": "11"}, ...]
 )
 ```
 
@@ -372,7 +370,6 @@ Raw documents:
 
 ```javascript
 await client.addRecords(collection, {
-    ids: ["id1", "id2", "id3", ...],
     metadatas: [{"chapter": "3", "verse": "16"}, {"chapter": "3", "verse": "5"}, {"chapter": "29", "verse": "11"}, ...],
     documents: ["lorem ipsum...", "doc2", "doc3", ...],
 })
@@ -401,7 +398,6 @@ collection.add(
     documents=["doc1", "doc2", "doc3", ...],
     embeddings=[[1.1, 2.3, 3.2], [4.5, 6.9, 4.4], [1.1, 2.3, 3.2], ...],
     metadatas=[{"chapter": "3", "verse": "16"}, {"chapter": "3", "verse": "5"}, {"chapter": "29", "verse": "11"}, ...],
-    ids=["id1", "id2", "id3", ...]
 )
 ```
 
@@ -410,7 +406,6 @@ collection.add(
 
 ```javascript
 await client.addRecords(collection, {
-    ids: ["id1", "id2", "id3", ...],
     embeddings: [[1.1, 2.3, 3.2], [4.5, 6.9, 4.4], [1.1, 2.3, 3.2], ...],
     metadatas: [{"chapter": "3", "verse": "16"}, {"chapter": "3", "verse": "5"}, {"chapter": "29", "verse": "11"}, ...],
     documents: ["lorem ipsum...", "doc2", "doc3", ...],
@@ -432,8 +427,7 @@ You can also store documents elsewhere, and just supply a list of `embeddings` a
 ```python
 collection.add(
     embeddings=[[1.1, 2.3, 3.2], [4.5, 6.9, 4.4], [1.1, 2.3, 3.2], ...],
-    metadatas=[{"chapter": "3", "verse": "16"}, {"chapter": "3", "verse": "5"}, {"chapter": "29", "verse": "11"}, ...],
-    ids=["id1", "id2", "id3", ...]
+    metadatas=[{"chapter": "3", "verse": "16"}, {"chapter": "3", "verse": "5"}, {"chapter": "29", "verse": "11"}, ...]
 )
 ```
 
@@ -442,7 +436,6 @@ collection.add(
 
 ```javascript
 await client.addRecords(collection, {
-    ids: ["id1", "id2", "id3", ...],
     embeddings: [[1.1, 2.3, 3.2], [4.5, 6.9, 4.4], [1.1, 2.3, 3.2], ...],
     metadatas: [{"chapter": "3", "verse": "16"}, {"chapter": "3", "verse": "5"}, {"chapter": "29", "verse": "11"}, ...],
 })

docs/docs.trychroma.com/pages/guides/multimodal.md

@@ -65,7 +65,6 @@ You can add data to a multi-modal collection by specifying the data modality. Fo
 
 ```python
 collection.add(
-    ids=['id1', 'id2', 'id3'],
     images=[...] # A list of numpy arrays representing images
 )
 ```
@@ -76,7 +75,6 @@ However, you can use Chroma in combination with data stored elsewhere, by adding
 
 ```python
 collection.add(
-    ids=['id1', 'id2', 'id3'],
     uris=[...] #  A list of strings representing URIs to data
 )
 ```
@@ -85,7 +83,6 @@ Since the embedding function is multi-modal, you can also add text to the same c
 
 ```python
 collection.add(
-    ids=['id4', 'id5', 'id6'],
     texts=["This is a document", "This is another document", "This is a third document"]
 )
 ```

docs/docs.trychroma.com/pages/reference/cheatsheet.md

@@ -101,18 +101,15 @@ collection.add(
     embeddings=[1.5, 2.9, 3.4],
     metadatas={"uri": "img9.png", "style": "style1"},
     documents="doc1000101",
-    ids="uri9",
 )
 # or many, up to 100k+!
 collection.add(
     embeddings=[[1.5, 2.9, 3.4], [9.8, 2.3, 2.9]],
     metadatas=[{"style": "style1"}, {"style": "style2"}],
-    ids=["uri9", "uri10"],
 )
 collection.add(
     documents=["doc1000101", "doc288822"],
     metadatas=[{"style": "style1"}, {"style": "style2"}],
-    ids=["uri9", "uri10"],
 )
 
 # update items in a collection
@@ -200,21 +197,18 @@ await collection.count()
 // add new items to a collection
 // either one at a time
 await collection.add({
-    ids: "id1",
     embeddings: [1.5, 2.9, 3.4],
     metadatas: {"source": "my_source"},
     documents: "This is a document",
 })
 // or many, up to 100k+!
 await collection.add({
-    ids: ["uri9", "uri10"],
     embeddings: [[1.5, 2.9, 3.4], [9.8, 2.3, 2.9]],
     metadatas: [{"style": "style1"}, {"style": "style2"}],
     documents: ["This is a document", 'that is a document']
 })
 // including just documents
 await collection.add({
-    ids: ["uri9", "uri10"],
     metadatas: [{"style": "style1"}, {"style": "style2"}],
     documents: ["doc1000101", "doc288822"],
 })

docs/docs.trychroma.com/pages/reference/js-collection.md

@@ -34,7 +34,6 @@ Add items to the collection
 
 ```javascript
 const response = await collection.add({
-  ids: ["id1", "id2"],
   embeddings: [
     [1, 2, 3],
     [4, 5, 6],
@@ -51,7 +50,7 @@ const response = await collection.add({
 | `params`             | `Object`                    | The parameters for the query.            |
 | `params.documents?`  | `string` \| `Documents`     | Optional documents of the items to add.  |
 | `params.embeddings?` | `Embedding` \| `Embeddings` | Optional embeddings of the items to add. |
-| `params.ids`         | `string` \| `IDs`           | IDs of the items to add.                 |
+| `params.ids`         | `string` \| `IDs`           | Optional IDs of the items to add.        |
 | `params.metadatas?`  | `Metadata` \| `Metadatas`   | Optional metadata of the items to add.   |
 
 #### Returns

docs/docs.trychroma.com/pages/reference/py-collection.md

@@ -23,25 +23,25 @@ The total number of embeddings added to the database
 ### add
 
 ```python
-def add(ids: OneOrMany[ID],
+def add(ids: Optiona[OneOrMany[ID]] = None,
         embeddings: Optional[OneOrMany[Embedding]] = None,
         metadatas: Optional[OneOrMany[Metadata]] = None,
-        documents: Optional[OneOrMany[Document]] = None) -> None
+        documents: Optional[OneOrMany[Document]] = None) -> AddResult
 ```
 
 Add embeddings to the data store.
 
 **Arguments**:
 
-- `ids` - The ids of the embeddings you wish to add
+- `ids` - The ids of the embeddings you wish to add. If None, Chroma will generate the ids using uuid v4.
 - `embeddings` - The embeddings to add. If None, embeddings will be computed based on the documents using the embedding_function set for the Collection. Optional.
 - `metadatas` - The metadata to associate with the embeddings. When querying, you can filter on this metadata. Optional.
 - `documents` - The documents to associate with the embeddings. Optional.
 
 
 **Returns**:
 
-  None
+  - `AddResult` - An AddResult object containing IDs.
 
 
 **Raises**: