add new litellm params for client_id, tenant_id etc

docs/my-website/docs/providers/azure.md

@@ -1,3 +1,8 @@
+
+import Image from '@theme/IdealImage';
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
 # Azure OpenAI
 ## API Keys, Params
 api_key, api_base, api_version etc can be passed directly to `litellm.completion` - see here or set as `litellm.api_key` params see here
@@ -12,7 +17,7 @@ os.environ["AZURE_AD_TOKEN"] = ""
 os.environ["AZURE_API_TYPE"] = ""
 ```
 
-## Usage
+## **Usage - LiteLLM Python SDK**
 <a target="_blank" href="https://colab.research.google.com/github/BerriAI/litellm/blob/main/cookbook/LiteLLM_Azure_OpenAI.ipynb">
   <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
 </a>
@@ -64,6 +69,126 @@ response = litellm.completion(
 )
 ```
 
+
+## **Usage - LiteLLM Proxy Server**
+
+Here's how to call Azure OpenAI models with the LiteLLM Proxy Server
+
+### 1. Save key in your environment
+
+```bash
+export AZURE_API_KEY=""
+```
+
+### 2. Start the proxy 
+
+<Tabs>
+<TabItem value="config" label="config.yaml">
+
+```yaml
+model_list:
+  - model_name: gpt-3.5-turbo
+    litellm_params:
+      model: azure/chatgpt-v-2
+      api_base: https://openai-gpt-4-test-v-1.openai.azure.com/
+      api_version: "2023-05-15"
+      api_key: os.environ/AZURE_API_KEY # The `os.environ/` prefix tells litellm to read this from the env.
+```
+</TabItem>
+<TabItem value="config-*" label="config.yaml - use tenant_id, client_id, client_secret">
+
+This uses the `ClientSecretCredential` 
+
+```yaml
+model_list:
+  - model_name: gpt-3.5-turbo
+    litellm_params:
+      model: azure/chatgpt-v-2
+      api_base: https://openai-gpt-4-test-v-1.openai.azure.com/
+      api_version: "2023-05-15"
+      tenant_id: os.environ/AZURE_TENANT_ID
+      client_id: os.environ/AZURE_CLIENT_ID
+      client_secret: os.environ/AZURE_CLIENT_SECRET
+```
+</TabItem>
+
+</Tabs>
+
+### 3. Test it
+
+
+<Tabs>
+<TabItem value="Curl" label="Curl Request">
+
+```shell
+curl --location 'http://0.0.0.0:4000/chat/completions' \
+--header 'Content-Type: application/json' \
+--data ' {
+      "model": "gpt-3.5-turbo",
+      "messages": [
+        {
+          "role": "user",
+          "content": "what llm are you"
+        }
+      ]
+    }
+'
+```
+</TabItem>
+<TabItem value="openai" label="OpenAI v1.0.0+">
+
+```python
+import openai
+client = openai.OpenAI(
+    api_key="anything",
+    base_url="http://0.0.0.0:4000"
+)
+
+response = client.chat.completions.create(model="gpt-3.5-turbo", messages = [
+    {
+        "role": "user",
+        "content": "this is a test request, write a short poem"
+    }
+])
+
+print(response)
+
+```
+</TabItem>
+<TabItem value="langchain" label="Langchain">
+
+```python
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    HumanMessagePromptTemplate,
+    SystemMessagePromptTemplate,
+)
+from langchain.schema import HumanMessage, SystemMessage
+
+chat = ChatOpenAI(
+    openai_api_base="http://0.0.0.0:4000", # set openai_api_base to the LiteLLM Proxy
+    model = "gpt-3.5-turbo",
+    temperature=0.1
+)
+
+messages = [
+    SystemMessage(
+        content="You are a helpful assistant that im using to make a test request to."
+    ),
+    HumanMessage(
+        content="test from litellm. tell me why it's amazing in 1 sentence"
+    ),
+]
+response = chat(messages)
+
+print(response)
+```
+</TabItem>
+</Tabs>
+
+
+
 ## Azure OpenAI Chat Completion Models
 
 :::tip

litellm/main.py

@@ -3231,6 +3231,9 @@ def embedding(
         "cooldown_time",
         "tags",
         "azure_ad_token_provider",
+        "tenant_id",
+        "client_id",
+        "client_secret",
     ]
     default_params = openai_params + litellm_params
     non_default_params = {

litellm/proxy/proxy_config.yaml

@@ -4,8 +4,9 @@ model_list:
       model: azure/chatgpt-v-2
       api_base: https://openai-gpt-4-test-v-1.openai.azure.com/
       api_version: "2023-05-15"
-      azure_ad_token_provider: True
-
+      tenant_id: os.environ/AZURE_TENANT_ID
+      client_id: os.environ/AZURE_CLIENT_ID
+      client_secret: os.environ/AZURE_CLIENT_SECRET
 
 guardrails:
   - guardrail_name: "lakera-pre-guard"

litellm/router_utils/client_initalization_utils.py

@@ -173,10 +173,13 @@ def set_client(litellm_router_instance: LitellmRouter, model: dict):
             organization = litellm.get_secret(organization_env_name)
             litellm_params["organization"] = organization
 
-        azure_ad_token_provider = litellm_params.get("azure_ad_token_provider", None)
-        if azure_ad_token_provider is not None:
+        if litellm_params.get("tenant_id"):
             verbose_router_logger.debug("Using Azure AD Token Provider for Azure Auth")
-            azure_ad_token_provider = get_azure_ad_token_from_entrata_id()
+            azure_ad_token_provider = get_azure_ad_token_from_entrata_id(
+                tenant_id=litellm_params.get("tenant_id"),
+                client_id=litellm_params.get("client_id"),
+                client_secret=litellm_params.get("client_secret"),
+            )
 
         if custom_llm_provider == "azure" or custom_llm_provider == "azure_text":
             if api_base is None or not isinstance(api_base, str):
@@ -507,13 +510,37 @@ def set_client(litellm_router_instance: LitellmRouter, model: dict):
                 )  # cache for 1 hr
 
 
-def get_azure_ad_token_from_entrata_id() -> Callable[[], str]:
-    from azure.identity import DefaultAzureCredential, get_bearer_token_provider
+def get_azure_ad_token_from_entrata_id(
+    tenant_id: str, client_id: str, client_secret: str
+) -> Callable[[], str]:
+    from azure.identity import (
+        ClientSecretCredential,
+        DefaultAzureCredential,
+        get_bearer_token_provider,
+    )
 
     verbose_router_logger.debug("Getting Azure AD Token from Entrata ID")
 
+    if tenant_id.startswith("os.environ/"):
+        tenant_id = litellm.get_secret(tenant_id)
+
+    if client_id.startswith("os.environ/"):
+        client_id = litellm.get_secret(client_id)
+
+    if client_secret.startswith("os.environ/"):
+        client_secret = litellm.get_secret(client_secret)
+    verbose_router_logger.debug(
+        "tenant_id %s, client_id %s, client_secret %s",
+        tenant_id,
+        client_id,
+        client_secret,
+    )
+    credential = ClientSecretCredential(tenant_id, client_id, client_secret)
+
+    verbose_router_logger.debug("credential %s", credential)
+
     token_provider = get_bearer_token_provider(
-        DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+        credential, "https://cognitiveservices.azure.com/.default"
     )
 
     verbose_router_logger.debug("token_provider %s", token_provider)

litellm/types/utils.py

@@ -1117,6 +1117,9 @@ all_litellm_params = [
     "cache_key",
     "max_retries",
     "azure_ad_token_provider",
+    "tenant_id",
+    "client_id",
+    "client_secret",
 ]