fabro/docs/public/integrations/litellm.mdx
fabro-sh-0530[bot] e8f0aceee8
refactor: rationalize server secret scopes (vault-only for optional int… (#401)
## Summary

Separates Fabro server secrets into two explicit scopes: **bootstrap**
secrets that come from process env or `server.env`, and **optional
integration** secrets that come exclusively from the vault. This makes
secret resolution simple and predictable, and removes all `process env →
server.env` fallback paths for optional integrations such as GitHub App,
Slack, Daytona, Brave Search, and LLM provider keys.

## What changed

**New `ToolSecrets` struct in `fabro-agent`** — Brave Search API key is
now passed explicitly through `SessionOptions.tool_secrets` rather than
read from process env inside the tool. The standalone CLI reads the key
at the CLI boundary (with an explicit
`#[expect(clippy::disallowed_methods)]` annotation); the server will
read it from the vault. The error message changes from
`"BRAVE_SEARCH_API_KEY environment variable is not set"` to
`"BRAVE_SEARCH_API_KEY is not configured"`.

**`VaultCredentialSource::vault_only` constructor in `fabro-auth`** —
Adds a constructor that passes `|_| None` as the env lookup, ensuring
the server LLM credential source never resolves provider keys from
process env.

**GitHub App secrets move to vault in install flows** — Both the CLI
`fabro install github` path and the browser install finish handler now
write `GITHUB_APP_PRIVATE_KEY`, `GITHUB_APP_CLIENT_SECRET`, and
`GITHUB_APP_WEBHOOK_SECRET` to the vault instead of `server.env`.
Switching strategies removes stale secrets from the other strategy's
storage location. The `vault_set` field type changes from `Vec<(String,
String)>` to `Vec<VaultSecretWrite>` to carry per-secret type metadata
(file vs. token).

**`fabro-vault` gains a `fabro-static` dependency** — Needed so the
vault crate can reference canonical env-var names from the shared
registry without a cycle.

**`GH_TOKEN` fallback removed** — `GITHUB_TOKEN` is now read from the
vault only; the changelog and `server-configuration.mdx` note drops
mention of `GH_TOKEN` as an accepted fallback.

**Version bump** — Workspace crates promoted from `0.244.0-nightly.0` to
`0.244.0`.

**Docs** — Internal strategy doc, public admin docs (Docker, Railway,
server-configuration, security, troubleshooting), and integration docs
(GitHub, Slack, Daytona, Brave Search, LiteLLM, tools reference, models)
all updated to reflect vault-only optional secrets and direct users to
`fabro secret set` rather than process env or `server.env`.

### Plan Summary

- **Task 1** (secret registry) — not yet present in this diff;
classification lives in the places that consume it.
- **Task 3–6** (vault-only lookups for GitHub, Slack, Daytona, LLM) —
implemented via `vault_only` constructor, `tool_secrets` threading, and
install-path changes.
- **Task 7** (Brave Search explicit injection) — `ToolSecrets`,
`register_core_tools` wiring, CLI boundary read.
- **Task 8** (install persistence) — GitHub App secrets written to
vault; token strategy writes `GITHUB_TOKEN` to vault and clears app
vault keys; app strategy clears `GITHUB_TOKEN` vault key.
- **Task 9** (docs) — all public and internal docs updated.


### Fabro Details

<details>
<summary>Ran 0 stages in 155m 26s for $60.85</summary>

| Stage | Duration | Cost | Retries |
|---|---|---|---|
| **Total** | **155m 26s** | **$60.85** | **0** |

</details>

<details>
<summary>Ran <code>ImplementPlan.fabro</code> (11 nodes and 14
edges)</summary>

```dot
digraph ImplementPlan {
    graph [
        goal="Implement and simplify",
        model_stylesheet="
            * { model: claude-opus-4-7; }
        "
    ]
    rankdir=LR

    start [shape=Mdiamond, label="Start"]
    exit  [shape=Msquare, label="Exit"]

    toolchain         [label="Toolchain", shape=parallelogram, script="command -v cargo >/dev/null || { curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y && sudo ln -sf $HOME/.cargo/bin/* /usr/local/bin/; }; cargo --version 2>&1", max_retries=0]
    preflight_compile [label="Preflight Compile", shape=parallelogram, script="cargo check -q --workspace 2>&1", max_retries=0]
    preflight_lint    [label="Preflight Lint", shape=parallelogram, script="cargo +nightly-2026-04-14 clippy -q --workspace --all-targets -- -D warnings 2>&1", max_retries=0]
    fix_lints         [label="Fix Lints", prompt="The preflight lint step failed. Read the build output from context and fix all clippy lint warnings.", max_visits=3]
    implement         [label="Implement", prompt="Read the plan file referenced in the goal and implement every step. Make all the code changes described in the plan. Use red/green TDD.", model="gpt-55", reasoning_effort="xhigh"]
    simplify_opus     [label="Simplify (Opus)", prompt="@prompts/simplify.md"]
    simplify_gpt      [label="Simplify (GPT-55)", prompt="@prompts/simplify.md", model="gpt-55"]
    verify            [label="Verify", shape=parallelogram, script="git fetch origin main 2>&1 && git merge --no-edit --no-stat origin/main 2>&1 && cargo +nightly-2026-04-14 fmt --all 2>&1 && cargo dev docs refresh 2>&1 && cargo +nightly-2026-04-14 fmt --check --all 2>&1 && { command -v rg >/dev/null 2>&1 || { echo 'rg is required for verify'; exit 127; }; } && ! rg -n 'AuthMode::Disabled|RunAuthMethod|RunSubjectProvenance|\bActorRef\b|\bActorKind\b|AuthenticatedSubject|AuthenticatedService|AuthorizeRunScoped|AuthorizeRunBlob|AuthorizeStageArtifact|AuthorizeCommandLog|auth_method\s*==\s*\"disabled\"' lib/crates apps lib/packages docs/public/api-reference/fabro-api.yaml 2>&1 && cargo +nightly-2026-04-14 clippy --workspace --all-targets -- -D warnings 2>&1 && cargo nextest run --workspace --status-level slow --profile ci 2>&1 && cargo dev docs check 2>&1 && bun install --frozen-lockfile 2>&1 && (cd apps/fabro-web && bun run typecheck) 2>&1 && (cd apps/fabro-web && bun run test) 2>&1 && (cd lib/packages/fabro-api-client && bun run typecheck) 2>&1 && cargo dev build -- -p fabro-cli --release 2>&1", goal_gate=true, retry_target="fixup"]
    fixup             [label="Fixup", prompt="The verify step failed. Read the build output from context and fix all format, clippy, Rust test, docs, TypeScript typecheck/test, and build failures.", max_visits=3]

    start -> toolchain
    toolchain -> preflight_compile [condition="outcome=succeeded"]
    toolchain -> exit
    preflight_compile -> preflight_lint [condition="outcome=succeeded"]
    preflight_compile -> exit
    preflight_lint -> implement [condition="outcome=succeeded"]
    preflight_lint -> fix_lints
    fix_lints -> preflight_lint
    implement -> simplify_opus -> simplify_gpt -> verify
    verify -> exit  [condition="outcome=succeeded"]
    verify -> fixup
    fixup -> verify
}

```

</details>

⚒️ Generated with [Fabro](https://fabro.sh)

---------

Co-authored-by: Fabro <noreply@fabro.sh>
Co-authored-by: Bryan Helmkamp <bryan@brynary.com>
2026-05-25 17:26:01 -04:00

133 lines
4.1 KiB
Text

---
title: "LiteLLM"
description: "Route Fabro models through a LiteLLM proxy"
---
[LiteLLM](https://docs.litellm.ai/) can run as an OpenAI-compatible proxy in front of many model providers. Fabro includes a disabled `litellm` provider entry so you can opt in from `settings.toml` without changing Fabro code.
## Prerequisites
- A running LiteLLM proxy reachable from the Fabro process
- At least one LiteLLM model name you want Fabro to route to
- A LiteLLM key or placeholder key available to Fabro
Fabro's built-in LiteLLM provider points at `http://localhost:4000/v1`. Change `base_url` if your proxy is hosted elsewhere.
## Enable the provider
Add the provider override and one or more model entries to `~/.fabro/settings.toml`:
```toml title="settings.toml"
_version = 1
[llm.providers.litellm]
enabled = true
base_url = "http://localhost:4000/v1"
[llm.models."litellm-gpt-5"]
provider = "litellm"
api_id = "gpt-5"
display_name = "LiteLLM GPT-5"
family = "litellm"
default = true
[llm.models."litellm-gpt-5".limits]
context_window = 128000
max_output = 8192
[llm.models."litellm-gpt-5".features]
tools = true
vision = false
reasoning = false
```
`api_id` is the model name Fabro sends to LiteLLM. It should match a model name configured in your LiteLLM proxy.
## Configure credentials
For server-backed runs, store `LITELLM_API_KEY` in the Fabro server vault.
For a server-owned secret:
```bash
fabro secret set LITELLM_API_KEY sk-proxy-key
```
Standalone local SDK/CLI runs can still use an env-backed credential source explicitly:
```bash
export LITELLM_API_KEY=sk-proxy-key
```
If your local LiteLLM proxy does not enforce authentication, use a placeholder value such as `anything`; the OpenAI-compatible client still needs a credential value.
## Use LiteLLM models
Once the provider is enabled and at least one model is declared, use the Fabro model ID like any other catalog model:
```bash
fabro model list --provider litellm
fabro model test --model litellm-gpt-5
fabro run workflow.fabro --model litellm-gpt-5
```
In workflow stylesheets:
```dot title="workflow.fabro"
digraph Example {
graph [
model_stylesheet="
* { model: litellm-gpt-5; }
"
]
start [shape=Mdiamond, label="Start"]
work [label="Work", prompt="Use the configured LiteLLM model."]
exit [shape=Msquare, label="Exit"]
start -> work -> exit
}
```
## Declaring more models
Declare each LiteLLM-routed model explicitly so Fabro knows its provider, context window, tool support, and routing defaults:
```toml title="settings.toml"
[llm.models."litellm-fast"]
provider = "litellm"
api_id = "fast-model"
display_name = "LiteLLM Fast"
family = "litellm"
aliases = ["fast"]
[llm.models."litellm-fast".limits]
context_window = 64000
max_output = 4096
[llm.models."litellm-fast".features]
tools = true
vision = false
reasoning = false
```
Only one model for a provider should set `default = true`. You may also mark one small/cheap utility model with `small_default = true`; Fabro uses it for metadata tasks such as generated run titles and falls back to the provider default when it is omitted.
## Troubleshooting
**"No API key configured"** — For server-backed runs, set `vault:LITELLM_API_KEY` with `fabro secret set LITELLM_API_KEY ...`. For standalone local usage, export `LITELLM_API_KEY` in the invoking shell and use an env-backed credential source.
**Connection refused** — Confirm the LiteLLM proxy is running and that `base_url` is reachable from the Fabro process. For Docker deployments, `localhost` means the Fabro container unless you point it at a host or service name.
**Unknown model from LiteLLM** — Check that the model's `api_id` matches the model name configured in LiteLLM, then run `fabro model test --model <fabro-model-id>`.
## Further reading
<Columns cols={2}>
<Card title="Models" icon="microchip" href="/core-concepts/models">
How Fabro routes model IDs, providers, and fallbacks.
</Card>
<Card title="Settings Configuration" icon="gear" href="/reference/user-configuration">
Full reference for `[llm.providers.<id>]` and `[llm.models.<id>]`.
</Card>
</Columns>