feat: add submodule of worker-vllm, updated fastapi endpoints

.gitmodules

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+[submodule "worker-vllm"]
+	path = worker-vllm
+	url = https://github.com/runpod-workers/worker-vllm

.runpod/README.md

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+![vLLM worker banner](https://image.runpod.ai/preview/vllm/vllm-banner.png)
+
+Run LLMs using [vLLM](https://docs.vllm.ai) with OpenAI-compatible and Anthropic-compatible APIs on Runpod's Load Balancer for high-throughput, multi-worker scalability.
+
+Built on [worker-vllm](https://github.com/runpod-workers/worker-vllm) as the base inference engine.
+
+---
+
+## Endpoint Configuration
+
+All behaviour is controlled through environment variables:
+
+| Environment Variable                | Description                                       | Default             | Options                                                            |
+| ----------------------------------- | ------------------------------------------------- | ------------------- | ------------------------------------------------------------------ |
+| `MODEL_NAME`                        | Path of the model weights                         | "facebook/opt-125m" | Local folder or Hugging Face repo ID                               |
+| `HF_TOKEN`                          | HuggingFace access token for gated/private models |                     | Your HuggingFace access token                                      |
+| `MAX_MODEL_LEN`                     | Model's maximum context length                    |                     | Integer (e.g., 4096)                                               |
+| `QUANTIZATION`                      | Quantization method                               |                     | "awq", "gptq", "squeezellm", "bitsandbytes"                        |
+| `TENSOR_PARALLEL_SIZE`              | Number of GPUs                                    | 1                   | Integer                                                            |
+| `GPU_MEMORY_UTILIZATION`            | Fraction of GPU memory to use                     | 0.95                | Float between 0.0 and 1.0                                          |
+| `MAX_NUM_SEQS`                      | Maximum number of sequences per iteration         | 256                 | Integer                                                            |
+| `ENABLE_AUTO_TOOL_CHOICE`           | Enable automatic tool selection                   | false               | boolean (true or false)                                            |
+| `TOOL_CALL_PARSER`                  | Parser for tool calls                             |                     | "mistral", "hermes", "llama3_json", "granite", "deepseek_v3", etc. |
+| `REASONING_PARSER`                  | Parser for reasoning-capable models               |                     | "deepseek_r1", "qwen3", "granite", "hunyuan_a13b"                  |
+| `OPENAI_SERVED_MODEL_NAME_OVERRIDE` | Override served model name in API                 |                     | String                                                             |
+| `MAX_CONCURRENCY`                   | Maximum concurrent requests                       | 300                 | Integer                                                            |
+
+**Pass any vLLM engine arg** not listed above by setting an env var with the **UPPERCASED** field name (e.g. `MAX_MODEL_LEN=4096`, `ENABLE_CHUNKED_PREFILL=true`). The worker auto-discovers all `AsyncEngineArgs` fields from env. See the [vLLM engine args docs](https://docs.vllm.ai/en/latest/configuration/engine_args) for all available options.
+
+For complete configuration options, see the [full configuration documentation](https://github.com/runpod-workers/worker-vllm/blob/main/docs/configuration.md).
+
+## API Endpoints
+
+This worker exposes direct HTTP endpoints (no Runpod serverless wrapper). Use your endpoint URL directly:
+
+```
+https://<ENDPOINT_ID>.api.runpod.ai/
+```
+
+| Path | Method | Description |
+|------|--------|-------------|
+| `/ping` | GET | Health check (204 = init, 200 = ready) |
+| `/v1/models` | GET | List available models |
+| `/v1/chat/completions` | POST | OpenAI chat completions |
+| `/v1/completions` | POST | OpenAI text completions |
+| `/v1/responses` | POST | OpenAI Responses API |
+| `/v1/messages` | POST | Anthropic Messages API |
+
+### OpenAI-Compatible API
+
+#### Chat Completions
+
+```bash
+curl -X POST "https://<ENDPOINT_ID>.api.runpod.ai/v1/chat/completions" \
+  -H "Authorization: Bearer $RUNPOD_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "meta-llama/Llama-3.1-8B-Instruct",
+    "messages": [
+      { "role": "system", "content": "You are a helpful assistant." },
+      { "role": "user", "content": "What is the capital of France?" }
+    ],
+    "max_tokens": 100,
+    "temperature": 0.7
+  }'
+```
+
+#### Chat Completions (Streaming)
+
+```bash
+curl -X POST "https://<ENDPOINT_ID>.api.runpod.ai/v1/chat/completions" \
+  -H "Authorization: Bearer $RUNPOD_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "meta-llama/Llama-3.1-8B-Instruct",
+    "messages": [
+      { "role": "user", "content": "Write a short story about a robot." }
+    ],
+    "max_tokens": 500,
+    "temperature": 0.8,
+    "stream": true
+  }'
+```
+
+#### Text Completions
+
+```bash
+curl -X POST "https://<ENDPOINT_ID>.api.runpod.ai/v1/completions" \
+  -H "Authorization: Bearer $RUNPOD_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "meta-llama/Llama-3.1-8B-Instruct",
+    "prompt": "The capital of France is",
+    "max_tokens": 64,
+    "temperature": 0.0
+  }'
+```
+
+---
+
+### Anthropic Messages API
+
+Compatible with the Anthropic SDK and Claude Code. Point `ANTHROPIC_BASE_URL` at your endpoint:
+
+```bash
+export ANTHROPIC_BASE_URL=https://<ENDPOINT_ID>.api.runpod.ai/
+export ANTHROPIC_API_KEY=$RUNPOD_API_KEY
+```
+
+#### Messages (Non-Streaming)
+
+```bash
+curl -X POST "https://<ENDPOINT_ID>.api.runpod.ai/v1/messages" \
+  -H "Authorization: Bearer $RUNPOD_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "meta-llama/Llama-3.1-8B-Instruct",
+    "messages": [
+      { "role": "user", "content": "What is the capital of France?" }
+    ],
+    "max_tokens": 100
+  }'
+```
+
+#### Messages (Streaming)
+
+```bash
+curl -X POST "https://<ENDPOINT_ID>.api.runpod.ai/v1/messages" \
+  -H "Authorization: Bearer $RUNPOD_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "meta-llama/Llama-3.1-8B-Instruct",
+    "messages": [
+      { "role": "user", "content": "Write a short story about a robot." }
+    ],
+    "max_tokens": 500,
+    "stream": true
+  }'
+```
+
+---
+
+## Usage
+
+Below are minimal `python` snippets to get started quickly.
+
+> Replace `<ENDPOINT_ID>` with your endpoint ID and `<API_KEY>` with a [RunPod API key](https://docs.runpod.io/get-started/api-keys).
+
+### OpenAI SDK
+
+```python
+from openai import OpenAI
+import os
+
+client = OpenAI(
+    api_key=os.getenv("RUNPOD_API_KEY"),
+    base_url=f"https://<ENDPOINT_ID>.api.runpod.ai/v1",
+)
+```
+
+`Chat Completions (Non-Streaming)`
+
+```python
+response = client.chat.completions.create(
+    model="meta-llama/Llama-3.1-8B-Instruct",
+    messages=[{"role": "user", "content": "Explain quantum computing in simple terms"}],
+    temperature=0,
+    max_tokens=100,
+)
+print(response.choices[0].message.content)
+```
+
+`Chat Completions (Streaming)`
+
+```python
+stream = client.chat.completions.create(
+    model="meta-llama/Llama-3.1-8B-Instruct",
+    messages=[{"role": "user", "content": "Explain quantum computing in simple terms"}],
+    temperature=0,
+    max_tokens=100,
+    stream=True,
+)
+for chunk in stream:
+    print(chunk.choices[0].delta.content or "", end="", flush=True)
+```
+
+### Anthropic SDK
+
+```python
+import anthropic
+import os
+
+client = anthropic.Anthropic(
+    api_key=os.getenv("RUNPOD_API_KEY"),
+    base_url=f"https://<ENDPOINT_ID>.api.runpod.ai/",
+)
+
+response = client.messages.create(
+    model="meta-llama/Llama-3.1-8B-Instruct",
+    messages=[{"role": "user", "content": "Explain quantum computing in simple terms"}],
+    max_tokens=100,
+)
+print(response.content[0].text)
+```
+
+### Claude Code
+
+```bash
+export ANTHROPIC_BASE_URL=https://<ENDPOINT_ID>.api.runpod.ai/
+export ANTHROPIC_API_KEY=$RUNPOD_API_KEY
+claude --model <MODEL_NAME>
+```
+
+## Compatibility
+
+For supported models, see the [vLLM supported models documentation](https://docs.vllm.ai/en/latest/models/supported_models.html).
+
+## Documentation
+
+- **[🚀 Deployment Guide](https://docs.runpod.io/serverless/vllm/get-started)** - Step-by-step setup
+- **[📖 Configuration Reference](https://github.com/runpod-workers/worker-vllm/blob/main/docs/configuration.md)** - All environment variables
+- **[🔧 Development Guide](https://github.com/runpod-workers/worker-vllm/blob/main/docs/conventions.md)** - Architecture and patterns