e588d97e0f
- Updated .env.example and config.yaml to include observability settings. - Added a new Phoenix service in docker-compose.yml for self-hosted tracing. - Enhanced README.md with instructions on enabling and using observability features. - Implemented tracing in the pipeline, including job spans and LLM stage spans. - Introduced ObservabilitySettings class in config.py for better configuration management. - Updated job.py and resources.py to support tracing without affecting fault isolation. - Minor adjustments to other files for compatibility with the new observability features.
27 lines
1.0 KiB
Plaintext
27 lines
1.0 KiB
Plaintext
# Gemini API key used by Weaviate's Gemini vectorizer backend and the Gemini LLM provider
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GEMINI_API_KEY=your-gemini-api-key
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# Optional LLM provider keys (required when config.yaml llm.provider is openai / anthropic)
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OPENAI_API_KEY=your-openai-api-key
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ANTHROPIC_API_KEY=your-anthropic-api-key
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# Weaviate connection (local Docker instance)
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WEAVIATE_HOST=localhost
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WEAVIATE_HTTP_PORT=8080
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WEAVIATE_GRPC_PORT=50051
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# Microsoft SQL Server connection
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SQL_DRIVER=ODBC Driver 17 for SQL Server
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SQL_SERVER=localhost
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SQL_DATABASE=your-database-name
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SQL_USERNAME=your-sql-username
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SQL_PASSWORD=your-sql-password
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# Observability (optional; see config.yaml observability: / README "Observability").
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# Every var below overrides the matching config.yaml value; unset = use config.yaml
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# (which defaults to tracing off). Uncomment PHOENIX_TRACING_ENABLED to turn tracing
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# on without editing config.yaml.
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# PHOENIX_TRACING_ENABLED=true
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# PHOENIX_COLLECTOR_ENDPOINT=http://localhost:6006/v1/traces
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# PHOENIX_PROJECT_NAME=ai-agro-support
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