[Fix] Add chat completion Example and simplify dependencies (#576)

examples/openai_chatcompletion_client.py

@@ -0,0 +1,33 @@
+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"
+
+# List models API
+models = openai.Model.list()
+print("Models:", models)
+
+model = models["data"][0]["id"]
+
+# Chat completion API
+chat_completion = openai.ChatCompletion.create(
+    model=model,
+    messages=[{
+        "role": "system",
+        "content": "You are a helpful assistant."
+    }, {
+        "role": "user",
+        "content": "Who won the world series in 2020?"
+    }, {
+        "role":
+        "assistant",
+        "content":
+        "The Los Angeles Dodgers won the World Series in 2020."
+    }, {
+        "role": "user",
+        "content": "Where was it played?"
+    }])
+
+print("Chat completion results:")
+print(chat_completion)

examples/openai_completion_client.py

@@ -3,26 +3,26 @@ 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"
-model = "facebook/opt-125m"
 
-# Test list models API
+# List models API
 models = openai.Model.list()
 print("Models:", models)
 
-# Test completion API
+model = models["data"][0]["id"]
-stream = True
+
+# Completion API
+stream = False
 completion = openai.Completion.create(
     model=model,
     prompt="A robot may not injure a human being",
     echo=False,
     n=2,
-    best_of=3,
     stream=stream,
     logprobs=3)
 
-# print the completion
+print("Completion results:")
 if stream:
     for c in completion:
         print(c)
 else:
-    print("Completion result:", completion)
+    print(completion)

requirements.txt

@@ -9,4 +9,3 @@ xformers >= 0.0.19
 fastapi
 uvicorn
 pydantic < 2  # Required for OpenAI server.
-fschat  # Required for OpenAI ChatCompletion Endpoint.

vllm/entrypoints/openai/api_server.py

@@ -13,9 +13,6 @@ from fastapi import BackgroundTasks, Request
 from fastapi.exceptions import RequestValidationError
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse, StreamingResponse
-from fastchat.conversation import Conversation, SeparatorStyle
-from fastchat.model.model_adapter import get_conversation_template
-
 import uvicorn
 
 from vllm.engine.arg_utils import AsyncEngineArgs
@@ -33,6 +30,13 @@ from vllm.sampling_params import SamplingParams
 from vllm.transformers_utils.tokenizer import get_tokenizer
 from vllm.utils import random_uuid
 
+try:
+    from fastchat.conversation import Conversation, SeparatorStyle
+    from fastchat.model.model_adapter import get_conversation_template
+    _fastchat_available = True
+except ImportError:
+    _fastchat_available = False
+
 TIMEOUT_KEEP_ALIVE = 5  # seconds
 
 logger = init_logger(__name__)
@@ -63,6 +67,11 @@ async def check_model(request) -> Optional[JSONResponse]:
 
 
 async def get_gen_prompt(request) -> str:
+    if not _fastchat_available:
+        raise ModuleNotFoundError(
+            "fastchat is not installed. Please install fastchat to use "
+            "the chat completion and conversation APIs: `$ pip install fschat`"
+        )
     conv = get_conversation_template(request.model)
     conv = Conversation(
         name=conv.name,