Openai API migrate (#2765)

docs/openai_api.md

@@ -39,24 +39,30 @@ pip install --upgrade openai
 
 Then, interact with model vicuna:
 ```python
-import openai
+from openai import OpenAI
 # to get proper authentication, make sure to use a valid key that's listed in
 # the --api-keys flag. if no flag value is provided, the `api_key` will be ignored.
-openai.api_key = "EMPTY"
-openai.api_base = "http://localhost:8000/v1"
+client = OpenAI(api_key="EMPTY", base_url="http://localhost:8000/v1", default_headers={"x-foo": "true"})
 
 model = "vicuna-7b-v1.5"
 prompt = "Once upon a time"
 
-# create a completion
-completion = openai.Completion.create(model=model, prompt=prompt, max_tokens=64)
+# create a completion (legacy)
+completion = client.completions.create(
+  model=model,
+  prompt=prompt
+)
 # print the completion
 print(prompt + completion.choices[0].text)
 
 # create a chat completion
-completion = openai.ChatCompletion.create(
-  model=model,
-  messages=[{"role": "user", "content": "Hello! What is your name?"}]
+completion = client.chat.completions.create(
+  model="vicuna-7b-v1.5",
+  response_format={ "type": "json_object" },
+  messages=[
+    {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
+    {"role": "user", "content": "Who won the world series in 2020?"}
+  ]
 )
 # print the completion
 print(completion.choices[0].message.content)

fastchat/serve/openai_api_server.py

@@ -375,6 +375,7 @@ async def show_available_models():
     return ModelList(data=model_cards)
 
 
+@app.post("/v1chat/completions", dependencies=[Depends(check_api_key)])
 @app.post("/v1/chat/completions", dependencies=[Depends(check_api_key)])
 async def create_chat_completion(request: ChatCompletionRequest):
     """Creates a completion for the chat message"""

playground/test_embedding/test_sentence_similarity.py

@@ -7,7 +7,7 @@
 from scipy.spatial.distance import cosine
 
 
-def get_embedding_from_api(word, model="vicuna-7b-v1.1"):
+def get_embedding_from_api(word, model="vicuna-7b-v1.5"):
     if "ada" in model:
         resp = openai.Embedding.create(
             model=model,

tests/test_openai_api.py

@@ -4,30 +4,53 @@
 Launch:
 python3 launch_openai_api_test_server.py
 """
+from distutils.version import LooseVersion
+import warnings
 
 import openai
 
+try:
+    from openai import OpenAI, AsyncOpenAI
+except ImportError:
+    warnings.warn("openai<1.0 is deprecated")
+
 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"]]
+    if LooseVersion(openai.__version__) < LooseVersion("1.0"):
+        model_list = openai.Model.list()
+    else:
+        client = OpenAI(api_key=openai.api_key, base_url=openai.api_base)
+        model_list = client.models.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,
-    )
+    if LooseVersion(openai.__version__) < LooseVersion("1.0"):
+        completion = openai.Completion.create(
+            model=model,
+            prompt=prompt,
+            logprobs=logprob,
+            max_tokens=64,
+            temperature=0,
+        )
+    else:
+        client = OpenAI(api_key=openai.api_key, base_url=openai.api_base)
+        # legacy
+        completion = client.completions.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(
@@ -38,42 +61,76 @@ def test_completion(model, logprob):
 
 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,
-    )
+    if LooseVersion(openai.__version__) < LooseVersion("1.0"):
+        res = openai.Completion.create(
+            model=model,
+            prompt=prompt,
+            max_tokens=64,
+            stream=True,
+            temperature=0,
+        )
+    else:
+        client = OpenAI(api_key=openai.api_key, base_url=openai.api_base)
+        # legacy
+        res = client.completions.create(
+            model=model,
+            prompt=prompt,
+            max_tokens=64,
+            stream=True,
+            temperature=0,
+        )
     print(prompt, end="")
     for chunk in res:
-        content = chunk["choices"][0]["text"]
+        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]}")
+    if LooseVersion(openai.__version__) < LooseVersion("1.0"):
+        embedding = openai.Embedding.create(model=model, input="Hello world!")
+    else:
+        client = OpenAI(api_key=openai.api_key, base_url=openai.api_base)
+        embedding = client.embeddings.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,
-    )
+    if LooseVersion(openai.__version__) < LooseVersion("1.0"):
+        completion = openai.ChatCompletion.create(
+            model=model,
+            messages=[{"role": "user", "content": "Hello! What is your name?"}],
+            temperature=0,
+        )
+    else:
+        client = OpenAI(api_key=openai.api_key, base_url=openai.api_base)
+        completion = client.chat.completions.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
-    )
+    if LooseVersion(openai.__version__) < LooseVersion("1.0"):
+        res = openai.ChatCompletion.create(
+            model=model, messages=messages, stream=True, temperature=0
+        )
+    else:
+        client = OpenAI(api_key=openai.api_key, base_url=openai.api_base)
+        res = client.chat.completions.create(
+            model=model, messages=messages, stream=True, temperature=0
+        )
     for chunk in res:
-        content = chunk["choices"][0]["delta"].get("content", "")
+        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()