> For the complete documentation index, see [llms.txt](https://docs.bito.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bito.ai/ai-architect/installation/install-ai-architect-self-hosted/prerequisites-and-requirements.md). # Prerequisites & requirements Everything you need before installing self-hosted AI Architect, for both Standalone and Enterprise deployments. ## Accounts and keys | Requirement | Where to get it | | ---------------------- | ------------------------------------------------------------------------------------------------- | | **Bito API key** | [alpha.bito.ai/home/advanced](https://alpha.bito.ai/home/advanced) (Settings → Advanced Settings) | | **Git provider token** | Your Git provider (see Git provider access below) | | **LLM key** (optional) | Only if you bring your own model (see LLM options below) | {% stepper %} {% step %} ### Git provider access A personal access token (PAT) lets AI Architect clone and index your repositories. Git authentication is **PAT-only**. SSH and OAuth helpers are not supported. Both cloud and enterprise (self-managed) editions are supported for every provider. Click a provider name to create the token before you install: | Provider | Editions supported | Token type | Scope / permission | Also provide | | -------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------- | ---------------------------------------------------------------- | ------------------ | ---------------------- | | [GitHub](https://github.com/settings/tokens) | GitHub.com · GitHub Enterprise Server | Classic PAT (**fine-grained not supported**) | `repo` | - | | [GitLab](https://gitlab.com/-/user_settings/personal_access_tokens) | GitLab.com · GitLab Self-Managed | Personal access token | `api` | - | | [Bitbucket Cloud](https://id.atlassian.com/manage-profile/security/api-tokens) | Cloud | API token | Repository read | Your account email | | Bitbucket Data Center / Server | Self-managed | HTTP access token (your instance → Profile → HTTP access tokens) | Repository read | Your username | | [Azure DevOps](https://learn.microsoft.com/en-us/azure/devops/organizations/accounts/use-personal-access-tokens-to-authenticate) | dev.azure.com · Azure DevOps Server | Personal access token | Full access | Your organization name | {% hint style="info" %} **Enterprise or self-managed instance** (for example `github.company.com`)? During install, answer yes when asked whether this is an enterprise version of your provider, and enter your custom domain. {% endhint %} {% endstep %} {% step %} ### LLM options By default, AI Architect uses Bito's LLM, covered by your Bito API key. To bring your own key (BYOK), configure one provider during install, or later with `bitoarch update-llm-config`. Click a provider name to create the credentials:
ProviderWhat you provide
AnthropicAPI key
OpenAIAPI key
Google GeminiAPI key. Model optional
Azure AIAPI key and endpoint URL (for example https://<resource>.openai.azure.com)
AWS BedrockAWS access key ID, secret access key, and Bedrock region
Google Vertex AIService-account key JSON (file path or inline), project ID, and region (for example us-central1). Model optional
PortkeyAPI token and model name (@provider/model). Gateway URL optional (defaults to https://api.portkey.ai/v1)
NovitaAPI key
* **Portkey** is an exclusive gateway. When set, it handles all routing, and other providers are not used. * With an Anthropic key, indexing costs approximately **$1 per MB** of indexable code. * There is no basic-indexing-only mode. A Bito or custom LLM key is required. For model selection and how to change providers later, see Custom LLM configuration. {% endstep %} {% endstepper %} ## Hardware requirements Size the host by the number of repositories you plan to index: | Tier | Repositories | vCPU | Memory | Storage | | ---------- | ------------ | ---- | ------- | ------- | | Minimum | up to 25 | 12 | 24 GB | 500 GB | | Ideal | 25-100 | 16 | 48 GB | 1.5 TB | | Enterprise | 100+ | 32+ | 128+ GB | 2-4 TB+ | * For repositories larger than 5 GB, add roughly 50% more memory and storage. * Keep total allocated memory under roughly 75% of host memory. * Indexing produces CPU and memory peaks above steady state, so the tiers include headroom. {% hint style="info" %} **Right-sizing by scale:** run `bitoarch config edit env` and tune `CIS_REPO_LIMIT` (default 50, maximum 500) and `CIS_REPO_SIZE_LIMIT` (default 1 GB per repository) to match your workload. {% endhint %} ## Network requirements AI Architect keeps your code and knowledge graph inside your environment, but it must reach a small set of endpoints. If you run behind a corporate firewall or proxy, allow the following. #### Outbound (egress) over HTTPS 443 | Destination | Purpose | When | | ---------------------------------- | ---------------------------------------------------------------------------------------- | ------------------- | | `*.bito.ai` | License and entitlement validation (always), plus Bito LLM inference unless you use BYOK | Install and runtime | | `docker.io` (`bitoai/*`) or mirror | Container image pulls | Install and upgrade | | Your Git host | Repository cloning | Indexing | | Your LLM provider endpoint | LLM inference, **only if BYOK** | Runtime | | Your Jira / Confluence host | Insights, **only if enabled** | Runtime | | `*.descope.com` and your IdP | SSO, **only if enabled** | Runtime | #### Inbound (ingress) Expose **only the MCP server**: `https://localhost:5001` (Standalone) or port `5001` behind TLS / your ingress (Enterprise). Keep all other services (5002-5006) **internal**. {% hint style="info" %} **Behind a proxy (Standalone)?** Export proxy variables before installing and exclude the internal service names: ``` export HTTP_PROXY=http://proxy:8080 HTTPS_PROXY=http://proxy:8080 export NO_PROXY=localhost,127.0.0.1,ai-architect-config,ai-architect-manager,ai-architect-provider ``` {% endhint %} ## Configuration file locations | File | Contents | Find it with | | ----------------------- | ------------------------------------------- | ---------------------------- | | `.env-bitoarch` | Secrets and resource/port settings | `bitoarch config path env` | | `.bitoarch-config.yaml` | Repository and ticket-tracker configuration | `bitoarch config path repos` | --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.bito.ai/ai-architect/installation/install-ai-architect-self-hosted/prerequisites-and-requirements.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.