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110 lines
3.8 KiB
TOML
110 lines
3.8 KiB
TOML
# QUICKSTART:
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# Copy this file to .secrets.toml in the same folder.
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# The minimum workable settings - set openai.key to your API key.
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# Set github.deployment_type to "user" and github.user_token to your GitHub personal access token.
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# This will allow you to run the CLI scripts in the scripts/ folder and the github_polling server.
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#
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# See README for details about GitHub App deployment.
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[openai]
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key = "" # Acquire through https://platform.openai.com
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#org = "<ORGANIZATION>" # Optional, may be commented out.
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# Uncomment the following for Azure OpenAI
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#api_type = "azure"
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#api_version = '2023-05-15' # Check Azure documentation for the current API version
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#api_base = "" # The base URL for your Azure OpenAI resource. e.g. "https://<your resource name>.openai.azure.com"
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#deployment_id = "" # The deployment name you chose when you deployed the engine
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#fallback_deployments = [] # For each fallback model specified in configuration.toml in the [config] section, specify the appropriate deployment_id
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[pinecone]
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api_key = "..."
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environment = "gcp-starter"
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[anthropic]
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key = "" # Optional, uncomment if you want to use Anthropic. Acquire through https://www.anthropic.com/
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[cohere]
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key = "" # Optional, uncomment if you want to use Cohere. Acquire through https://dashboard.cohere.ai/
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[replicate]
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key = "" # Optional, uncomment if you want to use Replicate. Acquire through https://replicate.com/
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[groq]
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key = "" # Acquire through https://console.groq.com/keys
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[xai]
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key = "" # Optional, uncomment if you want to use xAI. Acquire through https://console.x.ai/
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[huggingface]
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key = "" # Optional, uncomment if you want to use Huggingface Inference API. Acquire through https://huggingface.co/docs/api-inference/quicktour
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api_base = "" # the base url for your huggingface inference endpoint
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[ollama]
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api_base = "" # the base url for your local Llama 2, Code Llama, and other models inference endpoint. Acquire through https://ollama.ai/
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[vertexai]
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vertex_project = "" # the google cloud platform project name for your vertexai deployment
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vertex_location = "" # the google cloud platform location for your vertexai deployment
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[google_ai_studio]
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gemini_api_key = "" # the google AI Studio API key
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[github]
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# ---- Set the following only for deployment type == "user"
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user_token = "" # A GitHub personal access token with 'repo' scope.
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deployment_type = "user" #set to user by default
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# ---- Set the following only for deployment type == "app", see README for details.
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private_key = """\
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-----BEGIN RSA PRIVATE KEY-----
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<GITHUB PRIVATE KEY>
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-----END RSA PRIVATE KEY-----
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"""
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app_id = 123456 # The GitHub App ID, replace with your own.
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webhook_secret = "<WEBHOOK SECRET>" # Optional, may be commented out.
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[gitlab]
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# Gitlab personal access token
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personal_access_token = ""
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shared_secret = "" # webhook secret
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[bitbucket]
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# For Bitbucket authentication
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auth_type = "bearer" # "bearer" or "basic"
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# For bearer token authentication
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bearer_token = ""
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# For basic authentication (uses token only)
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basic_token = ""
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[bitbucket_server]
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# For Bitbucket Server bearer token
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bearer_token = ""
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webhook_secret = ""
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# For Bitbucket app
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app_key = ""
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base_url = ""
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[azure_devops]
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# For Azure devops personal access token
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org = ""
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pat = ""
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[azure_devops_server]
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# For Azure devops Server basic auth - configured in the webhook creation
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# Optional, uncomment if you want to use Azure devops webhooks. Value assinged when you create the webhook
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# webhook_username = "<basic auth user>"
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# webhook_password = "<basic auth password>"
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[deepseek]
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key = ""
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[deepinfra]
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key = ""
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[azure_ad]
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# Azure AD authentication for OpenAI services
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client_id = "" # Your Azure AD application client ID
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client_secret = "" # Your Azure AD application client secret
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tenant_id = "" # Your Azure AD tenant ID
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api_base = "" # Your Azure OpenAI service base URL (e.g., https://openai.xyz.com/) |