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Author SHA1 Message Date
Marut PandyaandGitHub 286d6ba702 Merge pull request #102 from carlson-svg/main
Add human readable worker-config.json
2024-08-26 20:22:47 -07:00
carlson-svg 8d734f8340 Merge branch 'add-worker-config' 2024-08-26 01:25:09 -07:00
carlson-svg 4fa4a8e0e6 added to worker config docs to table of contents + added side note 2024-08-26 01:20:18 -07:00
carlson-svg 39ce8a64c0 initial documentation for worker-config.json 2024-08-22 15:40:54 -07:00
carlson-svg 825ef25b60 changed to minimumCudaVersion to camel case 2024-08-21 12:47:48 -07:00
carlson-svg 1e9aeb6e8f adding "minimum_cuda_version" to each version 2024-08-21 12:44:45 -07:00
carlson-svg e6172dddd4 took out space in imageName from version 0.5.4 2024-08-19 15:17:20 -07:00
carlson-svg 21a1e138b4 updated version of human readable config 2024-08-18 23:57:19 -07:00
carlson-svg a40e7803ee converted to human readable format 2024-08-18 23:24:40 -07:00
CarlsonandGitHub 5e245793bc Merge pull request #1 from carlson-svg/add-worker-config
v0 worker-config
2024-08-13 20:43:47 -07:00
Marut PandyaandGitHub 2111c9e7a5 Update README.md 2024-08-12 21:02:43 -07:00
carlson-svg 0ae11ea6df v0 worker-config 2024-08-09 15:10:08 -07:00
Marut PandyaandGitHub 7f46582949 Merge pull request #96 from runpod-workers/rel-v0.5.4
update vllm version 0.5.4
2024-08-09 15:01:16 -07:00
Marut PandyaandGitHub 571ef2b805 Update README.md 2024-08-09 14:58:46 -07:00
pandyamarut 967eaba573 change to float
Signed-off-by: pandyamarut <pandyamarut@gmail.com>
2024-08-09 14:41:07 -07:00
Marut PandyaandGitHub eb75a3ac03 Merge pull request #95 from runpod-workers/runpod-package-update
Update runpod package version
2024-08-09 12:04:25 -07:00
pandyamarut 9cb9336cf5 update vllm version 0.5.4
Signed-off-by: pandyamarut <pandyamarut@gmail.com>
2024-08-09 12:01:42 -07:00
pandyamarutandGitHub 6a15a9e750 Update package version 2024-08-07 22:38:37 +00:00
Marut PandyaandGitHub f023f57217 Update README.md 2024-08-07 15:38:26 -07:00
Marut PandyaandGitHub 673597fd46 Update README.md 2024-08-07 15:32:23 -07:00
Marut PandyaandGitHub c50543ebd9 Update README.md 2024-08-07 15:30:33 -07:00
Marut PandyaandGitHub 17a2d844ec Merge pull request #93 from runpod-workers/up-rdme
Update README.md
2024-08-05 14:36:39 -07:00
pandyamarut 3498e99b2f update
Signed-off-by: pandyamarut <pandyamarut@gmail.com>
2024-08-05 14:33:56 -07:00
pandyamarut 5da96ce9a6 update
Signed-off-by: pandyamarut <pandyamarut@gmail.com>
2024-08-05 14:26:56 -07:00
Marut PandyaandGitHub e32626ca9d Update README.md 2024-08-05 14:19:38 -07:00
6 changed files with 969 additions and 28 deletions
+1 -1
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@@ -12,7 +12,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install --upgrade -r /requirements.txt
# Install vLLM (switching back to pip installs since issues that required building fork are fixed and space optimization is not as important since caching) and FlashInfer
RUN python3 -m pip install vllm==0.5.3.post1 && \
RUN python3 -m pip install vllm==0.5.4 && \
python3 -m pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.3
# Setup for Option 2: Building the Image with the Model included
+99 -18
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@@ -18,8 +18,9 @@ Deploy OpenAI-Compatible Blazing-Fast LLM Endpoints powered by the [vLLM](https:
### 1. UI for Deploying vLLM Worker on RunPod console:
![Demo of Deploying vLLM Worker on RunPod console with new UI](media/ui_demo.gif)
### 2. Worker vLLM `v1.1` with vLLM `0.5.3` now available under `stable` tags
Update v1.1 is now available, use the image tag `runpod/worker-v1-vllm:stable-cuda12.1.0`.
### 2. Worker vLLM `v1.2.0` with vLLM `0.5.4` now available under `stable` tags
Update v1.2.0 is now available, use the image tag `runpod/worker-v1-vllm:v1.2.0stable-cuda12.1.0`.
### 3. OpenAI-Compatible [Embedding Worker](https://github.com/runpod-workers/worker-infinity-embedding) Released
Deploy your own OpenAI-compatible Serverless Endpoint on RunPod with multiple embedding models and fast inference for RAG and more!
@@ -57,6 +58,10 @@ Worker vLLM is now cached on all RunPod machines, resulting in near-instant depl
- [Input Request Parameters](#input-request-parameters)
- [Text Input Formats](#text-input-formats)
- [Sampling Parameters](#sampling-parameters)
- [Worker Config](#worker-config)
- [Writing your worker-config.json](#writing-your-worker-configjson)
- [Example of schema](#example-of-schema)
- [Example of versions](#example-of-versions)
# Setting up the Serverless Worker
@@ -87,7 +92,7 @@ Below is a summary of the available RunPod Worker images, categorized by image s
- RunPod Account
#### Environment Variables/Settings
> Note: `0` is equivalent to `False` and `1` is equivalent to `True` for boolean values.
> Note: `0` is equivalent to `False` and `1` is equivalent to `True` for boolean as int values.
| `Name` | `Default` | `Type/Choices` | `Description` |
|-------------------------------------------|-----------------------|--------------------------------------------|---------------|
@@ -95,11 +100,12 @@ Below is a summary of the available RunPod Worker images, categorized by image s
| `TOKENIZER` | None | `str` | Name or path of the Hugging Face tokenizer to use. |
| `SKIP_TOKENIZER_INIT` | False | `bool` | Skip initialization of tokenizer and detokenizer. |
| `TOKENIZER_MODE` | 'auto' | ['auto', 'slow'] | The tokenizer mode. |
| `TRUST_REMOTE_CODE` | False | `bool` | Trust remote code from Hugging Face. |
| `TRUST_REMOTE_CODE` | `False` | `bool` | Trust remote code from Hugging Face. |
| `DOWNLOAD_DIR` | None | `str` | Directory to download and load the weights. |
| `LOAD_FORMAT` | 'auto' | ['auto', 'pt', 'safetensors', 'npcache', 'dummy', 'tensorizer', 'bitsandbytes'] | The format of the model weights to load. |
| `LOAD_FORMAT` | 'auto' | `str` | The format of the model weights to load. |
| `HF_TOKEN` | - | `str` | Hugging Face token for private and gated models.|
| `DTYPE` | 'auto' | ['auto', 'half', 'float16', 'bfloat16', 'float', 'float32'] | Data type for model weights and activations. |
| `KV_CACHE_DTYPE` | 'auto' | ['auto', 'fp8', 'fp8_e5m2', 'fp8_e4m3'] | Data type for KV cache storage. |
| `KV_CACHE_DTYPE` | 'auto' | ['auto', 'fp8'] | Data type for KV cache storage. |
| `QUANTIZATION_PARAM_PATH` | None | `str` | Path to the JSON file containing the KV cache scaling factors. |
| `MAX_MODEL_LEN` | None | `int` | Model context length. |
| `GUIDED_DECODING_BACKEND` | 'outlines' | ['outlines', 'lm-format-enforcer'] | Which engine will be used for guided decoding by default. |
@@ -109,26 +115,19 @@ Below is a summary of the available RunPod Worker images, categorized by image s
| `TENSOR_PARALLEL_SIZE` | 1 | `int` | Number of tensor parallel replicas. |
| `MAX_PARALLEL_LOADING_WORKERS` | None | `int` | Load model sequentially in multiple batches. |
| `RAY_WORKERS_USE_NSIGHT` | False | `bool` | If specified, use nsight to profile Ray workers. |
| `BLOCK_SIZE` | 16 | [8, 16, 32] | Token block size for contiguous chunks of tokens. |
| `ENABLE_PREFIX_CACHING` | False | `bool` | Enables automatic prefix caching. |
| `DISABLE_SLIDING_WINDOW` | False | `bool` | Disables sliding window, capping to sliding window size. |
| `USE_V2_BLOCK_MANAGER` | False | `bool` | Use BlockSpaceMangerV2. |
| `NUM_LOOKAHEAD_SLOTS` | 0 | `int` | Experimental scheduling config necessary for speculative decoding. |
| `SEED` | 0 | `int` | Random seed for operations. |
| `SWAP_SPACE` | 4 | `int` | CPU swap space size (GiB) per GPU. |
| `GPU_MEMORY_UTILIZATION` | 0.90 | `float` | The fraction of GPU memory to be used for the model executor. |
| `NUM_GPU_BLOCKS_OVERRIDE` | None | `int` | If specified, ignore GPU profiling result and use this number of GPU blocks. |
| `MAX_NUM_BATCHED_TOKENS` | None | `int` | Maximum number of batched tokens per iteration. |
| `MAX_NUM_SEQS` | 256 | `int` | Maximum number of sequences per iteration. |
| `MAX_LOGPROBS` | 20 | `int` | Max number of log probs to return when logprobs is specified in SamplingParams. |
| `DISABLE_LOG_STATS` | False | `bool` | Disable logging statistics. |
| `QUANTIZATION` | None | [*QUANTIZATION_METHODS, None] | Method used to quantize the weights. |
| `QUANTIZATION` | None | ['awq', 'squeezellm', 'gptq'] | Method used to quantize the weights. |
| `ROPE_SCALING` | None | `dict` | RoPE scaling configuration in JSON format. |
| `ROPE_THETA` | None | `float` | RoPE theta. Use with rope_scaling. |
| `ENFORCE_EAGER` | False | `bool` | Always use eager-mode PyTorch. |
| `MAX_CONTEXT_LEN_TO_CAPTURE` | None | `int` | Maximum context length covered by CUDA graphs. |
| `MAX_SEQ_LEN_TO_CAPTURE` | 8192 | `int` | Maximum sequence length covered by CUDA graphs. |
| `DISABLE_CUSTOM_ALL_REDUCE` | False | `bool` | See ParallelConfig. |
| `TOKENIZER_POOL_SIZE` | 0 | `int` | Size of tokenizer pool to use for asynchronous tokenization. |
| `TOKENIZER_POOL_TYPE` | 'ray' | `str` | Type of tokenizer pool to use for asynchronous tokenization. |
| `TOKENIZER_POOL_EXTRA_CONFIG` | None | `dict` | Extra config for tokenizer pool. |
@@ -140,7 +139,6 @@ Below is a summary of the available RunPod Worker images, categorized by image s
| `LONG_LORA_SCALING_FACTORS` | None | `tuple` | Specify multiple scaling factors for LoRA adapters. |
| `MAX_CPU_LORAS` | None | `int` | Maximum number of LoRAs to store in CPU memory. |
| `FULLY_SHARDED_LORAS` | False | `bool` | Enable fully sharded LoRA layers. |
| `DEVICE` | 'auto' | ['auto', 'cuda', 'neuron', 'cpu', 'openvino', 'tpu', 'xpu'] | Device type for vLLM execution. |
| `SCHEDULER_DELAY_FACTOR` | 0.0 | `float` | Apply a delay before scheduling next prompt. |
| `ENABLE_CHUNKED_PREFILL` | False | `bool` | Enable chunked prefill requests. |
| `SPECULATIVE_MODEL` | None | `str` | The name of the draft model to be used in speculative decoding. |
@@ -168,7 +166,7 @@ Below is a summary of the available RunPod Worker images, categorized by image s
| `MAX_PARALLEL_LOADING_WORKERS` | `None` | `int` |Load model sequentially in multiple batches, to avoid RAM OOM when using tensor parallel and large models. |
| `BLOCK_SIZE` | `16` | `8`, `16`, `32` |Token block size for contiguous chunks of tokens. |
| `SWAP_SPACE` | `4` | `int` |CPU swap space size (GiB) per GPU. |
| `ENFORCE_EAGER` | `0` | boolean as `int` |Always use eager-mode PyTorch. If False(`0`), will use eager mode and CUDA graph in hybrid for maximal performance and flexibility. |
| `ENFORCE_EAGER` | False | `bool` |Always use eager-mode PyTorch. If False(`0`), will use eager mode and CUDA graph in hybrid for maximal performance and flexibility. |
| `MAX_SEQ_LEN_TO_CAPTURE` | `8192` | `int` |Maximum context length covered by CUDA graphs. When a sequence has context length larger than this, we fall back to eager mode.|
| `DISABLE_CUSTOM_ALL_REDUCE` | `0` | `int` |Enables or disables custom all reduce. |
**Streaming Batch Size Settings**:
@@ -182,8 +180,8 @@ The way this works is that the first request will have a batch size of `DEFAULT_
| `OPENAI_RESPONSE_ROLE` | `assistant` | `str` |Role of the LLM's Response in OpenAI Chat Completions. |
**Serverless Settings**
| `MAX_CONCURRENCY` | `300` | `int` |Max concurrent requests per worker. vLLM has an internal queue, so you don't have to worry about limiting by VRAM, this is for improving scaling/load balancing efficiency |
| `DISABLE_LOG_STATS` | `1` | boolean as `int` |Enables or disables vLLM stats logging. |
| `DISABLE_LOG_REQUESTS` | `1` | boolean as `int` |Enables or disables vLLM request logging. |
| `DISABLE_LOG_STATS` | False | `bool` |Enables or disables vLLM stats logging. |
| `DISABLE_LOG_REQUESTS` | False | `bool` |Enables or disables vLLM request logging. |
> [!TIP]
> If you are facing issues when using Mixtral 8x7B, Quantized models, or handling unusual models/architectures, try setting `TRUST_REMOTE_CODE` to `1`.
@@ -520,3 +518,86 @@ Your list can contain any number of messages, and each message usually can have
]
```
</details>
# Worker Config
The worker config is a JSON file that is used to build the form that helps users configure their serverless endpoint on the RunPod Web Interface.
Note: This is a new feature and only works for workers that use one model
## Writing your worker-config.json
The JSON consists of two main parts, schema and versions.
- `schema`: Here you specify the form fields that will be displayed to the user.
- `env_var_name`: The name of the environment variable that is being set using the form field.
- `value`: This is the default value of the form field. It will be shown in the UI as such unless the user changes it.
- `title`: This is the title of the form field in the UI.
- `description`: This is the description of the form field in the UI.
- `required`: This is a boolean that specifies if the form field is required.
- `type`: This is the type of the form field. Options are:
- `text`: Environment variable is a string so user inputs text in form field.
- `select`: User selects one option from the dropdown. You must provide the `options` key value pair after type if using this.
- `toggle`: User toggles between true and false.
- `number`: User inputs a number in the form field.
- `options`: Specify the options the user can select from if the type is `select`. DO NOT include this unless the `type` is `select`.
- `versions`: This is where you call the form fields specified in `schema` and organize them into categories.
- `imageName`: This is the name of the Docker image that will be used to run the serverless endpoint.
- `minimumCudaVersion`: This is the minimum CUDA version that is required to run the serverless endpoint.
- `categories`: This is where you call the keys of the form fields specified in `schema` and organize them into categories. Each category is a toggle list of forms on the Web UI.
- `title`: This is the title of the category in the UI.
- `settings`: This is the array of settings schemas specified in `schema` associated with the category.
## Example of schema
```json
{
"schema": {
"TOKENIZER": {
"env_var_name": "TOKENIZER",
"value": "",
"title": "Tokenizer",
"description": "Name or path of the Hugging Face tokenizer to use.",
"required": false,
"type": "text"
},
"TOKENIZER_MODE": {
"env_var_name": "TOKENIZER_MODE",
"value": "auto",
"title": "Tokenizer Mode",
"description": "The tokenizer mode.",
"required": false,
"type": "select",
"options": [
{ "value": "auto", "label": "auto" },
{ "value": "slow", "label": "slow" }
]
},
...
}
}
```
## Example of versions
```json
{
"versions": {
"0.5.4": {
"imageName": "runpod/worker-v1-vllm:v1.2.0stable-cuda12.1.0",
"minimumCudaVersion": "12.1",
"categories": [
{
"title": "LLM Settings",
"settings": [
"TOKENIZER", "TOKENIZER_MODE", "OTHER_SETTINGS_SCHEMA_KEYS_YOU_HAVE_SPECIFIED_0", ...
]
},
{
"title": "Tokenizer Settings",
"settings": [
"OTHER_SETTINGS_SCHEMA_KEYS_0", "OTHER_SETTINGS_SCHEMA_KEYS_1", ...
]
},
...
]
}
}
}
```
+1 -1
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@@ -1,7 +1,7 @@
ray
pandas
pyarrow
runpod==1.6.2
runpod==1.7.0
huggingface-hub
packaging
typing-extensions==4.7.1
+2 -2
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@@ -126,7 +126,7 @@ class OpenAIvLLMEngine(vLLMEngine):
self.model_config = await self.llm.get_model_config()
self.chat_engine = OpenAIServingChat(
engine=self.llm,
async_engine_client=self.llm,
model_config=self.model_config,
served_model_names=[self.served_model_name],
response_role=self.response_role,
@@ -136,7 +136,7 @@ class OpenAIvLLMEngine(vLLMEngine):
request_logger=None
)
self.completion_engine = OpenAIServingCompletion(
engine=self.llm,
async_engine_client=self.llm,
model_config=self.model_config,
served_model_names=[self.served_model_name],
lora_modules=[],
+6 -6
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@@ -13,9 +13,9 @@ RENAME_ARGS_MAP = {
}
DEFAULT_ARGS = {
"disable_log_stats": True,
"disable_log_requests": True,
"gpu_memory_utilization": 0.9,
"disable_log_stats": os.getenv('DISABLE_LOG_STATS', 'False').lower() == 'true',
"disable_log_requests": os.getenv('DISABLE_LOG_REQUESTS', 'False').lower() == 'true',
"gpu_memory_utilization": float(os.getenv('GPU_MEMORY_UTILIZATION', 0.95)),
"pipeline_parallel_size": int(os.getenv('PIPELINE_PARALLEL_SIZE', 1)),
"tensor_parallel_size": int(os.getenv('TENSOR_PARALLEL_SIZE', 1)),
"served_model_name": os.getenv('SERVED_MODEL_NAME', None),
@@ -162,8 +162,8 @@ def get_engine_args():
args["max_seq_len_to_capture"] = int(os.getenv("MAX_CONTEXT_LEN_TO_CAPTURE"))
logging.warning("Using MAX_CONTEXT_LEN_TO_CAPTURE is deprecated. Please use MAX_SEQ_LEN_TO_CAPTURE instead.")
if "gemma-2" in args.get("model", "").lower():
os.environ["VLLM_ATTENTION_BACKEND"] = "FLASHINFER"
logging.info("Using FLASHINFER for gemma-2 model.")
# if "gemma-2" in args.get("model", "").lower():
# os.environ["VLLM_ATTENTION_BACKEND"] = "FLASHINFER"
# logging.info("Using FLASHINFER for gemma-2 model.")
return AsyncEngineArgs(**args)
+860
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@@ -0,0 +1,860 @@
{
"versions": {
"0.5.4": {
"imageName": "runpod/worker-v1-vllm:v1.2.0stable-cuda12.1.0",
"minimumCudaVersion": "12.1",
"categories": [
{
"title": "LLM Settings",
"settings": [
"TOKENIZER", "TOKENIZER_MODE", "SKIP_TOKENIZER_INIT", "TRUST_REMOTE_CODE",
"DOWNLOAD_DIR", "LOAD_FORMAT", "DTYPE", "KV_CACHE_DTYPE", "QUANTIZATION_PARAM_PATH",
"MAX_MODEL_LEN", "GUIDED_DECODING_BACKEND", "DISTRIBUTED_EXECUTOR_BACKEND",
"WORKER_USE_RAY", "RAY_WORKERS_USE_NSIGHT", "PIPELINE_PARALLEL_SIZE",
"TENSOR_PARALLEL_SIZE", "MAX_PARALLEL_LOADING_WORKERS", "ENABLE_PREFIX_CACHING",
"DISABLE_SLIDING_WINDOW", "USE_V2_BLOCK_MANAGER", "NUM_LOOKAHEAD_SLOTS",
"SEED", "NUM_GPU_BLOCKS_OVERRIDE", "MAX_NUM_BATCHED_TOKENS", "MAX_NUM_SEQS",
"MAX_LOGPROBS", "DISABLE_LOG_STATS", "QUANTIZATION", "ROPE_SCALING", "ROPE_THETA",
"TOKENIZER_POOL_SIZE", "TOKENIZER_POOL_TYPE", "TOKENIZER_POOL_EXTRA_CONFIG",
"ENABLE_LORA", "MAX_LORAS", "MAX_LORA_RANK", "LORA_EXTRA_VOCAB_SIZE",
"LORA_DTYPE", "LONG_LORA_SCALING_FACTORS", "MAX_CPU_LORAS", "FULLY_SHARDED_LORAS",
"DEVICE", "SCHEDULER_DELAY_FACTOR", "ENABLE_CHUNKED_PREFILL", "SPECULATIVE_MODEL",
"NUM_SPECULATIVE_TOKENS", "SPECULATIVE_DRAFT_TENSOR_PARALLEL_SIZE",
"SPECULATIVE_MAX_MODEL_LEN", "SPECULATIVE_DISABLE_BY_BATCH_SIZE",
"NGRAM_PROMPT_LOOKUP_MAX", "NGRAM_PROMPT_LOOKUP_MIN", "SPEC_DECODING_ACCEPTANCE_METHOD",
"TYPICAL_ACCEPTANCE_SAMPLER_POSTERIOR_THRESHOLD", "TYPICAL_ACCEPTANCE_SAMPLER_POSTERIOR_ALPHA",
"MODEL_LOADER_EXTRA_CONFIG", "PREEMPTION_MODE", "PREEMPTION_CHECK_PERIOD",
"PREEMPTION_CPU_CAPACITY", "MAX_LOG_LEN", "DISABLE_LOGGING_REQUEST"
]
},
{
"title": "Tokenizer Settings",
"settings": [
"TOKENIZER_NAME", "TOKENIZER_REVISION", "CUSTOM_CHAT_TEMPLATE"
]
},
{
"title": "System Settings",
"settings": [
"GPU_MEMORY_UTILIZATION", "MAX_PARALLEL_LOADING_WORKERS", "BLOCK_SIZE",
"SWAP_SPACE", "ENFORCE_EAGER", "MAX_SEQ_LEN_TO_CAPTURE", "DISABLE_CUSTOM_ALL_REDUCE"
]
},
{
"title": "Streaming Settings",
"settings": [
"DEFAULT_BATCH_SIZE", "DEFAULT_MIN_BATCH_SIZE", "DEFAULT_BATCH_SIZE_GROWTH_FACTOR"
]
},
{
"title": "OpenAI Settings",
"settings": [
"RAW_OPENAI_OUTPUT", "OPENAI_RESPONSE_ROLE", "OPENAI_SERVED_MODEL_NAME_OVERRIDE"
]
},
{
"title": "Serverless Settings",
"settings": [
"MAX_CONCURRENCY", "DISABLE_LOG_STATS", "DISABLE_LOG_REQUESTS"
]
}
]
},
"0.5.3": {
"imageName": "runpod/worker-v1-vllm:stable-cuda12.1.0",
"minimumCudaVersion": "12.1",
"categories": [
{
"title": "LLM Settings",
"settings": [
"TOKENIZER", "TOKENIZER_MODE", "SKIP_TOKENIZER_INIT", "TRUST_REMOTE_CODE",
"DOWNLOAD_DIR", "LOAD_FORMAT", "DTYPE", "KV_CACHE_DTYPE", "QUANTIZATION_PARAM_PATH",
"MAX_MODEL_LEN", "GUIDED_DECODING_BACKEND", "DISTRIBUTED_EXECUTOR_BACKEND",
"WORKER_USE_RAY", "RAY_WORKERS_USE_NSIGHT", "PIPELINE_PARALLEL_SIZE",
"TENSOR_PARALLEL_SIZE", "MAX_PARALLEL_LOADING_WORKERS", "ENABLE_PREFIX_CACHING",
"DISABLE_SLIDING_WINDOW", "USE_V2_BLOCK_MANAGER", "NUM_LOOKAHEAD_SLOTS",
"SEED", "NUM_GPU_BLOCKS_OVERRIDE", "MAX_NUM_BATCHED_TOKENS", "MAX_NUM_SEQS",
"MAX_LOGPROBS", "DISABLE_LOG_STATS", "QUANTIZATION", "ROPE_SCALING", "ROPE_THETA",
"TOKENIZER_POOL_SIZE", "TOKENIZER_POOL_TYPE", "TOKENIZER_POOL_EXTRA_CONFIG",
"ENABLE_LORA", "MAX_LORAS", "MAX_LORA_RANK", "LORA_EXTRA_VOCAB_SIZE",
"LORA_DTYPE", "LONG_LORA_SCALING_FACTORS", "MAX_CPU_LORAS", "FULLY_SHARDED_LORAS",
"DEVICE", "SCHEDULER_DELAY_FACTOR", "ENABLE_CHUNKED_PREFILL", "SPECULATIVE_MODEL",
"NUM_SPECULATIVE_TOKENS", "SPECULATIVE_DRAFT_TENSOR_PARALLEL_SIZE",
"SPECULATIVE_MAX_MODEL_LEN", "SPECULATIVE_DISABLE_BY_BATCH_SIZE",
"NGRAM_PROMPT_LOOKUP_MAX", "NGRAM_PROMPT_LOOKUP_MIN", "SPEC_DECODING_ACCEPTANCE_METHOD",
"TYPICAL_ACCEPTANCE_SAMPLER_POSTERIOR_THRESHOLD", "TYPICAL_ACCEPTANCE_SAMPLER_POSTERIOR_ALPHA",
"MODEL_LOADER_EXTRA_CONFIG", "PREEMPTION_MODE", "PREEMPTION_CHECK_PERIOD",
"PREEMPTION_CPU_CAPACITY", "MAX_LOG_LEN", "DISABLE_LOGGING_REQUEST"
]
},
{
"title": "Tokenizer Settings",
"settings": [
"TOKENIZER_NAME", "TOKENIZER_REVISION", "CUSTOM_CHAT_TEMPLATE"
]
},
{
"title": "System Settings",
"settings": [
"GPU_MEMORY_UTILIZATION", "MAX_PARALLEL_LOADING_WORKERS", "BLOCK_SIZE",
"SWAP_SPACE", "ENFORCE_EAGER", "MAX_SEQ_LEN_TO_CAPTURE", "DISABLE_CUSTOM_ALL_REDUCE"
]
},
{
"title": "Streaming Settings",
"settings": [
"DEFAULT_BATCH_SIZE", "DEFAULT_MIN_BATCH_SIZE", "DEFAULT_BATCH_SIZE_GROWTH_FACTOR"
]
},
{
"title": "OpenAI Settings",
"settings": [
"RAW_OPENAI_OUTPUT", "OPENAI_RESPONSE_ROLE", "OPENAI_SERVED_MODEL_NAME_OVERRIDE"
]
},
{
"title": "Serverless Settings",
"settings": [
"MAX_CONCURRENCY", "DISABLE_LOG_STATS", "DISABLE_LOG_REQUESTS"
]
}
]
},
"0.4.2": {
"imageName": "runpod/worker-vllm:stable-cuda12.1.0",
"minimumCudaVersion": "12.1",
"categories": [
{
"title": "LLM Settings",
"settings": [
"MODEL_REVISION", "MAX_MODEL_LEN", "BASE_PATH", "LOAD_FORMAT", "QUANTIZATION",
"TRUST_REMOTE_CODE", "SEED", "KV_CACHE_DTYPE", "DTYPE"
]
},
{
"title": "Tokenizer Settings",
"settings": [
"TOKENIZER_NAME", "TOKENIZER_REVISION", "CUSTOM_CHAT_TEMPLATE"
]
},
{
"title": "System Settings",
"settings": [
"GPU_MEMORY_UTILIZATION", "MAX_PARALLEL_LOADING_WORKERS", "BLOCK_SIZE",
"SWAP_SPACE", "ENFORCE_EAGER", "MAX_SEQ_LEN_TO_CAPTURE", "DISABLE_CUSTOM_ALL_REDUCE"
]
},
{
"title": "Streaming Settings",
"settings": [
"DEFAULT_BATCH_SIZE", "DEFAULT_MIN_BATCH_SIZE", "DEFAULT_BATCH_SIZE_GROWTH_FACTOR"
]
},
{
"title": "OpenAI Settings",
"settings": [
"RAW_OPENAI_OUTPUT", "OPENAI_RESPONSE_ROLE", "OPENAI_SERVED_MODEL_NAME_OVERRIDE"
]
},
{
"title": "Serverless Settings",
"settings": [
"MAX_CONCURRENCY", "DISABLE_LOG_STATS", "DISABLE_LOG_REQUESTS"
]
}
]
}
},
"schema": {
"TOKENIZER": {
"env_var_name": "TOKENIZER",
"value": "",
"title": "Tokenizer",
"description": "Name or path of the Hugging Face tokenizer to use.",
"required": false,
"type": "text"
},
"TOKENIZER_MODE": {
"env_var_name": "TOKENIZER_MODE",
"value": "auto",
"title": "Tokenizer Mode",
"description": "The tokenizer mode.",
"required": false,
"type": "select",
"options": [
{ "value": "auto", "label": "auto" },
{ "value": "slow", "label": "slow" }
]
},
"SKIP_TOKENIZER_INIT": {
"env_var_name": "SKIP_TOKENIZER_INIT",
"value": false,
"title": "Skip Tokenizer Init",
"description": "Skip initialization of tokenizer and detokenizer.",
"required": false,
"type": "toggle"
},
"TRUST_REMOTE_CODE": {
"env_var_name": "TRUST_REMOTE_CODE",
"value": false,
"title": "Trust Remote Code",
"description": "Trust remote code from Hugging Face.",
"required": false,
"type": "toggle"
},
"DOWNLOAD_DIR": {
"env_var_name": "DOWNLOAD_DIR",
"value": "",
"title": "Download Directory",
"description": "Directory to download and load the weights.",
"required": false,
"type": "text"
},
"LOAD_FORMAT": {
"env_var_name": "LOAD_FORMAT",
"value": "auto",
"title": "Load Format",
"description": "The format of the model weights to load.",
"required": false,
"type": "select",
"options": [
{ "value": "auto", "label": "auto" },
{ "value": "pt", "label": "pt" },
{ "value": "safetensors", "label": "safetensors" },
{ "value": "npcache", "label": "npcache" },
{ "value": "dummy", "label": "dummy" },
{ "value": "tensorizer", "label": "tensorizer" },
{ "value": "bitsandbytes", "label": "bitsandbytes" }
]
},
"DTYPE": {
"env_var_name": "DTYPE",
"value": "auto",
"title": "Data Type",
"description": "Data type for model weights and activations.",
"required": false,
"type": "select",
"options": [
{ "value": "auto", "label": "auto" },
{ "value": "half", "label": "half" },
{ "value": "float16", "label": "float16" },
{ "value": "bfloat16", "label": "bfloat16" },
{ "value": "float", "label": "float" },
{ "value": "float32", "label": "float32" }
]
},
"KV_CACHE_DTYPE": {
"env_var_name": "KV_CACHE_DTYPE",
"value": "auto",
"title": "KV Cache Data Type",
"description": "Data type for KV cache storage.",
"required": false,
"type": "select",
"options": [
{ "value": "auto", "label": "auto" },
{ "value": "fp8", "label": "fp8" }
]
},
"QUANTIZATION_PARAM_PATH": {
"env_var_name": "QUANTIZATION_PARAM_PATH",
"value": "",
"title": "Quantization Param Path",
"description": "Path to the JSON file containing the KV cache scaling factors.",
"required": false,
"type": "text"
},
"MAX_MODEL_LEN": {
"env_var_name": "MAX_MODEL_LEN",
"value": "",
"title": "Max Model Length",
"description": "Model context length.",
"required": false,
"type": "number"
},
"GUIDED_DECODING_BACKEND": {
"env_var_name": "GUIDED_DECODING_BACKEND",
"value": "outlines",
"title": "Guided Decoding Backend",
"description": "Which engine will be used for guided decoding by default.",
"required": false,
"type": "select",
"options": [
{ "value": "outlines", "label": "outlines" },
{ "value": "lm-format-enforcer", "label": "lm-format-enforcer" }
]
},
"DISTRIBUTED_EXECUTOR_BACKEND": {
"env_var_name": "DISTRIBUTED_EXECUTOR_BACKEND",
"value": "",
"title": "Distributed Executor Backend",
"description": "Backend to use for distributed serving.",
"required": false,
"type": "select",
"options": [
{ "value": "ray", "label": "ray" },
{ "value": "mp", "label": "mp" }
]
},
"WORKER_USE_RAY": {
"env_var_name": "WORKER_USE_RAY",
"value": false,
"title": "Worker Use Ray",
"description": "Deprecated, use --distributed-executor-backend=ray.",
"required": false,
"type": "toggle"
},
"RAY_WORKERS_USE_NSIGHT": {
"env_var_name": "RAY_WORKERS_USE_NSIGHT",
"value": false,
"title": "Ray Workers Use Nsight",
"description": "If specified, use nsight to profile Ray workers.",
"required": false,
"type": "toggle"
},
"PIPELINE_PARALLEL_SIZE": {
"env_var_name": "PIPELINE_PARALLEL_SIZE",
"value": 1,
"title": "Pipeline Parallel Size",
"description": "Number of pipeline stages.",
"required": false,
"type": "number"
},
"TENSOR_PARALLEL_SIZE": {
"env_var_name": "TENSOR_PARALLEL_SIZE",
"value": 1,
"title": "Tensor Parallel Size",
"description": "Number of tensor parallel replicas.",
"required": false,
"type": "number"
},
"MAX_PARALLEL_LOADING_WORKERS": {
"env_var_name": "MAX_PARALLEL_LOADING_WORKERS",
"value": "",
"title": "Max Parallel Loading Workers",
"description": "Load model sequentially in multiple batches.",
"required": false,
"type": "number"
},
"ENABLE_PREFIX_CACHING": {
"env_var_name": "ENABLE_PREFIX_CACHING",
"value": false,
"title": "Enable Prefix Caching",
"description": "Enables automatic prefix caching.",
"required": false,
"type": "toggle"
},
"DISABLE_SLIDING_WINDOW": {
"env_var_name": "DISABLE_SLIDING_WINDOW",
"value": false,
"title": "Disable Sliding Window",
"description": "Disables sliding window, capping to sliding window size.",
"required": false,
"type": "toggle"
},
"USE_V2_BLOCK_MANAGER": {
"env_var_name": "USE_V2_BLOCK_MANAGER",
"value": false,
"title": "Use V2 Block Manager",
"description": "Use BlockSpaceMangerV2.",
"required": false,
"type": "toggle"
},
"NUM_LOOKAHEAD_SLOTS": {
"env_var_name": "NUM_LOOKAHEAD_SLOTS",
"value": 0,
"title": "Num Lookahead Slots",
"description": "Experimental scheduling config necessary for speculative decoding.",
"required": false,
"type": "number"
},
"SEED": {
"env_var_name": "SEED",
"value": 0,
"title": "Seed",
"description": "Random seed for operations.",
"required": false,
"type": "number"
},
"NUM_GPU_BLOCKS_OVERRIDE": {
"env_var_name": "NUM_GPU_BLOCKS_OVERRIDE",
"value": "",
"title": "Num GPU Blocks Override",
"description": "If specified, ignore GPU profiling result and use this number of GPU blocks.",
"required": false,
"type": "number"
},
"MAX_NUM_BATCHED_TOKENS": {
"env_var_name": "MAX_NUM_BATCHED_TOKENS",
"value": "",
"title": "Max Num Batched Tokens",
"description": "Maximum number of batched tokens per iteration.",
"required": false,
"type": "number"
},
"MAX_NUM_SEQS": {
"env_var_name": "MAX_NUM_SEQS",
"value": 256,
"title": "Max Num Seqs",
"description": "Maximum number of sequences per iteration.",
"required": false,
"type": "number"
},
"MAX_LOGPROBS": {
"env_var_name": "MAX_LOGPROBS",
"value": 20,
"title": "Max Logprobs",
"description": "Max number of log probs to return when logprobs is specified in SamplingParams.",
"required": false,
"type": "number"
},
"DISABLE_LOG_STATS": {
"env_var_name": "DISABLE_LOG_STATS",
"value": false,
"title": "Disable Log Stats",
"description": "Disable logging statistics.",
"required": false,
"type": "toggle"
},
"QUANTIZATION": {
"env_var_name": "QUANTIZATION",
"value": "",
"title": "Quantization",
"description": "Method used to quantize the weights.",
"required": false,
"type": "select",
"options": [
{ "value": "None", "label": "None" },
{ "value": "awq", "label": "AWQ" },
{ "value": "squeezellm", "label": "SqueezeLLM" },
{ "value": "gptq", "label": "GPTQ" }
]
},
"ROPE_SCALING": {
"env_var_name": "ROPE_SCALING",
"value": "",
"title": "RoPE Scaling",
"description": "RoPE scaling configuration in JSON format.",
"required": false,
"type": "text"
},
"ROPE_THETA": {
"env_var_name": "ROPE_THETA",
"value": "",
"title": "RoPE Theta",
"description": "RoPE theta. Use with rope_scaling.",
"required": false,
"type": "number"
},
"TOKENIZER_POOL_SIZE": {
"env_var_name": "TOKENIZER_POOL_SIZE",
"value": 0,
"title": "Tokenizer Pool Size",
"description": "Size of tokenizer pool to use for asynchronous tokenization.",
"required": false,
"type": "number"
},
"TOKENIZER_POOL_TYPE": {
"env_var_name": "TOKENIZER_POOL_TYPE",
"value": "ray",
"title": "Tokenizer Pool Type",
"description": "Type of tokenizer pool to use for asynchronous tokenization.",
"required": false,
"type": "text"
},
"TOKENIZER_POOL_EXTRA_CONFIG": {
"env_var_name": "TOKENIZER_POOL_EXTRA_CONFIG",
"value": "",
"title": "Tokenizer Pool Extra Config",
"description": "Extra config for tokenizer pool.",
"required": false,
"type": "text"
},
"ENABLE_LORA": {
"env_var_name": "ENABLE_LORA",
"value": false,
"title": "Enable LoRA",
"description": "If True, enable handling of LoRA adapters.",
"required": false,
"type": "toggle"
},
"MAX_LORAS": {
"env_var_name": "MAX_LORAS",
"value": 1,
"title": "Max LoRAs",
"description": "Max number of LoRAs in a single batch.",
"required": false,
"type": "number"
},
"MAX_LORA_RANK": {
"env_var_name": "MAX_LORA_RANK",
"value": 16,
"title": "Max LoRA Rank",
"description": "Max LoRA rank.",
"required": false,
"type": "number"
},
"LORA_EXTRA_VOCAB_SIZE": {
"env_var_name": "LORA_EXTRA_VOCAB_SIZE",
"value": 256,
"title": "LoRA Extra Vocab Size",
"description": "Maximum size of extra vocabulary for LoRA adapters.",
"required": false,
"type": "number"
},
"LORA_DTYPE": {
"env_var_name": "LORA_DTYPE",
"value": "auto",
"title": "LoRA Data Type",
"description": "Data type for LoRA.",
"required": false,
"type": "select",
"options": [
{ "value": "auto", "label": "auto" },
{ "value": "float16", "label": "float16" },
{ "value": "bfloat16", "label": "bfloat16" },
{ "value": "float32", "label": "float32" }
]
},
"LONG_LORA_SCALING_FACTORS": {
"env_var_name": "LONG_LORA_SCALING_FACTORS",
"value": "",
"title": "Long LoRA Scaling Factors",
"description": "Specify multiple scaling factors for LoRA adapters.",
"required": false,
"type": "text"
},
"MAX_CPU_LORAS": {
"env_var_name": "MAX_CPU_LORAS",
"value": "",
"title": "Max CPU LoRAs",
"description": "Maximum number of LoRAs to store in CPU memory.",
"required": false,
"type": "number"
},
"FULLY_SHARDED_LORAS": {
"env_var_name": "FULLY_SHARDED_LORAS",
"value": false,
"title": "Fully Sharded LoRAs",
"description": "Enable fully sharded LoRA layers.",
"required": false,
"type": "toggle"
},
"DEVICE": {
"env_var_name": "DEVICE",
"value": "auto",
"title": "Device",
"description": "Device type for vLLM execution.",
"required": false,
"type": "select",
"options": [
{ "value": "auto", "label": "auto" },
{ "value": "cuda", "label": "cuda" },
{ "value": "neuron", "label": "neuron" },
{ "value": "cpu", "label": "cpu" },
{ "value": "openvino", "label": "openvino" },
{ "value": "tpu", "label": "tpu" },
{ "value": "xpu", "label": "xpu" }
]
},
"SCHEDULER_DELAY_FACTOR": {
"env_var_name": "SCHEDULER_DELAY_FACTOR",
"value": 0.0,
"title": "Scheduler Delay Factor",
"description": "Apply a delay before scheduling next prompt.",
"required": false,
"type": "number"
},
"ENABLE_CHUNKED_PREFILL": {
"env_var_name": "ENABLE_CHUNKED_PREFILL",
"value": false,
"title": "Enable Chunked Prefill",
"description": "Enable chunked prefill requests.",
"required": false,
"type": "toggle"
},
"SPECULATIVE_MODEL": {
"env_var_name": "SPECULATIVE_MODEL",
"value": "",
"title": "Speculative Model",
"description": "The name of the draft model to be used in speculative decoding.",
"required": false,
"type": "text"
},
"NUM_SPECULATIVE_TOKENS": {
"env_var_name": "NUM_SPECULATIVE_TOKENS",
"value": "",
"title": "Num Speculative Tokens",
"description": "The number of speculative tokens to sample from the draft model.",
"required": false,
"type": "number"
},
"SPECULATIVE_DRAFT_TENSOR_PARALLEL_SIZE": {
"env_var_name": "SPECULATIVE_DRAFT_TENSOR_PARALLEL_SIZE",
"value": "",
"title": "Speculative Draft Tensor Parallel Size",
"description": "Number of tensor parallel replicas for the draft model.",
"required": false,
"type": "number"
},
"SPECULATIVE_MAX_MODEL_LEN": {
"env_var_name": "SPECULATIVE_MAX_MODEL_LEN",
"value": "",
"title": "Speculative Max Model Length",
"description": "The maximum sequence length supported by the draft model.",
"required": false,
"type": "number"
},
"SPECULATIVE_DISABLE_BY_BATCH_SIZE": {
"env_var_name": "SPECULATIVE_DISABLE_BY_BATCH_SIZE",
"value": "",
"title": "Speculative Disable by Batch Size",
"description": "Disable speculative decoding if the number of enqueue requests is larger than this value.",
"required": false,
"type": "number"
},
"NGRAM_PROMPT_LOOKUP_MAX": {
"env_var_name": "NGRAM_PROMPT_LOOKUP_MAX",
"value": "",
"title": "Ngram Prompt Lookup Max",
"description": "Max size of window for ngram prompt lookup in speculative decoding.",
"required": false,
"type": "number"
},
"NGRAM_PROMPT_LOOKUP_MIN": {
"env_var_name": "NGRAM_PROMPT_LOOKUP_MIN",
"value": "",
"title": "Ngram Prompt Lookup Min",
"description": "Min size of window for ngram prompt lookup in speculative decoding.",
"required": false,
"type": "number"
},
"SPEC_DECODING_ACCEPTANCE_METHOD": {
"env_var_name": "SPEC_DECODING_ACCEPTANCE_METHOD",
"value": "rejection_sampler",
"title": "Speculative Decoding Acceptance Method",
"description": "Specify the acceptance method for draft token verification in speculative decoding.",
"required": false,
"type": "select",
"options": [
{ "value": "rejection_sampler", "label": "rejection_sampler" },
{ "value": "typical_acceptance_sampler", "label": "typical_acceptance_sampler" }
]
},
"TYPICAL_ACCEPTANCE_SAMPLER_POSTERIOR_THRESHOLD": {
"env_var_name": "TYPICAL_ACCEPTANCE_SAMPLER_POSTERIOR_THRESHOLD",
"value": "",
"title": "Typical Acceptance Sampler Posterior Threshold",
"description": "Set the lower bound threshold for the posterior probability of a token to be accepted.",
"required": false,
"type": "number"
},
"TYPICAL_ACCEPTANCE_SAMPLER_POSTERIOR_ALPHA": {
"env_var_name": "TYPICAL_ACCEPTANCE_SAMPLER_POSTERIOR_ALPHA",
"value": "",
"title": "Typical Acceptance Sampler Posterior Alpha",
"description": "A scaling factor for the entropy-based threshold for token acceptance.",
"required": false,
"type": "number"
},
"MODEL_LOADER_EXTRA_CONFIG": {
"env_var_name": "MODEL_LOADER_EXTRA_CONFIG",
"value": "",
"title": "Model Loader Extra Config",
"description": "Extra config for model loader.",
"required": false,
"type": "text"
},
"PREEMPTION_MODE": {
"env_var_name": "PREEMPTION_MODE",
"value": "",
"title": "Preemption Mode",
"description": "If 'recompute', the engine performs preemption-aware recomputation. If 'save', the engine saves activations into the CPU memory as preemption happens.",
"required": false,
"type": "text"
},
"PREEMPTION_CHECK_PERIOD": {
"env_var_name": "PREEMPTION_CHECK_PERIOD",
"value": 1.0,
"title": "Preemption Check Period",
"description": "How frequently the engine checks if a preemption happens.",
"required": false,
"type": "number"
},
"PREEMPTION_CPU_CAPACITY": {
"env_var_name": "PREEMPTION_CPU_CAPACITY",
"value": 2,
"title": "Preemption CPU Capacity",
"description": "The percentage of CPU memory used for the saved activations.",
"required": false,
"type": "number"
},
"MAX_LOG_LEN": {
"env_var_name": "MAX_LOG_LEN",
"value": "",
"title": "Max Log Length",
"description": "Max number of characters or ID numbers being printed in log.",
"required": false,
"type": "number"
},
"DISABLE_LOGGING_REQUEST": {
"env_var_name": "DISABLE_LOGGING_REQUEST",
"value": false,
"title": "Disable Logging Request",
"description": "Disable logging requests.",
"required": false,
"type": "toggle"
},
"TOKENIZER_NAME": {
"env_var_name": "TOKENIZER_NAME",
"value": "",
"title": "Tokenizer Name",
"description": "Tokenizer repo to use a different tokenizer than the model's default",
"required": false,
"type": "text"
},
"TOKENIZER_REVISION": {
"env_var_name": "TOKENIZER_REVISION",
"value": "",
"title": "Tokenizer Revision",
"description": "Tokenizer revision to load",
"required": false,
"type": "text"
},
"CUSTOM_CHAT_TEMPLATE": {
"env_var_name": "CUSTOM_CHAT_TEMPLATE",
"value": "",
"title": "Custom Chat Template",
"description": "Custom chat jinja template",
"required": false,
"type": "text"
},
"GPU_MEMORY_UTILIZATION": {
"env_var_name": "GPU_MEMORY_UTILIZATION",
"value": "0.95",
"title": "GPU Memory Utilization",
"description": "Sets GPU VRAM utilization",
"required": false,
"type": "number"
},
"BLOCK_SIZE": {
"env_var_name": "BLOCK_SIZE",
"value": "16",
"title": "Block Size",
"description": "Token block size for contiguous chunks of tokens",
"required": false,
"type": "number"
},
"SWAP_SPACE": {
"env_var_name": "SWAP_SPACE",
"value": "4",
"title": "Swap Space",
"description": "CPU swap space size (GiB) per GPU",
"required": false,
"type": "number"
},
"ENFORCE_EAGER": {
"env_var_name": "ENFORCE_EAGER",
"value": false,
"title": "Enforce Eager",
"description": "Always use eager-mode PyTorch. If False (0), will use eager mode and CUDA graph in hybrid for maximal performance and flexibility",
"required": false,
"type": "toggle"
},
"MAX_SEQ_LEN_TO_CAPTURE": {
"env_var_name": "MAX_SEQ_LEN_TO_CAPTURE",
"value": "8192",
"title": "CUDA Graph Max Content Length",
"description": "Maximum context length covered by CUDA graphs. If a sequence has context length larger than this, we fall back to eager mode",
"required": false,
"type": "number"
},
"DISABLE_CUSTOM_ALL_REDUCE": {
"env_var_name": "DISABLE_CUSTOM_ALL_REDUCE",
"value": false,
"title": "Disable Custom All Reduce",
"description": "Enables or disables custom all reduce",
"required": false,
"type": "toggle"
},
"DEFAULT_BATCH_SIZE": {
"env_var_name": "DEFAULT_BATCH_SIZE",
"value": "50",
"title": "Default Final Batch Size",
"description": "Default and Maximum batch size for token streaming to reduce HTTP calls",
"required": false,
"type": "number"
},
"DEFAULT_MIN_BATCH_SIZE": {
"env_var_name": "DEFAULT_MIN_BATCH_SIZE",
"value": "1",
"title": "Default Starting Batch Size",
"description": "Batch size for the first request, which will be multiplied by the growth factor every subsequent request",
"required": false,
"type": "number"
},
"DEFAULT_BATCH_SIZE_GROWTH_FACTOR": {
"env_var_name": "DEFAULT_BATCH_SIZE_GROWTH_FACTOR",
"value": "3",
"title": "Default Batch Size Growth Factor",
"description": "Growth factor for dynamic batch size",
"required": false,
"type": "number"
},
"RAW_OPENAI_OUTPUT": {
"env_var_name": "RAW_OPENAI_OUTPUT",
"value": true,
"title": "Raw OpenAI Output",
"description": "Raw OpenAI output instead of just the text",
"required": false,
"type": "toggle"
},
"OPENAI_RESPONSE_ROLE": {
"env_var_name": "OPENAI_RESPONSE_ROLE",
"value": "assistant",
"title": "OpenAI Response Role",
"description": "Role of the LLM's Response in OpenAI Chat Completions",
"required": false,
"type": "text"
},
"OPENAI_SERVED_MODEL_NAME_OVERRIDE": {
"env_var_name": "OPENAI_SERVED_MODEL_NAME_OVERRIDE",
"value": "",
"title": "OpenAI Served Model Name Override",
"description": "Overrides the name of the served model from model repo/path to specified name, which you will then be able to use the value for the `model` parameter when making OpenAI requests",
"required": false,
"type": "text"
},
"MAX_CONCURRENCY": {
"env_var_name": "MAX_CONCURRENCY",
"value": "300",
"title": "Max Concurrency",
"description": "Max concurrent requests per worker. vLLM has an internal queue, so you don't have to worry about limiting by VRAM, this is for improving scaling/load balancing efficiency",
"required": false,
"type": "number"
},
"MODEL_REVISION": {
"env_var_name": "MODEL_REVISION",
"value": "",
"title": "Model Revision",
"description": "Model revision (branch) to load",
"required": false,
"type": "text"
},
"BASE_PATH": {
"env_var_name": "BASE_PATH",
"value": "/runpod-volume",
"title": "Base Path",
"description": "Storage directory for Huggingface cache and model",
"required": false,
"type": "text"
},
"DISABLE_LOG_REQUESTS": {
"env_var_name": "DISABLE_LOG_REQUESTS",
"value": true,
"title": "Disable Log Requests",
"description": "Enables or disables vLLM request logging",
"required": false,
"type": "toggle"
}
}
}