Spaces:
Runtime error
Runtime error
File size: 4,069 Bytes
8655a4b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 |
"""
Test the OpenAI compatible server
Launch:
python3 launch_openai_api_test_server.py --multimodal
"""
import openai
from fastchat.utils import run_cmd
openai.api_key = "EMPTY" # Not support yet
openai.base_url = "http://localhost:8000/v1/"
def encode_image(image):
import base64
from io import BytesIO
import requests
from PIL import Image
if image.startswith("http://") or image.startswith("https://"):
response = requests.get(image)
image = Image.open(BytesIO(response.content)).convert("RGB")
else:
image = Image.open(image).convert("RGB")
buffered = BytesIO()
image.save(buffered, format="PNG")
img_b64_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
return img_b64_str
def test_list_models():
model_list = openai.models.list()
names = [x.id for x in model_list.data]
return names
def test_chat_completion(model):
image_url = "https://picsum.photos/seed/picsum/1024/1024"
base64_image_url = f"data:image/jpeg;base64,{encode_image(image_url)}"
# No Image
completion = openai.chat.completions.create(
model=model,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "Tell me about alpacas."},
],
}
],
temperature=0,
)
print(completion.choices[0].message.content)
print("=" * 25)
# Image using url link
completion = openai.chat.completions.create(
model=model,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What’s in this image?"},
{"type": "image_url", "image_url": {"url": image_url}},
],
}
],
temperature=0,
)
print(completion.choices[0].message.content)
print("=" * 25)
# Image using base64 image url
completion = openai.chat.completions.create(
model=model,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What’s in this image?"},
{"type": "image_url", "image_url": {"url": base64_image_url}},
],
}
],
temperature=0,
)
print(completion.choices[0].message.content)
print("=" * 25)
def test_chat_completion_stream(model):
image_url = "https://picsum.photos/seed/picsum/1024/1024"
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "What’s in this image?"},
{"type": "image_url", "image_url": {"url": image_url}},
],
}
]
res = openai.chat.completions.create(
model=model, messages=messages, stream=True, temperature=0
)
for chunk in res:
try:
content = chunk.choices[0].delta.content
if content is None:
content = ""
except Exception as e:
content = chunk.choices[0].delta.get("content", "")
print(content, end="", flush=True)
print()
def test_openai_curl():
run_cmd(
"""curl http://localhost:8000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "llava-v1.5-7b",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "What’s in this image?"
},
{
"type": "image_url",
"image_url": {
"url": "https://picsum.photos/seed/picsum/1024/1024"
}
}
]
}
],
"max_tokens": 300
}'
"""
)
print()
if __name__ == "__main__":
models = test_list_models()
print(f"models: {models}")
for model in models:
print(f"===== Test {model} ======")
test_chat_completion(model)
test_chat_completion_stream(model)
test_openai_curl()
|