Sync v2.0 version of code to github repo

docs/online_serving/README.md

@@ -0,0 +1,97 @@
+# OpenAI Protocol-Compatible API Server
+
+FastDeploy provides a service-oriented deployment solution that is compatible with the OpenAI protocol. Users can quickly deploy it using the following command:
+
+```bash
+python -m fastdeploy.entrypoints.openai.api_server \
+       --model baidu/ERNIE-4.5-0.3B-Paddle \
+       --port 8188 --tensor-parallel-size 8 \
+       --max-model-len 32768
+```
+
+For more usage methods of the command line during service deployment, refer to [Parameter Descriptions](../parameters.md).
+
+## Sending User Requests
+
+The FastDeploy interface is compatible with the OpenAI protocol, allowing user requests to be sent directly using OpenAI's request method.
+
+Here is an example of sending a user request using the curl command:
+
+```bash
+curl -X POST "http://0.0.0.0:8188/v1/chat/completions" \
+-H "Content-Type: application/json" \
+-d '{
+  "messages": [
+    {"role": "user", "content": "Hello!"}
+  ]
+}'
+```
+Here is an example of sending a user request using a Python script:
+```python
+import openai
+host = "0.0.0.0"
+port = "8170"
+client = openai.Client(base_url=f"http://{host}:{port}/v1", api_key="null")
+
+response = client.chat.completions.create(
+    model="null",
+    messages=[
+        {"role": "system", "content": "I'm a helpful AI assistant."},
+        {"role": "user", "content": "Rewrite Li Bai's 'Quiet Night Thought' as a modern poem"},
+    ],
+    stream=True,
+)
+for chunk in response:
+    if chunk.choices[0].delta:
+        print(chunk.choices[0].delta.content, end='')
+print('\n')
+```
+
+For a description of the OpenAI protocol, refer to the document [OpenAI Chat Completion API](https://platform.openai.com/docs/api-reference/chat/create).
+
+## Parameter Differences
+### Request Parameter Differences
+The differences in request parameters between FastDeploy and the OpenAI protocol are as follows. Other request parameters will be ignored:
+- `prompt` (supported only in the `v1/completions` interface)
+- `messages` (supported only in the `v1/chat/completions` interface)
+- `frequency_penalty`: Optional[float] = 0.0
+- `max_tokens`: Optional[int] = 16
+- `presence_penalty`: Optional[float] = 0.0
+- `stream`: Optional[bool] = False
+- `stream_options`: Optional[StreamOptions] = None
+- `temperature`: Optional[float] = None
+- `top_p`: Optional[float] = None
+- `metadata`: Optional[dict] = None (supported only in `v1/chat/completions` for configuring additional parameters, e.g., `meta_data={"enable_thinking": True}`)
+    - `min_tokens`: Optional[int] = 1 (minimum number of tokens generated)
+    - `reasoning_max_tokens`: Optional[int] = None (maximum number of tokens for reasoning content, defaults to the same as `max_tokens`)
+    - `enable_thinking`: Optional[bool] = True (whether to enable reasoning for models that support deep thinking)
+    - `repetition_penalty`: Optional[float] = None (coefficient for directly penalizing repeated token generation (>1 penalizes repetition, <1 encourages repetition))
+
+> Note: For multimodal models, since the reasoning chain is enabled by default, resulting in overly long outputs, `max_tokens` can be set to the model's maximum output length or the default value can be used.
+
+### Return Field Differences
+
+The additional return fields added by FastDeploy are as follows:
+
+- `arrival_time`: Returns the cumulative time taken for all tokens
+- `reasoning_content`: The returned result of the reasoning chain
+
+Overview of return parameters:
+```python
+ChatCompletionStreamResponse:
+    id: str
+    object: str = "chat.completion.chunk"
+    created: int = Field(default_factory=lambda: int(time.time()))
+    model: str
+    choices: List[ChatCompletionResponseStreamChoice]
+ ChatCompletionResponseStreamChoice:
+    index: int
+    delta: DeltaMessage
+    finish_reason: Optional[Literal["stop", "length"]] = None
+    arrival_time: Optional[float] = None
+DeltaMessage:
+    role: Optional[str] = None
+    content: Optional[str] = None
+    token_ids: Optional[List[int]] = None
+    reasoning_content: Optional[str] = None
+```