Fixes before release (#254)

* Fixes before release
This commit is contained in:
Aymeric Roucher 2025-01-17 20:20:28 +01:00 committed by GitHub
parent a4d029da88
commit e3ae1800e2
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7 changed files with 16 additions and 14 deletions

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@ -136,8 +136,8 @@ messages = [
{"role": "user", "content": "No need to help, take it easy."}, {"role": "user", "content": "No need to help, take it easy."},
] ]
model = LiteLLMModel("anthropic/claude-3-5-sonnet-latest", temperature=0.2) model = LiteLLMModel("anthropic/claude-3-5-sonnet-latest", temperature=0.2, max_tokens=10)
print(model(messages, max_tokens=10)) print(model(messages))
``` ```
[[autodoc]] LiteLLMModel [[autodoc]] LiteLLMModel
@ -145,12 +145,13 @@ print(model(messages, max_tokens=10))
### OpenAiServerModel ### OpenAiServerModel
This class lets you call any OpenAIServer compatible model. This class lets you call any OpenAIServer compatible model.
Here's how you can set it: Here's how you can set it (you can customise the `api_base` url to point to another server):
```py ```py
from smolagents import OpenAIServerModel
model = OpenAIServerModel( model = OpenAIServerModel(
model_id="gpt-4o", model_id="gpt-4o",
base_url="https://api.openai.com/v1", api_base="https://api.openai.com/v1",
api_key=os.environ["OPENAI_API_KEY"], api_key=os.environ["OPENAI_API_KEY"],
) )
model=LiteLLMModel("gpt-4o", api_key=os.environ["OPENAI_API_KEY"])
``` ```

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@ -173,9 +173,9 @@ Transformers 附带了一个用于增强 agent 的默认工具箱,您可以在
您可以通过调用 [`load_tool`] 函数和要执行的任务手动使用工具。 您可以通过调用 [`load_tool`] 函数和要执行的任务手动使用工具。
```python ```python
from smolagents import load_tool from smolagents import DuckDuckGoSearchTool
search_tool = load_tool("web_search") search_tool = DuckDuckGoSearchTool()
print(search_tool("Who's the current president of Russia?")) print(search_tool("Who's the current president of Russia?"))
``` ```

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@ -136,8 +136,8 @@ messages = [
{"role": "user", "content": "No need to help, take it easy."}, {"role": "user", "content": "No need to help, take it easy."},
] ]
model = LiteLLMModel("anthropic/claude-3-5-sonnet-latest", temperature=0.2) model = LiteLLMModel("anthropic/claude-3-5-sonnet-latest", temperature=0.2, max_tokens=10)
print(model(messages, max_tokens=10)) print(model(messages))
``` ```
[[autodoc]] LiteLLMModel [[autodoc]] LiteLLMModel

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@ -23,5 +23,5 @@ mcp_server_params = StdioServerParameters(
with ToolCollection.from_mcp(mcp_server_params) as tool_collection: with ToolCollection.from_mcp(mcp_server_params) as tool_collection:
# print(tool_collection.tools[0](request={"term": "efficient treatment hangover"})) # print(tool_collection.tools[0](request={"term": "efficient treatment hangover"}))
agent = CodeAgent(tools=tool_collection.tools, model=HfApiModel()) agent = CodeAgent(tools=tool_collection.tools, model=HfApiModel(), max_steps=4)
agent.run("Find studies about hangover?") agent.run("Find me one risk associated with drinking alcohol regularly on low doses for humans.")

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@ -37,7 +37,8 @@ litellm = [
"litellm>=1.55.10", "litellm>=1.55.10",
] ]
mcp = [ mcp = [
"mcpadapt>=0.0.6" "mcpadapt>=0.0.6",
"mcp",
] ]
openai = [ openai = [
"openai>=1.58.1" "openai>=1.58.1"

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@ -43,7 +43,7 @@ class E2BExecutor:
# ) # )
# print("Installation of agents package finished.") # print("Installation of agents package finished.")
self.logger = logger self.logger = logger
additional_imports = additional_imports + ["pickle5"] additional_imports = additional_imports + ["pickle5", "smolagents"]
if len(additional_imports) > 0: if len(additional_imports) > 0:
execution = self.sbx.commands.run( execution = self.sbx.commands.run(
"pip install " + " ".join(additional_imports) "pip install " + " ".join(additional_imports)

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@ -85,7 +85,7 @@ class TestDocs:
def setup_class(cls): def setup_class(cls):
cls._tmpdir = tempfile.mkdtemp() cls._tmpdir = tempfile.mkdtemp()
cls.launch_args = ["python3"] cls.launch_args = ["python3"]
cls.docs_dir = Path(__file__).parent.parent / "docs" / "source" cls.docs_dir = Path(__file__).parent.parent / "docs" / "source" / "en"
cls.extractor = DocCodeExtractor() cls.extractor = DocCodeExtractor()
if not cls.docs_dir.exists(): if not cls.docs_dir.exists():