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feat: update skill specification
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莘权 马
parent
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commit
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2 changed files with 189 additions and 85 deletions
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@ -1,72 +1,149 @@
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skillapi: "0.1.0"
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info:
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title: "Agent Skill Specification"
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version: "1.0"
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entities:
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Assistant:
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skills:
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- name: text_to_speech
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description: Text-to-speech
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id: text_to_speech.text_to_speech
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x-prerequisite:
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- name: AZURE_TTS_SUBSCRIPTION_KEY
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description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
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- name: AZURE_TTS_REGION
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description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
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arguments:
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text: 'The text used for voice conversion. Required.'
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lang: 'The value can contain a language code such as en (English), or a locale such as en-US (English - United States). The optional parameter are "English", "Chinese". Default value: "Chinese".'
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voice: 'Default value: "zh-CN-XiaomoNeural".'
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style: 'Speaking style to express different emotions like cheerfulness, empathy, and calm. The optional parameter values are "affectionate", "angry", "calm", "cheerful", "depressed", "disgruntled", "embarrassed", "envious", "fearful", "gentle", "sad", "serious". Default value: "affectionate".'
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role: 'With roles, the same voice can act as a different age and gender. The optional parameter values are "Girl", "Boy", "OlderAdultFemale", "OlderAdultMale", "SeniorFemale", "SeniorMale", "YoungAdultFemale", "YoungAdultMale". Default value: "Girl".'
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examples:
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- ask: 'A girl says "hello world"'
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answer: 'text_to_speech(text="hello world", role="Girl")'
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- ask: 'A boy affectionate says "hello world"'
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answer: 'text_to_speech(text="hello world", role="Boy", style="affectionate")'
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- ask: 'A boy says "你好"'
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answer: 'text_to_speech(text="你好", role="Boy", lang="Chinese")'
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- ask: 'How to speak "你好"?'
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answer: 'text_to_speech(text="你好", lang="Chinese")'
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returns:
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type: string
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format: base64
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summary: assistant
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description: assistant
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skills:
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- name: text_to_speech
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description: Text-to-speech
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id: text_to_speech.text_to_speech
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required:
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oneOf:
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- schema:
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type: object
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properties:
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AZURE_TTS_SUBSCRIPTION_KEY:
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type: string
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description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
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AZURE_TTS_REGION:
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type: string
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description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
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- schema:
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type: object
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properties:
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IFLYTEK_APP_ID:
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type: string
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description: "Application ID is used to access your iFlyTek service API, see: `https://console.xfyun.cn/services/tts`"
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IFLYTEK_API_KEY:
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type: string
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description: "WebAPI argument, see: `https://console.xfyun.cn/services/tts`"
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IFLYTEK_API_SECRET:
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type: string
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description: "WebAPI argument, see: `https://console.xfyun.cn/services/tts`"
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parameters:
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text:
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description: 'The text used for voice conversion.'
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required: true
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type: string
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lang:
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description: 'The value can contain a language code such as en (English), or a locale such as en-US (English - United States).'
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type: string
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enum:
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- English
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- Chinese
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default: Chinese
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voice:
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description: Name of voice styles
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type: string
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default: zh-CN-XiaomoNeural
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style:
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type: string
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description: Speaking style to express different emotions like cheerfulness, empathy, and calm.
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enum:
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- affectionate
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- angry
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- calm
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- cheerful
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- depressed
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- disgruntled
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- embarrassed
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- envious
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- fearful
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- gentle
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- sad
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- serious
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default: affectionate
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role:
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type: string
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description: With roles, the same voice can act as a different age and gender.
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enum:
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- Girl
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- Boy
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- OlderAdultFemale
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- OlderAdultMale
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- SeniorFemale
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- SeniorMale
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- YoungAdultFemale
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- YoungAdultMale
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default: Girl
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examples:
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- ask: 'A girl says "hello world"'
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answer: 'text_to_speech(text="hello world", role="Girl")'
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- ask: 'A boy affectionate says "hello world"'
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answer: 'text_to_speech(text="hello world", role="Boy", style="affectionate")'
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- ask: 'A boy says "你好"'
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answer: 'text_to_speech(text="hello world", role="Boy", lang="Chinese")'
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returns:
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type: string
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format: base64
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- name: text_to_image
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description: Create a drawing based on the text.
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id: text_to_image.text_to_image
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x-prerequisite:
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- name: OPENAI_API_KEY
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description: "OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`"
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- name: METAGPT_TEXT_TO_IMAGE_MODEL_URL
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description: "Model url."
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arguments:
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text: 'The text used for image conversion. Required.'
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size_type: 'Default value: "512x512".'
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examples:
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- ask: 'Draw a girl'
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answer: 'text_to_image(text="Draw a girl", size_type="512x512")'
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- ask: 'Draw an apple'
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answer: 'text_to_image(text="Draw an apple", size_type="512x512")'
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- ask: 'Draw an apple picture'
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answer: 'text_to_image(text="Draw an apple", size_type="512x512")'
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- ask: 'Draw an apple image'
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answer: 'text_to_image(text="Draw an apple", size_type="512x512")'
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returns:
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type: string
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format: base64
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- name: text_to_image
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description: Create a drawing based on the text.
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id: text_to_image.text_to_image
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required:
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oneOf:
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- name: OPENAI_API_KEY
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type: string
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description: "OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`"
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- name: METAGPT_TEXT_TO_IMAGE_MODEL_URL
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type: string
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description: "Model url."
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parameters:
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text:
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description: 'The text used for image conversion.'
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type: string
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required: true
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size_type:
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description: size type
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type: string
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default: "512x512"
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examples:
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- ask: 'Draw a girl'
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answer: 'text_to_image(text="Draw a girl", size_type="512x512")'
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- ask: 'Draw an apple'
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answer: 'text_to_image(text="Draw an apple", size_type="512x512")'
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returns:
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type: string
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format: base64
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- name: web_search
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description: Perform Google searches to provide real-time information.
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id: web_search.web_search
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x-prerequisite:
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- name: SEARCH_ENGINE
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description: "Supported values: serpapi/google/serper/ddg"
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- name: SERPER_API_KEY
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description: "SERPER API KEY, For more details, checkout: `https://serper.dev/api-key`"
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arguments:
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query: 'The search query. Required.'
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max_results: 'The number of search results to retrieve. Default value: 6.'
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examples:
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- ask: 'Search for information about artificial intelligence'
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answer: 'web_search(query="Search for information about artificial intelligence", max_results=6)'
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- ask: 'Find news articles about climate change'
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answer: 'web_search(query="Find news articles about climate change", max_results=6)'
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returns:
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type: string
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- name: web_search
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description: Perform Google searches to provide real-time information.
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id: web_search.web_search
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required:
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- name: SEARCH_ENGINE
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type: string
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description: "Supported values: serpapi/google/serper/ddg"
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- name: SERPER_API_KEY
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type: string
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description: "SERPER API KEY, For more details, checkout: `https://serper.dev/api-key`"
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parameters:
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query:
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type: string
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description: 'The search query.'
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required: true
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max_results:
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type: number
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default: 6
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description: 'The number of search results to retrieve.'
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examples:
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- ask: 'Search for information about artificial intelligence'
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answer: 'web_search(query="Search for information about artificial intelligence", max_results=6)'
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- ask: 'Find news articles about climate change'
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answer: 'web_search(query="Find news articles about climate change", max_results=6)'
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returns:
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type: string
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@ -7,10 +7,10 @@
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@Desc : Skill YAML Configuration Loader.
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"""
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from pathlib import Path
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from typing import Dict, List, Optional
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from typing import Dict, List, Optional, Union
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import yaml
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from pydantic import BaseModel, Field
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from pydantic import BaseModel
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from metagpt.config import CONFIG
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@ -25,29 +25,43 @@ class Returns(BaseModel):
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format: Optional[str] = None
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class Prerequisite(BaseModel):
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name: str
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type: Optional[str] = None
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description: Optional[str] = None
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default: Optional[str] = None
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class Parameter(BaseModel):
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type: str
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description: str = None
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class Skill(BaseModel):
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name: str
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description: str
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id: str
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x_prerequisite: Optional[List[Prerequisite]] = Field(default=None, alias="x-prerequisite")
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arguments: Dict
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description: str = None
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id: str = None
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required: Optional[Union[List, Dict]] = None
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parameters: Dict[str, Parameter] = None
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examples: List[Example]
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returns: Returns
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@property
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def arguments(self) -> Dict:
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if not self.parameters:
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return {}
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ret = {}
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for k, v in self.parameters.items():
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ret[k] = v.description if v.description else ""
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return ret
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class EntitySkills(BaseModel):
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class Entity(BaseModel):
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name: str = None
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skills: List[Skill]
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class Components(BaseModel):
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pass
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class SkillsDeclaration(BaseModel):
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entities: Dict[str, EntitySkills]
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skillapi: str
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entities: Dict[str, Entity]
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components: Components = None
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class SkillLoader:
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@ -60,8 +74,8 @@ class SkillLoader:
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def get_skill_list(self, entity_name: str = "Assistant") -> Dict:
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"""Return the skill name based on the skill description."""
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entity_skills = self.get_entity(entity_name)
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if not entity_skills:
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entity = self.get_entity(entity_name)
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if not entity:
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return {}
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agent_skills = CONFIG.agent_skills
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@ -73,7 +87,7 @@ class SkillLoader:
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names = [AgentSkill(**i).name for i in agent_skills]
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description_to_name_mappings = {}
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for s in entity_skills.skills:
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for s in entity.skills:
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if s.name not in names:
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continue
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description_to_name_mappings[s.description] = s.name
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@ -89,8 +103,21 @@ class SkillLoader:
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if sk.name == name:
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return sk
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def get_entity(self, name) -> EntitySkills:
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def get_entity(self, name) -> Entity:
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"""Return a list of skills for the entity."""
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if not self._skills:
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return None
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return self._skills.entities.get(name)
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if __name__ == "__main__":
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CONFIG.agent_skills = [
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{"id": 1, "name": "text_to_speech", "type": "builtin", "config": {}, "enabled": True},
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{"id": 2, "name": "text_to_image", "type": "builtin", "config": {}, "enabled": True},
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{"id": 3, "name": "ai_call", "type": "builtin", "config": {}, "enabled": True},
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{"id": 3, "name": "data_analysis", "type": "builtin", "config": {}, "enabled": True},
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{"id": 5, "name": "crawler", "type": "builtin", "config": {"engine": "ddg"}, "enabled": True},
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{"id": 6, "name": "knowledge", "type": "builtin", "config": {}, "enabled": True},
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]
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loader = SkillLoader()
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print(loader.get_skill_list())
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