Description:
Some ASAN and TSAN builds require a local JDK (https://github.com/envoyproxy/envoy-mobile/pull/1870/checks?check_run_id=3874356472) so we add them to those workflows

Risk Level: Low
Testing: See asan and tsan checks
Docs Changes: N/A
Release Notes:  N/A

Signed-off-by: Luis Fernando Pino Duque <luis@engflow.com>
Signed-off-by: JP Simard <jp@jpsim.com>

Description:
Some ASAN and TSAN builds require a local JDK (https://github.com/envoyproxy/envoy-mobile/pull/1870/checks?check_run_id=3874356472) so we add them to those workflows

Risk Level: Low
Testing: See asan and tsan checks
Docs Changes: N/A
Release Notes:  N/A

Signed-off-by: Luis Fernando Pino Duque <luis@engflow.com>
Signed-off-by: JP Simard <jp@jpsim.com>

…1878)

**Description**

This commit adds a translator that will convert a request sent to
`/anthropic/v1/messages` and `/v1/messages` endpoints for OpenAI schema
backends. It does not matter whether the OpenAI schema backend natively
supports the endpoint (e.g. vLLM) as translating should be a light/fast
enough process. This approach is also more versatile and future-proof
than just passing through the Anthropic Message Request to a backend
that natively supports it. It also follows the already-existing
structure for adding translators, path processor factories, and schema
translation.

A major example use case would be using AI Gateway to route requests
from Claude Code to several AI backends like locally hosted vLLM models
with LoRA adapters.

NOTE: vLLM is only used for local testing as I do not have access to
compute. The intended goal for this PR is to support any OpenAI
compatible backend/services using an Anthropic interface.

**Related Issues/PRs (if applicable)**

Fixes #1372 
Fixes #1867 

**Special notes for reviewers (if applicable)**
Claude Code was used to write most of the tests but were verified. It
would also be nice if the maintainers could review the other PR #1843 as
some of the Anthropic apischema here can be updated once #1843 is
merged.

<details>

<summary>Functional Test Results</summary>

Test for anthropic endpoints for OpenAI schema backends that natively
support it:
```
$ curl -v http://localhost:8080/v1/messages   -H "Content-Type: application/json"   -d '{
    "model": "Qwen/Qwen2.5-0.5B-Instruct",
    "messages": [
      {"role": "user", "content": "Say hello!"}
    ],
    "max_tokens": 100
  }'
* Host localhost:8080 was resolved.
* IPv6: ::1
* IPv4: 127.0.0.1
*   Trying [::1]:8080...
* Connected to localhost (::1) port 8080
> POST /v1/messages HTTP/1.1
> Host: localhost:8080
> User-Agent: curl/8.5.0
> Accept: */*
> Content-Type: application/json
> Content-Length: 143
> 
< HTTP/1.1 200 OK
< date: Fri, 20 Feb 2026 18:46:04 GMT
< server: uvicorn
< content-type: application/json
< content-length: 331
< 
* Connection #0 to host localhost left intact
{"id":"chatcmpl-36ec5b3d-4273-41e9-966b-ed742f7a93d1","type":"message","role":"assistant","content":[{"type":"text","text":"Hello! How can I assist you today?"}],"model":"Qwen/Qwen2.5-0.5B-Instruct","stop_reason":"end_turn","usage":{"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"input_tokens":32,"output_tokens":10}}
```
```
$ curl -v http://localhost:8080/anthropic/v1/messages   -H "Content-Type: application/json"   -d '{
    "model": "Qwen/Qwen2.5-0.5B-Instruct",
    "messages": [
      {"role": "user", "content": "Say hello!"}
    ],
    "max_tokens": 100
  }'
* Host localhost:8080 was resolved.
* IPv6: ::1
* IPv4: 127.0.0.1
*   Trying [::1]:8080...
* Connected to localhost (::1) port 8080
> POST /anthropic/v1/messages HTTP/1.1
> Host: localhost:8080
> User-Agent: curl/8.5.0
> Accept: */*
> Content-Type: application/json
> Content-Length: 143
> 
< HTTP/1.1 200 OK
< date: Fri, 20 Feb 2026 18:46:44 GMT
< server: uvicorn
< content-type: application/json
< content-length: 331
< 
* Connection #0 to host localhost left intact
{"id":"chatcmpl-f639ff32-4f89-48c5-b5b1-56878e641da6","type":"message","role":"assistant","content":[{"type":"text","text":"Hello! How can I assist you today?"}],"model":"Qwen/Qwen2.5-0.5B-Instruct","stop_reason":"end_turn","usage":{"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"input_tokens":32,"output_tokens":10}}
```

Port Forward logs
```
$ kubectl port-forward -n envoy-gateway-system svc/$ENVOY_SERVICE 8080:80
Forwarding from 127.0.0.1:8080 -> 10080
Forwarding from [::1]:8080 -> 10080
Handling connection for 8080
Handling connection for 8080
Handling connection for 8080
```

vLLM Logs (for both requests)
```
(APIServer pid=141923) INFO:     Started server process [141923]
(APIServer pid=141923) INFO:     Waiting for application startup.
(APIServer pid=141923) INFO:     Application startup complete.
(APIServer pid=141923) INFO:     172.18.0.2:46854 - "POST /v1/chat/completions HTTP/1.1" 200 OK
(APIServer pid=141923) INFO 02-20 13:46:05 [loggers.py:257] Engine 000: Avg prompt throughput: 3.2 tokens/s, Avg generation throughput: 1.0 tokens/s, Running: 0 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.0%, Prefix cache hit rate: 0.0%
(APIServer pid=141923) INFO 02-20 13:46:15 [loggers.py:257] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.0%, Prefix cache hit rate: 0.0%
(APIServer pid=141923) INFO:     172.18.0.2:47216 - "POST /v1/chat/completions HTTP/1.1" 200 OK
(APIServer pid=141923) INFO 02-20 13:46:45 [loggers.py:257] Engine 000: Avg prompt throughput: 3.2 tokens/s, Avg generation throughput: 1.0 tokens/s, Running: 0 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.0%, Prefix cache hit rate: 25.0%
(APIServer pid=141923) INFO 02-20 13:46:55 [loggers.py:257] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.0%, Prefix cache hit rate: 25.0%
```

</details>

---------

Signed-off-by: Chang Min <changminbark@gmail.com>
Co-authored-by: Ignasi Barrera <ignasi@tetrate.io>