Merge branch 'main' into akshoop/fastuuid-dep-make-optional

Author: akshoop

.github/workflows/test-mcp.yml

@@ -0,0 +1,48 @@
+name: LiteLLM MCP Tests (folder - tests/mcp_tests)
+
+on:
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    timeout-minutes: 25
+
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Thank You Message
+      run: |
+        echo "### 🙏 Thank you for contributing to LiteLLM!" >> $GITHUB_STEP_SUMMARY
+        echo "Your PR is being tested now. We appreciate your help in making LiteLLM better!" >> $GITHUB_STEP_SUMMARY
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.12'
+
+    - name: Install Poetry
+      uses: snok/install-poetry@v1
+
+    - name: Install dependencies
+      run: |
+        poetry install --with dev,proxy-dev --extras "proxy semantic-router"
+        poetry run pip install "pytest==7.3.1"
+        poetry run pip install "pytest-retry==1.6.3"
+        poetry run pip install "pytest-cov==5.0.0"
+        poetry run pip install "pytest-asyncio==0.21.1"
+        poetry run pip install "respx==0.22.0"
+        poetry run pip install "pydantic==2.10.2"
+        poetry run pip install "mcp==1.10.1"
+        poetry run pip install pytest-xdist
+
+    - name: Setup litellm-enterprise as local package
+      run: |
+        cd enterprise
+        python -m pip install -e .
+        cd ..
+
+    - name: Run MCP tests
+      run: |
+        poetry run pytest tests/mcp_tests -x -vv -n 4 --cov=litellm --cov-report=xml --durations=5

cookbook/litellm_proxy_server/cli_token_usage.py

@@ -0,0 +1,62 @@
+#!/usr/bin/env python3
+"""
+Example: Using CLI token with LiteLLM SDK
+
+This example shows how to use the CLI authentication token
+in your Python scripts after running `litellm-proxy login`.
+"""
+
+from textwrap import indent
+import litellm
+LITELLM_BASE_URL = "http://localhost:4000/"
+
+
+def main():
+    """Using CLI token with LiteLLM SDK"""
+    print("🚀 Using CLI Token with LiteLLM SDK")
+    print("=" * 40)
+    #litellm._turn_on_debug()
+    
+    # Get the CLI token
+    api_key = litellm.get_litellm_gateway_api_key()
+    
+    if not api_key:
+        print("❌ No CLI token found. Please run 'litellm-proxy login' first.")
+        return
+    
+    print("✅ Found CLI token.")
+
+    available_models = litellm.get_valid_models(
+        check_provider_endpoint=True,
+        custom_llm_provider="litellm_proxy",
+        api_key=api_key,
+        api_base=LITELLM_BASE_URL
+    )
+    
+    print("✅ Available models:")
+    if available_models:
+        for i, model in enumerate(available_models, 1):
+            print(f"   {i:2d}. {model}")
+    else:
+        print("   No models available")
+    
+    # Use with LiteLLM
+    try:
+        response = litellm.completion(
+            model="litellm_proxy/gemini/gemini-2.5-flash",
+            messages=[{"role": "user", "content": "Hello from CLI token!"}],
+            api_key=api_key,
+            base_url=LITELLM_BASE_URL
+        )
+        print(f"✅ LLM Response: {response.model_dump_json(indent=4)}")
+    except Exception as e:
+        print(f"❌ Error: {e}")
+
+
+if __name__ == "__main__":
+    main()
+    
+    print("\n💡 Tips:")
+    print("1. Run 'litellm-proxy login' to authenticate first")
+    print("2. Replace 'https://your-proxy.com' with your actual proxy URL")
+    print("3. The token is stored locally at ~/.litellm/token.json")

docs/my-website/docs/completion/provider_specific_params.md

@@ -423,16 +423,17 @@ model_list:
 curl -X POST 'http://0.0.0.0:4000/chat/completions' \
 -H 'Content-Type: application/json' \
 -H 'Authorization: Bearer sk-1234' \
--D '{
+-d '{
   "model": "llama-3-8b-instruct",
   "messages": [
     {
       "role": "user",
       "content": "What'\''s the weather like in Boston today?"
     }
   ],
-  "adapater_id": "my-special-adapter-id" # 👈 PROVIDER-SPECIFIC PARAM
-  }'
+  "adapater_id": "my-special-adapter-id"
+}'
+```
 
 ## Provider-Specific Metadata Parameters
 
@@ -482,5 +483,4 @@ response = litellm.completion(
 ```
 
 </TabItem>
-</Tabs>
-```
+</Tabs>

docs/my-website/docs/completion/usage.md

@@ -26,6 +26,7 @@ response = completion(
 
 print(response.usage)
 ```
+> **Note:** LiteLLM supports endpoint bridging—if a model does not natively support a requested endpoint, LiteLLM will automatically route the call to the correct supported endpoint (such as bridging `/chat/completions` to `/responses` or vice versa) based on the model's `mode`set in `model_prices_and_context_window`.
 
 ## Streaming Usage
 

docs/my-website/docs/enterprise.md

@@ -1,6 +1,11 @@
 import Image from '@theme/IdealImage';
 
 # Enterprise
+
+:::info
+✨ SSO is free for up to 5 users. After that, an enterprise license is required. [Get Started with Enterprise here](https://www.litellm.ai/enterprise)
+:::
+
 For companies that need SSO, user management and professional support for LiteLLM Proxy
 
 :::info

docs/my-website/docs/fine_tuning.md

@@ -13,6 +13,8 @@ This is an Enterprise only endpoint [Get Started with Enterprise here](https://c
 | Feature | Supported | Notes | 
 |-------|-------|-------|
 | Supported Providers | OpenAI, Azure OpenAI, Vertex AI | - |
+
+#### ⚡️See an exhaustive list of supported models and providers at [models.litellm.ai](https://models.litellm.ai/)
 | Cost Tracking | 🟡 | [Let us know if you need this](https://github.com/BerriAI/litellm/issues) |
 | Logging | ✅ | Works across all logging integrations |
 

docs/my-website/docs/getting_started.md

@@ -32,7 +32,8 @@ Next Steps 👉 [Call all supported models - e.g. Claude-2, Llama2-70b, etc.](./
 More details 👉
 
 - [Completion() function details](./completion/)
-- [All supported models / providers on LiteLLM](./providers/)
+- [Overview of supported models / providers on LiteLLM](./providers/)
+- [Search all models / providers](https://models.litellm.ai/)
 - [Build your own OpenAI proxy](https://github.com/BerriAI/liteLLM-proxy/tree/main)
 
 ## streaming

docs/my-website/docs/image_edits.md

@@ -18,6 +18,9 @@ LiteLLM provides image editing functionality that maps to OpenAI's `/images/edit
 | Supported LiteLLM Proxy Versions | 1.71.1+ | |
 | Supported LLM providers | **OpenAI** | Currently only `openai` is supported |
 
+ #### ⚡️See all supported models and providers at [models.litellm.ai](https://models.litellm.ai/)
+
+
 ## Usage
 
 ### LiteLLM Python SDK

docs/my-website/docs/image_generation.md

@@ -279,6 +279,8 @@ print(f"response: {response}")
 
 ## Supported Providers
 
+#### ⚡️See all supported models and providers at [models.litellm.ai](https://models.litellm.ai/)
+
 | Provider | Documentation Link |
 |----------|-------------------|
 | OpenAI | [OpenAI Image Generation →](./providers/openai) |

docs/my-website/docs/index.md

@@ -524,6 +524,15 @@ try:
 except OpenAIError as e:
     print(e)
 ```
+### See How LiteLLM Transforms Your Requests
+
+Want to understand how LiteLLM parses and normalizes your LLM API requests? Use the `/utils/transform_request` endpoint to see exactly how your request is transformed internally.
+
+You can try it out now directly on our Demo App!
+Go to the [LiteLLM API docs for transform_request](https://litellm-api.up.railway.app/#/llm%20utils/transform_request_utils_transform_request_post)
+
+LiteLLM will show you the normalized, provider-agnostic version of your request. This is useful for debugging, learning, and understanding how LiteLLM handles different providers and options.
+
 
 ### Logging Observability - Log LLM Input/Output ([Docs](https://docs.litellm.ai/docs/observability/callbacks))
 LiteLLM exposes pre defined callbacks to send data to Lunary, MLflow, Langfuse, Helicone, Promptlayer, Traceloop, Slack