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69 lines
3.7 KiB
Markdown
69 lines
3.7 KiB
Markdown
# GitHub Dev Team with AI Agents
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Build a Dev Team using event driven agents. This project is an experiment and is not intended to be used in production.
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## Background
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From a natural language specification, set out to integrate a team of AI agents into your team’s dev process, either for discrete tasks on an existing repo (unit tests, pipeline expansions, PRs for specific intents), developing a new feature, or even building an application from scratch. Starting from an existing repo and a broad statement of intent, work with multiple AI agents, each of which has a different emphasis - from architecture, to task breakdown, to plans for individual tasks, to code output, code review, efficiency, documentation, build, writing tests, setting up pipelines, deployment, integration tests, and then validation.
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The system will present a view that facilitates chain-of-thought coordination across multiple trees of reasoning with the dev team agents.
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## Get it running
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Check [the getting started guide](./docs/github-flow-getting-started.md).
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## Demo
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https://github.com/microsoft/azure-openai-dev-skills-orchestrator/assets/10728102/cafb1546-69ab-4c27-aaf5-1968313d637f
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## Solution overview
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## How it works
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* User begins with creating an issue and then stateing what they want to accomplish, natural language, as simple or as detailed as needed.
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* Product manager agent will respond with a Readme, which can be iterated upon.
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* User approves the readme or gives feedback via issue comments.
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* Once the readme is approved, the user closes the issue and the Readme is commited to a PR.
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* Developer lead agent responds with a decomposed plan for development, which also can be iterated upon.
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* User approves the plan or gives feedback via issue comments.
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* Once the readme is approved, the user closes the issue and the plan is used to break down the task to different developer agents.
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* Developer agents respond with code, which can be iterated upon.
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* User approves the code or gives feedback via issue comments.
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* Once the code is approved, the user closes the issue and the code is commited to a PR.
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```mermaid
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graph TD;
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NEA([NewAsk event]) -->|Hubber| NEA1[Creation of PM issue, DevLead issue, and new branch];
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RR([ReadmeRequested event]) -->|ProductManager| PM1[Generation of new README];
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NEA1 --> RR;
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PM1 --> RG([ReadmeGenerated event]);
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RG -->|Hubber| RC[Post the readme as a new comment on the issue];
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RC --> RCC([ReadmeChainClosed event]);
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RCC -->|ProductManager| RCR([ReadmeCreated event]);
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RCR --> |AzureGenie| RES[Store Readme in blob storage];
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RES --> RES2([ReadmeStored event]);
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RES2 --> |Hubber| REC[Readme commited to branch and create new PR];
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DPR([DevPlanRequested event]) -->|DeveloperLead| DPG[Generation of new development plan];
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NEA1 --> DPR;
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DPG --> DPGE([DevPlanGenerated event]);
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DPGE -->|Hubber| DPGEC[Posting the plan as a new comment on the issue];
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DPGEC --> DPCC([DevPlanChainClosed event]);
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DPCC -->|DeveloperLead| DPCE([DevPlanCreated event]);
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DPCE --> |Hubber| DPC[Creates a Dev issue for each subtask];
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DPC([CodeGenerationRequested event]) -->|Developer| CG[Generation of new code];
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CG --> CGE([CodeGenerated event]);
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CGE -->|Hubber| CGC[Posting the code as a new comment on the issue];
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CGC --> CCCE([CodeChainClosed event]);
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CCCE -->|Developer| CCE([CodeCreated event]);
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CCE --> |AzureGenie| CS[Store code in blob storage and schedule a run in the sandbox];
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CS --> SRC([SandboxRunCreated event]);
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SRC --> |Sandbox| SRM[Check every minute if the run finished];
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SRM --> SRF([SandboxRunFinished event]);
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SRF --> |Hubber| SRCC[Code files commited to branch];
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``` |