docs(bedrock): document the native Responses API route for OpenAI models

docs/providers/bedrock.md

@@ -1981,6 +1981,71 @@ curl --location 'http://0.0.0.0:4000/chat/completions' \
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+## OpenAI models on the native Responses API
+
+AWS serves its OpenAI models on bedrock-runtime's own Responses endpoint, `https://bedrock-runtime.{region}.amazonaws.com/openai/v1/responses`. For the models that opt in, LiteLLM sends your `/v1/responses` request there in the shape it arrived in, instead of translating it into Converse through the Chat Completions bridge. That is what makes Responses-only parameters work: `prompt_cache_key` reaches Bedrock and the repeat call reports cached tokens in `usage.input_tokens_details`, where the bridge answered 400 with `bedrock does not support parameters: ['prompt_cache_key']`.
+
+A model opts in through `"supported_endpoints": ["/v1/responses"]` on its entry in the [model cost map](https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json). Today that is the `us.` and `global.` inference profiles of GPT-5.4, GPT-5.5, GPT-5.6 (Sol, Terra, Luna), and GPT-6 (Astra, Sol, Luna), so `bedrock/us.openai.gpt-6-astra` and `bedrock/global.openai.gpt-5.6-sol` take the native route while `bedrock/openai.gpt-oss-120b-1:0` keeps the bridge. The flag can be overridden per deployment through `model_info` on the proxy or `litellm.register_model` in the SDK, so onboarding a model is a JSON change.
+
+Authentication, regions, and cost tracking work the same as on Converse: SigV4 credentials or a Bedrock API key as `api_key`, with the host picked from the region's partition. An `aws_bedrock_runtime_endpoint` that already ends in `/openai/v1/responses`, `/v1/responses`, or `/responses` is used as is.
+
+What is different on the native route: `background` is dropped with a proxy-log warning, since bedrock-runtime rejects it and the bridge never forwarded it either. A `web_search` tool is dropped with a warning, since bedrock-runtime answers that web search is not supported. `file_search` keeps LiteLLM's emulation. Remote `http(s)` image URLs, in `input_image` blocks, in `function_call_output` lists, and in `computer_call_output` screenshots, are downloaded and inlined as data URIs, because bedrock-runtime accepts only `data:` and `s3://` images. Streaming works as on OpenAI.
+
+<Tabs>
+<TabItem value="sdk" label="SDK">
+
+```python title="Native Responses API SDK Usage" showLineNumbers
+import os
+from litellm import responses
+
+os.environ["AWS_ACCESS_KEY_ID"] = "your-aws-access-key"
+os.environ["AWS_SECRET_ACCESS_KEY"] = "your-aws-secret-key"
+os.environ["AWS_REGION_NAME"] = "us-east-1"
+
+response = responses(
+    model="bedrock/us.openai.gpt-6-astra",
+    input="Reply with the single word pong.",
+    prompt_cache_key="my-session",
+)
+print(response.output_text)
+```
+
+</TabItem>
+
+<TabItem value="proxy" label="Proxy">
+
+**1. Add to config**
+
+```yaml title="config.yaml" showLineNumbers
+model_list:
+  - model_name: bedrock-gpt-6-astra
+    litellm_params:
+      model: bedrock/us.openai.gpt-6-astra
+      aws_region_name: us-east-1
+```
+
+**2. Start the proxy**
+
+```bash
+litellm --config /path/to/config.yaml
+```
+
+**3. Call `/v1/responses`**
+
+```bash
+curl http://0.0.0.0:4000/v1/responses \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer $LITELLM_KEY" \
+  -d '{
+    "model": "bedrock-gpt-6-astra",
+    "input": "Reply with the single word pong.",
+    "prompt_cache_key": "my-session"
+  }'
+```
+
+</TabItem>
+</Tabs>
+
 ## TwelveLabs Pegasus - Video Understanding
 
 TwelveLabs Pegasus 1.2 is a video understanding model that can analyze and describe video content. LiteLLM supports this model through Bedrock's `/invoke` endpoint.