Add digitalocean provider

.circleci/config.yml

@@ -1154,7 +1154,7 @@ jobs:
           name: Install Helm
           command: |
             curl https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3 | bash
-      
+
       # Install kind
       - run:
           name: Install Kind
@@ -1162,7 +1162,7 @@ jobs:
             curl -Lo ./kind https://kind.sigs.k8s.io/dl/v0.20.0/kind-linux-amd64
             chmod +x ./kind
             sudo mv ./kind /usr/local/bin/kind
-      
+
       # Install kubectl
       - run:
           name: Install kubectl
@@ -1170,19 +1170,19 @@ jobs:
             curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
             chmod +x kubectl
             sudo mv kubectl /usr/local/bin/
-      
+
       # Create kind cluster
       - run:
           name: Create Kind Cluster
           command: |
             kind create cluster --name litellm-test
-      
+
       # Run helm lint
       - run:
           name: Run helm lint
           command: |
             helm lint ./deploy/charts/litellm-helm
-      
+
       # Run helm tests
       - run:
           name: Run helm tests
@@ -1191,15 +1191,15 @@ jobs:
             # Wait for pod to be ready
             echo "Waiting 30 seconds for pod to be ready..."
             sleep 30
-            
+
             # Print pod logs before running tests
             echo "Printing pod logs..."
             kubectl logs $(kubectl get pods -l app.kubernetes.io/name=litellm -o jsonpath="{.items[0].metadata.name}")
-            
+
             # Run the helm tests
             helm test litellm --logs
             helm test litellm --logs
-      
+
       # Cleanup
       - run:
           name: Cleanup
@@ -1309,7 +1309,7 @@ jobs:
             echo "=== Printing Full Container Startup Logs ==="
             docker logs my-app
             echo "=== End of Full Container Startup Logs ==="
-            
+
             if docker logs my-app 2>&1 | grep -q "prisma schema out of sync with db. Consider running these sql_commands to sync the two"; then
               echo "Expected message found in logs. Test passed."
             else
@@ -1427,6 +1427,7 @@ jobs:
               -e LANGFUSE_PROJECT2_PUBLIC=$LANGFUSE_PROJECT2_PUBLIC \
               -e LANGFUSE_PROJECT1_SECRET=$LANGFUSE_PROJECT1_SECRET \
               -e LANGFUSE_PROJECT2_SECRET=$LANGFUSE_PROJECT2_SECRET \
+              -e DIGITALOCEAN_API_KEY=$DIGITALOCEAN_API_KEY \
               --name my-app \
               -v $(pwd)/proxy_server_config.yaml:/app/config.yaml \
               my-app:latest \
@@ -1552,6 +1553,7 @@ jobs:
               -e LANGFUSE_PROJECT2_PUBLIC=$LANGFUSE_PROJECT2_PUBLIC \
               -e LANGFUSE_PROJECT1_SECRET=$LANGFUSE_PROJECT1_SECRET \
               -e LANGFUSE_PROJECT2_SECRET=$LANGFUSE_PROJECT2_SECRET \
+              -e DIGITALOCEAN_API_KEY=$DIGITALOCEAN_API_KEY \
               --name my-app \
               -v $(pwd)/litellm/proxy/example_config_yaml/oai_misc_config.yaml:/app/config.yaml \
               my-app:latest \
@@ -2030,7 +2032,7 @@ jobs:
           no_output_timeout:
             120m
             # Clean up first container
-      
+
   proxy_build_from_pip_tests:
     # Change from docker to machine executor
     machine:
@@ -2235,17 +2237,17 @@ jobs:
               curl -sSL https://rvm.io/mpapis.asc | gpg --import -
               curl -sSL https://rvm.io/pkuczynski.asc | gpg --import -
             }
-            
+
             # Install Ruby version manager (RVM)
             curl -sSL https://get.rvm.io | bash -s stable
-            
+
             # Source RVM from the correct location
             source $HOME/.rvm/scripts/rvm
-            
+
             # Install Ruby 3.2.2
             rvm install 3.2.2
             rvm use 3.2.2 --default
-            
+
             # Install latest Bundler
             gem install bundler
 
@@ -2408,32 +2410,32 @@ jobs:
             python -m pip install toml
             # Get current version from pyproject.toml
             CURRENT_VERSION=$(python -c "import toml; print(toml.load('pyproject.toml')['tool']['poetry']['version'])")
-            
+
             # Get last published version from PyPI
             LAST_VERSION=$(curl -s https://pypi.org/pypi/litellm-proxy-extras/json | python -c "import json, sys; print(json.load(sys.stdin)['info']['version'])")
-            
+
             echo "Current version: $CURRENT_VERSION"
             echo "Last published version: $LAST_VERSION"
-            
+
             # Compare versions using Python's packaging.version
             VERSION_COMPARE=$(python -c "from packaging import version; print(1 if version.parse('$CURRENT_VERSION') < version.parse('$LAST_VERSION') else 0)")
-            
+
             echo "Version compare: $VERSION_COMPARE"
             if [ "$VERSION_COMPARE" = "1" ]; then
               echo "Error: Current version ($CURRENT_VERSION) is less than last published version ($LAST_VERSION)"
               exit 1
             fi
-            
+
             # If versions are equal or current is greater, check contents
             pip download --no-deps litellm-proxy-extras==$LAST_VERSION -d /tmp
-            
+
             echo "Contents of /tmp directory:"
             ls -la /tmp
-            
+
             # Find the downloaded file (could be .whl or .tar.gz)
             DOWNLOADED_FILE=$(ls /tmp/litellm_proxy_extras-*)
             echo "Downloaded file: $DOWNLOADED_FILE"
-            
+
             # Extract based on file extension
             if [[ "$DOWNLOADED_FILE" == *.whl ]]; then
                 echo "Extracting wheel file..."
@@ -2444,10 +2446,10 @@ jobs:
                 tar -xzf "$DOWNLOADED_FILE" -C /tmp
                 EXTRACTED_DIR="/tmp/litellm_proxy_extras-$LAST_VERSION"
             fi
-            
+
             echo "Contents of extracted package:"
             ls -R "$EXTRACTED_DIR"
-            
+
             # Compare contents
             if ! diff -r "$EXTRACTED_DIR/litellm_proxy_extras" ./litellm_proxy_extras; then
               if [ "$CURRENT_VERSION" = "$LAST_VERSION" ]; then
@@ -2513,16 +2515,16 @@ jobs:
             export NVM_DIR="/opt/circleci/.nvm"
             source "$NVM_DIR/nvm.sh"
             source "$NVM_DIR/bash_completion"
-            
+
             # Install and use Node version
             nvm install v18.17.0
             nvm use v18.17.0
-            
+
             cd ui/litellm-dashboard
-            
+
             # Install dependencies first
             npm install
-            
+
             # Now source the build script
             source ./build_ui.sh
       - run:
@@ -2569,7 +2571,7 @@ jobs:
           name: Install Playwright Browsers
           command: |
             npx playwright install
-      
+
       - run:
           name: Build Docker image
           command: docker build -t my-app:latest -f ./docker/Dockerfile.database .
@@ -2933,4 +2935,4 @@ workflows:
             - proxy_pass_through_endpoint_tests
             - check_code_and_doc_quality
             - publish_proxy_extras
-      
+

README.md

@@ -44,7 +44,7 @@ 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">
@@ -129,7 +129,7 @@ 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
@@ -227,7 +227,7 @@ $ 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+
@@ -259,7 +259,7 @@ 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
 
@@ -332,6 +332,7 @@ 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)                              | ✅                                                       | ✅                                                                               | ✅                                                                                   | ✅                                                                                 |                                                                               |                                                                         |
+| [DigitalOcean](https://docs.litellm.ai/docs/providers/digitalocean)                              | ✅                                                       | ✅                                                                               |                                                                                   |                                                                                  |                                                                               |                                                                         |
 
 [**Read the Docs**](https://docs.litellm.ai/docs/)
 
@@ -344,7 +345,7 @@ 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**
@@ -356,7 +357,7 @@ This covers:
 
 LiteLLM follows the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html).
 
-We run: 
+We run:
 - Ruff for [formatting and linting checks](https://github.com/BerriAI/litellm/blob/e19bb55e3b4c6a858b6e364302ebbf6633a51de5/.circleci/config.yml#L320)
 - Mypy + Pyright for typing [1](https://github.com/BerriAI/litellm/blob/e19bb55e3b4c6a858b6e364302ebbf6633a51de5/.circleci/config.yml#L90), [2](https://github.com/BerriAI/litellm/blob/e19bb55e3b4c6a858b6e364302ebbf6633a51de5/.pre-commit-config.yaml#L4)
 - Black for [formatting](https://github.com/BerriAI/litellm/blob/e19bb55e3b4c6a858b6e364302ebbf6633a51de5/.circleci/config.yml#L79)

docs/my-website/Dockerfile

@@ -4,6 +4,6 @@ COPY . /app
 WORKDIR /app
 RUN pip install -r requirements.txt
 
-EXPOSE $PORT 
+EXPOSE 3000
 
-CMD litellm --host 0.0.0.0 --port $PORT --workers 10 --config config.yaml
+CMD litellm --host 0.0.0.0 --port 3000 --workers 10 --config config.yaml

docs/my-website/sidebars.js

@@ -245,7 +245,8 @@ const sidebars = {
         "providers/sambanova",
         "providers/custom_llm_server",
         "providers/petals",
-        "providers/snowflake"
+        "providers/snowflake",
+        "providers/digitalocean",
       ],
     },
     {

litellm/__init__.py

@@ -193,6 +193,7 @@ baseten_key: Optional[str] = None
 aleph_alpha_key: Optional[str] = None
 nlp_cloud_key: Optional[str] = None
 snowflake_key: Optional[str] = None
+digitalocean_api_key: Optional[str] = None
 common_cloud_provider_auth_params: dict = {
     "params": ["project", "region_name", "token"],
     "providers": ["vertex_ai", "bedrock", "watsonx", "azure", "vertex_ai_beta"],
@@ -431,6 +432,7 @@ galadriel_models: List = []
 sambanova_models: List = []
 assemblyai_models: List = []
 snowflake_models: List = []
+digitalocean_models: List = []
 
 
 def is_bedrock_pricing_only_model(key: str) -> bool:
@@ -588,6 +590,8 @@ def add_known_models():
             jina_ai_models.append(key)
         elif value.get("litellm_provider") == "snowflake":
             snowflake_models.append(key)
+        elif value.get("litellm_provider") == "digitalocean":
+            digitalocean_models.append(key)
 
 
 add_known_models()
@@ -664,6 +668,7 @@ model_list = (
     + assemblyai_models
     + jina_ai_models
     + snowflake_models
+    + digitalocean_models
 )
 
 model_list_set = set(model_list)
@@ -721,6 +726,7 @@ models_by_provider: dict = {
     "assemblyai": assemblyai_models,
     "jina_ai": jina_ai_models,
     "snowflake": snowflake_models,
+    "digitalocean": digitalocean_models,
 }
 
 # mapping for those models which have larger equivalents
@@ -963,7 +969,7 @@ from .llms.openai.chat.o_series_transformation import (
 )
 
 from .llms.snowflake.chat.transformation import SnowflakeConfig
-
+from .llms.digitalocean.chat.transformation import DigitalOceanConfig
 openaiOSeriesConfig = OpenAIOSeriesConfig()
 from .llms.openai.chat.gpt_transformation import (
     OpenAIGPTConfig,

litellm/constants.py

@@ -157,6 +157,7 @@ LITELLM_CHAT_PROVIDERS = [
     "hosted_vllm",
     "lm_studio",
     "galadriel",
+    "digitalocean"
 ]
 
 

litellm/litellm_core_utils/get_llm_provider_logic.py

@@ -321,6 +321,8 @@ def get_llm_provider(  # noqa: PLR0915
             custom_llm_provider = "openai"
         elif model in litellm.empower_models:
             custom_llm_provider = "empower"
+        elif model in litellm.digitalocean_models:
+            custom_llm_provider = "digitalocean"
         elif model == "*":
             custom_llm_provider = "openai"
         if not custom_llm_provider:
@@ -580,6 +582,13 @@ 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 == "digitalocean":
+        (
+            api_base,
+            dynamic_api_key,
+        ) = litellm.DigitalOceanConfig()._get_openai_compatible_provider_info(
+            api_base, api_key
+        )
 
     if api_base is not None and not isinstance(api_base, str):
         raise Exception("api base needs to be a string. api_base={}".format(api_base))

litellm/llms/digitalocean/chat/transformation.py

@@ -0,0 +1,191 @@
+"""
+Translate from OpenAI's `/v1/chat/completions` to DigitalOcean AI Agent's `/v1/chat/completions`
+"""
+
+from typing import List, Optional, Tuple, Union, Dict
+
+from pydantic import BaseModel
+
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import (
+    AllMessageValues,
+    ChatCompletionAssistantMessage,
+    ChatCompletionToolParam,
+    ChatCompletionToolParamFunctionChunk,
+)
+
+from ...openai_like.chat.transformation import OpenAILikeChatConfig
+
+
+class DigitalOceanConfig(OpenAILikeChatConfig):
+
+    # DigitalOcean-specific parameters:
+    stream_options: Optional[Dict] = 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
+
+    def __init__(
+        self,
+        frequency_penalty: Optional[float] = None,
+        function_call: Optional[Union[str, Dict]] = None,
+        functions: Optional[List] = None,
+        logit_bias: Optional[Dict] = None,
+        max_tokens: Optional[int] = None,
+        max_completion_tokens: Optional[int] = None,  # Additional field; interchangeable with max_tokens per spec
+        n: Optional[int] = None,
+        presence_penalty: Optional[float] = None,
+        retrieval_method: Optional[str] = None,  # expected values: "rewrite", "step_back", "sub_queries", "none"
+        stop: Optional[Union[str, List[str]]] = None,
+        stream: Optional[bool] = None,
+        temperature: Optional[float] = None,
+        top_p: Optional[float] = None,
+        response_format: Optional[Dict] = None,
+        tools: Optional[List] = None,
+        tool_choice: Optional[Union[str, Dict]] = 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:
+        base_params = super().get_supported_openai_params(model)
+        try:
+            base_params.remove("max_retries")
+        except ValueError:
+            pass
+        return base_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("DIGITALOCEAN_API_KEY")
+        if api_key is None:
+            raise ValueError("DigitalOcean 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:
+
+        complete_url = f"{api_base}/api/v1/chat/completions"
+        return complete_url
+
+    def _transform_messages(self, messages: List[AllMessageValues], model: str) -> List:
+        for idx, message in enumerate(messages):
+            """
+            1. Don't pass 'null' function_call assistant message to groq - https://github.com/BerriAI/litellm/issues/5839
+            """
+            if isinstance(message, BaseModel):
+                _message = message.model_dump()
+            else:
+                _message = message
+            assistant_message = _message.get("role") == "assistant"
+            if assistant_message:
+                new_message = ChatCompletionAssistantMessage(role="assistant")
+                for k, v in _message.items():
+                    if v is not None:
+                        new_message[k] = v  # type: ignore
+                messages[idx] = new_message
+
+        return messages
+
+    def _get_openai_compatible_provider_info(
+        self, api_base: Optional[str], api_key: Optional[str]
+    ) -> Tuple[Optional[str], Optional[str]]:
+        api_base = (
+            api_base
+            or get_secret_str("DIGITALOCEAN_AGENT_ENDPOINT")
+            or get_secret_str("DO_AGENT_ENDPOINT")
+        )  # type: ignore
+        dynamic_api_key = api_key or get_secret_str("DO_API_KEY") or get_secret_str("DIGITALOCEAN_API_KEY")
+        return api_base, dynamic_api_key
+
+
+
+    def _create_json_tool_call_for_response_format(
+        self,
+        json_schema: dict,
+    ):
+        """
+        Handles creating a tool call for getting responses in JSON format.
+
+        Args:
+            json_schema (Optional[dict]): The JSON schema the response should be in
+
+        Returns:
+            AnthropicMessagesTool: The tool call to send to Anthropic API to get responses in JSON format
+        """
+        return ChatCompletionToolParam(
+            type="function",
+            function=ChatCompletionToolParamFunctionChunk(
+                name="json_tool_call",
+                parameters=json_schema,
+            ),
+        )
+
+    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,  # groq supports max_completion_tokens
+    ) -> dict:
+        _response_format = non_default_params.get("response_format")
+        if _response_format is not None and isinstance(_response_format, dict):
+            json_schema: Optional[dict] = None
+            if "response_schema" in _response_format:
+                json_schema = _response_format["response_schema"]
+            elif "json_schema" in _response_format:
+                json_schema = _response_format["json_schema"]["schema"]
+            """
+            When using tools in this way: - https://docs.anthropic.com/en/docs/build-with-claude/tool-use#json-mode
+            - You usually want to provide a single tool
+            - You should set tool_choice (see Forcing tool use) to instruct the model to explicitly use that tool
+            - Remember that the model will pass the input to the tool, so the name of the tool and description should be from the model’s perspective.
+            """
+            if json_schema is not None:
+                _tool_choice = {
+                    "type": "function",
+                    "function": {"name": "json_tool_call"},
+                }
+                _tool = self._create_json_tool_call_for_response_format(
+                    json_schema=json_schema,
+                )
+                optional_params["tools"] = [_tool]
+                optional_params["tool_choice"] = _tool_choice
+                optional_params["json_mode"] = True
+                non_default_params.pop(
+                    "response_format", None
+                )  # only remove if it's a json_schema - handled via using groq's tool calling params.
+        optional_params = super().map_openai_params(
+            non_default_params, optional_params, model, drop_params
+        )
+
+        return optional_params

litellm/main.py

@@ -3065,6 +3065,26 @@ def completion(  # type: ignore # noqa: PLR0915
                     additional_args={"headers": headers},
                 )
                 raise e
+        elif custom_llm_provider == "digitalocean":
+
+            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="digitalocean",
+                timeout=timeout,
+                headers=headers,
+                encoding=encoding,
+                api_key=api_key,
+                logging_obj=logging,  # model call logging done inside the class as we make need to modify I/O to fit aleph alpha's requirements
+                client=client,
+            )
 
         elif custom_llm_provider == "custom":
             url = litellm.api_base or api_base or ""

litellm/types/utils.py

@@ -2102,6 +2102,7 @@ class LlmProviders(str, Enum):
     TOPAZ = "topaz"
     ASSEMBLYAI = "assemblyai"
     SNOWFLAKE = "snowflake"
+    DIGITALOCEAN = "digitalocean"
 
 
 # Create a set of all provider values for quick lookup

litellm/utils.py

@@ -3705,6 +3705,17 @@ def get_optional_params(  # noqa: PLR0915
                 else False
             ),
         )
+    elif custom_llm_provider == "digitalocean":
+        optional_params = litellm.DigitalOceanConfig().map_openai_params(
+            non_default_params=non_default_params,
+            optional_params=optional_params,
+            model=model,
+            drop_params=(
+                drop_params
+                if drop_params is not None and isinstance(drop_params, bool)
+                else False
+            ),
+        )
     elif custom_llm_provider == "openai":
         optional_params = litellm.OpenAIConfig().map_openai_params(
             non_default_params=non_default_params,
@@ -6569,6 +6580,8 @@ class ProviderConfigManager:
             return litellm.LiteLLMProxyChatConfig()
         elif litellm.LlmProviders.OPENAI == provider:
             return litellm.OpenAIGPTConfig()
+        elif litellm.LlmProviders.DIGITALOCEAN == provider:
+            return litellm.DigitalOceanConfig()
         return None
 
     @staticmethod

proxy_server_config.yaml

@@ -18,7 +18,7 @@ model_list:
       api_version: "2023-05-15"
       api_key: os.environ/AZURE_API_KEY # The `os.environ/` prefix tells litellm to read this from the env. See https://docs.litellm.ai/docs/simple_proxy#load-api-keys-from-vault
   - model_name: gpt-3.5-turbo-large
-    litellm_params: 
+    litellm_params:
       model: "gpt-3.5-turbo-1106"
       api_key: os.environ/OPENAI_API_KEY
       rpm: 480
@@ -36,9 +36,9 @@ model_list:
   - model_name: sagemaker-completion-model
     litellm_params:
       model: sagemaker/berri-benchmarking-Llama-2-70b-chat-hf-4
-      input_cost_per_second: 0.000420  
+      input_cost_per_second: 0.000420
   - model_name: text-embedding-ada-002
-    litellm_params: 
+    litellm_params:
       model: azure/azure-embedding-model
       api_key: os.environ/AZURE_API_KEY
       api_base: https://openai-gpt-4-test-v-1.openai.azure.com/
@@ -106,7 +106,7 @@ model_list:
     litellm_params:
       model: openai/*
       api_key: os.environ/OPENAI_API_KEY
-  
+
 
   # provider specific wildcard routing
   - model_name: "anthropic/*"
@@ -137,18 +137,23 @@ model_list:
       model: openai/my-fake-model
       api_key: my-fake-key
       api_base: https://exampleopenaiendpoint-production.up.railway.appxxxx/
+  - model_name: "digitalocean/*"
+    litellm_params:
+      model: "digitalocean/*"
+      api_key: os.environ/DIGITALOCEAN_API_KEY
+      api_base: os.environ/DIGITALOCEAN_AGENT_ENDPOINT
 
 
 litellm_settings:
   # set_verbose: True  # Uncomment this if you want to see verbose logs; not recommended in production
   drop_params: True
-  # max_budget: 100 
+  # max_budget: 100
   # budget_duration: 30d
   num_retries: 5
   request_timeout: 600
   telemetry: False
   context_window_fallbacks: [{"gpt-3.5-turbo": ["gpt-3.5-turbo-large"]}]
-  default_team_settings: 
+  default_team_settings:
     - team_id: team-1
       success_callback: ["langfuse"]
       failure_callback: ["langfuse"]
@@ -180,14 +185,14 @@ files_settings:
     api_key: os.environ/OPENAI_API_KEY
 
 router_settings:
-  routing_strategy: usage-based-routing-v2 
+  routing_strategy: usage-based-routing-v2
   redis_host: os.environ/REDIS_HOST
   redis_password: os.environ/REDIS_PASSWORD
   redis_port: os.environ/REDIS_PORT
   enable_pre_call_checks: true
-  model_group_alias: {"my-special-fake-model-alias-name": "fake-openai-endpoint-3"} 
+  model_group_alias: {"my-special-fake-model-alias-name": "fake-openai-endpoint-3"}
 
-general_settings: 
+general_settings:
   master_key: sk-1234 # [OPTIONAL] Use to enforce auth on proxy. See - https://docs.litellm.ai/docs/proxy/virtual_keys
   store_model_in_db: True
   proxy_budget_rescheduler_min_time: 60
@@ -200,7 +205,7 @@ general_settings:
     - path: "/v1/rerank"                                  # route you want to add to LiteLLM Proxy Server
       target: "https://api.cohere.com/v1/rerank"          # URL this route should forward requests to
       headers:                                            # headers to forward to this URL
-        content-type: application/json                    # (Optional) Extra Headers to pass to this endpoint 
+        content-type: application/json                    # (Optional) Extra Headers to pass to this endpoint
         accept: application/json
       forward_headers: True
 
@@ -208,4 +213,4 @@ general_settings:
   # settings for using redis caching
   # REDIS_HOST: redis-16337.c322.us-east-1-2.ec2.cloud.redislabs.com
   # REDIS_PORT: "16337"
-  # REDIS_PASSWORD: 
+  # REDIS_PASSWORD:

tests/litellm/llms/digitalocean/chat/test_digitalocean_chat_transformation.py

@@ -0,0 +1,60 @@
+import os
+import sys
+import pytest
+
+sys.path.insert(
+    0, os.path.abspath("../../../../..")
+)  # Adds the parent directory to the system path
+
+from litellm.llms.digitalocean.chat.transformation import DigitalOceanConfig
+
+DO_ENDPOINT_PATH = "/api/v1/chat/completions"
+DO_BASE_URL = "https://api.digitalocean.com"
+
+@pytest.fixture
+def config():
+    return DigitalOceanConfig()
+
+def test_validate_environment_sets_headers(monkeypatch, config):
+    monkeypatch.setenv("DIGITALOCEAN_API_KEY", "test-key")
+    headers = {}
+    result = config.validate_environment(
+        headers=headers,
+        model="digitalocean/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(config):
+    url = config.get_complete_url(
+        api_base=DO_BASE_URL,
+        api_key="test-key",
+        model="digitalocean/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="digitalocean/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("DIGITALOCEAN_AGENT_ENDPOINT", DO_BASE_URL)
+    monkeypatch.setenv("DIGITALOCEAN_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"

ui/litellm-dashboard/out/assets/logos/digitalocean.svg

@@ -0,0 +1,229 @@
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+<!-- Created with Inkscape (http://www.inkscape.org/) -->
+
+<svg
+   width="68.544662mm"
+   height="68.542419mm"
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+   version="1.1"
+   id="svg5"
+   inkscape:version="1.1.2 (b8e25be833, 2022-02-05)"
+   sodipodi:docname="DigitalOcean 2016 Icon.svg"
+   xmlns:inkscape="http://www.inkscape.org/namespaces/inkscape"
+   xmlns:sodipodi="http://sodipodi.sourceforge.net/DTD/sodipodi-0.dtd"
+   xmlns="http://www.w3.org/2000/svg"
+   xmlns:svg="http://www.w3.org/2000/svg">
+  <sodipodi:namedview
+     id="namedview7"
+     pagecolor="#ffffff"
+     bordercolor="#666666"
+     borderopacity="1.0"
+     inkscape:pageshadow="2"
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ui/litellm-dashboard/src/components/add_model/provider_specific_fields.tsx

@@ -327,7 +327,27 @@ const PROVIDER_CREDENTIAL_FIELDS: Record<Providers, ProviderCredentialField[]> =
     label: "API Key",
     type: "password",
     required: true
-  }]
+  }],
+  [Providers.DigitalOcean]: [
+    {
+      key: "endpoint",
+      label: "DigitalOcean Endpoint",
+      placeholder: "https://...",
+      required: true
+    },
+
+    {
+      key: "base_model",
+      label: "Base Model",
+      placeholder: "digitalocean/mistral-nemo"
+    },
+    {
+      key: "api_key",
+      label: "DigitalOcean API Key",
+      type: "password",
+      required: true
+    }
+  ]
 };
 
 const ProviderSpecificFields: React.FC<ProviderSpecificFieldsProps> = ({
@@ -335,7 +355,7 @@ const ProviderSpecificFields: React.FC<ProviderSpecificFieldsProps> = ({
   uploadProps
 }) => {
   const selectedProviderEnum = Providers[selectedProvider as keyof typeof Providers] as Providers;
-  
+
   // Simply use the fields as defined in PROVIDER_CREDENTIAL_FIELDS
   const allFields = React.useMemo(() => {
     return PROVIDER_CREDENTIAL_FIELDS[selectedProviderEnum] || [];
@@ -353,7 +373,7 @@ const ProviderSpecificFields: React.FC<ProviderSpecificFieldsProps> = ({
             className={field.key === "vertex_credentials" ? "mb-0" : undefined}
           >
             {field.type === "select" ? (
-              <Select 
+              <Select
                 placeholder={field.placeholder}
                 defaultValue={field.defaultValue}
               >
@@ -368,9 +388,9 @@ 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>

ui/litellm-dashboard/src/components/provider_info_helpers.tsx

@@ -25,10 +25,9 @@ export enum Providers {
     Perplexity = "Perplexity",
     TogetherAI = "TogetherAI",
     Openrouter = "Openrouter",
-    FireworksAI = "Fireworks AI"
-
+    FireworksAI = "Fireworks AI",
+    DigitalOcean = "DigitalOcean"
   }
-  
 export const provider_map: Record<string, string> = {
     OpenAI: "openai",
     OpenAI_Text: "text-completion-openai",
@@ -53,7 +52,8 @@ export const provider_map: Record<string, string> = {
     Perplexity: "perplexity",
     TogetherAI: "togetherai",
     Openrouter: "openrouter",
-    FireworksAI: "fireworks_ai"
+    FireworksAI: "fireworks_ai",
+    DigitalOcean: "digitalocean"
 };
 
 const asset_logos_folder = '/ui/assets/logos/';
@@ -82,7 +82,8 @@ export const providerLogoMap: Record<string, string> = {
     [Providers.Sambanova]: `${asset_logos_folder}sambanova.svg`,
     [Providers.TogetherAI]: `${asset_logos_folder}togetherai.svg`,
     [Providers.Vertex_AI]: `${asset_logos_folder}google.svg`,
-    [Providers.xAI]: `${asset_logos_folder}xai.svg`
+    [Providers.xAI]: `${asset_logos_folder}xai.svg`,
+    [Providers.DigitalOcean]: `${asset_logos_folder}digitalocean.svg`
 };
 
 export const getProviderLogoAndName = (providerValue: string): { logo: string, displayName: string } => {
@@ -136,9 +137,9 @@ 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 (
@@ -151,7 +152,7 @@ export const getPlaceholder = (selectedProvider: string): string => {
           providerModels.push(key);
         }
       });
-  
+
       // Special case for cohere_chat
       // we need both cohere_chat and cohere models to show on dropdown
       if (providerKey == Providers.Cohere) {
@@ -168,6 +169,6 @@ export const getPlaceholder = (selectedProvider: string): string => {
         });
       }
     }
-  
+
     return providerModels;
   };