Merge branch 'modelscope:main' into main

.github/workflows/unittest.yml

@@ -24,9 +24,9 @@ jobs:
     - name: Install Minimal Dependencies
       run: |
         pip install -q -e .
-    - name: Run import tests
+    - name: Run minimal import tests
       run: |
-        python -c "import agentscope; print(agentscope.__version__)"
+        python tests/minimal.py
     - name: Install Full Dependencies
       run: |
         pip install -q -e .[full]

docs/sphinx_doc/en/source/tutorial/104-usecase.md

@@ -291,7 +291,7 @@ With the game logic and agents set up, you're ready to run the Werewolf game. By
 
 ```bash
 cd examples/game_werewolf
-python main.py  # Assuming the pipeline is implemented in main.py
+python werewolf.py  # Assuming the pipeline is implemented in werewolf.py
 ```
 
 It is recommended that you start the game in [AgentScope Studio](https://modelscope.github.io/agentscope/en/tutorial/209-gui.html), where you

docs/sphinx_doc/zh_CN/source/tutorial/104-usecase.md

@@ -170,7 +170,7 @@ for i in range(1, MAX_GAME_ROUND + 1):
     # Night phase: werewolves discuss
     hint = HostMsg(content=Prompts.to_wolves.format(n2s(wolves)))
     with msghub(wolves, announcement=hint) as hub:
-      	set_parsers(wolves, Prompts.wolves_discuss_parser)
+        set_parsers(wolves, Prompts.wolves_discuss_parser)
         for _ in range(MAX_WEREWOLF_DISCUSSION_ROUND):
             x = sequentialpipeline(wolves)
             if x.metadata.get("finish_discussion", False):
@@ -295,7 +295,7 @@ for i in range(1, MAX_GAME_ROUND + 1):
 
 ```bash
 cd examples/game_werewolf
-python main.py  # Assuming the pipeline is implemented in main.py
+python werewolf.py  # Assuming the pipeline is implemented in werewolf.py
 ```
 
 建议您在在 [AgentScope Studio](https://modelscope.github.io/agentscope/zh_CN/tutorial/209-gui.html) 中启动游戏，在对应的链接中您将看到下面的内容输出。

docs/sphinx_doc/zh_CN/source/tutorial/209-gui.md

@@ -70,7 +70,7 @@ agentscope.init(
     # ...
     project="xxx",
     name="xxx",
-    studio_url="http://127.0.0.1：5000"          # AgentScope Studio 的 URL
+    studio_url="http://127.0.0.1:5000"          # AgentScope Studio 的 URL
 )
 ```
 

src/agentscope/models/ollama_model.py

@@ -359,7 +359,7 @@ def format(
         system_content = "\n".join(system_content_template)
 
         system_message = {
-            "role": "system",
+            "role": "user",
             "content": system_content,
         }
 

src/agentscope/models/post_model.py

@@ -8,7 +8,6 @@
 import requests
 from loguru import logger
 
-from .gemini_model import GeminiChatWrapper
 from .openai_model import OpenAIChatWrapper
 from .model import ModelWrapperBase, ModelResponse
 from ..constants import _DEFAULT_MAX_RETRIES
@@ -221,6 +220,8 @@ def format(
 
         # Gemini
         elif model_name and model_name.startswith("gemini"):
+            from .gemini_model import GeminiChatWrapper
+
             return GeminiChatWrapper.format(*args)
 
         # Include DashScope, ZhipuAI, Ollama, the other models supported by

tests/format_test.py

@@ -283,7 +283,7 @@ def test_ollama_chat(self) -> None:
         # correct format
         ground_truth = [
             {
-                "role": "system",
+                "role": "user",
                 "content": (
                     "You are a helpful assistant\n"
                     "\n"

tests/minimal.py

@@ -0,0 +1,51 @@
+# -*- coding: utf-8 -*-
+"""
+Minimal case for agentscope
+"""
+import agentscope
+from agentscope.agents import DialogAgent
+
+print(agentscope.__version__)
+agentscope.init(
+    project="minimal",
+    model_configs=[
+        {
+            "model_type": "dashscope_chat",
+            "config_name": "qwen",
+            "model_name": "qwen-max",
+            "api_key": "xxx",
+        },
+        {
+            "model_type": "openai_chat",
+            "config_name": "gpt-4",
+            "model_name": "gpt-4",
+            "api_key": "xxx",
+            "organization": "xxx",
+            "generate_args": {"temperature": 0.5},
+        },
+        {
+            "model_type": "post_api_chat",
+            "config_name": "my_post_api",
+            "api_url": "https://xxx",
+            "headers": {},
+            "json_args": {},
+        },
+    ],
+)
+a = DialogAgent(
+    name="A",
+    sys_prompt="You are a helpful assistant.",
+    model_config_name="my_post_api",
+)
+
+b = DialogAgent(
+    name="B",
+    sys_prompt="You are a helpful assistant.",
+    model_config_name="qwen",
+)
+
+c = DialogAgent(
+    name="C",
+    sys_prompt="You are a helpful assistant.",
+    model_config_name="gpt-4",
+)