[Feat] support dimensions OpenAI embedding param

docs/my-website/docs/embedding/supported_embedding.md

@@ -13,16 +13,20 @@ response = embedding(model='text-embedding-ada-002', input=["good morning from l
 
 - `model`: *string* - ID of the model to use. `model='text-embedding-ada-002'`
 
-- `input`: *array* - Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for text-embedding-ada-002), cannot be an empty string, and any array must be 2048 dimensions or less. 
-```
+- `input`: *string or array* - Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for text-embedding-ada-002), cannot be an empty string, and any array must be 2048 dimensions or less. 
+```python
 input=["good morning from litellm"]
 ```
 
 ### Optional LiteLLM Fields
 
 - `user`: *string (optional)* A unique identifier representing your end-user, 
 
-- `timeout`: *integer* - The maximum time, in seconds, to wait for the API to respond. Defaults to 600 seconds (10 minutes).
+- `dimensions`: *integer (Optional)* The number of dimensions the resulting output embeddings should have. Only supported in OpenAI/Azure text-embedding-3 and later models.
+
+- `encoding_format`: *string (Optional)* The format to return the embeddings in. Can be either `"float"` or `"base64"`. Defaults to `encoding_format="float"`
+
+- `timeout`: *integer (Optional)* - The maximum time, in seconds, to wait for the API to respond. Defaults to 600 seconds (10 minutes).
 
 - `api_base`: *string (optional)* - The api endpoint you want to call the model with
 
@@ -66,7 +70,12 @@ input=["good morning from litellm"]
 from litellm import embedding
 import os
 os.environ['OPENAI_API_KEY'] = ""
-response = embedding('text-embedding-ada-002', input=["good morning from litellm"])
+response = embedding(
+    model="text-embedding-3-small",
+    input=["good morning from litellm", "this is another item"],
+    metadata={"anything": "good day"},
+    dimensions=5 # Only supported in text-embedding-3 and later models.
+)
 ```
 
 | Model Name           | Function Call                               | Required OS Variables                |

litellm/main.py

@@ -2224,6 +2224,7 @@ def embedding(
     model,
     input=[],
     # Optional params
+    dimensions: Optional[int] = None,
     timeout=600,  # default to 10 minutes
     # set api_base, api_version, api_key
     api_base: Optional[str] = None,
@@ -2244,6 +2245,7 @@ def embedding(
     Parameters:
     - model: The embedding model to use.
     - input: The input for which embeddings are to be generated.
+    - dimensions: The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models.
     - timeout: The timeout value for the API call, default 10 mins
     - litellm_call_id: The call ID for litellm logging.
     - litellm_logging_obj: The litellm logging object.
@@ -2277,6 +2279,7 @@ def embedding(
     output_cost_per_second = kwargs.get("output_cost_per_second", None)
     openai_params = [
         "user",
+        "dimensions",
         "request_timeout",
         "api_base",
         "api_version",
@@ -2345,7 +2348,9 @@ def embedding(
         api_key=api_key,
     )
     optional_params = get_optional_params_embeddings(
+        model=model,
         user=user,
+        dimensions=dimensions,
         encoding_format=encoding_format,
         custom_llm_provider=custom_llm_provider,
         **non_default_params,

litellm/tests/test_embedding.py

@@ -64,7 +64,9 @@ def test_openai_embedding_3():
             model="text-embedding-3-small",
             input=["good morning from litellm", "this is another item"],
             metadata={"anything": "good day"},
+            dimensions=5,
         )
+        print(f"response:", response)
         litellm_response = dict(response)
         litellm_response_keys = set(litellm_response.keys())
         litellm_response_keys.discard("_response_ms")
@@ -80,6 +82,7 @@ def test_openai_embedding_3():
         response = client.embeddings.create(
             model="text-embedding-3-small",
             input=["good morning from litellm", "this is another item"],
+            dimensions=5,
         )
 
         response = dict(response)

litellm/utils.py

@@ -3313,8 +3313,10 @@ def get_optional_params_image_gen(
 
 def get_optional_params_embeddings(
     # 2 optional params
+    model=None,
     user=None,
     encoding_format=None,
+    dimensions=None,
     custom_llm_provider="",
     **kwargs,
 ):
@@ -3325,14 +3327,27 @@ def get_optional_params_embeddings(
     for k, v in special_params.items():
         passed_params[k] = v
 
-    default_params = {"user": None, "encoding_format": None}
+    default_params = {"user": None, "encoding_format": None, "dimensions": None}
 
     non_default_params = {
         k: v
         for k, v in passed_params.items()
         if (k in default_params and v != default_params[k])
     }
     ## raise exception if non-default value passed for non-openai/azure embedding calls
+    if custom_llm_provider == "openai":
+        # 'dimensions` is only supported in `text-embedding-3` and later models
+
+        if (
+            model is not None
+            and "text-embedding-3" not in model
+            and "dimensions" in non_default_params.keys()
+        ):
+            raise UnsupportedParamsError(
+                status_code=500,
+                message=f"Setting dimensions is not supported for OpenAI `text-embedding-3` and later models. To drop it from the call, set `litellm.drop_params = True`.",
+            )
+
     if (
         custom_llm_provider != "openai"
         and custom_llm_provider != "azure"