diff --git a/.gitignore b/.gitignore index 7a440d3..177e7db 100644 --- a/.gitignore +++ b/.gitignore @@ -4,6 +4,8 @@ # Log files *.log +node_modules/ + # Byte-compiled / optimized / DLL files __pycache__/ *.py[codz] diff --git a/README.md b/README.md index 235bccd..4d6e44a 100644 --- a/README.md +++ b/README.md @@ -91,6 +91,10 @@ The `WritingBot` will read and write the files inside `code` folder based on spe The MicroBots create a containerized environment and mount the specified directory with restricting the permissions to read-only or read/write based on Bot used. It ensures that the AI agents operate within defined boundaries which enhances security and control over code modifications as well as protecting the local environment. +## Azure Pipelines Log Analyzer + +Microbots includes a custom Azure DevOps task, `MicrobotsLogAnalyzer@0`, for analyzing logs with Azure OpenAI models through an Azure Resource Manager Service Connection. See [docs/azure-pipelines-log-analyzer.md](docs/azure-pipelines-log-analyzer.md) to publish and use the task. + #Legal Notice Trademarks This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft’s Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party’s policies. \ No newline at end of file diff --git a/azure-pipelines/MicrobotsLogAnalyzerTask/index.js b/azure-pipelines/MicrobotsLogAnalyzerTask/index.js new file mode 100644 index 0000000..73b96b8 --- /dev/null +++ b/azure-pipelines/MicrobotsLogAnalyzerTask/index.js @@ -0,0 +1,184 @@ +"use strict"; + +const fs = require("fs"); +const path = require("path"); +const { spawnSync } = require("child_process"); +const tl = require("azure-pipelines-task-lib/task"); +const { loginAzureRM } = require("azure-pipelines-tasks-azure-arm-rest/azCliUtility"); + +const DEFAULT_API_VERSION = "2025-03-01-preview"; +const DEFAULT_TIMEOUT_SECONDS = "600"; +const VENV_NAME = "microbots-log-analyzer-venv"; +const VENV_READY_MARKER = ".microbots-venv-ready-v1"; + +function runCommand(command, args, env) { + const result = spawnSync(command, args, { stdio: "inherit", env: env || process.env }); + if (result.error) throw new Error(`Failed to run ${command}: ${result.error.message}`); + if (result.status !== 0) throw new Error(`${command} ${args.join(" ")} -> exit ${result.status}`); +} + +function input(name, required) { + const value = tl.getInput(name, required); + return value ? value.trim() : value; +} + +function resolveLogPath(codebasePath, logFilePath) { + return path.isAbsolute(logFilePath) + ? path.resolve(logFilePath) + : path.resolve(codebasePath, logFilePath); +} + +function getInputs() { + const inputs = { + serviceConnection: input("serviceConnection", true), + deploymentName: input("deploymentName", true), + endpoint: input("endpoint", true), + apiVersion: input("apiVersion", false) || DEFAULT_API_VERSION, + codebasePath: tl.getPathInput("codebasePath", true, true), + logFilePath: input("logFilePath", true), + timeoutSeconds: input("timeoutSeconds", false) || DEFAULT_TIMEOUT_SECONDS, + }; + + validateInputs(inputs); + return inputs; +} + +function validateInputs(inputs) { + if (!fs.existsSync(inputs.codebasePath)) { + throw new Error(`codebasePath does not exist: ${inputs.codebasePath}`); + } + + if (!fs.statSync(inputs.codebasePath).isDirectory()) { + throw new Error(`codebasePath must be a directory: ${inputs.codebasePath}`); + } + + const logPath = resolveLogPath(inputs.codebasePath, inputs.logFilePath); + if (!fs.existsSync(logPath) || !fs.statSync(logPath).isFile()) { + throw new Error(`logFilePath does not exist: ${logPath}`); + } + inputs.logFilePath = logPath; + + try { + const endpoint = new URL(inputs.endpoint); + if (endpoint.protocol !== "https:" && endpoint.protocol !== "http:") throw new Error(); + } catch (_) { + throw new Error(`endpoint must be a valid HTTP or HTTPS URL: ${inputs.endpoint}`); + } + + const timeoutSeconds = Number(inputs.timeoutSeconds); + if (!Number.isSafeInteger(timeoutSeconds) || timeoutSeconds <= 0) { + throw new Error(`timeoutSeconds must be a positive integer: ${inputs.timeoutSeconds}`); + } + inputs.timeoutSeconds = String(timeoutSeconds); +} + +async function loginWithServiceConnection(serviceConnection) { + console.log("##[section]MicrobotsLogAnalyzer: authenticating with Azure service connection"); + const previousAzureOutput = process.env.AZURE_CORE_OUTPUT; + const originalLoc = tl.loc; + + process.env.AZURE_CORE_OUTPUT = "none"; + tl.loc = function loc(key, ...args) { + if (key === "LoginFailed" || key === "ErrorInSettingUpSubscription") return key; + return originalLoc(key, ...args); + }; + + try { + await loginAzureRM(serviceConnection); + } catch (error) { + throw new Error(`Azure service connection login failed for '${serviceConnection}': ${error.message || String(error)}`); + } finally { + tl.loc = originalLoc; + if (previousAzureOutput === undefined) delete process.env.AZURE_CORE_OUTPUT; + else process.env.AZURE_CORE_OUTPUT = previousAzureOutput; + } + + console.log("##[section]MicrobotsLogAnalyzer: Azure authentication complete"); +} + +function venvPythonPath(venvDir) { + return process.platform === "win32" + ? path.join(venvDir, "Scripts", "python.exe") + : path.join(venvDir, "bin", "python"); +} + +function setupVenv() { + const venvRoot = process.env.AGENT_TEMPDIRECTORY + || process.env.PIPELINE_WORKSPACE + || process.env.RUNNER_TEMP + || "/tmp"; + const venvDir = path.join(venvRoot, VENV_NAME); + const python = venvPythonPath(venvDir); + const venvReadyFile = path.join(venvDir, VENV_READY_MARKER); + + if (fs.existsSync(python) && fs.existsSync(venvReadyFile)) { + console.log(`##[section]MicrobotsLogAnalyzer: reusing Python environment at ${venvDir}`); + return python; + } + + if (fs.existsSync(venvDir)) fs.rmSync(venvDir, { recursive: true, force: true }); + + console.log(`##[section]MicrobotsLogAnalyzer: creating Python environment at ${venvDir}`); + runCommand("python3", ["-m", "venv", venvDir]); + console.log("Installing Python dependencies (microbots, Azure identity)..."); + runCommand(python, ["-m", "pip", "install", "--quiet", "--upgrade", "pip"]); + runCommand(python, ["-m", "pip", "install", "--quiet", "microbots[azure_ad]"]); + fs.writeFileSync(venvReadyFile, new Date().toISOString()); + + return python; +} + +function microbotsEnvironment(inputs) { + return Object.assign({}, process.env, { + OPEN_AI_DEPLOYMENT_NAME: inputs.deploymentName, + OPEN_AI_END_POINT: inputs.endpoint, + OPEN_AI_API_VERSION: inputs.apiVersion, + AZURE_OPENAI_ENDPOINT: inputs.endpoint, + AZURE_OPENAI_API_VERSION: inputs.apiVersion, + AZURE_AUTH_METHOD: "azure_ad", + }); +} + +function runLogAnalyzer(python, inputs) { + const script = [ + "import os, sys, textwrap", + "from azure.identity import AzureCliCredential, get_bearer_token_provider", + "from microbots import LogAnalysisBot", + "codebase_path = os.path.abspath(sys.argv[1])", + "log_file_path = sys.argv[2]", + "timeout_seconds = int(sys.argv[3])", + "os.chdir(codebase_path)", + "print(f'MicrobotsLogAnalyzer: analyzing {log_file_path} with deployment {os.environ[\"OPEN_AI_DEPLOYMENT_NAME\"]}', flush=True)", + "print(f'MicrobotsLogAnalyzer: timeout is {timeout_seconds} seconds', flush=True)", + "token_provider = get_bearer_token_provider(AzureCliCredential(), 'https://cognitiveservices.azure.com/.default')", + "bot = LogAnalysisBot(model=f\"azure-openai/{os.environ['OPEN_AI_DEPLOYMENT_NAME']}\", folder_to_mount=codebase_path, token_provider=token_provider)", + "result = bot.run(file_name=log_file_path, timeout_in_seconds=timeout_seconds)", + "message = result.result or result.error or ''", + "print('##[section]MicrobotsLogAnalyzer: LLM analysis')", + "print('============================================================')", + "print('MICROBOTS LOG ANALYSIS')", + "print('============================================================')", + "for paragraph in str(message).splitlines() or ['']:", + " print(textwrap.fill(paragraph, width=125) if paragraph.strip() else '')", + "print('============================================================')", + "sys.exit(0 if result.status else 1)", + ].join("\n"); + + runCommand(python, ["-c", script, inputs.codebasePath, inputs.logFilePath, inputs.timeoutSeconds], microbotsEnvironment(inputs)); +} + +async function run() { + try { + const inputs = getInputs(); + await loginWithServiceConnection(inputs.serviceConnection); + const python = setupVenv(); + runLogAnalyzer(python, inputs); + tl.setResult(tl.TaskResult.Succeeded, "LogAnalysisBot completed"); + } catch (error) { + tl.setResult(tl.TaskResult.Failed, error.message || String(error)); + } finally { + try { spawnSync("az", ["account", "clear"], { stdio: "ignore" }); } catch (_) {} + } +} + +run(); diff --git a/azure-pipelines/MicrobotsLogAnalyzerTask/package-lock.json b/azure-pipelines/MicrobotsLogAnalyzerTask/package-lock.json new file mode 100644 index 0000000..db18649 --- /dev/null +++ b/azure-pipelines/MicrobotsLogAnalyzerTask/package-lock.json @@ -0,0 +1,1747 @@ +{ + "name": "microbots-log-analyzer-task", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": 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Authenticates via the supplied Azure Resource Manager service connection.", + "category": "Utility", + "author": "Microbots contributors", + "version": { + "Major": 0, + "Minor": 1, + "Patch": 0 + }, + "instanceNameFormat": "Microbots Log Analyzer: $(logFilePath)", + "inputs": [ + { + "name": "serviceConnection", + "type": "connectedService:AzureRM", + "label": "Azure Resource Manager connection", + "required": true, + "helpMarkDown": "Service connection used to obtain a token for Azure OpenAI." + }, + { + "name": "deploymentName", + "type": "string", + "label": "Deployment name", + "required": true, + "helpMarkDown": "Azure OpenAI deployment name used by Microbots." + }, + { + "name": "endpoint", + "type": "string", + "label": "Azure OpenAI endpoint", + "required": true, + "helpMarkDown": "Azure OpenAI resource endpoint, for example https://my-resource.openai.azure.com/." + }, + { + "name": "apiVersion", + "type": "string", + "label": "API version", + "defaultValue": "2025-03-01-preview", + "required": false + }, + { + "name": "codebasePath", + "type": "filePath", + "label": "Codebase path", + "required": true, + "helpMarkDown": "Path to the repository or source folder Microbots can inspect while analyzing the log." + }, + { + "name": "logFilePath", + "type": "string", + "label": "Log file path", + "required": true, + "helpMarkDown": "Path to the log file. (Both Absolute Path and Relative to Codebase Path are supported.)" + }, + { + "name": "timeoutSeconds", + "type": "string", + "label": "Timeout in seconds", + "defaultValue": "600", + "required": false + } + ], + "execution": { + "Node20_1": { + "target": "index.js" + } + }, + "restrictions": { + "commands": { + "mode": "restricted" + }, + "settableVariables": { + "allowed": [] + } + } +} diff --git a/azure-pipelines/vss-extension.json b/azure-pipelines/vss-extension.json new file mode 100644 index 0000000..9cbb5b7 --- /dev/null +++ b/azure-pipelines/vss-extension.json @@ -0,0 +1,33 @@ +{ + "manifestVersion": 1, + "id": "microbots-log-analyzer", + "name": "Microbots Log Analyzer", + "version": "0.1.0", + "publisher": "microsoft", + "targets": [ + { + "id": "Microsoft.VisualStudio.Services" + } + ], + "description": "Azure Pipelines task for running Microbots log analysis with Azure OpenAI.", + "categories": [ + "Azure Pipelines" + ], + "files": [ + { + "path": "MicrobotsLogAnalyzerTask" + } + ], + "contributions": [ + { + "id": "microbots-log-analyzer-task", + "type": "ms.vss-distributed-task.task", + "targets": [ + "ms.vss-distributed-task.tasks" + ], + "properties": { + "name": "MicrobotsLogAnalyzerTask" + } + } + ] +} diff --git a/docs/azure-pipelines-log-analyzer.md b/docs/azure-pipelines-log-analyzer.md new file mode 100644 index 0000000..23a4b34 --- /dev/null +++ b/docs/azure-pipelines-log-analyzer.md @@ -0,0 +1,77 @@ +# MicrobotsLogAnalyzer Azure Pipelines Task + +`MicrobotsLogAnalyzer` is an Azure DevOps custom task that runs Microbots `LogAnalysisBot` against a log file. It authenticates to Azure OpenAI through an Azure Resource Manager Service Connection, creates an isolated Python venv on the build agent, installs `microbots[azure_ad]`, and prints the root-cause analysis into the pipeline logs. + +## Prerequisites + +- Azure DevOps organization where you can install custom extensions. +- Azure Resource Manager Service Connection with permission to request tokens for the Azure OpenAI resource. The pipeline must be authorized to use this service connection. +- Azure Pipelines agent with `azure-cli`, `python3`, `pip` and `python3 -m venv` support. +- Azure OpenAI deployment that works with Microbots and is reachable by the service connection. +- Node.js on the machine where you package and publish the extension. + +## Publish The Task + +From a clone of this repository: + +```bash +npm install -g tfx-cli + +cd azure-pipelines/MicrobotsLogAnalyzerTask +npm ci --omit=dev + +cd .. +tfx extension create --manifest-globs vss-extension.json +tfx extension publish --manifest-globs vss-extension.json --token --share-with +``` + +Update the `publisher` value in `vss-extension.json` before running `tfx extension create`. The task folder must contain `node_modules` when the VSIX is created, so run `npm ci --omit=dev` before packaging. + +After publishing, install the extension into the Azure DevOps organization that owns your pipelines. + +When publishing an update, increment both versions before packaging: + +- `azure-pipelines/vss-extension.json` controls the extension version. +- `azure-pipelines/MicrobotsLogAnalyzerTask/task.json` controls the task version shown to Azure Pipelines. + +You can use `tfx extension create --manifest-globs vss-extension.json --rev-version` to increment the extension patch version, but task behavior changes still need a `task.json` version bump. + +## Use It In A Pipeline + +See the complete sample pipeline at [docs/examples/azure-pipelines/microbots-log-analyzer.yml](examples/azure-pipelines/microbots-log-analyzer.yml). + +```yaml +- task: MicrobotsLogAnalyzer@0 + displayName: Analyze build log + inputs: + serviceConnection: my-azure-service-connection + deploymentName: my-azure-openai-deployment + endpoint: https://my-azure-openai-resource.openai.azure.com/ + codebasePath: $(Build.SourcesDirectory) + logFilePath: logs/build.log + timeoutSeconds: 600 +``` + +The log file must exist before `MicrobotsLogAnalyzer@0` runs. Relative `logFilePath` values are resolved from `codebasePath`; absolute paths are also supported. + +## Inputs + +| Input | Required | Default | Description | +|---|---:|---|---| +| `serviceConnection` | Yes | - | Azure Resource Manager Service Connection used for Azure CLI login. | +| `deploymentName` | Yes | - | Azure OpenAI deployment name. | +| `endpoint` | Yes | - | Azure OpenAI endpoint, for example `https://my-resource.openai.azure.com/`. | +| `apiVersion` | No | `2025-03-01-preview` | Azure OpenAI API version passed to Microbots. | +| `codebasePath` | Yes | - | Repository or source folder Microbots can inspect while analyzing the log. | +| `logFilePath` | Yes | - | Log file path. Use an absolute path, or a relative path resolved from `codebasePath`. | +| `timeoutSeconds` | No | `600` | Maximum time for `LogAnalysisBot.run()`. | + +## How It Works + +1. Azure Pipelines runs the task with the `Node20_1` task handler. +2. The task logs in with the supplied Azure Resource Manager Service Connection. +3. The task creates or reuses a virtual environment (`microbots-log-analyzer-venv`). +4. The task installs `microbots[azure_ad]` into that virtual environment. +5. A short Python runner creates `LogAnalysisBot` with `AzureCliCredential`, mounts `codebasePath` as context, passes `logFilePath` to `LogAnalysisBot.run()`, and prints the analysis result. + +The task clears the Azure CLI account at the end of the run. Its task manifest also uses Azure Pipelines command restrictions so analyzed log content cannot set arbitrary pipeline variables. diff --git a/docs/examples/azure-pipelines/microbots-log-analyzer.yml b/docs/examples/azure-pipelines/microbots-log-analyzer.yml new file mode 100644 index 0000000..d742f8e --- /dev/null +++ b/docs/examples/azure-pipelines/microbots-log-analyzer.yml @@ -0,0 +1,27 @@ +trigger: +- none + +jobs: +- job: MicrobotsLogAnalyzer + pool: + vmImage: ubuntu-latest + timeoutInMinutes: 30 + steps: + - checkout: self + + - bash: | + set -euo pipefail + command -v az >/dev/null 2>&1 || { echo '##[error]azure-cli is required on the agent'; exit 1; } + command -v python3 >/dev/null 2>&1 || { echo '##[error]python3 is required on the agent'; exit 1; } + python3 -m venv --help >/dev/null 2>&1 || { echo '##[error]python3 venv support is required'; exit 1; } + displayName: Check MicrobotsLogAnalyzer prerequisites + + - task: MicrobotsLogAnalyzer@0 + displayName: Analyze build log + inputs: + serviceConnection: my-azure-service-connection + deploymentName: my-azure-openai-deployment + endpoint: https://my-azure-openai-resource.openai.azure.com/ + codebasePath: $(Build.SourcesDirectory) + logFilePath: logs/build.log + timeoutSeconds: 600 diff --git a/mkdocs.yml b/mkdocs.yml index 34a415d..0306179 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -65,6 +65,7 @@ nav: - Guides: - CopilotBot: copilot-bot.md - Authentication: authentication.md + - Azure Pipelines Log Analyzer: azure-pipelines-log-analyzer.md - Tools: - "Custom Tool Integration Walkthrough": blog/guides/tesseract_ocr_tool_use.md - Blogs: