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# Conflicts: # pr_agent/tools/pr_description.py
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@ -16,6 +16,10 @@ key = "" # Acquire through https://platform.openai.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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@ -24,6 +28,14 @@ key = "" # Optional, uncomment if you want to use Cohere. Acquire through https:
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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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[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 huggingface inference endpoint
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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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@ -43,5 +55,12 @@ webhook_secret = "<WEBHOOK SECRET>" # Optional, may be commented out.
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personal_access_token = ""
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[bitbucket]
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# Bitbucket personal bearer token
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# For Bitbucket personal/repository bearer token
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bearer_token = ""
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# For Bitbucket app
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app_key = ""
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base_url = ""
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[litellm]
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LITELLM_TOKEN = "" # see https://docs.litellm.ai/docs/debugging/hosted_debugging for details and instructions on how to get a token
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@ -10,8 +10,8 @@ use_repo_settings_file=true
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ai_timeout=180
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max_description_tokens = 500
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max_commits_tokens = 500
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litellm_debugger=false
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secret_provider="google_cloud_storage"
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cli_mode=false
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[pr_reviewer] # /review #
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require_focused_review=false
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@ -87,4 +87,27 @@ polling_interval_seconds = 30
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[local]
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# LocalGitProvider settings - uncomment to use paths other than default
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# description_path= "path/to/description.md"
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# review_path= "path/to/review.md"
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# review_path= "path/to/review.md"
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[gerrit]
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# endpoint to the gerrit service
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# url = "ssh://gerrit.example.com:29418"
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# user for gerrit authentication
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# user = "ai-reviewer"
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# patch server where patches will be saved
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# patch_server_endpoint = "http://127.0.0.1:5000/patch"
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# token to authenticate in the patch server
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# patch_server_token = ""
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[litellm]
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#use_client = false
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[pr_similar_issue]
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skip_comments = false
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force_update_dataset = false
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max_issues_to_scan = 500
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[pinecone]
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# fill and place in .secrets.toml
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#api_key = ...
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# environment = "gcp-starter"
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