Compare commits
4 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 63550d5af3 | |||
| 7ec0e11938 | |||
| 191fbbfe18 | |||
| 9a4a39c71b |
+2
-2
@@ -30,7 +30,7 @@ from lib.data_types import (
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BenchmarkResult
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)
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VERSION = "0.2.1"
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VERSION = "0.2.0"
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MSG_HISTORY_LEN = 100
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log = logging.getLogger(__file__)
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@@ -431,4 +431,4 @@ class Backend:
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if os.path.isfile(self.model_log_file) is True:
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return await tail_log()
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else:
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await sleep(1)
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await asyncio.sleep(1)
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+25
-45
@@ -3,58 +3,38 @@ import logging
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from typing import List
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import ssl
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from asyncio import run, gather
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import asyncio
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from lib.backend import Backend
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from lib.metrics import Metrics
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from aiohttp import web
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log = logging.getLogger(__file__)
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def start_server(backend: Backend, routes: List[web.RouteDef], **kwargs):
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try:
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log.debug("getting certificate...")
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use_ssl = os.environ.get("USE_SSL", "false") == "true"
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if use_ssl is True:
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ssl_context = ssl.create_default_context(ssl.Purpose.CLIENT_AUTH)
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ssl_context.load_cert_chain(
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certfile="/etc/instance.crt",
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keyfile="/etc/instance.key",
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)
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else:
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ssl_context = None
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log.debug("getting certificate...")
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use_ssl = os.environ.get("USE_SSL", "false") == "true"
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if use_ssl is True:
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ssl_context = ssl.create_default_context(ssl.Purpose.CLIENT_AUTH)
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ssl_context.load_cert_chain(
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certfile="/etc/instance.crt",
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keyfile="/etc/instance.key",
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)
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else:
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ssl_context = None
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async def main():
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log.debug("starting server...")
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app = web.Application()
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app.add_routes(routes)
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runner = web.AppRunner(app)
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await runner.setup()
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site = web.TCPSite(
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runner,
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ssl_context=ssl_context,
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port=int(os.environ["WORKER_PORT"]),
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**kwargs
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)
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await gather(site.start(), backend._start_tracking())
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async def main():
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log.debug("starting server...")
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app = web.Application()
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app.add_routes(routes)
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runner = web.AppRunner(app)
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await runner.setup()
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site = web.TCPSite(
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runner,
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ssl_context=ssl_context,
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port=int(os.environ["WORKER_PORT"]),
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**kwargs
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)
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await gather(site.start(), backend._start_tracking())
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run(main())
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except Exception as e:
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err_msg = f"PyWorker failed to launch: {e}"
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log.error(err_msg)
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async def beacon():
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metrics = Metrics()
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metrics._set_version(getattr(backend, "version", "0"))
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metrics._set_mtoken(getattr(backend, "mtoken", ""))
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try:
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while True:
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metrics._model_errored(err_msg)
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await metrics._Metrics__send_metrics_and_reset()
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await asyncio.sleep(10)
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finally:
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await metrics.aclose()
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run(beacon())
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run(main())
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+2
-48
@@ -41,14 +41,6 @@ echo_var DEBUG_LOG
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echo_var PYWORKER_LOG
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echo_var MODEL_LOG
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# if instance is rebooted, we want to clear out the log file so pyworker doesn't read lines
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# from the run prior to reboot. past logs are saved in $MODEL_LOG.old for debugging only
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if [ -e "$MODEL_LOG" ]; then
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echo "Rotating model log at $MODEL_LOG to $MODEL_LOG.old"
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cat "$MODEL_LOG" >> "$MODEL_LOG.old"
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: > "$MODEL_LOG"
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fi
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# Populate /etc/environment with quoted values
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if ! grep -q "VAST" /etc/environment; then
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env -0 | grep -zEv "^(HOME=|SHLVL=)|CONDA" | while IFS= read -r -d '' line; do
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@@ -132,43 +124,5 @@ cd "$SERVER_DIR"
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echo "launching PyWorker server"
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set +e
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python3 -m "workers.$BACKEND.server" |& tee -a "$PYWORKER_LOG"
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PY_STATUS=${PIPESTATUS[0]}
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set -e
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if [ "${PY_STATUS}" -ne 0 ]; then
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echo "PyWorker exited with status ${PY_STATUS}; notifying autoscaler..."
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ERROR_MSG="PyWorker exited: code ${PY_STATUS}"
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MTOKEN="${MASTER_TOKEN:-}"
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VERSION="${PYWORKER_VERSION:-0}"
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IFS=',' read -r -a REPORT_ADDRS <<< "${REPORT_ADDR}"
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for addr in "${REPORT_ADDRS[@]}"; do
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curl -sS -X POST -H 'Content-Type: application/json' \
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-d "$(cat <<JSON
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{
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"id": ${CONTAINER_ID:-0},
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"mtoken": "${MTOKEN}",
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"version": "${VERSION}",
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"loadtime": 0,
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"new_load": 0,
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"cur_load": 0,
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"rej_load": 0,
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"max_perf": 0,
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"cur_perf": 0,
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"error_msg": "${ERROR_MSG}",
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"num_requests_working": 0,
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"num_requests_recieved": 0,
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"additional_disk_usage": 0,
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"working_request_idxs": [],
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"cur_capacity": 0,
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"max_capacity": 0,
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"url": "${URL}"
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}
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JSON
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)" "${addr%/}/worker_status/" || true
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done
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fi
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echo "launching PyWorker server done"
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(python3 -m "workers.$BACKEND.server" |& tee -a "$PYWORKER_LOG") &
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echo "launching PyWorker server done"
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+19
-27
@@ -34,30 +34,12 @@ uv pip install -r requirements.txt
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Several examples have been provided in the client to help you get started with your own implementation.
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First, set your API key as an environment variable:
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### Completions
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Call to `/v1/completions` with json response
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```bash
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export VAST_API_KEY=<your_api_key>
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```
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The `--model` and `--endpoint` flags are optional. If not provided, they default to `Qwen/Qwen3-8B` and `my-vllm-endpoint` respectively.
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### Chat Completion (streaming)
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Call to `/v1/chat/completions` with streaming response
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```bash
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python -m workers.openai.client --chat-stream --endpoint <ENDPOINT_NAME> --model <MODEL_NAME>
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```
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### Interactive Chat (streaming)
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Interactive session with calls to `/v1/chat/completions`.
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Type `clear` to clear the chat history or `quit` to exit.
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```bash
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python -m workers.openai.client --interactive --endpoint <ENDPOINT_NAME> --model <MODEL_NAME>
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python -m workers.openai.client -k <API_KEY> -e <ENDPOINT_NAME> --completion --model <MODEL_NAME>
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```
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### Chat Completion (json)
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@@ -65,7 +47,15 @@ python -m workers.openai.client --interactive --endpoint <ENDPOINT_NAME> --model
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Call to `/v1/chat/completions` with json response
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```bash
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python -m workers.openai.client --chat --endpoint <ENDPOINT_NAME> --model <MODEL_NAME>
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python -m workers.openai.client -k <API_KEY> -e <ENDPOINT_NAME> --chat --model <MODEL_NAME>
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```
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### Chat Completion (streaming)
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Call to `/v1/chat/completions` with streaming response
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```bash
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python -m workers.openai.client -k <API_KEY> -e <ENDPOINT_NAME> --chat-stream --model <MODEL_NAME>
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```
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### Tool Use (json)
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@@ -75,14 +65,16 @@ Call to `/v1/chat/completions` with tool and json response.
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This test defines a simple tool which will list the contents of the local pyworker directory. The output is then analysed by the model.
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```bash
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python -m workers.openai.client --tools --endpoint <ENDPOINT_NAME> --model <MODEL_NAME>
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python -m workers.openai.client -k <API_KEY> -e <ENDPOINT_NAME> --tools --model <MODEL_NAME>
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```
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### Completions
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### Interactive Chat (streaming)
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Call to `/v1/completions` with json response
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Interactive session with calls to `/v1/chat/completions`.
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Type `clear` to clear the chat history or `quit` to exit.
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```bash
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python -m workers.openai.client --completion --endpoint <ENDPOINT_NAME> --model <MODEL_NAME>
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python -m workers.openai.client -k <API_KEY> -e <ENDPOINT_NAME> --interactive --model <MODEL_NAME>
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```
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+16
-32
@@ -18,7 +18,7 @@ logging.basicConfig(
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log = logging.getLogger(__file__)
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# ---------------------- Prompts ----------------------
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COMPLETIONS_PROMPT = "Zebras are primarily grazers and can subsist on lower-quality vegetation. They are preyed on mainly by"
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COMPLETIONS_PROMPT = "the capital of USA is"
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CHAT_PROMPT = "Think step by step: Tell me about the Python programming language."
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TOOLS_PROMPT = (
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"Can you list the files in the current working directory and tell me what you see? "
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@@ -97,9 +97,9 @@ def _tool_state_to_message_tool_calls(state: Dict[int, Dict[str, Any]]) -> List[
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# ---- OpenAI-compatible calls (non-streaming) ----
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async def call_completions(client: Serverless, *, model: str, prompt: str, endpoint_name: str, **kwargs) -> Dict[str, Any]:
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async def call_completions(client: Serverless, *, model: str, prompt: str, **kwargs) -> Dict[str, Any]:
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endpoint = await client.get_endpoint(name=endpoint_name)
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endpoint = await client.get_endpoint(name=ENDPOINT_NAME)
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payload = {
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"input": {
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@@ -113,9 +113,9 @@ async def call_completions(client: Serverless, *, model: str, prompt: str, endpo
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resp = await endpoint.request("/v1/completions", payload, cost=payload["input"]["max_tokens"])
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return resp["response"]
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async def call_chat_completions(client: Serverless, *, model: str, messages: List[Dict[str, Any]], endpoint_name: str, **kwargs) -> Dict[str, Any]:
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async def call_chat_completions(client: Serverless, *, model: str, messages: List[Dict[str, Any]], **kwargs) -> Dict[str, Any]:
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endpoint = await client.get_endpoint(name=endpoint_name)
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endpoint = await client.get_endpoint(name=ENDPOINT_NAME)
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payload = {
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"input": {
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@@ -132,9 +132,9 @@ async def call_chat_completions(client: Serverless, *, model: str, messages: Lis
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return resp["response"]
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# ---- Streaming variants ----
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async def stream_completions(client: Serverless, *, model: str, prompt: str, endpoint_name: str, **kwargs):
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async def stream_completions(client: Serverless, *, model: str, prompt: str, **kwargs):
|
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endpoint = await client.get_endpoint(name=endpoint_name)
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endpoint = await client.get_endpoint(name=ENDPOINT_NAME)
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||||
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||||
payload = {
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"input": {
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@@ -150,9 +150,9 @@ async def stream_completions(client: Serverless, *, model: str, prompt: str, end
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resp = await endpoint.request("/v1/completions", payload, cost=payload["input"]["max_tokens"], stream=True)
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return resp["response"] # async generator
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||||
|
||||
async def stream_chat_completions(client: Serverless, *, model: str, messages: List[Dict[str, Any]], endpoint_name: str, **kwargs):
|
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async def stream_chat_completions(client: Serverless, *, model: str, messages: List[Dict[str, Any]], **kwargs):
|
||||
|
||||
endpoint = await client.get_endpoint(name=endpoint_name)
|
||||
endpoint = await client.get_endpoint(name=ENDPOINT_NAME)
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||||
|
||||
payload = {
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||||
"input": {
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||||
@@ -174,10 +174,9 @@ async def stream_chat_completions(client: Serverless, *, model: str, messages: L
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class APIDemo:
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"""Demo and testing functionality for the API client"""
|
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|
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def __init__(self, client: Serverless, model: str, endpoint_name: str, tool_manager: Optional[ToolManager] = None):
|
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def __init__(self, client: Serverless, model: str, tool_manager: Optional[ToolManager] = None):
|
||||
self.client = client
|
||||
self.model = model
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||||
self.endpoint_name = endpoint_name
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||||
self.tool_manager = tool_manager or ToolManager()
|
||||
|
||||
# ----- Streaming handler -----
|
||||
@@ -186,15 +185,10 @@ class APIDemo:
|
||||
reasoning_content = ""
|
||||
printed_reasoning = False
|
||||
printed_answer = False
|
||||
finish_reason = None
|
||||
|
||||
async for chunk in stream:
|
||||
choice = (chunk.get("choices") or [{}])[0]
|
||||
delta = choice.get("delta", {})
|
||||
|
||||
# Track finish reason
|
||||
if choice.get("finish_reason"):
|
||||
finish_reason = choice.get("finish_reason")
|
||||
|
||||
# reasoning tokens
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||||
rc = delta.get("reasoning_content")
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||||
@@ -225,8 +219,6 @@ class APIDemo:
|
||||
print(f"Reasoning tokens: {len(reasoning_content.split())}")
|
||||
if printed_answer:
|
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print(f"Response tokens: {len(full_response.split())}")
|
||||
if finish_reason:
|
||||
print(f"Finish reason: {finish_reason}")
|
||||
|
||||
return full_response
|
||||
|
||||
@@ -239,7 +231,6 @@ class APIDemo:
|
||||
client=self.client,
|
||||
model=self.model,
|
||||
prompt=COMPLETIONS_PROMPT,
|
||||
endpoint_name=self.endpoint_name,
|
||||
max_tokens=MAX_TOKENS,
|
||||
temperature=DEFAULT_TEMPERATURE,
|
||||
)
|
||||
@@ -258,7 +249,6 @@ class APIDemo:
|
||||
client=self.client,
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
endpoint_name=self.endpoint_name,
|
||||
max_tokens=MAX_TOKENS,
|
||||
temperature=DEFAULT_TEMPERATURE
|
||||
)
|
||||
@@ -271,7 +261,6 @@ class APIDemo:
|
||||
client=self.client,
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
endpoint_name=self.endpoint_name,
|
||||
max_tokens=MAX_TOKENS,
|
||||
temperature=DEFAULT_TEMPERATURE
|
||||
)
|
||||
@@ -298,7 +287,6 @@ class APIDemo:
|
||||
client=self.client,
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
endpoint_name=self.endpoint_name,
|
||||
tools=minimal_tool,
|
||||
tool_choice="none",
|
||||
max_tokens=10
|
||||
@@ -324,7 +312,6 @@ class APIDemo:
|
||||
client=self.client,
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
endpoint_name=self.endpoint_name,
|
||||
tools=self.tool_manager.get_ls_tool_definition(),
|
||||
tool_choice="auto",
|
||||
max_tokens=MAX_TOKENS,
|
||||
@@ -402,7 +389,6 @@ class APIDemo:
|
||||
client=self.client,
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
endpoint_name=self.endpoint_name,
|
||||
max_tokens=MAX_TOKENS,
|
||||
temperature=DEFAULT_TEMPERATURE,
|
||||
)
|
||||
@@ -441,6 +427,7 @@ class APIDemo:
|
||||
print("=" * 60)
|
||||
print("INTERACTIVE STREAMING CHAT")
|
||||
print("=" * 60)
|
||||
print(f"Using model: {self.model}")
|
||||
print("Type 'quit' to exit, 'clear' to clear history")
|
||||
print()
|
||||
|
||||
@@ -466,8 +453,7 @@ class APIDemo:
|
||||
stream = await stream_chat_completions(
|
||||
client=self.client,
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
endpoint_name=self.endpoint_name,
|
||||
messages=messages,
|
||||
max_tokens=MAX_TOKENS,
|
||||
temperature=0.7
|
||||
)
|
||||
@@ -487,8 +473,8 @@ class APIDemo:
|
||||
# ---------------------- CLI ----------------------
|
||||
def build_arg_parser() -> argparse.ArgumentParser:
|
||||
p = argparse.ArgumentParser(description="Vast vLLM Demo (Serverless SDK)")
|
||||
p.add_argument("--model", default=DEFAULT_MODEL, help=f"Model to use for requests (default: {DEFAULT_MODEL})")
|
||||
p.add_argument("--endpoint", default=ENDPOINT_NAME, help=f"Vast endpoint name (default: {ENDPOINT_NAME})")
|
||||
p.add_argument("--model", required=True, help="Model to use for requests (required)")
|
||||
p.add_argument("--endpoint", default="my-vllm-endpoint", help="Vast endpoint name (default: my-vllm-endpoint)")
|
||||
|
||||
modes = p.add_mutually_exclusive_group(required=False)
|
||||
modes.add_argument("--completion", action="store_true", help="Test completions endpoint")
|
||||
@@ -516,14 +502,12 @@ async def main_async():
|
||||
print("Please specify exactly one test mode")
|
||||
sys.exit(1)
|
||||
|
||||
print("=" * 60)
|
||||
print(f"Using model: {args.model}")
|
||||
print(f"Using endpoint: {args.endpoint}")
|
||||
|
||||
print("=" * 60)
|
||||
|
||||
try:
|
||||
async with Serverless() as client:
|
||||
demo = APIDemo(client, args.model, args.endpoint, ToolManager())
|
||||
demo = APIDemo(client, args.model, ToolManager())
|
||||
|
||||
if args.completion:
|
||||
await demo.demo_completions()
|
||||
|
||||
@@ -11,7 +11,6 @@ MODEL_SERVER_START_LOG_MSG = [
|
||||
"llama runner started", # Ollama
|
||||
'"message":"Connected","target":"text_generation_router"', # TGI
|
||||
'"message":"Connected","target":"text_generation_router::server"', # TGI
|
||||
"main: model loaded" # llama.cpp
|
||||
]
|
||||
|
||||
MODEL_SERVER_ERROR_LOG_MSGS = [
|
||||
|
||||
Reference in New Issue
Block a user