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Commit 4d3a2c28 authored by zhuwenwen's avatar zhuwenwen
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Merge tag 'v0.6.5' into v0.6.5-dev

parents 92ec5d8e 2d1b9baa
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Showing with 1300 additions and 204 deletions
examples/openai_chat_embedding_client_for_multimodal.py 0 → 100644
View file @ 4d3a2c28
import argparse
import base64
import io
import requests
from PIL import Image
image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
def vlm2vec():
response = requests.post(
"http://localhost:8000/v1/embeddings",
json={
"model":
"TIGER-Lab/VLM2Vec-Full",
"messages": [{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "Represent the given image."
},
],
}],
"encoding_format":
"float",
},
)
response.raise_for_status()
response_json = response.json()
print("Embedding output:", response_json["data"][0]["embedding"])
def dse_qwen2_vl(inp: dict):
# Embedding an Image
if inp["dtype"] == "image":
messages = [{
"role":
"user",
"content": [{
"type": "image_url",
"image_url": {
"url": inp["image_url"],
}
}, {
"type": "text",
"text": "What is shown in this image?"
}]
}]
# Embedding a Text Query
else:
# MrLight/dse-qwen2-2b-mrl-v1 requires a placeholder image
# of the minimum input size
buffer = io.BytesIO()
image_placeholder = Image.new("RGB", (56, 56))
image_placeholder.save(buffer, "png")
buffer.seek(0)
image_placeholder = base64.b64encode(buffer.read()).decode('utf-8')
messages = [{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{image_placeholder}",
}
},
{
"type": "text",
"text": f"Query: {inp['content']}"
},
]
}]
response = requests.post(
"http://localhost:8000/v1/embeddings",
json={
"model": "MrLight/dse-qwen2-2b-mrl-v1",
"messages": messages,
"encoding_format": "float",
},
)
response.raise_for_status()
response_json = response.json()
print("Embedding output:", response_json["data"][0]["embedding"])
if __name__ == '__main__':
parser = argparse.ArgumentParser(
"Script to call a specified VLM through the API. Make sure to serve "
"the model with --task embed before running this.")
parser.add_argument("model",
type=str,
choices=["vlm2vec", "dse_qwen2_vl"],
required=True,
help="Which model to call.")
args = parser.parse_args()
if args.model == "vlm2vec":
vlm2vec()
elif args.model == "dse_qwen2_vl":
dse_qwen2_vl({
"dtye": "image",
"image_url": image_url,
})
dse_qwen2_vl({
"dtype": "text",
"content": "What is the weather like today?",
})
examples/openai_cross_encoder_score.py 0 → 100644
View file @ 4d3a2c28
"""
Example online usage of Score API.
Run `vllm serve <model> --task score` to start up the server in vLLM.
"""
import argparse
import pprint
import requests
def post_http_request(prompt: dict, api_url: str) -> requests.Response:
headers = {"User-Agent": "Test Client"}
response = requests.post(api_url, headers=headers, json=prompt)
return response
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--host", type=str, default="localhost")
parser.add_argument("--port", type=int, default=8000)
parser.add_argument("--model", type=str, default="BAAI/bge-reranker-v2-m3")
args = parser.parse_args()
api_url = f"http://{args.host}:{args.port}/score"
model_name = args.model
text_1 = "What is the capital of Brazil?"
text_2 = "The capital of Brazil is Brasilia."
prompt = {"model": model_name, "text_1": text_1, "text_2": text_2}
score_response = post_http_request(prompt=prompt, api_url=api_url)
print("Prompt when text_1 and text_2 are both strings:")
pprint.pprint(prompt)
print("Score Response:")
pprint.pprint(score_response.json())
text_1 = "What is the capital of France?"
text_2 = [
"The capital of Brazil is Brasilia.", "The capital of France is Paris."
]
prompt = {"model": model_name, "text_1": text_1, "text_2": text_2}
score_response = post_http_request(prompt=prompt, api_url=api_url)
print("Prompt when text_1 is string and text_2 is a list:")
pprint.pprint(prompt)
print("Score Response:")
pprint.pprint(score_response.json())
text_1 = [
"What is the capital of Brazil?", "What is the capital of France?"
]
text_2 = [
"The capital of Brazil is Brasilia.", "The capital of France is Paris."
]
prompt = {"model": model_name, "text_1": text_1, "text_2": text_2}
score_response = post_http_request(prompt=prompt, api_url=api_url)
print("Prompt when text_1 and text_2 are both lists:")
pprint.pprint(prompt)
print("Score Response:")
pprint.pprint(score_response.json())
examples/openai_example_batch.jsonl
View file @ 4d3a2c28
{"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "meta-llama/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are a helpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}
{"custom_id": "request-2", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "meta-llama/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are an unhelpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}
{"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "meta-llama/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are a helpful assistant."},{"role": "user", "content": "Hello world!"}],"max_completion_tokens": 1000}}
{"custom_id": "request-2", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "meta-llama/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are an unhelpful assistant."},{"role": "user", "content": "Hello world!"}],"max_completion_tokens": 1000}}
examples/openai_vision_api_client.py deleted 100644 → 0
View file @ 92ec5d8e
"""An example showing how to use vLLM to serve VLMs.
Launch the vLLM server with the following command:
(single image inference with Llava)
vllm serve llava-hf/llava-1.5-7b-hf --chat-template template_llava.jinja
(multi-image inference with Phi-3.5-vision-instruct)
vllm serve microsoft/Phi-3.5-vision-instruct --max-model-len 4096 \
--trust-remote-code --limit-mm-per-prompt image=2
"""
import base64
import requests
from openai import OpenAI
# Modify OpenAI's API key and API base to use vLLM's API server.
openai_api_key = "EMPTY"
openai_api_base = "http://localhost:8000/v1"
client = OpenAI(
# defaults to os.environ.get("OPENAI_API_KEY")
api_key=openai_api_key,
base_url=openai_api_base,
)
models = client.models.list()
model = models.data[0].id
# Single-image input inference
image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
## Use image url in the payload
chat_completion_from_url = client.chat.completions.create(
messages=[{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's in this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
},
],
}],
model=model,
max_tokens=64,
)
result = chat_completion_from_url.choices[0].message.content
print("Chat completion output:", result)
## Use base64 encoded image in the payload
def encode_image_base64_from_url(image_url: str) -> str:
"""Encode an image retrieved from a remote url to base64 format."""
with requests.get(image_url) as response:
response.raise_for_status()
result = base64.b64encode(response.content).decode('utf-8')
return result
image_base64 = encode_image_base64_from_url(image_url=image_url)
chat_completion_from_base64 = client.chat.completions.create(
messages=[{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's in this image?"
},
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{image_base64}"
},
},
],
}],
model=model,
max_tokens=64,
)
result = chat_completion_from_base64.choices[0].message.content
print(f"Chat completion output:{result}")
# Multi-image input inference
image_url_duck = "https://upload.wikimedia.org/wikipedia/commons/d/da/2015_Kaczka_krzy%C5%BCowka_w_wodzie_%28samiec%29.jpg"
image_url_lion = "https://upload.wikimedia.org/wikipedia/commons/7/77/002_The_lion_king_Snyggve_in_the_Serengeti_National_Park_Photo_by_Giles_Laurent.jpg"
chat_completion_from_url = client.chat.completions.create(
messages=[{
"role":
"user",
"content": [
{
"type": "text",
"text": "What are the animals in these images?"
},
{
"type": "image_url",
"image_url": {
"url": image_url_duck
},
},
{
"type": "image_url",
"image_url": {
"url": image_url_lion
},
},
],
}],
model=model,
max_tokens=64,
)
result = chat_completion_from_url.choices[0].message.content
print("Chat completion output:", result)
examples/production_monitoring/grafana.json
View file @ 4d3a2c28
{
"__inputs": [
],
"__elements": {},
"__requires": [
{
"type": "grafana",
"id": "grafana",
"name": "Grafana",
"version": "10.4.2"
},
{
"type": "panel",
"id": "heatmap",
"name": "Heatmap",
"version": ""
},
{
"type": "datasource",
"id": "prometheus",
"name": "Prometheus",
"version": "1.0.0"
},
{
"type": "panel",
"id": "timeseries",
"name": "Time series",
"version": ""
}
],
"annotations": {
"list": [
{
......@@ -54,7 +25,7 @@
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 0,
"id": null,
"id": 1,
"links": [],
"liveNow": false,
"panels": [
......@@ -76,6 +47,7 @@
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
......@@ -241,6 +213,7 @@
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
......@@ -358,6 +331,7 @@
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
......@@ -523,6 +497,7 @@
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
......@@ -658,6 +633,7 @@
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
......@@ -823,6 +799,7 @@
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
......@@ -984,7 +961,7 @@
"unit": "none"
}
},
"pluginVersion": "10.4.2",
"pluginVersion": "11.2.0",
"targets": [
{
"datasource": {
......@@ -1076,7 +1053,7 @@
"unit": "none"
}
},
"pluginVersion": "10.4.2",
"pluginVersion": "11.2.0",
"targets": [
{
"datasource": {
......@@ -1117,6 +1094,7 @@
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
......@@ -1147,8 +1125,7 @@
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
"color": "green"
},
{
"color": "red",
......@@ -1199,6 +1176,319 @@
],
"title": "Finish Reason",
"type": "timeseries"
},
{
"datasource": {
"default": false,
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisBorderShow": false,
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "seconds",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
"hideFrom": {
"legend": false,
"tooltip": false,
"viz": false
},
"insertNulls": false,
"lineInterpolation": "linear",
"lineWidth": 1,
"pointSize": 5,
"scaleDistribution": {
"type": "linear"
},
"showPoints": "auto",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green"
},
{
"color": "red",
"value": 80
}
]
}
},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 32
},
"id": 14,
"options": {
"legend": {
"calcs": [],
"displayMode": "list",
"placement": "bottom",
"showLegend": true
},
"tooltip": {
"mode": "single",
"sort": "none"
}
},
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "edx8memhpd9tsa"
},
"disableTextWrap": false,
"editorMode": "code",
"expr": "rate(vllm:request_queue_time_seconds_sum{model_name=\"$model_name\"}[$__rate_interval])",
"fullMetaSearch": false,
"includeNullMetadata": true,
"instant": false,
"legendFormat": "__auto",
"range": true,
"refId": "A",
"useBackend": false
}
],
"title": "Queue Time",
"type": "timeseries"
},
{
"datasource": {
"default": false,
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisBorderShow": false,
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
"hideFrom": {
"legend": false,
"tooltip": false,
"viz": false
},
"insertNulls": false,
"lineInterpolation": "linear",
"lineWidth": 1,
"pointSize": 5,
"scaleDistribution": {
"type": "linear"
},
"showPoints": "auto",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green"
},
{
"color": "red",
"value": 80
}
]
}
},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 40
},
"id": 15,
"options": {
"legend": {
"calcs": [],
"displayMode": "list",
"placement": "bottom",
"showLegend": true
},
"tooltip": {
"mode": "single",
"sort": "none"
}
},
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "edx8memhpd9tsa"
},
"disableTextWrap": false,
"editorMode": "code",
"expr": "rate(vllm:request_prefill_time_seconds_sum{model_name=\"$model_name\"}[$__rate_interval])",
"fullMetaSearch": false,
"includeNullMetadata": true,
"instant": false,
"legendFormat": "Prefill",
"range": true,
"refId": "A",
"useBackend": false
},
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"editorMode": "code",
"expr": "rate(vllm:request_decode_time_seconds_sum{model_name=\"$model_name\"}[$__rate_interval])",
"hide": false,
"instant": false,
"legendFormat": "Decode",
"range": true,
"refId": "B"
}
],
"title": "Requests Prefill and Decode Time",
"type": "timeseries"
},
{
"datasource": {
"default": false,
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisBorderShow": false,
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"barWidthFactor": 0.6,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
"hideFrom": {
"legend": false,
"tooltip": false,
"viz": false
},
"insertNulls": false,
"lineInterpolation": "linear",
"lineWidth": 1,
"pointSize": 5,
"scaleDistribution": {
"type": "linear"
},
"showPoints": "auto",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green"
},
{
"color": "red",
"value": 80
}
]
}
},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 40
},
"id": 16,
"options": {
"legend": {
"calcs": [],
"displayMode": "list",
"placement": "bottom",
"showLegend": true
},
"tooltip": {
"mode": "single",
"sort": "none"
}
},
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "edx8memhpd9tsa"
},
"disableTextWrap": false,
"editorMode": "code",
"expr": "rate(vllm:request_max_num_generation_tokens_sum{model_name=\"$model_name\"}[$__rate_interval])",
"fullMetaSearch": false,
"includeNullMetadata": true,
"instant": false,
"legendFormat": "Tokens",
"range": true,
"refId": "A",
"useBackend": false
}
],
"title": "Max Generation Token in Sequence Group",
"type": "timeseries"
}
],
"refresh": "",
......@@ -1207,21 +1497,34 @@
"templating": {
"list": [
{
"type": "datasource",
"name": "DS_PROMETHEUS",
"label": "datasource",
"current": {},
"current": {
"selected": false,
"text": "prometheus",
"value": "edx8memhpd9tsa"
},
"hide": 0,
"includeAll": false,
"label": "datasource",
"multi": false,
"name": "DS_PROMETHEUS",
"options": [],
"query": "prometheus",
"queryValue": "",
"refresh": 1,
"regex": "",
"skipUrlSync": false
"skipUrlSync": false,
"type": "datasource"
},
{
"current": {
"selected": false,
"text": "/share/datasets/public_models/Meta-Llama-3-8B-Instruct",
"value": "/share/datasets/public_models/Meta-Llama-3-8B-Instruct"
},
"datasource": {
"type": "prometheus",
"uid": "edx8memhpd9tsa"
},
"definition": "label_values(model_name)",
"hide": 0,
"includeAll": false,
......@@ -1249,7 +1552,6 @@
"timezone": "",
"title": "vLLM",
"uid": "b281712d-8bff-41ef-9f3f-71ad43c05e9b",
"version": 1,
"version": 8,
"weekStart": ""
}
examples/run_cluster.sh
View file @ 4d3a2c28
......@@ -14,7 +14,7 @@ PATH_TO_HF_HOME="$4"
shift 4
# Additional arguments are passed directly to the Docker command
ADDITIONAL_ARGS="$@"
ADDITIONAL_ARGS=("$@")
# Validate node type
if [ "${NODE_TYPE}" != "--head" ] && [ "${NODE_TYPE}" != "--worker" ]; then
......@@ -45,5 +45,5 @@ docker run \
--shm-size 10.24g \
--gpus all \
-v "${PATH_TO_HF_HOME}:/root/.cache/huggingface" \
${ADDITIONAL_ARGS} \
"${ADDITIONAL_ARGS[@]}" \
"${DOCKER_IMAGE}" -c "${RAY_START_CMD}"
examples/template_dse_qwen2_vl.jinja 0 → 100644
View file @ 4d3a2c28
{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}{% raw %}<|im_start|>system
You are a helpful assistant.<|im_end|>
{% endraw %}{% endif %}<|im_start|>{{ message['role'] }}{% raw %}
{% endraw %}{% if message['content'] is string %}{{ message['content'] }}<|im_end|>{% raw %}
{% endraw %}{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>{% raw %}
{% endraw %}{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant{% raw %}
{% endraw %}{% endif %}<|endoftext|>
\ No newline at end of file
examples/template_vlm2vec.jinja 0 → 100644
View file @ 4d3a2c28
{%- if messages | length > 1 -%}
{{ raise_exception('Embedding models should only embed one message at a time') }}
{%- endif -%}
{% set vars = namespace(parts=[], next_image_id=1) %}
{%- for message in messages -%}
{%- for content in message['content'] -%}
{%- if content['type'] == 'text' -%}
{%- set vars.parts = vars.parts + [content['text']] %}
{%- elif content['type'] == 'image' -%}
{%- set vars.parts = vars.parts + ['<|image_{i:d}|>'.format(i=vars.next_image_id)] %}
{%- set vars.next_image_id = vars.next_image_id + 1 %}
{%- endif -%}
{%- endfor -%}
{%- endfor -%}
{{ vars.parts | join(' ') }}
examples/tool_chat_template_granite.jinja 0 → 100644
View file @ 4d3a2c28
{%- if tools %}
{{- '<|start_of_role|>available_tools<|end_of_role|>
' }}
{%- for tool in tools %}
{{- tool | tojson(indent=4) }}
{%- if not loop.last %}
{{- '
' }}
{%- endif %}
{%- endfor %}
{{- '<|end_of_text|>
' }}
{%- endif %}
{%- for message in messages %}
{%- if message['role'] == 'system' %}
{{- '<|start_of_role|>system<|end_of_role|>' + message['content'] + '<|end_of_text|>
' }}
{%- elif message['role'] == 'user' %}
{{- '<|start_of_role|>user<|end_of_role|>' + message['content'] + '<|end_of_text|>
' }}
{%- elif message['role'] == 'assistant_tool_call' or (message['role'] == 'assistant' and message.tool_calls is defined) %}
{{- '<|start_of_role|>assistant<|end_of_role|><|tool_call|>' + message.tool_calls|map(attribute='function')|list|tojson(indent=4) + '<|end_of_text|>
' }}
{%- elif message['role'] == 'assistant' %}
{{- '<|start_of_role|>assistant<|end_of_role|>' + message['content'] + '<|end_of_text|>
' }}
{%- elif message['role'] == 'tool_response' or message['role'] == 'tool' %}
{{- '<|start_of_role|>tool_response<|end_of_role|>' + message['content'] + '<|end_of_text|>
' }}
{%- endif %}
{%- if loop.last and add_generation_prompt %}
{{- '<|start_of_role|>assistant<|end_of_role|>' }}
{%- endif %}
{%- endfor %}
examples/tool_chat_template_granite_20b_fc.jinja 0 → 100644
View file @ 4d3a2c28
{%- macro json_to_python_type(json_spec) %}
{%- set basic_type_map = {
"string": "str",
"number": "float",
"integer": "int",
"boolean": "bool"
} %}
{%- if basic_type_map[json_spec.type] is defined %}
{{- basic_type_map[json_spec.type] }}
{%- elif json_spec.type == "array" %}
{{- "list[" + json_to_python_type(json_spec|items) + "]" }}
{%- elif json_spec.type == "object" %}
{%- if json_spec.additionalProperties is defined %}
{{- "dict[str, " + json_to_python_type(json_spec.additionalProperties) + ']' }}
{%- else %}
{{- "dict" }}
{%- endif %}
{%- elif json_spec.type is iterable %}
{{- "Union[" }}
{%- for t in json_spec.type %}
{{- json_to_python_type({"type": t}) }}
{%- if not loop.last %}
{{- "," }}
{%- endif %}
{%- endfor %}
{{- "]" }}
{%- else %}
{{- "Any" }}
{%- endif %}
{%- endmacro %}
{%- if not full_function_description is defined %}
{%- set full_function_description = false %}
{%- endif %}
{%- macro full_description(tool) %}
{{- tool.name + '(' }}
{%- if tool.parameters is defined %}
{%- for param_name, param_fields in tool.parameters.properties|items %}
{{- param_name + ": " + json_to_python_type(param_fields) }}
{%- if not loop.last %}
{{- ", " }}
{%- endif %}
{%- endfor %}
{%- endif %}
{{- ")" }}
{%- if tool.return is defined %}
{{- " -> " + json_to_python_type(tool.return) }}
{%- endif %}
{{- " - " + tool.description + "\n\n" }}
{%- if tool.parameters is defined %}
{%- for param_name, param_fields in tool.parameters.properties|items %}
{%- if loop.first %}
{{- " Args:\n" }}
{%- endif %}
{{- " " + param_name + "(" + json_to_python_type(param_fields) + "): " + param_fields.description|trim }}
{%- endfor %}
{%- endif %}
{%- if tool.return is defined and tool.return.description is defined %}
{{- "\n Returns:\n " + tool.return.description }}
{%- endif %}
{{- '"' }}
{%- endmacro %}
{%- macro simple_description(tool) %}
{{- tool.description }}
{%- endmacro %}
{%- macro function_description(tool) %}
{%- if full_function_description %}
{{- full_description(tool) }}
{%- else %}
{{- simple_description(tool) }}
{%- endif %}
{%- endmacro %}
{%- if messages[0]["role"] == "system" %}
{%- set sys_prompt = messages[0]["content"] %}
{%- set loop_messages = messages[1:] %}
{%- else %}
{%- set loop_messages = messages %}
{% set sys_prompt = 'You are a helpful assistant with access to the following function calls. Your task is to understand the given conversation with function calls and responses and generate natural language response as the ASSISTANT to continue the conversation. You may use the following function calls to understand how to respond to the user query.' %}
{%- endif %}
{{ 'SYSTEM: ' + sys_prompt }}
{% if tools is iterable and tools | length > 0 %}
<|function_call_library|>
{%- for tool in tools %}
{%- if tool.function is defined %}
{%- set tool = tool.function %}
{%- endif %}
{{- '{"name": "' + tool.name + '", ' }}
{{- '"description": "' + function_description(tool) }}
{{- ', "parameters": ' }}
{%- if not tool.parameters is defined or tool.parameters.properties | length == 0 %}
{{- "{}" }}
{%- else %}
{{- tool.parameters|tojson }}
{%- endif %}
{{- "}" }}
{%- if not loop.last %}
{{- "\n" }}
{%- endif %}
{%- endfor %}
If none of the functions are relevant or the given question lacks the parameters required by the function, please output \"<function_call> {\"name\": \"no_function\", \"arguments\": {}}\".
{%- endif %}
{% for message in messages %}
{% if message['role'] == 'user' %}
{{- '\nUSER: ' + message['content'] }}
{% elif message['role'] == 'assistant' and message.tool_calls is defined %}
{{- '\nASSISTANT:' }}
{% for tc in message.tool_calls %}
{{- '<function_call> ' + {'name': tc.function.name, 'arguments': tc.function.arguments}|tojson }}
{% endfor %}
{{- '<|endoftext|>' }}
{% elif message['role'] == 'assistant' %}
{{- '\nASSISTANT: ' + message['content'] + ' <|endoftext|>' }}
{% elif message['role'] == 'tool' %}
{{- '<function_response> ' + message['content'] }}
{%- else %}
{{- raise_exception("Unexpected combination of role and message content") }}
{% endif %}
{% if loop.last and add_generation_prompt %}
{{- '\nASSISTANT: ' }}
{% endif %}
{% endfor %}
examples/tool_chat_template_internlm2_tool.jinja 0 → 100644
View file @ 4d3a2c28
{%- if messages[0]["role"] == "system" %}
{%- set system_message = messages[0]["content"] %}
{%- set loop_messages = messages[1:] %}
{%- else %}
{%- set loop_messages = messages %}
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{{- bos_token }}
{%- if system_message is defined %}
{{- "<|im_start|>system\n" + system_message + "<|im_end|>\n" }}
{%- endif %}
{%- if tools is not none %}
{{- "<|im_start|>system name=<|plugin|>\n[" }}
{%- for tool in tools %}
{{- tool.function|tojson }}
{%- if not loop.last %}
{{- ", " }}
{%- else %}
{{- "]" }}
{%- endif %}
{%- endfor %}
{{- "<|im_end|>\n" }}
{%- endif %}
{%- for message in loop_messages %}
{%- if message["role"] == "user" %}
{{- "<|im_start|>user\n" + message["content"] + "<|im_end|>\n"}}
{%- elif message.tool_calls is defined and message.tool_calls is not none %}
{%- set content = message["content"] if message["content"] else "" %}
{{- "<|im_start|>assistant\n" + content }}
{%- for tool_call in message.tool_calls %}
{%- set function=tool_call.function %}
{{- "<|action_start|><|plugin|>\n" }}
{{- '{"name": "' + function.name + '", '}}
{{- '"arguments": ' + function.arguments|tojson + '}' }}
{{- "<|action_end|>" }}
{%- endfor %}
{{- "<|im_end|>\n" }}
{%- elif message["role"] == "assistant" %}
{{- "<|im_start|>assistant\n" + message["content"] + "<|im_end|>\n"}}
{%- elif message["role"] == "tool_results" or message["role"] == "tool" or message["role"] == "function" %}
{%- if message.content is defined and message.content.content is defined %}
{%- set content = message.content.content %}
{%- else %}
{%- set content = message.content %}
{%- endif %}
{{- "<|im_start|>environment name=<|plugin|>\n" + content|string + "<|im_end|>\n" }}
{%- else %}
{{- raise_exception("Only user and assistant and tool_results and tool and function roles are supported, with the exception of an initial optional system message!") }}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- endif %}
\ No newline at end of file
examples/tool_chat_template_llama3.1_json.jinja 0 → 100644
View file @ 4d3a2c28
{{- bos_token }}
{%- if custom_tools is defined %}
{%- set tools = custom_tools %}
{%- endif %}
{%- if not tools_in_user_message is defined %}
{#- Llama 3.1 doesn't pass all tests if the tools are in the system prompt #}
{%- set tools_in_user_message = true %}
{%- endif %}
{%- if not date_string is defined %}
{%- if strftime_now is defined %}
{%- set date_string = strftime_now("%d %b %Y") %}
{%- else %}
{%- set date_string = "26 Jul 2024" %}
{%- endif %}
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
{%- if messages[0]['content'] is string %}
{%- set system_message = messages[0]['content']|trim %}
{%- else %}
{%- set system_message = messages[0]['content'][0]['text']|trim %}
{%- endif %}
{%- set messages = messages[1:] %}
{%- else %}
{%- if tools is not none %}
{%- set system_message = "You are a helpful assistant with tool calling capabilities. Only reply with a tool call if the function exists in the library provided by the user. If it doesn't exist, just reply directly in natural language. When you receive a tool call response, use the output to format an answer to the original user question." %}
{%- else %}
{%- set system_message = "" %}
{%- endif %}
{%- endif %}
{#- System message #}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if tools is not none %}
{{- "Environment: ipython\n" }}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n" }}
{{- "Today Date: " + date_string + "\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
{{- "You have access to the following functions. To call a function, please respond with JSON for a function call. " }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. ' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}
{#- Custom tools are passed in a user message with some extra guidance #}
{%- if tools_in_user_message and not tools is none %}
{#- Extract the first user message so we can plug it in here #}
{%- if messages | length != 0 %}
{%- if messages[0]['content'] is string %}
{%- set first_user_message = messages[0]['content']|trim %}
{%- else %}
{%- set first_user_message = messages[0]['content'] | selectattr('type', 'equalto', 'text') | map(attribute='text') | map('trim') | join('\n') %}
{%- endif %}
{%- set messages = messages[1:] %}
{%- else %}
{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
{%- endif %}
{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
{{- "Given the following functions, please respond with a JSON for a function call " }}
{{- "with its proper arguments that best answers the given prompt.\n\n" }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. ' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{{- first_user_message + "<|eot_id|>"}}
{%- endif %}
{%- for message in messages %}
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n' }}
{%- if message['content'] is string %}
{{- message['content'] | trim}}
{%- else %}
{%- for content in message['content'] %}
{%- if content['type'] == 'text' %}
{{- content['text'] | trim }}
{%- endif %}
{%- endfor %}
{%- endif %}
{{- '<|eot_id|>' }}
{%- elif 'tool_calls' in message %}
{%- if not message.tool_calls|length == 1 %}
{{- raise_exception("This model only supports single tool-calls at once!") }}
{%- endif %}
{%- set tool_call = message.tool_calls[0].function %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
{{- '{"name": "' + tool_call.name + '", ' }}
{{- '"parameters": ' }}
{{- tool_call.arguments | tojson }}
{{- "}" }}
{{- "<|eot_id|>" }}
{%- elif message.role == "tool" or message.role == "ipython" %}
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
{%- if message.content is string %}
{{- { "output": message.content } | tojson }}
{%- else %}
{%- for content in message['content'] %}
{%- if content['type'] == 'text' %}
{{- { "output": content['text'] } | tojson }}
{%- endif %}
{%- endfor %}
{%- endif %}
{{- "<|eot_id|>" }}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif %}
examples/tool_chat_template_llama3.2_json.jinja 0 → 100644
View file @ 4d3a2c28
{{- bos_token }}
{%- if custom_tools is defined %}
{%- set tools = custom_tools %}
{%- endif %}
{%- if not tools_in_user_message is defined %}
{%- set tools_in_user_message = false %}
{%- endif %}
{%- if not date_string is defined %}
{%- if strftime_now is defined %}
{%- set date_string = strftime_now("%d %b %Y") %}
{%- else %}
{%- set date_string = "26 Jul 2024" %}
{%- endif %}
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{#- Find out if there are any images #}
{% set image_ns = namespace(has_images=false) %}
{%- for message in messages %}
{%- for content in message['content'] %}
{%- if content['type'] == 'image' %}
{%- set image_ns.has_images = true %}
{%- endif %}
{%- endfor %}
{%- endfor %}
{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
{%- if messages[0]['content'] is string %}
{%- set system_message = messages[0]['content']|trim %}
{%- else %}
{%- set system_message = messages[0]['content'][0]['text']|trim %}
{%- endif %}
{%- set messages = messages[1:] %}
{%- else %}
{%- if tools is not none %}
{%- set system_message = "You are a helpful assistant with tool calling capabilities. Only reply with a tool call if the function exists in the library provided by the user. If it doesn't exist, just reply directly in natural language. When you receive a tool call response, use the output to format an answer to the original user question." %}
{%- else %}
{%- set system_message = "" %}
{%- endif %}
{%- endif %}
{#- System message if there are no images, if the user supplied one, or if tools are used (default tool system message) #}
{%- if system_message or not image_ns.has_images %}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if tools is not none %}
{{- "Environment: ipython\n" }}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n" }}
{{- "Today Date: " + date_string + "\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
{{- "You have access to the following functions. To call a function, please respond with JSON for a function call. " }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. ' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}
{%- endif %}
{#- Custom tools are passed in a user message with some extra guidance #}
{%- if tools_in_user_message and not tools is none %}
{#- Extract the first user message so we can plug it in here #}
{%- if messages | length != 0 %}
{%- if messages[0]['content'] is string %}
{%- set first_user_message = messages[0]['content']|trim %}
{%- else %}
{%- set first_user_message = messages[0]['content'] | selectattr('type', 'equalto', 'text') | map(attribute='text') | map('trim') | join('\n') %}
{%- endif %}
{%- set messages = messages[1:] %}
{%- else %}
{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
{%- endif %}
{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
{{- "Given the following functions, please respond with a JSON for a function call " }}
{{- "with its proper arguments that best answers the given prompt.\n\n" }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. ' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{{- first_user_message + "<|eot_id|>"}}
{%- endif %}
{%- for message in messages %}
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n' }}
{%- if message['content'] is string %}
{{- message['content'] | trim}}
{%- else %}
{%- for content in message['content'] %}
{%- if content['type'] == 'image' %}
{{- '<|image|>' }}
{%- elif content['type'] == 'text' %}
{{- content['text'] | trim }}
{%- endif %}
{%- endfor %}
{%- endif %}
{{- '<|eot_id|>' }}
{%- elif 'tool_calls' in message %}
{%- if not message.tool_calls|length == 1 %}
{{- raise_exception("This model only supports single tool-calls at once!") }}
{%- endif %}
{%- set tool_call = message.tool_calls[0].function %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
{{- '{"name": "' + tool_call.name + '", ' }}
{{- '"parameters": ' }}
{{- tool_call.arguments | tojson }}
{{- "}" }}
{{- "<|eot_id|>" }}
{%- elif message.role == "tool" or message.role == "ipython" %}
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
{%- if message.content is string %}
{{- { "output": message.content } | tojson }}
{%- else %}
{%- for content in message['content'] %}
{%- if content['type'] == 'text' %}
{{- { "output": content['text'] } | tojson }}
{%- endif %}
{%- endfor %}
{%- endif %}
{{- "<|eot_id|>" }}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif %}
examples/tool_chat_template_llama3.2_pythonic.jinja 0 → 100644
View file @ 4d3a2c28
{{- bos_token }}
{%- if custom_tools is defined %}
{%- set tools = custom_tools %}
{%- endif %}
{%- if not tools_in_user_message is defined %}
{%- set tools_in_user_message = false %}
{%- endif %}
{%- if not date_string is defined %}
{%- if strftime_now is defined %}
{%- set date_string = strftime_now("%d %b %Y") %}
{%- else %}
{%- set date_string = "26 Jul 2024" %}
{%- endif %}
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
{%- set system_message = messages[0]['content']|trim %}
{%- set messages = messages[1:] %}
{%- else %}
{%- set system_message = "You are a helpful assistant with tool calling capabilities. Only reply with a tool call if the function exists in the library provided by the user. If it doesn't exist, just reply directly in natural language. When you receive a tool call response, use the output to format an answer to the original user question." %}
{%- endif %}
{#- System message #}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if tools is not none %}
{{- "Environment: ipython\n" }}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n" }}
{{- "Today Date: " + date_string + "\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
{{- "You have access to the following functions. To call functions, please respond with a python list of the calls. " }}
{{- 'Respond in the format [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)] ' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}
{#- Custom tools are passed in a user message with some extra guidance #}
{%- if tools_in_user_message and not tools is none %}
{#- Extract the first user message so we can plug it in here #}
{%- if messages | length != 0 %}
{%- set first_user_message = messages[0]['content']|trim %}
{%- set messages = messages[1:] %}
{%- else %}
{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
{%- endif %}
{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
{{- "Given the following functions, please respond with a python list for function calls " }}
{{- "with their proper arguments to best answer the given prompt.\n\n" }}
{{- 'Respond in the format [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)] ' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{{- first_user_message + "<|eot_id|>"}}
{%- endif %}
{%- for message in messages %}
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
{%- elif 'tool_calls' in message %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n[' -}}
{%- for tool_call in message.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- tool_call.name + '(' -}}
{%- for param in tool_call.arguments %}
{{- param + '=' -}}
{{- "%sr" | format(tool_call.arguments[param]) -}}
{% if not loop.last %}, {% endif %}
{%- endfor %}
{{- ')' -}}
{% if not loop.last %}, {% endif %}
{%- endfor %}
{{- ']<|eot_id|>' -}}
{%- elif message.role == "tool" or message.role == "ipython" %}
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
{%- if message.content is mapping %}
{{- message.content | tojson }}
{%- else %}
{{- { "output": message.content } | tojson }}
{%- endif %}
{{- "<|eot_id|>" }}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif %}
examples/tool_chat_template_mistral_parallel.jinja
View file @ 4d3a2c28
......@@ -6,8 +6,7 @@
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{%- if tools is defined %}
{%- elif tools is not none %}
{%- set parallel_tool_prompt = "You are a helpful assistant that can call tools. If you call one or more tools, format them in a single JSON array or objects, where each object is a tool call, not as separate objects outside of an array or multiple arrays. Use the format [{\"name\": tool call name, \"arguments\": tool call arguments}, additional tool calls] if you call more than one tool. If you call tools, do not attempt to interpret them or otherwise provide a response until you receive a tool call result that you can interpret for the user." %}
{%- if system_message is defined %}
{%- set system_message = parallel_tool_prompt + "\n\n" + system_message %}
......
examples/tool_chat_template_toolace.jinja 0 → 100644
View file @ 4d3a2c28
{{- bos_token }}
{%- if custom_tools is defined %}
{%- set tools = custom_tools %}
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
{%- set system_message = messages[0]['content']|trim %}
{%- set messages = messages[1:] %}
{%- else %}
{%- set system_message = "You are a helpful assistant with tool calling capabilities. Only reply with a tool call if the function exists in the library provided by the user. If it doesn't exist, just reply directly in natural language." %}
{%- endif %}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
{{- "You are an expert in composing functions. You are given a question and a set of possible functions. Based on the question, you will need to make one or more function/tool calls to achieve the purpose.\n" }}
{{- "If none of the function can be used, point it out. If the given question lacks the parameters required by the function, also point it out.\n" }}
{{- "You should only return the function call in tools call sections.\n\n" }}
{{- "If you decide to invoke any of the function(s), you MUST put it in the format of [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)]\n" }}
{{- "You SHOULD NOT include any other text in the response.\n" }}
{{- "Here is a list of functions in JSON format that you can invoke.\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{{- "\n" }}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}
{%- for message in messages %}
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
{%- elif 'tool_calls' in message %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n[' -}}
{%- for tool_call in message.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- tool_call.name + '(' -}}
{%- for param in tool_call.arguments %}
{{- param + '=' -}}
{{- "%sr" | format(tool_call.arguments[param]) -}}
{% if not loop.last %}, {% endif %}
{%- endfor %}
{{- ')' -}}
{% if not loop.last %}, {% endif %}
{%- endfor %}
{{- ']<|eot_id|>' -}}
{%- elif message.role == "tool" or message.role == "ipython" %}
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
{%- if message.content is mapping %}
{{- message.content | tojson }}
{%- else %}
{{- { "output": message.content } | tojson }}
{%- endif %}
{{- "<|eot_id|>" }}
{%- endif %}
{%- endfor %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
find_cuda_init.py 0 → 100644
View file @ 4d3a2c28
import importlib
import traceback
from typing import Callable
from unittest.mock import patch
def find_cuda_init(fn: Callable[[], object]) -> None:
"""
Helper function to debug CUDA re-initialization errors.
If `fn` initializes CUDA, prints the stack trace of how this happens.
"""
from torch.cuda import _lazy_init
stack = None
def wrapper():
nonlocal stack
stack = traceback.extract_stack()
return _lazy_init()
with patch("torch.cuda._lazy_init", wrapper):
fn()
if stack is not None:
print("==== CUDA Initialized ====")
print("".join(traceback.format_list(stack)).strip())
print("==========================")
if __name__ == "__main__":
find_cuda_init(
lambda: importlib.import_module("vllm.model_executor.models.llava"))
format.sh
View file @ 4d3a2c28
......@@ -21,27 +21,44 @@ builtin cd "$(dirname "${BASH_SOURCE:-$0}")"
ROOT="$(git rev-parse --show-toplevel)"
builtin cd "$ROOT" || exit 1
check_command() {
if ! command -v "$1" &> /dev/null; then
echo "❓❓$1 is not installed, please run \`pip install -r requirements-lint.txt\`"
exit 1
fi
}
check_command yapf
check_command ruff
check_command mypy
check_command codespell
check_command isort
check_command clang-format
YAPF_VERSION=$(yapf --version | awk '{print $2}')
RUFF_VERSION=$(ruff --version | awk '{print $2}')
MYPY_VERSION=$(mypy --version | awk '{print $2}')
CODESPELL_VERSION=$(codespell --version)
ISORT_VERSION=$(isort --vn)
CLANGFORMAT_VERSION=$(clang-format --version | awk '{print $3}')
SPHINX_LINT_VERSION=$(sphinx-lint --version | awk '{print $2}')
# # params: tool name, tool version, required version
tool_version_check() {
if [[ $2 != $3 ]]; then
echo "Wrong $1 version installed: $3 is required, not $2."
expected=$(grep "$1" requirements-lint.txt | cut -d'=' -f3)
if [[ "$2" != "$expected" ]]; then
echo "❓❓Wrong $1 version installed: $expected is required, not $2."
exit 1
fi
}
tool_version_check "yapf" $YAPF_VERSION "$(grep yapf requirements-lint.txt | cut -d'=' -f3)"
tool_version_check "ruff" $RUFF_VERSION "$(grep "ruff==" requirements-lint.txt | cut -d'=' -f3)"
tool_version_check "mypy" "$MYPY_VERSION" "$(grep mypy requirements-lint.txt | cut -d'=' -f3)"
tool_version_check "isort" "$ISORT_VERSION" "$(grep isort requirements-lint.txt | cut -d'=' -f3)"
tool_version_check "codespell" "$CODESPELL_VERSION" "$(grep codespell requirements-lint.txt | cut -d'=' -f3)"
tool_version_check "clang-format" "$CLANGFORMAT_VERSION" "$(grep clang-format requirements-lint.txt | cut -d'=' -f3)"
tool_version_check "yapf" "$YAPF_VERSION"
tool_version_check "ruff" "$RUFF_VERSION"
tool_version_check "mypy" "$MYPY_VERSION"
tool_version_check "isort" "$ISORT_VERSION"
tool_version_check "codespell" "$CODESPELL_VERSION"
tool_version_check "clang-format" "$CLANGFORMAT_VERSION"
tool_version_check "sphinx-lint" "$SPHINX_LINT_VERSION"
YAPF_FLAGS=(
'--recursive'
......@@ -96,17 +113,7 @@ echo 'vLLM yapf: Done'
# Run mypy
echo 'vLLM mypy:'
mypy --follow-imports skip # Note that this is less strict than CI
mypy tests --follow-imports skip
mypy vllm/attention --follow-imports skip
mypy vllm/distributed --follow-imports skip
mypy vllm/engine --follow-imports skip
mypy vllm/executor --follow-imports skip
mypy vllm/lora --follow-imports skip
mypy vllm/model_executor --follow-imports skip
mypy vllm/prompt_adapter --follow-imports skip
mypy vllm/spec_decode --follow-imports skip
mypy vllm/worker --follow-imports skip
tools/mypy.sh
echo 'vLLM mypy: Done'
......@@ -263,7 +270,7 @@ clang_format_changed() {
MERGEBASE="$(git merge-base origin/main HEAD)"
# Get the list of changed files, excluding the specified ones
changed_files=$(git diff --name-only --diff-filter=ACM "$MERGEBASE" -- '*.h' '*.cpp' '*.cu' '*.cuh' | grep -vFf <(printf "%s\n" "${CLANG_FORMAT_EXCLUDES[@]}"))
changed_files=$(git diff --name-only --diff-filter=ACM "$MERGEBASE" -- '*.h' '*.cpp' '*.cu' '*.cuh' | (grep -vFf <(printf "%s\n" "${CLANG_FORMAT_EXCLUDES[@]}") || echo -e))
if [ -n "$changed_files" ]; then
echo "$changed_files" | xargs -P 5 clang-format -i
fi
......@@ -286,12 +293,29 @@ else
fi
echo 'vLLM clang-format: Done'
echo 'vLLM actionlint:'
tools/actionlint.sh -color
echo 'vLLM actionlint: Done'
echo 'vLLM shellcheck:'
tools/shellcheck.sh
echo 'vLLM shellcheck: Done'
echo 'excalidraw png check:'
tools/png-lint.sh
echo 'excalidraw png check: Done'
if ! git diff --quiet &>/dev/null; then
echo 'Reformatted files. Please review and stage the changes.'
echo 'Changes not staged for commit:'
echo
echo
echo "🔍🔍There are files changed by the format checker or by you that are not added and committed:"
git --no-pager diff --name-only
echo "🔍🔍Format checker passed, but please add, commit and push all the files above to include changes made by the format checker."
exit 1
else
echo "✨🎉 Format check passed! Congratulations! 🎉✨"
fi
echo 'vLLM sphinx-lint:'
tools/sphinx-lint.sh
echo 'vLLM sphinx-lint: Done'
pyproject.toml
View file @ 4d3a2c28
......@@ -6,12 +6,15 @@ requires = [
"packaging",
"setuptools>=61",
"setuptools-scm>=8.0",
"torch == 2.4.0",
"torch == 2.5.1",
"wheel",
"jinja2",
]
build-backend = "setuptools.build_meta"
[tool.setuptools_scm]
# version_file = "vllm/_version.py" # currently handled by `setup.py:get_version()`
[tool.ruff]
# Allow lines to be as long as 80.
line-length = 80
......@@ -31,7 +34,7 @@ select = [
# Pyflakes
"F",
# pyupgrade
# "UP",
"UP",
# flake8-bugbear
"B",
# flake8-simplify
......@@ -52,14 +55,12 @@ ignore = [
]
[tool.mypy]
python_version = "3.8"
ignore_missing_imports = true
check_untyped_defs = true
follow_imports = "silent"
# After fixing type errors resulting from follow_imports: "skip" -> "silent",
# move the directory here and remove it from format.sh and mypy.yaml
# move the directory here and remove it from tools/mypy.sh
files = [
"vllm/*.py",
"vllm/adapter_commons",
......@@ -67,7 +68,7 @@ files = [
"vllm/entrypoints",
"vllm/core",
"vllm/inputs",
"vllm/logging",
"vllm/logging_utils",
"vllm/multimodal",
"vllm/platforms",
"vllm/transformers_utils",
......@@ -92,6 +93,11 @@ skip_gitignore = true
[tool.pytest.ini_options]
markers = [
"skip_global_cleanup",
"core_model: run this model test in each PR instead of just daily",
"distributed_2_gpus: run this test only in distributed tests for 2 GPUs",
"core_model: enable this model test in each PR instead of only nightly",
"cpu_model: enable this model test in CPU tests",
"quant_model: run this model test under Quantized category",
"split: run this test as part of a split",
"distributed: run this test only in distributed GPU tests",
"skip_v1: do not run this test with v1",
"optional: optional tests that are automatically skipped, include --optional to run them",
]
python_only_dev.py 0 → 100644
View file @ 4d3a2c28
msg = """Old style python only build (without compilation) is deprecated, please check https://docs.vllm.ai/en/latest/getting_started/installation.html#python-only-build-without-compilation for the new way to do python only build (without compilation).
TL;DR:
VLLM_USE_PRECOMPILED=1 pip install -e .
or
export VLLM_COMMIT=33f460b17a54acb3b6cc0b03f4a17876cff5eafd # use full commit hash from the main branch
export VLLM_PRECOMPILED_WHEEL_LOCATION=https://vllm-wheels.s3.us-west-2.amazonaws.com/${VLLM_COMMIT}/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl
pip install -e .
""" # noqa
print(msg)
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