Spaces:
Runtime error
Runtime error
File size: 3,482 Bytes
ec0c335 |
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 |
"""
Test the OpenAI compatible server
Launch:
python3 launch_openai_api_test_server.py
"""
import openai
from fastchat.utils import run_cmd
openai.api_key = "EMPTY" # Not support yet
openai.api_base = "http://localhost:8000/v1"
def test_list_models():
model_list = openai.Model.list()
names = [x["id"] for x in model_list["data"]]
return names
def test_completion(model, logprob):
prompt = "Once upon a time"
completion = openai.Completion.create(
model=model,
prompt=prompt,
logprobs=logprob,
max_tokens=64,
temperature=0,
)
print(f"full text: {prompt + completion.choices[0].text}", flush=True)
if completion.choices[0].logprobs is not None:
print(
f"logprobs: {completion.choices[0].logprobs.token_logprobs[:10]}",
flush=True,
)
def test_completion_stream(model):
prompt = "Once upon a time"
res = openai.Completion.create(
model=model,
prompt=prompt,
max_tokens=64,
stream=True,
temperature=0,
)
print(prompt, end="")
for chunk in res:
content = chunk["choices"][0]["text"]
print(content, end="", flush=True)
print()
def test_embedding(model):
embedding = openai.Embedding.create(model=model, input="Hello world!")
print(f"embedding len: {len(embedding['data'][0]['embedding'])}")
print(f"embedding value[:5]: {embedding['data'][0]['embedding'][:5]}")
def test_chat_completion(model):
completion = openai.ChatCompletion.create(
model=model,
messages=[{"role": "user", "content": "Hello! What is your name?"}],
temperature=0,
)
print(completion.choices[0].message.content)
def test_chat_completion_stream(model):
messages = [{"role": "user", "content": "Hello! What is your name?"}]
res = openai.ChatCompletion.create(
model=model, messages=messages, stream=True, temperature=0
)
for chunk in res:
content = chunk["choices"][0]["delta"].get("content", "")
print(content, end="", flush=True)
print()
def test_openai_curl():
run_cmd("curl http://localhost:8000/v1/models")
run_cmd(
"""
curl http://localhost:8000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "vicuna-7b-v1.5",
"messages": [{"role": "user", "content": "Hello! What is your name?"}]
}'
"""
)
run_cmd(
"""
curl http://localhost:8000/v1/completions \
-H "Content-Type: application/json" \
-d '{
"model": "vicuna-7b-v1.5",
"prompt": "Once upon a time",
"max_tokens": 41,
"temperature": 0.5
}'
"""
)
run_cmd(
"""
curl http://localhost:8000/v1/embeddings \
-H "Content-Type: application/json" \
-d '{
"model": "vicuna-7b-v1.5",
"input": "Hello world!"
}'
"""
)
if __name__ == "__main__":
models = test_list_models()
print(f"models: {models}")
for model in models:
print(f"===== Test {model} ======")
if model in ["fastchat-t5-3b-v1.0"]:
logprob = None
else:
logprob = 1
test_completion(model, logprob)
test_completion_stream(model)
test_chat_completion(model)
test_chat_completion_stream(model)
try:
test_embedding(model)
except openai.error.APIError as e:
print(f"Embedding error: {e}")
print("===== Test curl =====")
test_openai_curl()
|