mirror of
https://github.com/FoundationAgents/MetaGPT.git
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100 lines
3.4 KiB
YAML
100 lines
3.4 KiB
YAML
llm:
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api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options
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base_url: "YOUR_BASE_URL"
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api_key: "YOUR_API_KEY"
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model: "gpt-4-turbo-preview" # or gpt-3.5-turbo-1106 / gpt-4-1106-preview
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proxy: "YOUR_PROXY" # for LLM API requests
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# timeout: 600 # Optional. If set to 0, default value is 300.
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pricing_plan: "" # Optional. If invalid, it will be automatically filled in with the value of the `model`.
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# Azure-exclusive pricing plan mappings：
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# - gpt-3.5-turbo 4k: "gpt-3.5-turbo-1106"
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# - gpt-4-turbo: "gpt-4-turbo-preview"
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# - gpt-4-turbo-vision: "gpt-4-vision-preview"
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# - gpt-4 8k: "gpt-4"
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# See for more: https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/
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# Role's custom configuration
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roles:
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- role: "ProductManager" # role's className or role's role_id
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llm:
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api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options
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base_url: "YOUR_BASE_URL"
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api_key: "YOUR_API_KEY"
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proxy: "YOUR_PROXY" # for LLM API requests
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model: "gpt-4-turbo-1106"
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- role: "Architect"
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llm:
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api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options
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base_url: "YOUR_BASE_URL"
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api_key: "YOUR_API_KEY"
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proxy: "YOUR_PROXY" # for LLM API requests
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model: "gpt-35-turbo"
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- role: "ProjectManager"
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llm:
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api_type: "azure"
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base_url: "YOUR_BASE_URL"
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api_key: "YOUR_API_KEY"
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api_version: "YOUR_API_VERSION"
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model: "gpt-4-1106"
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- role: "Engineer"
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llm:
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api_type: "azure"
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base_url: "YOUR_BASE_URL"
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api_key: "YOUR_API_KEY"
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api_version: "YOUR_API_VERSION"
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model: "gpt-35-turbo-1106"
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repair_llm_output: true # when the output is not a valid json, try to repair it
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proxy: "YOUR_PROXY" # for tools like requests, playwright, selenium, etc.
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search:
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api_type: "google"
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api_key: "YOUR_API_KEY"
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cse_id: "YOUR_CSE_ID"
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browser:
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engine: "playwright" # playwright/selenium
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browser_type: "chromium" # playwright: chromium/firefox/webkit; selenium: chrome/firefox/edge/ie
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mermaid:
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engine: "pyppeteer"
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path: "/Applications/Google Chrome.app"
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redis:
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host: "YOUR_HOST"
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port: 32582
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password: "YOUR_PASSWORD"
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db: "0"
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s3:
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access_key: "YOUR_ACCESS_KEY"
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secret_key: "YOUR_SECRET_KEY"
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endpoint: "YOUR_ENDPOINT"
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secure: false
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bucket: "test"
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exp_pool:
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enabled: false
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enable_read: false
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enable_write: false
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persist_path: .chroma_exp_data # The directory.
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retrieval_type: bm25 # Default is `bm25`, can be set to `chroma` for vector storage, which requires setting up embedding.
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use_llm_ranker: true # Default is `true`, it will use LLM Reranker to get better result.
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collection_name: experience_pool # When `retrieval_type` is `chroma`, `collection_name` is the collection name in chromadb.
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role_zero:
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enable_longterm_memory: false # Whether to use long-term memory. Default is `false`.
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longterm_memory_persist_path: .role_memory_data # The directory to save data.
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memory_k: 200 # The capacity of short-term memory.
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similarity_top_k: 5 # The number of long-term memories to retrieve.
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use_llm_ranker: false # Whether to use LLM Reranker to get better result. Default is `false`.
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azure_tts_subscription_key: "YOUR_SUBSCRIPTION_KEY"
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azure_tts_region: "eastus"
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iflytek_api_id: "YOUR_APP_ID"
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iflytek_api_key: "YOUR_API_KEY"
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iflytek_api_secret: "YOUR_API_SECRET"
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metagpt_tti_url: "YOUR_MODEL_URL"
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