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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"]) |  | ||||||
| ``` | ``` | ||||||
|  | @ -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?")) | ||||||
| ``` | ``` | ||||||
| 
 | 
 | ||||||
|  |  | ||||||
|  | @ -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 | ||||||
|  | @ -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.") | ||||||
|  |  | ||||||
|  | @ -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" | ||||||
|  |  | ||||||
|  | @ -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) | ||||||
|  |  | ||||||
|  | @ -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(): | ||||||
|  |  | ||||||
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