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9.4 KiB
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{"repo": "agentuniverse-ai/agentuniverse", "files": {"examples/sample_apps/toolkit_demo_app/intelligence/agentic/llm/buildin/deepseek/channel/deepseek_v3_official_channel.yaml": {"254ecd280f54c2d2de654bbe5373e9f947d2dedf": {"t": 1785745219.895114, "n": 369, "h": "ba8d548363c680e5", "c": "channel_name: 'deepseek-v3-official'\nchannel_api_key: '${DEEPSEEK_API_KEY}'\nchannel_api_base: 'https://api.deepseek.com/v1'\nchannel_model_name: 'deepseek-chat'\nmodel_support_stream: True\nmodel_support_max_context_length: 65536\nmodel_is_openai_protocol_compatible: True\nmeta_class: 'agentuniverse.llm.llm_channel.deepseek_official_llm_channel.DeepseekOfficialLLMChannel'"}, "2b57498fcf26276f1c6ba74767d66e4ad9eca0b5": {"t": 1785748852.7609286, "n": 369, "h": "ba8d548363c680e5", "c": "channel_name: 'deepseek-v3-official'\nchannel_api_key: '${DEEPSEEK_API_KEY}'\nchannel_api_base: 'https://api.deepseek.com/v1'\nchannel_model_name: 'deepseek-chat'\nmodel_support_stream: True\nmodel_support_max_context_length: 65536\nmodel_is_openai_protocol_compatible: True\nmeta_class: 'agentuniverse.llm.llm_channel.deepseek_official_llm_channel.DeepseekOfficialLLMChannel'"}}, "examples/third_party_examples/apps/primary_chinese_teacher_agent/intelligence/agentic/llm/deepseek_llm.yaml": {"254ecd280f54c2d2de654bbe5373e9f947d2dedf": {"t": 1785745222.0549035, "n": 244, "h": "6ed55cf22d98710a", "c": "name: 'deepseek-llm'\ndescription: 'deepseek-chat'\nmodel_name: 'deepseek-chat'\nmax_tokens: 2000\napi_key: '${DEEPSEEK_API_KEY}'\nmetadata:\n type: 'LLM'\n module: 'agentuniverse.llm.default.deep_seek_openai_style_llm'\n class: 'DefaultDeepSeekLLM'"}, "a09013d12e0cf896cdb3a45458bd20f2bbf0f0f6": {"t": 1785748853.730945, "n": 244, "h": "6ed55cf22d98710a", "c": "name: 'deepseek-llm'\ndescription: 'deepseek-chat'\nmodel_name: 'deepseek-chat'\nmax_tokens: 2000\napi_key: '${DEEPSEEK_API_KEY}'\nmetadata:\n type: 'LLM'\n module: 'agentuniverse.llm.default.deep_seek_openai_style_llm'\n class: 'DefaultDeepSeekLLM'"}}, "docs/guidebook/en/In-Depth_Guides/Components/LLMs/DeepSeek_LLM_Use.md": {"254ecd280f54c2d2de654bbe5373e9f947d2dedf": {"t": 1785746428.7305818, "n": 2879, "h": "7d80c547bdc606dd", "c": "# DeepSeek Usage\n## 1. Create the relevant file.\nCreate a YAML file, for example, user_deepseek_llm.yaml\nPaste the following content into your user_deepseek_llm.yaml file.\n```yaml\nname: 'user_deepseek_llm'\ndescription: 'default default_deepseek_llm llm with spi'\nmodel_name: 'deepseek-chat'\nmax_tokens: 1000\ntemperature: 0.5\napi_key: '${DEEPSEEK_API_KEY}'\napi_base: 'https://api.deepseek.com/v1'\norganization: '${DEEPSEEK_ORGANIZATION}'\nproxy: '${DEEPSEEK_PROXY}'\nstreaming: True\nmetadata:\n type: 'LLM'\n module: 'agentuniverse.llm.default.deep_seek_openai_style_llm'\n class: 'DefaultDeepSeekLLM'\n```\n\n**Note:**\n\nThe model parameters such as `api_key`, `api_base`, `organization`, and `proxy` can be configured in three ways:\n\n1. Direct String Value: Enter the API key string directly in the configuration file.\n\n ```yaml\n api_key: 'sk-xxx'\n ```\n\n2. Environment Variable Placeholder: Use the `${VARIABLE_NAME}` syntax to load from environment variables. When `agentUniverse` is launched, it will automatically read the corresponding value from the environment variables.\n\n ```yaml\n api_key: '${DEEPSEEK_API_KEY}'\n ```\n\n3. Custom Function Loading: Use the `@FUNC` annotation to dynamically load the API key via a custom function at runtime.\n\n ```yaml\n api_key: '@FUNC(load_api_key(model_name=\"deepseek\"))'\n ```\n\n The function needs to be defined in the `YamlFuncExtension` class within the `yaml_func_extension.py` file. You can refer to the example in the sample project's [YamlFuncExtension](../../../../../../examples/sample_standard_app/config/yaml_func_extension.py). When `agentUniverse` loads this configuration:\n - It parses the `@FUNC` annotation.\n - Executes the `load_api_key` function with the corresponding parameters.\n - Replaces the annotation content with the function's return value.\n \n## 2. Environment Setup\nIn the example YAML, model keys and other parameters are configured using environment variable placeholders. The following section will introduce methods for setting environment variables.\n\nMust be configured: DEEPSEEK_API_KEY \nOptional: DEEPSEEK_API_BASE, DEEPSEEK_PROXY, DEEPSEEK_ORGANIZATION\n### 2.1 Configure through Python code\n```python\nimport os\nos.environ['DEEPSEEK_API_KEY'] = 'sk-***'\nos.environ['DEEPSEEK_API_BASE'] = 'https://xxxxxx'\n```\n### 2.2 Configure through the configuration file\nIn the custom_key.toml file under the config directory of the project, add the configuration:\n```toml\nDEEPSEEK_API_KEY=\"sk-******\"\nDEEPSEEK_API_BASE=\"https://xxxxxx\"\nDEEPSEEK_ORGANIZATION = ''\nDEEPSEEK_PROXY = ''\n```\n## 3. Obtaining the DeepSeek API KEY \nPlease refer to the official documentation of DEEPSEEK:https://platform.deepseek.com/api_keys\n\n## 4. Tips\nIn the agentuniverse, we have established an LLM named default_deepseek_llm. Users can directly utilize it after configuring their DEEPSEEK_API_KEY.\n\n"}, "de82bffcf1c28498819bdcafbee8b5146ead7402": {"t": 1785748853.9422274, "n": 2879, "h": "7d80c547bdc606dd", "c": "# DeepSeek Usage\n## 1. Create the relevant file.\nCreate a YAML file, for example, user_deepseek_llm.yaml\nPaste the following content into your user_deepseek_llm.yaml file.\n```yaml\nname: 'user_deepseek_llm'\ndescription: 'default default_deepseek_llm llm with spi'\nmodel_name: 'deepseek-chat'\nmax_tokens: 1000\ntemperature: 0.5\napi_key: '${DEEPSEEK_API_KEY}'\napi_base: 'https://api.deepseek.com/v1'\norganization: '${DEEPSEEK_ORGANIZATION}'\nproxy: '${DEEPSEEK_PROXY}'\nstreaming: True\nmetadata:\n type: 'LLM'\n module: 'agentuniverse.llm.default.deep_seek_openai_style_llm'\n class: 'DefaultDeepSeekLLM'\n```\n\n**Note:**\n\nThe model parameters such as `api_key`, `api_base`, `organization`, and `proxy` can be configured in three ways:\n\n1. Direct String Value: Enter the API key string directly in the configuration file.\n\n ```yaml\n api_key: 'sk-xxx'\n ```\n\n2. Environment Variable Placeholder: Use the `${VARIABLE_NAME}` syntax to load from environment variables. When `agentUniverse` is launched, it will automatically read the corresponding value from the environment variables.\n\n ```yaml\n api_key: '${DEEPSEEK_API_KEY}'\n ```\n\n3. Custom Function Loading: Use the `@FUNC` annotation to dynamically load the API key via a custom function at runtime.\n\n ```yaml\n api_key: '@FUNC(load_api_key(model_name=\"deepseek\"))'\n ```\n\n The function needs to be defined in the `YamlFuncExtension` class within the `yaml_func_extension.py` file. You can refer to the example in the sample project's [YamlFuncExtension](../../../../../../examples/sample_standard_app/config/yaml_func_extension.py). When `agentUniverse` loads this configuration:\n - It parses the `@FUNC` annotation.\n - Executes the `load_api_key` function with the corresponding parameters.\n - Replaces the annotation content with the function's return value.\n \n## 2. Environment Setup\nIn the example YAML, model keys and other parameters are configured using environment variable placeholders. The following section will introduce methods for setting environment variables.\n\nMust be configured: DEEPSEEK_API_KEY \nOptional: DEEPSEEK_API_BASE, DEEPSEEK_PROXY, DEEPSEEK_ORGANIZATION\n### 2.1 Configure through Python code\n```python\nimport os\nos.environ['DEEPSEEK_API_KEY'] = 'sk-***'\nos.environ['DEEPSEEK_API_BASE'] = 'https://xxxxxx'\n```\n### 2.2 Configure through the configuration file\nIn the custom_key.toml file under the config directory of the project, add the configuration:\n```toml\nDEEPSEEK_API_KEY=\"sk-******\"\nDEEPSEEK_API_BASE=\"https://xxxxxx\"\nDEEPSEEK_ORGANIZATION = ''\nDEEPSEEK_PROXY = ''\n```\n## 3. Obtaining the DeepSeek API KEY \nPlease refer to the official documentation of DEEPSEEK:https://platform.deepseek.com/api_keys\n\n## 4. Tips\nIn the agentuniverse, we have established an LLM named default_deepseek_llm. Users can directly utilize it after configuring their DEEPSEEK_API_KEY.\n\n"}, "34ad6b09a91735e2ab1db39e259f1f09825dd3cb": {"t": 1785748855.1887944, "n": 1192, "h": "26efd067afa90959", "c": "# DeepSeek Usage\n## 1. Create the relevant file.\nCreate a YAML file, for example, user_deepseek_llm.yaml\nPaste the following content into your user_deepseek_llm.yaml file.\n```yaml\nname: 'user_deepseek_llm'\ndescription: 'default default_deepseek_llm llm with spi'\nmodel_name: 'deepseek-chat'\nmax_tokens: 1000\nmetadata:\n type: 'LLM'\n module: 'agentuniverse.llm.default.deep_seek_openai_style_llm'\n class: 'DefaultDeepSeekLLM'\n```\n## 2. Environment Setup\nMust be configured: DEEPSEEK_API_KEY \nOptional: DEEPSEEK_API_BASE\n### 2.1 Configure through Python code\n```python\nimport os\nos.environ['DEEPSEEK_API_KEY'] = 'sk-***'\nos.environ['DEEPSEEK_API_BASE'] = 'https://xxxxxx'\n```\n### 2.2 Configure through the configuration file\nIn the custom_key.toml file under the config directory of the project, add the configuration:\n```toml\nDEEPSEEK_API_KEY=\"sk-******\"\nDEEPSEEK_API_BASE=\"https://xxxxxx\"\n```\n## 3. Obtaining the DeepSeek API KEY \nPlease refer to the official documentation of DEEPSEEK:https://platform.deepseek.com/api_keys\n\n## 4. Tips\nIn the agentuniverse, we have established an LLM named default_deepseek_llm. Users can directly utilize it after configuring their DEEPSEEK_API_KEY.\n\n"}}}} |