Add digitalocean provider (#12169)

* Add digitalocean provider * Add digitalocean provider * Revert "Add digitalocean provider" This reverts commit 96dda40f45b3d12ea03e861d060ec81460b7759e. * changes * fixes * Update transformation * refactoring * rename provider to Gradient AI * fixes * Incorporte review comments * revert changes * fix typo * revert change * incorporated review comments * Revert "Incorporte review comments" This reverts commit 37bd51bd54ef4fd52ccc12866e47f8de9476d597. * changes * Revert "Revert "Incorporte review comments" This reverts commit 37bd51bd54ef4fd52ccc12866e47f8de9476d597." This reverts commit 68c8a198ee0d6441c3a52f6c6a49c9c95a4cb0a8. * changes * fixes * Update provider_specific_fields.tsx
2026-08-18 06:26:16 +00:00 · 2025-08-09 16:26:33 -07:00
parent f60a9cf908
commit 0e53b1feab
15 changed files with 752 additions and 26 deletions
@@ -47,7 +47,7 @@ Support for more providers. Missing a provider or LLM Platform, raise a [feature
 # Usage ([**Docs**](https://docs.litellm.ai/docs/))

 > [!IMPORTANT]
-> LiteLLM v1.0.0 now requires `openai>=1.0.0`. Migration guide [here](https://docs.litellm.ai/docs/migration)  
+> LiteLLM v1.0.0 now requires `openai>=1.0.0`. Migration guide [here](https://docs.litellm.ai/docs/migration)
 > LiteLLM v1.40.14+ now requires `pydantic>=2.0.0`. No changes required.

 <a target="_blank" href="https://colab.research.google.com/github/BerriAI/litellm/blob/main/cookbook/liteLLM_Getting_Started.ipynb">
@@ -132,7 +132,7 @@ print(response)

 ## Streaming ([Docs](https://docs.litellm.ai/docs/completion/stream))

-liteLLM supports streaming the model response back, pass `stream=True` to get a streaming iterator in response.  
+liteLLM supports streaming the model response back, pass `stream=True` to get a streaming iterator in response.
 Streaming is supported for all models (Bedrock, Huggingface, TogetherAI, Azure, OpenAI, etc.)

 ```python
@@ -234,7 +234,7 @@ $ litellm --model huggingface/bigcode/starcoder


 > [!IMPORTANT]
-> 💡 [Use LiteLLM Proxy with Langchain (Python, JS), OpenAI SDK (Python, JS) Anthropic SDK, Mistral SDK, LlamaIndex, Instructor, Curl](https://docs.litellm.ai/docs/proxy/user_keys)  
+> 💡 [Use LiteLLM Proxy with Langchain (Python, JS), OpenAI SDK (Python, JS) Anthropic SDK, Mistral SDK, LlamaIndex, Instructor, Curl](https://docs.litellm.ai/docs/proxy/user_keys)

 ```python
 import openai # openai v1.0.0+
@@ -266,7 +266,7 @@ echo 'LITELLM_MASTER_KEY="sk-1234"' > .env

 # Add the litellm salt key - you cannot change this after adding a model
 # It is used to encrypt / decrypt your LLM API Key credentials
-# We recommend - https://1password.com/password-generator/ 
+# We recommend - https://1password.com/password-generator/
 # password generator to get a random hash for litellm salt key
 echo 'LITELLM_SALT_KEY="sk-1234"' >> .env

@@ -340,6 +340,7 @@ curl 'http://0.0.0.0:4000/key/generate' \
 | [xinference [Xorbits Inference]](https://docs.litellm.ai/docs/providers/xinference) |                                                         |                                                                                 |                                                                                     |                                                                                   | ✅                                                                             |                                                                         |
 | [FriendliAI](https://docs.litellm.ai/docs/providers/friendliai)                              | ✅                                                       | ✅                                                                               | ✅                                                                                   | ✅                                                                                 |                                                                               |                                                                         |
 | [Galadriel](https://docs.litellm.ai/docs/providers/galadriel)                              | ✅                                                       | ✅                                                                               | ✅                                                                                   | ✅                                                                                 |                                                                               |                                                                         |
+| [GradientAI](https://docs.litellm.ai/docs/providers/gradient_ai)                              | ✅                                                       | ✅                                                                               |                                                                                   |                                                                                  |                                                                               |                                                                         |
 | [Novita AI](https://novita.ai/models/llm?utm_source=github_litellm&utm_medium=github_readme&utm_campaign=github_link)                     | ✅                                                       | ✅                                                                               | ✅                                                                                   | ✅                                                                                 |                                                                               |                                                                         |
 | [Featherless AI](https://docs.litellm.ai/docs/providers/featherless_ai)                              | ✅                                                       | ✅                                                                               | ✅                                                                                   | ✅                                                                                 |                                                                               |                                                                         |
 | [Nebius AI Studio](https://docs.litellm.ai/docs/providers/nebius)                             | ✅                                                       | ✅                                                                               | ✅                                                                                   | ✅                                                                                 | ✅                                                                             |                                                                         |
@@ -348,7 +349,7 @@ curl 'http://0.0.0.0:4000/key/generate' \

 ## Contributing

-Interested in contributing? Contributions to LiteLLM Python SDK, Proxy Server, and LLM integrations are both accepted and highly encouraged! 
+Interested in contributing? Contributions to LiteLLM Python SDK, Proxy Server, and LLM integrations are both accepted and highly encouraged!

 **Quick start:** `git clone` → `make install-dev` → `make format` → `make lint` → `make test-unit`

@@ -359,7 +360,7 @@ For companies that need better security, user management and professional suppor

 [Talk to founders](https://calendly.com/d/4mp-gd3-k5k/litellm-1-1-onboarding-chat)

-This covers: 
+This covers:
 - ✅ **Features under the [LiteLLM Commercial License](https://docs.litellm.ai/docs/proxy/enterprise):**
 - ✅ **Feature Prioritization**
 - ✅ **Custom Integrations**
@@ -0,0 +1,79 @@
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# GradientAI
+https://digitalocean.com/products/gradientai
+
+
+LiteLLM provides native support for GradientAI models.
+To use a GradientAI model, specify it as `gradient_ai/<model-name>` in your LiteLLM requests.
+
+
+## API Key & Endpoint
+
+Set your credentials and endpoint as environment variables:
+
+```python
+import os
+os.environ['GRADIENT_AI_API_KEY'] = "your-api-key"
+os.environ['GRADIENT_AI_AGENT_ENDPOINT'] = "https://api.gradient_ai.com/api/v1/chat"  # default endpoint
+```
+
+## Sample Usage
+
+```python
+from litellm import completion
+import os
+
+os.environ['GRADIENT_AI_API_KEY'] = "your-api-key"
+response = completion(
+    model="gradient_ai/model-name",
+    messages=[
+        {"role": "user", "content": "Hello, how are you?"}
+    ],
+)
+print(response.choices[0].message.content)
+```
+
+## Streaming Example
+
+```python
+from litellm import completion
+import os
+
+os.environ['GRADIENT_AI_API_KEY'] = "your-api-key"
+response = completion(
+    model="gradient_ai/model-name",
+    messages=[
+        {"role": "user", "content": "Write a story about a robot learning to love"}
+    ],
+    stream=True,
+)
+
+for chunk in response:
+    print(chunk.choices[0].delta.content or "", end="")
+```
+
+## Supported Parameters
+
+| Parameter                        | Type         | Description                                                        |
+|-----------------------------------|--------------|--------------------------------------------------------------------|
+| `temperature`                     | float        | Controls randomness (0.0-2.0)                                      |
+| `top_p`                           | float        | Nucleus sampling parameter (0.0-1.0)                               |
+| `max_tokens`                      | int          | Maximum tokens to generate                                         |
+| `max_completion_tokens`           | int          | Alternative to max_tokens                                          |
+| `stream`                          | bool         | Whether to stream the response                                     |
+| `k`                               | int          | Top results to return from knowledge bases                         |
+| `retrieval_method`                | string       | Retrieval strategy (rewrite/step_back/sub_queries/none)            |
+| `frequency_penalty`               | float        | Penalizes repeated tokens (-2.0 to 2.0)                            |
+| `presence_penalty`                | float        | Penalizes tokens based on presence (-2.0 to 2.0)                   |
+| `stop`                            | string/list  | Sequences to stop generation                                       |
+| `kb_filters`                      | List[Dict]   | Filters for knowledge base retrieval                               |
+| `instruction_override`            | string       | Override agent's default instruction                               |
+| `include_retrieval_info`          | bool         | Include document retrieval metadata                                |
+| `include_guardrails_info`         | bool         | Include guardrail trigger metadata                                 |
+| `provide_citations`               | bool         | Include citations in response                                      |
+
+---
+
+For more details, see [DigitalOcean GradientAI documentation](https://digitalocean.com/products/gradientai).
@@ -82,12 +82,12 @@ const sidebars = {
        "tutorials/cost_tracking_coding",
      ]
    },
-    
+
  ],
  // But you can create a sidebar manually
  tutorialSidebar: [
    { type: "doc", id: "index" }, // NEW
-    
+
    {
      type: "category",
      label: "LiteLLM Proxy Server",
@@ -214,7 +214,7 @@ const sidebars = {
            "proxy/dynamic_logging"
          ],
        },
-        
+
        {
          type: "category",
          label: "Secret Managers",
@@ -467,6 +467,7 @@ const sidebars = {
        "providers/custom_llm_server",
        "providers/petals",
        "providers/snowflake",
+        "providers/gradient_ai",
        "providers/featherless_ai",
        "providers/nebius",
        "providers/dashscope",
@@ -505,7 +506,7 @@ const sidebars = {

      ]
    },
-    
+
    {
      type: "category",
      label: "Routing, Loadbalancing & Fallbacks",
@@ -536,7 +537,7 @@ const sidebars = {
        },
      ],
    },
-    
+
    {
      type: "category",
      label: "Load Testing",
@@ -231,6 +231,7 @@ aleph_alpha_key: Optional[str] = None
 nlp_cloud_key: Optional[str] = None
 novita_api_key: Optional[str] = None
 snowflake_key: Optional[str] = None
+gradient_ai_api_key: Optional[str] = None
 nebius_key: Optional[str] = None
 common_cloud_provider_auth_params: dict = {
    "params": ["project", "region_name", "token"],
@@ -520,6 +521,7 @@ sambanova_models: List = []
 novita_models: List = []
 assemblyai_models: List = []
 snowflake_models: List = []
+gradient_ai_models: List = []
 llama_models: List = []
 nscale_models: List = []
 nebius_models: List = []
@@ -703,6 +705,8 @@ def add_known_models():
            jina_ai_models.append(key)
        elif value.get("litellm_provider") == "snowflake":
            snowflake_models.append(key)
+        elif value.get("litellm_provider") == "gradient_ai":
+            gradient_ai_models.append(key)
        elif value.get("litellm_provider") == "featherless_ai":
            featherless_ai_models.append(key)
        elif value.get("litellm_provider") == "deepgram":
@@ -802,6 +806,7 @@ model_list = (
    + assemblyai_models
    + jina_ai_models
    + snowflake_models
+    + gradient_ai_models
    + llama_models
    + featherless_ai_models
    + nscale_models
@@ -875,6 +880,7 @@ models_by_provider: dict = {
    "assemblyai": assemblyai_models,
    "jina_ai": jina_ai_models,
    "snowflake": snowflake_models,
+    "gradient_ai": gradient_ai_models,
    "meta_llama": llama_models,
    "nscale": nscale_models,
    "featherless_ai": featherless_ai_models,
@@ -1141,7 +1147,7 @@ from .llms.openai.chat.o_series_transformation import (
 )

 from .llms.snowflake.chat.transformation import SnowflakeConfig
-
+from .llms.gradient_ai.chat.transformation import GradientAIConfig
 openaiOSeriesConfig = OpenAIOSeriesConfig()
 from .llms.openai.chat.gpt_transformation import (
    OpenAIGPTConfig,
@@ -270,6 +270,7 @@ LITELLM_CHAT_PROVIDERS = [
    "llamafile",
    "lm_studio",
    "galadriel",
+    "gradient_ai",
    "github_copilot",  # GitHub Copilot Chat API
    "novita",
    "meta_llama",
@@ -351,6 +351,8 @@ def get_llm_provider(  # noqa: PLR0915
            custom_llm_provider = "openai"
        elif model in litellm.empower_models:
            custom_llm_provider = "empower"
+        elif model in litellm.gradient_ai_models:
+            custom_llm_provider = "gradient_ai"
        elif model == "*":
            custom_llm_provider = "openai"
        # bytez models
@@ -664,6 +666,13 @@ def _get_openai_compatible_provider_info(  # noqa: PLR0915
            or f"https://{get_secret('SNOWFLAKE_ACCOUNT_ID')}.snowflakecomputing.com/api/v2/cortex/inference:complete"
        )  # type: ignore
        dynamic_api_key = api_key or get_secret_str("SNOWFLAKE_JWT")
+    elif custom_llm_provider == "gradient_ai":
+        (
+            api_base,
+            dynamic_api_key,
+        ) = litellm.GradientAIConfig()._get_openai_compatible_provider_info(
+            api_base, api_key
+        )
    elif custom_llm_provider == "featherless_ai":
        (
            api_base,
@@ -0,0 +1,147 @@
+from typing import List, Optional, Tuple, Union, Dict, Literal
+
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import (
+    AllMessageValues,
+)
+
+from ...openai_like.chat.transformation import OpenAILikeChatConfig
+
+# Default GradientAI endpoint
+GRADIENT_AI_SERVERLESS_ENDPOINT = "https://inference.do-ai.run"
+
+
+class GradientAIConfig(OpenAILikeChatConfig):
+
+    k: Optional[int] = None
+    kb_filters: Optional[List[Dict]] = None
+    filter_kb_content_by_query_metadata: Optional[bool] = None
+    instruction_override: Optional[str] = None
+    include_functions_info: Optional[bool] = None
+    include_retrieval_info: Optional[bool] = None
+    include_guardrails_info: Optional[bool] = None
+    provide_citations: Optional[bool] = None
+    retrieval_method: Optional[Literal["rewrite", "step_back", "sub_queries", "none"]] = None
+
+    def __init__(
+        self,
+        frequency_penalty: Optional[float] = None,
+        max_tokens: Optional[int] = None,
+        max_completion_tokens: Optional[int] = None,
+        presence_penalty: Optional[float] = None,
+        retrieval_method: Optional[str] = None,
+        stop: Optional[Union[str, List[str]]] = None,
+        stream: Optional[bool] = None,
+        temperature: Optional[float] = None,
+        top_p: Optional[float] = None,
+        k: Optional[int] = None,
+        kb_filters: Optional[List[Dict]] = None,
+        filter_kb_content_by_query_metadata: Optional[bool] = None,
+        instruction_override: Optional[str] = None,
+        include_functions_info: Optional[bool] = None,
+        include_retrieval_info: Optional[bool] = None,
+        include_guardrails_info: Optional[bool] = None,
+        provide_citations: Optional[bool] = None,
+    ) -> None:
+        locals_ = locals().copy()
+        for key, value in locals_.items():
+            if key != "self" and value is not None:
+                setattr(self.__class__, key, value)
+
+    @classmethod
+    def get_config(cls):
+        return super().get_config()
+
+    def get_supported_openai_params(self, model: str) -> list:
+        supported_params = [
+            "frequency_penalty",
+            "max_tokens",
+            "max_completion_tokens",
+            "presence_penalty",
+            "stop",
+            "stream",
+            "stream_options",
+            "temperature",
+            "top_p",
+            # GradientAI specific parameters
+            "k",
+            "kb_filters",
+            "filter_kb_content_by_query_metadata",
+            "instruction_override",
+            "include_functions_info",
+            "include_retrieval_info",
+            "include_guardrails_info",
+            "provide_citations",
+            "retrieval_method",
+        ]
+        return supported_params
+
+    def validate_environment(self,
+                             headers: dict,
+                             model: str,
+                             messages: List[AllMessageValues],
+                             optional_params: dict,
+                             litellm_params: dict,
+                             api_key: Optional[str] = None,
+                             api_base: Optional[str] = None):
+        api_key = api_key or get_secret_str("GRADIENT_AI_API_KEY")
+        if api_key is None:
+            raise ValueError("GradientAI API key not found")
+        if headers is None:
+            headers = {}
+        headers["Authorization"] = f"Bearer {api_key}"
+        headers["Content-Type"] = "application/json"
+        return headers
+
+    def get_complete_url(
+        self,
+        api_base: Optional[str],
+        api_key: Optional[str],
+        model: str,
+        optional_params: dict,
+        litellm_params: dict,
+        stream: Optional[bool] = None,
+    ) -> str:
+        gradient_ai_endpoint = get_secret_str("GRADIENT_AI_AGENT_ENDPOINT")
+        complete_url = f"{GRADIENT_AI_SERVERLESS_ENDPOINT}/v1/chat/completions"
+
+        if api_base and api_base != GRADIENT_AI_SERVERLESS_ENDPOINT:
+            complete_url = f"{api_base}/api/v1/chat/completions"
+        elif gradient_ai_endpoint and gradient_ai_endpoint != GRADIENT_AI_SERVERLESS_ENDPOINT:
+            complete_url = f"{gradient_ai_endpoint}/api/v1/chat/completions"
+
+        return complete_url
+
+    def _get_openai_compatible_provider_info(
+        self, api_base: Optional[str], api_key: Optional[str]
+    ) -> Tuple[Optional[str], Optional[str]]:
+        gradient_ai_endpoint = get_secret_str("GRADIENT_AI_AGENT_ENDPOINT")
+
+        if not api_base and not gradient_ai_endpoint:
+            api_base = GRADIENT_AI_SERVERLESS_ENDPOINT
+        else:
+            api_base = api_base or gradient_ai_endpoint
+
+        dynamic_api_key = api_key or get_secret_str("GRADIENT_AI_API_KEY")
+        return api_base, dynamic_api_key
+
+    def map_openai_params(
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool = False,
+        replace_max_completion_tokens_with_max_tokens: bool = False,
+    ) -> dict:
+        supported_openai_params = self.get_supported_openai_params(model=model)
+        for param, value in non_default_params.items():
+            if param in supported_openai_params:
+                optional_params[param] = value
+            elif not drop_params:
+                from litellm.utils import UnsupportedParamsError
+                raise UnsupportedParamsError(
+                    status_code=400,
+                    message=f"GradientAI does not support parameter '{param}'. To drop unsupported params, set `drop_params=True`."
+                )
+
+        return optional_params
@@ -3303,6 +3303,25 @@ def completion(  # type: ignore # noqa: PLR0915
                    additional_args={"headers": headers},
                )
                raise e
+        elif custom_llm_provider == "gradient_ai":
+
+            api_base = litellm.api_base or api_base
+            response = base_llm_http_handler.completion(
+                model=model,
+                stream=stream,
+                messages=messages,
+                acompletion=acompletion,
+                api_base=api_base,
+                model_response=model_response,
+                optional_params=optional_params,
+                litellm_params=litellm_params,
+                custom_llm_provider="gradient_ai",
+                timeout=timeout,
+                headers=headers,
+                encoding=encoding,
+                api_key=api_key,
+                logging_obj=logging,
+            )

        elif custom_llm_provider == "bytez":
            api_key = (
@@ -1618,7 +1618,7 @@ class ImageResponse(OpenAIImageResponse, BaseLiteLLMOpenAIResponseObject):

    usage: Optional[ImageUsage] = None  # type: ignore
    """
-    Users might use litellm with older python versions, we don't want this to break for them. 
+    Users might use litellm with older python versions, we don't want this to break for them.
    Happens when their OpenAIImageResponse has the old OpenAI usage class.
    """

@@ -2324,6 +2324,7 @@ class LlmProviders(str, Enum):
    ASSEMBLYAI = "assemblyai"
    GITHUB_COPILOT = "github_copilot"
    SNOWFLAKE = "snowflake"
+    GRADIENT_AI = "gradient_ai"
    LLAMA = "meta_llama"
    NSCALE = "nscale"
    PG_VECTOR = "pg_vector"
@@ -6963,6 +6963,8 @@ class ProviderConfigManager:
            return litellm.LiteLLMProxyChatConfig()
        elif litellm.LlmProviders.OPENAI == provider:
            return litellm.OpenAIGPTConfig()
+        elif litellm.LlmProviders.GRADIENT_AI == provider:
+            return litellm.GradientAIConfig()
        elif litellm.LlmProviders.NSCALE == provider:
            return litellm.NscaleConfig()
        elif litellm.LlmProviders.OCI == provider:
@@ -17098,6 +17098,130 @@
        "litellm_provider": "snowflake",
        "mode": "chat"
    },
+    "gradient_ai/anthropic-claude-3.7-sonnet": {
+        "input_cost_per_token": 3e-06,
+        "output_cost_per_token": 15e-06,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 1024,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/anthropic-claude-3.5-sonnet": {
+        "input_cost_per_token": 3e-06,
+        "output_cost_per_token": 15e-06,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 1024,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/anthropic-claude-3.5-haiku": {
+        "input_cost_per_token": 8e-07,
+        "output_cost_per_token": 4e-06,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 1024,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/anthropic-claude-3-opus": {
+        "input_cost_per_token": 15e-06,
+        "output_cost_per_token": 75e-06,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 1024,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/deepseek-r1-distill-llama-70b": {
+        "input_cost_per_token": 99e-08,
+        "output_cost_per_token": 99e-08,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 8000,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/llama3.3-70b-instruct": {
+        "input_cost_per_token": 65e-08,
+        "output_cost_per_token": 65e-08,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 2048,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/llama3-8b-instruct": {
+        "input_cost_per_token": 2e-07,
+        "output_cost_per_token": 2e-07,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 512,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/mistral-nemo-instruct-2407": {
+        "input_cost_per_token": 3e-07,
+        "output_cost_per_token": 3e-07,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 512,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/openai-o3": {
+        "input_cost_per_token": 2e-06,
+        "output_cost_per_token": 8e-06,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 100000,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/openai-o3-mini": {
+        "input_cost_per_token": 11e-07,
+        "output_cost_per_token": 44e-07,
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 100000,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/openai-gpt-4o": {
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 16384,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/openai-gpt-4o-mini": {
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 16384,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
+    "gradient_ai/alibaba-qwen3-32b": {
+        "litellm_provider": "gradient_ai",
+        "mode": "chat",
+        "max_tokens": 2048,
+        "supported_endpoints": ["/v1/chat/completions"],
+        "supported_modalities": ["text"],
+        "supports_tool_choice": false
+    },
    "nscale/meta-llama/Llama-4-Scout-17B-16E-Instruct": {
        "input_cost_per_token": 9e-08,
        "output_cost_per_token": 2.9e-07,
@@ -0,0 +1,91 @@
+import os
+import sys
+import pytest
+
+sys.path.insert(
+    0, os.path.abspath("../../../../..")
+)  # Adds the parent directory to the system path
+
+from litellm.llms.gradient_ai.chat.transformation import GradientAIConfig, GRADIENT_AI_SERVERLESS_ENDPOINT
+
+DO_ENDPOINT_PATH = "/api/v1/chat/completions"
+DO_BASE_URL = "https://api.gradient_ai.com"
+
+@pytest.fixture
+def config():
+    return GradientAIConfig()
+
+def test_validate_environment_sets_headers(monkeypatch, config):
+    monkeypatch.setenv("GRADIENT_AI_API_KEY", "test-key")
+    headers = {}
+    result = config.validate_environment(
+        headers=headers,
+        model="gradient_ai/test-model",
+        messages=[],
+        optional_params={},
+        litellm_params={},
+        api_key=None,
+        api_base=None,
+    )
+    assert result["Authorization"] == "Bearer test-key"
+    assert result["Content-Type"] == "application/json"
+
+def test_get_complete_url_custom_base(config):
+    url = config.get_complete_url(
+        api_base=DO_BASE_URL,
+        api_key="test-key",
+        model="gradient_ai/test-model",
+        optional_params={},
+        litellm_params={},
+        stream=False,
+    )
+    assert url == f"{DO_BASE_URL}{DO_ENDPOINT_PATH}"
+
+def test_get_complete_url_default_serverless(monkeypatch, config):
+    monkeypatch.delenv("GRADIENT_AI_AGENT_ENDPOINT", raising=False)
+    url = config.get_complete_url(
+        api_base=None,
+        api_key="test-key",
+        model="gradient_ai/test-model",
+        optional_params={},
+        litellm_params={},
+        stream=False,
+    )
+    assert url == f"{GRADIENT_AI_SERVERLESS_ENDPOINT}/v1/chat/completions"
+
+def test_get_complete_url_with_env_endpoint(monkeypatch, config):
+    monkeypatch.setenv("GRADIENT_AI_AGENT_ENDPOINT", DO_BASE_URL)
+    url = config.get_complete_url(
+        api_base=None,
+        api_key="test-key",
+        model="gradient_ai/test-model",
+        optional_params={},
+        litellm_params={},
+        stream=False,
+    )
+    assert url == f"{DO_BASE_URL}{DO_ENDPOINT_PATH}"
+
+def test_transform_messages_handles_dicts_only(config):
+    messages = [
+        {"role": "assistant", "content": "Hello!"},
+        {"role": "user", "content": "Hi!"},
+    ]
+    out = config._transform_messages(messages, model="gradient_ai/test-model")
+    assert out[0]["role"] == "assistant"
+    assert out[0]["content"] == "Hello!"
+    assert out[1]["role"] == "user"
+    assert out[1]["content"] == "Hi!"
+
+def test_get_openai_compatible_provider_info_env(monkeypatch, config):
+    monkeypatch.setenv("GRADIENT_AI_AGENT_ENDPOINT", DO_BASE_URL)
+    monkeypatch.setenv("GRADIENT_AI_API_KEY", "env-key")
+    api_base, api_key = config._get_openai_compatible_provider_info(None, None)
+    assert api_base == DO_BASE_URL
+    assert api_key == "env-key"
+
+def test_get_openai_compatible_provider_info_default(monkeypatch, config):
+    monkeypatch.delenv("GRADIENT_AI_AGENT_ENDPOINT", raising=False)
+    monkeypatch.setenv("GRADIENT_AI_API_KEY", "env-key")
+    api_base, api_key = config._get_openai_compatible_provider_info(None, None)
+    assert api_base == GRADIENT_AI_SERVERLESS_ENDPOINT
+    assert api_key == "env-key"
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@@ -374,6 +374,20 @@ const PROVIDER_CREDENTIAL_FIELDS: Record<Providers, ProviderCredentialField[]> =
    type: "password",
    required: true
  }],
+  [Providers.GradientAI]: [
+    {
+      key: "api_base",
+      label: "GradientAI Endpoint",
+      placeholder: "https://...",
+      required: false
+    },
+    {
+      key: "api_key",
+      label: "GradientAI API Key",
+      type: "password",
+      required: true
+    }
+  ],
  [Providers.Triton]: [{
    key: "api_key",
    label: "API Key",
@@ -446,7 +460,7 @@ const ProviderSpecificFields: React.FC<ProviderSpecificFieldsProps> = ({
    onChange(info: any) {
      console.log("Upload onChange triggered in ProviderSpecificFields");
      console.log("Current form values:", form.getFieldsValue());
-      
+
      if (info.file.status !== "uploading") {
        console.log(info.file, info.fileList);
      }
@@ -465,7 +479,7 @@ const ProviderSpecificFields: React.FC<ProviderSpecificFieldsProps> = ({
            className={field.key === "vertex_credentials" ? "mb-0" : undefined}
          >
            {field.type === "select" ? (
-              <Select 
+              <Select
                placeholder={field.placeholder}
                defaultValue={field.defaultValue}
              >
@@ -476,14 +490,14 @@ const ProviderSpecificFields: React.FC<ProviderSpecificFieldsProps> = ({
                ))}
              </Select>
            ) : field.type === "upload" ? (
-              <Upload 
+              <Upload
                {...handleUpload}
                onChange={(info) => {
                  // First call the original onChange
                  if (uploadProps?.onChange) {
                    uploadProps.onChange(info);
                  }
-                  
+
                  // Check the field value after a short delay
                  setTimeout(() => {
                    const value = form.getFieldValue(field.key);
@@ -494,9 +508,9 @@ const ProviderSpecificFields: React.FC<ProviderSpecificFieldsProps> = ({
                <Button2 icon={<UploadOutlined />}>Click to Upload</Button2>
              </Upload>
            ) : (
-              <TextInput 
-                placeholder={field.placeholder} 
-                type={field.type === "password" ? "password" : "text"} 
+              <TextInput
+                placeholder={field.placeholder}
+                type={field.type === "password" ? "password" : "text"}
              />
            )}
          </Form.Item>
@@ -536,4 +550,4 @@ const ProviderSpecificFields: React.FC<ProviderSpecificFieldsProps> = ({
  );
 };

-export default ProviderSpecificFields;
+export default ProviderSpecificFields;
@@ -17,6 +17,7 @@ export enum Providers {
  ElevenLabs = "ElevenLabs",            
  FireworksAI = "Fireworks AI",         
  Google_AI_Studio = "Google AI Studio",
+  GradientAI = "GradientAI",
  Groq = "Groq",                       
  JinaAI = "Jina AI",                 
  MistralAI = "Mistral AI",             
@@ -35,7 +36,7 @@ export enum Providers {
  Voyage = "Voyage AI",                
  xAI = "xAI",                          
 }
-  
+
 export const provider_map: Record<string, string> = {
    OpenAI: "openai",
    OpenAI_Text: "text-completion-openai",
@@ -61,6 +62,7 @@ export const provider_map: Record<string, string> = {
    TogetherAI: "together_ai",
    Openrouter: "openrouter",
    FireworksAI: "fireworks_ai",
+    GradientAI: "gradient_ai",
    Triton: "triton",
    Deepgram: "deepgram",
    ElevenLabs: "elevenlabs",
@@ -99,6 +101,7 @@ export const providerLogoMap: Record<string, string> = {
    [Providers.TogetherAI]: `${asset_logos_folder}togetherai.svg`,
    [Providers.Vertex_AI]: `${asset_logos_folder}google.svg`,
    [Providers.xAI]: `${asset_logos_folder}xai.svg`,
+    [Providers.GradientAI]: `${asset_logos_folder}gradientai.svg`,
    [Providers.Triton]: `${asset_logos_folder}nvidia_triton.png`,
    [Providers.Deepgram]: `${asset_logos_folder}deepgram.png`,
    [Providers.ElevenLabs]: `${asset_logos_folder}elevenlabs.png`,
@@ -169,9 +172,9 @@ export const getPlaceholder = (selectedProvider: string): string => {
    console.log(`Provider key: ${providerKey}`);
    let custom_llm_provider = provider_map[providerKey];
    console.log(`Provider mapped to: ${custom_llm_provider}`);
-    
+
    let providerModels: Array<string> = [];
-    
+
    if (providerKey && typeof modelMap === "object") {
      Object.entries(modelMap).forEach(([key, value]) => {
        if (
@@ -184,7 +187,6 @@ export const getPlaceholder = (selectedProvider: string): string => {
          providerModels.push(key);
        }
      });
-  
      // Special case for cohere
      // we need both cohere_chat and cohere models to show on dropdown
      if (providerKey == Providers.Cohere) {
@@ -217,6 +219,6 @@ export const getPlaceholder = (selectedProvider: string): string => {
        });
      }
    }
-  
+
    return providerModels;
  };