Bump version to v0.2.33 (#2717)

fastchat/__init__.py

@@ -1 +1 @@
-__version__ = "0.2.32"
+__version__ = "0.2.33"

fastchat/serve/gradio_web_server.py

@@ -610,7 +610,7 @@ def build_single_model_ui(models, add_promotion_links=False):
 # 🏔️ Chat with Open Large Language Models
 {promotion}
 
-## 👉 Choose any model to chat
+## Choose any model to chat
 """
 
     state = gr.State()
@@ -635,7 +635,7 @@ def build_single_model_ui(models, add_promotion_links=False):
         with gr.Column(scale=20):
             textbox = gr.Textbox(
                 show_label=False,
-                placeholder="Enter your prompt here and press ENTER",
+                placeholder="👉 Enter your prompt and press ENTER",
                 container=False,
                 elem_id="input_box",
             )

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "fschat"
-version = "0.2.32"
+version = "0.2.33"
 description = "An open platform for training, serving, and evaluating large language model based chatbots."
 readme = "README.md"
 requires-python = ">=3.8"

tests/test_openai_api.py

@@ -22,17 +22,28 @@ def test_list_models():
 def test_completion(model, logprob):
     prompt = "Once upon a time"
     completion = openai.Completion.create(
-        model=model, prompt=prompt, logprobs=logprob, max_tokens=64
+        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}", flush=True)
+        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
+        model=model,
+        prompt=prompt,
+        max_tokens=64,
+        stream=True,
+        temperature=0,
     )
     print(prompt, end="")
     for chunk in res:
@@ -49,14 +60,18 @@ def test_embedding(model):
 
 def test_chat_completion(model):
     completion = openai.ChatCompletion.create(
-        model=model, messages=[{"role": "user", "content": "Hello! What is your name?"}]
+        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)
+    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)