docs(gemini.md): add gemini thinking to docs

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

@@ -39,14 +39,164 @@ response = completion(
 - temperature
 - top_p
 - max_tokens
+- max_completion_tokens
 - stream
 - tools
 - tool_choice
+- functions
 - response_format
 - n
 - stop
+- logprobs
+- frequency_penalty
+- modalities
+- reasoning_content
+
+**Anthropic Params**
+- thinking (used to set max budget tokens across anthropic/gemini models)
+
+[**See Updated List**](https://github.com/BerriAI/litellm/blob/main/litellm/llms/gemini/chat/transformation.py#L70)
+
+
+
+## Usage - Thinking / `reasoning_content`
+
+LiteLLM translates OpenAI's `reasoning_effort` to Gemini's `thinking` parameter. [Code](https://github.com/BerriAI/litellm/blob/620664921902d7a9bfb29897a7b27c1a7ef4ddfb/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py#L362)
+
+**Mapping**
+
+| reasoning_effort | thinking |
+| ---------------- | -------- |
+| "low"            | "budget_tokens": 1024 |
+| "medium"         | "budget_tokens": 2048 |
+| "high"           | "budget_tokens": 4096 |
+
+<Tabs>
+<TabItem value="sdk" label="SDK">
+
+```python
+from litellm import completion
+
+resp = completion(
+    model="gemini/gemini-2.5-flash-preview-04-17",
+    messages=[{"role": "user", "content": "What is the capital of France?"}],
+    reasoning_effort="low",
+)
+
+```
+
+</TabItem>
+
+<TabItem value="proxy" label="PROXY">
+
+1. Setup config.yaml
+
+```yaml
+- model_name: gemini-2.5-flash
+  litellm_params:
+    model: gemini/gemini-2.5-flash-preview-04-17
+    api_key: os.environ/GEMINI_API_KEY
+```
+
+2. Start proxy
+
+```bash
+litellm --config /path/to/config.yaml
+```
+
+3. Test it! 
+
+```bash
+curl http://0.0.0.0:4000/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer <YOUR-LITELLM-KEY>" \
+  -d '{
+    "model": "gemini-2.5-flash",
+    "messages": [{"role": "user", "content": "What is the capital of France?"}],
+    "reasoning_effort": "low"
+  }'
+```
+
+</TabItem>
+</Tabs>
+
+
+**Expected Response**
+
+```python
+ModelResponse(
+    id='chatcmpl-c542d76d-f675-4e87-8e5f-05855f5d0f5e',
+    created=1740470510,
+    model='claude-3-7-sonnet-20250219',
+    object='chat.completion',
+    system_fingerprint=None,
+    choices=[
+        Choices(
+            finish_reason='stop',
+            index=0,
+            message=Message(
+                content="The capital of France is Paris.",
+                role='assistant',
+                tool_calls=None,
+                function_call=None,
+                reasoning_content='The capital of France is Paris. This is a very straightforward factual question.'
+            ),
+        )
+    ],
+    usage=Usage(
+        completion_tokens=68,
+        prompt_tokens=42,
+        total_tokens=110,
+        completion_tokens_details=None,
+        prompt_tokens_details=PromptTokensDetailsWrapper(
+            audio_tokens=None,
+            cached_tokens=0,
+            text_tokens=None,
+            image_tokens=None
+        ),
+        cache_creation_input_tokens=0,
+        cache_read_input_tokens=0
+    )
+)
+```
+
+### Pass `thinking` to Gemini models
+
+You can also pass the `thinking` parameter to Gemini models.
+
+This is translated to Gemini's [`thinkingConfig` parameter](https://ai.google.dev/gemini-api/docs/thinking#set-budget).
+
+<Tabs>
+<TabItem value="sdk" label="SDK">
+
+```python
+response = litellm.completion(
+  model="gemini/gemini-2.5-flash-preview-04-17",
+  messages=[{"role": "user", "content": "What is the capital of France?"}],
+  thinking={"type": "enabled", "budget_tokens": 1024},
+)
+```
+
+</TabItem>
+<TabItem value="proxy" label="PROXY">
+
+```bash
+curl http://0.0.0.0:4000/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer $LITELLM_KEY" \
+  -d '{
+    "model": "gemini/gemini-2.5-flash-preview-04-17",
+    "messages": [{"role": "user", "content": "What is the capital of France?"}],
+    "thinking": {"type": "enabled", "budget_tokens": 1024}
+  }'
+```
+
+</TabItem>
+</Tabs>
+
+
+
 
-[**See Updated List**](https://github.com/BerriAI/litellm/blob/1c747f3ad372399c5b95cc5696b06a5fbe53186b/litellm/llms/vertex_httpx.py#L122)
 
 ## Passing Gemini Specific Params
 ### Response schema 

docs/my-website/docs/reasoning_content.md

@@ -16,6 +16,8 @@ Supported Providers:
 - Vertex AI (Anthropic) (`vertexai/`)
 - OpenRouter (`openrouter/`)
 - XAI (`xai/`)
+- Google AI Studio (`google/`)
+- Vertex AI (`vertex_ai/`)
 
 LiteLLM will standardize the `reasoning_content` in the response and `thinking_blocks` in the assistant message.
 
@@ -23,7 +25,7 @@ LiteLLM will standardize the `reasoning_content` in the response and `thinking_b
 "message": {
     ...
     "reasoning_content": "The capital of France is Paris.",
-    "thinking_blocks": [
+    "thinking_blocks": [ # only returned for Anthropic models
         {
             "type": "thinking",
             "thinking": "The capital of France is Paris.",