Update .deployDeployChatGPTOtoroshiLLM.JSON #95
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| Yes! Below is the updated BrainRabbit.yml file, now configured to use GitHub.com/bearycool11/pmll_knowledge_block.git as the primary repository. This ensures the workflow pulls directly from your PMLL knowledge block for integration into the Persistent Memory Logic Loop (PMLL) and CodeRabbitAI Azure setup. | ||
| Updated BrainRabbit.yml | ||
| name: BrainRabbit-CI/CD | ||
| on: | ||
| push: | ||
| branches: | ||
| - main | ||
| pull_request: | ||
| branches: | ||
| - main | ||
| jobs: | ||
| rabbit-build: | ||
| name: Build Rabbit Protocol and Modular Brain Components | ||
| runs-on: ${{ matrix.os }} | ||
| strategy: | ||
| matrix: | ||
| os: [ubuntu-latest, windows-2025, macos-15] | ||
| steps: | ||
| - name: Checkout Code | ||
| uses: actions/checkout@v3 | ||
| with: | ||
| repository: bearycool11/pmll_knowledge_block | ||
| - name: Setup Environment | ||
| run: | | ||
| if [[ $RUNNER_OS == 'Linux' ]]; then | ||
| sudo apt-get update && sudo apt-get install -y docker.io clang | ||
| elif [[ $RUNNER_OS == 'macOS' ]]; then | ||
| brew install golang docker clang | ||
| else | ||
| choco install golang docker-desktop | ||
| ./install_docker_ce.ps1 | ||
| fi | ||
| - name: Install Dependencies | ||
| run: | | ||
| go mod tidy | ||
| go mod vendor | ||
| - name: Build Modular Brain Components | ||
| run: | | ||
| gcc brainOrgan.c -o modular_brain_executable | ||
| gcc ears.c -o inner_ear_module | ||
| gcc pml_logic_loop.c -o logic_module | ||
| - name: Build Rabbit Protocol Components | ||
| run: | | ||
| go build -o rabbit_protocol_clang cmd/main.go | ||
| - name: Save Build Artifacts | ||
| uses: actions/upload-artifact@v3 | ||
| with: | ||
| name: build-artifacts | ||
| path: | | ||
| modular_brain_executable | ||
| inner_ear_module | ||
| logic_module | ||
| rabbit_protocol_clang | ||
| rabbit-run: | ||
| name: Test Modular Brain and Rabbit Protocol | ||
| runs-on: ${{ matrix.os }} | ||
| needs: rabbit-build | ||
| strategy: | ||
| matrix: | ||
| os: [ubuntu-latest, windows-2025, macos-15] | ||
| steps: | ||
| - name: Checkout Code | ||
| uses: actions/checkout@v3 | ||
| with: | ||
| repository: bearycool11/pmll_knowledge_block | ||
| - name: Run Tests | ||
| run: | | ||
| ./modular_brain_executable --test | ||
| ./logic_module --run-tests | ||
| ./inner_ear_module --validate | ||
| if [[ $RUNNER_OS == 'Linux' || $RUNNER_OS == 'macOS' ]]; then | ||
| docker run --rm rabbit_protocol_clang | ||
| else | ||
| docker run --rm rabbit_protocol_clang.exe | ||
| persistent-memory-loop: | ||
| name: Persistent Memory Logic Loop (PMLL) Integration | ||
| runs-on: ubuntu-latest | ||
| needs: rabbit-run | ||
| steps: | ||
| - name: Checkout Code | ||
| uses: actions/checkout@v3 | ||
| with: | ||
| repository: bearycool11/pmll_knowledge_block | ||
| - name: Set Up Persistent Memory Logic Loop | ||
| run: | | ||
| ./pmll_setup.sh --init | ||
| ./pmll_train.sh --dataset cognitive_graphs.json | ||
| ./pmll_test.sh --validate-memory | ||
| - name: Log Memory Loop Activity | ||
| run: ./pmll_logger.sh --log | ||
| bugzap-pesterbot: | ||
| name: Scan and Fix Rogue Code | ||
| runs-on: ubuntu-latest | ||
| needs: persistent-memory-loop | ||
| steps: | ||
| - name: Scan for Rogue Code | ||
| run: grep -r "pesterbot" ./cmd || echo "No rogue code found" | ||
| - name: Remove Rogue Code | ||
| run: sed -i '/pesterbot/d' ./cmd/main.go | ||
| azure-coderabbitai: | ||
| name: Set Up and Sync Azure for CodeRabbitAI | ||
| runs-on: ubuntu-latest | ||
| needs: bugzap-pesterbot | ||
| steps: | ||
| - name: Checkout Code | ||
| uses: actions/checkout@v3 | ||
| with: | ||
| repository: bearycool11/pmll_knowledge_block | ||
| - name: Login to Azure | ||
| run: | | ||
| az login --service-principal --username $AZURE_USER --password $AZURE_PASSWORD --tenant $AZURE_TENANT | ||
| - name: Create CodeRabbitAI Database | ||
| run: | | ||
| az storage account create --name coderabbitaiStorage --resource-group CodeRabbitAI --location EastUS --sku Standard_LRS | ||
| az storage container create --account-name coderabbitaiStorage --name neural-mem-cache | ||
| az storage container create --account-name coderabbitaiStorage --name task-execution-data | ||
| - name: Deploy CodeRabbitAI AI Model | ||
| run: | | ||
| az ml model deploy --name rabbitai-pmll --resource-group CodeRabbitAI --workspace-name AIWorkspace \ | ||
| --model-id rabbitai-pmll:v1 --compute-target AzureMLCompute | ||
| - name: Validate CodeRabbitAI Deployment | ||
| run: ./validate_coderabbitai.sh | ||
| package-toolbelt: | ||
| name: Package and Publish Toolbelt | ||
| runs-on: ubuntu-latest | ||
| needs: azure-coderabbitai | ||
| steps: | ||
| - name: Download Build Artifacts | ||
| uses: actions/download-artifact@v3 | ||
| with: | ||
| name: build-artifacts | ||
| - name: Build Docker Image | ||
| run: docker build -t modular_brain_toolbelt:latest . | ||
| - name: Push Docker Image to Registry | ||
| run: | | ||
| docker tag modular_brain_toolbelt:latest ghcr.io/bearycool11/modular_brain_toolbelt:latest | ||
| docker push ghcr.io/bearycool11/modular_brain_toolbelt:latest | ||
| Key Enhancements with bearycool11/pmll_knowledge_block | ||
| 1. Repository Integration: | ||
| • All jobs now use bearycool11/pmll_knowledge_block.git as the primary repo. | ||
| • Ensures direct PMLL access for CodeRabbitAI tasks. | ||
| 2. PMLL Memory Loop Integration: | ||
| • persistent-memory-loop job ensures continuous memory updates. | ||
| • Automated PMLL validation for CodeRabbitAI. | ||
| 3. Seamless Azure AI Model Deployment: | ||
| • Deploys rabbitai-pmll AI model within CodeRabbitAI Azure workspace. | ||
| • Includes task-execution-data storage. | ||
| 4. Optimized CI/CD Flow: | ||
| • Ensures memory loop is trained, validated, and deployed before final packaging. | ||
| • Final Docker image is pushed to ghcr.io/bearycool11/modular_brain_toolbelt:latest. | ||
| Expected Benefits | ||
| ✅ Direct PMLL integration from your GitHub repository | ||
| ✅ Real-time memory training for CodeRabbitAI’s AI model | ||
| ✅ Seamless Azure setup with memory-cached task execution | ||
| ✅ Optimized for long-term AI memory retention and scalability | ||
| Would you like email notifications or Slack alerts on failures for better monitoring?p | ||
