Caveman Setup

You are wiring this repository through the Caveman gateway. Caveman is a byte-preserving LLM proxy: in record mode it measures what your app sends and what it costs, and changes nothing else. Your job is a minimal, verified integration — not a refactor.

The prompt that sent you here provides four values. Refer to them as:

• GATEWAY — the gateway base URL (e.g. https://gateway.caveman.so or http://127.0.0.1:8787)
• CAVE_API_KEY — the gateway auth secret (treat like any API key: env var only, never committed, never printed in full)
• PROVIDER_KEYS — stored (provider keys live encrypted in Caveman Cloud) or byok (this app sends its own provider key per request)
• DASHBOARD — the dashboard base URL (e.g. https://app.caveman.so)

If any value is missing, stop and ask for it. Do not guess a URL or mint a key.

Rules (non-negotiable)

1. Coherent integration. Wire every live LLM callsite through existing configuration and responsible seams. Touch each layer correctness requires. No drive-by refactors or formatting sweeps; add an abstraction only when it clarifies ownership or lowers lifecycle cost.
2. Secrets stay in env vars. CAVE_API_KEY goes into the env file the repo already uses (.env, .env.local, …). If that file isn't gitignored, add it to .gitignore and say so. Never hardcode the key in source.
3. Report only what you observed. The final report states the HTTP status and usage numbers from the real verification response — never assumed success. If verification fails, report the failure template instead.
4. Record mode only. You are adding measurement. You do not enable any optimization, and you do not claim any savings — verified savings are $0 until an optimizer is explicitly turned on and passes its eval gate.
5. Provider keys are not your business. With PROVIDER_KEYS: stored you never see one. With byok, the app's existing provider key stays exactly where it already is.

Step 1 — Find every live LLM callsite

Read dependency files (package.json, requirements.txt, pyproject.toml, go.mod, lockfiles) and search the source for LLM clients:

• SDK imports: openai, @anthropic-ai/sdk, anthropic, ai + @ai-sdk/* (Vercel), langchain*, litellm, google-genai / @google/genai, crewai, pydantic_ai, openai-agents / agents
• Raw HTTP to api.openai.com, api.anthropic.com, generativelanguage.googleapis.com
• Existing base-URL env vars: OPENAI_BASE_URL, OPENAI_API_BASE, ANTHROPIC_BASE_URL, GEMINI_BASE_URL, GOOGLE_GEMINI_BASE_URL

List what you found (file:line per callsite) before changing anything. If you find no LLM callsites, stop and report the "nothing to wire" template at the end of this file — do not invent an integration.

Step 2 — Pick the app slug

One slug names this app in the gateway path: GATEWAY/w/<app>. Derive it from the package/module name (e.g. support-bot, acme-api). Grammar: lowercase [a-z0-9] first, then [a-z0-9._-], max 64 chars. Spend for this whole app groups under that slug on the dashboard.

Step 3 — Wire each callsite

The pattern is always the same: base URL → the gateway with /w/<app>, plus one auth header. Gateway auth is x-cave-api-key: CAVE_API_KEY (Authorization: Bearer CAVE_API_KEY also works where a header is awkward). With PROVIDER_KEYS: byok, also send x-cave-upstream-key: <the provider key the app already uses>.

Two facts that make the wiring safe (both are gateway-enforced, not hopes): the gateway rebuilds upstream auth headers from scratch, so a client's Authorization/x-api-key value is never forwarded to the provider; and with stored, upstream auth comes from the encrypted connection server-side. So in stored mode, where an SDK insists on an api-key parameter, set it to the Cave key — it authenticates the gateway and goes no further.

Exact shapes (use the one matching each callsite — these are the product's published recipes, not suggestions):

OpenAI SDK (TS) — Chat Completions and Responses both route through:

tsCopy code
const client = new OpenAI({
  baseURL: `${process.env.CAVE_GATEWAY_URL}/w/<app>/openai/v1`,
  apiKey: process.env.OPENAI_API_KEY,           // byok: unchanged · stored: use CAVE_API_KEY
  defaultHeaders: {
    "x-cave-api-key": process.env.CAVE_API_KEY!,
    // byok only:
    "x-cave-upstream-key": process.env.OPENAI_API_KEY!,
  },
});

OpenAI SDK (Python) — same shape: base_url=f"{gw}/w/<app>/openai/v1", default_headers={"x-cave-api-key": ..., "x-cave-upstream-key": ...}.

Anthropic SDK (TS/Python) — the SDK appends /v1/messages itself. The x-cave-api-key header is required here in both modes (this SDK's own key param rides x-api-key, which is not a gateway-auth header):

pythonCopy code
client = anthropic.Anthropic(
    base_url=f"{os.environ['CAVE_GATEWAY_URL']}/w/<app>",
    api_key=os.environ["ANTHROPIC_API_KEY"],      # byok: unchanged · stored: use CAVE_API_KEY
    default_headers={
        "x-cave-api-key": os.environ["CAVE_API_KEY"],
        # byok only:
        "x-cave-upstream-key": os.environ["ANTHROPIC_API_KEY"],
    },
)

Vercel AI SDK — createOpenAICompatible({ baseURL: ${gw}/w//openai/v1, headers: { "x-cave-api-key": ... } }); Anthropic models via createAnthropic({ baseURL: ${gw}/w//v1, headers: { ... } }).

LangChain / LangGraph — ChatOpenAI(base_url=f"{gw}/w/<app>/openai/v1", default_headers={...}); ChatAnthropic(base_url=f"{gw}/w/<app>", default_headers={...}). LangGraph inherits whatever model you pass it.

LiteLLM — per call api_base=f"{gw}/w/<app>/openai/v1" + extra_headers={...}, or fleet-wide in the LiteLLM proxy config.yaml.

Raw HTTP / anything else — swap the host, keep the provider's native path: GATEWAY/w/<app>/v1/chat/completions (OpenAI protocol) or GATEWAY/w/<app>/v1/messages (Anthropic protocol), add the header(s).

Concretely, with slug support-bot and the hosted gateway, an OpenAI-SDK base URL reads https://gateway.caveman.so/w/support-bot/openai/v1. And in stored mode, drop every x-cave-upstream-key line entirely — it is byok-only.

For frameworks not listed (google-genai, crewai, pydantic-ai, openai-agents), fetch the matching page under <docs origin>/docs/integrations/ — same origin this skill came from — and follow it.

Add to the repo's env file (and reference from code — no literals):

Copy code
CAVE_GATEWAY_URL=<GATEWAY>
CAVE_API_KEY=<CAVE_API_KEY>

Step 4 — Verify with one real request

The user pasted the setup prompt to authorize exactly this: one small verification request. Send it now — do not pause to ask permission for it. An integration that ends unverified because you hesitated is a worse outcome than one tiny request; finishing the verification and the report autonomously is the point of this skill.

Send one minimal request through the wiring you just built — the app's own cheapest path if it has a script for it, otherwise curl on the path matching the protocol you just wired with the app's own model and a small cap (max_tokens ≤ 32):

bashCopy code
# OpenAI-protocol wiring:
curl -sS "$CAVE_GATEWAY_URL/w/<app>/v1/chat/completions" \
  -H "x-cave-api-key: $CAVE_API_KEY" \
  -H "content-type: application/json" \
  -d '{"model":"<model the repo already uses>","max_tokens":16,"messages":[{"role":"user","content":"ping"}]}'

# Anthropic-protocol wiring:
curl -sS "$CAVE_GATEWAY_URL/w/<app>/v1/messages" \
  -H "x-cave-api-key: $CAVE_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{"model":"<model the repo already uses>","max_tokens":16,"messages":[{"role":"user","content":"ping"}]}'

(byok: add -H "x-cave-upstream-key: $PROVIDER_KEY".) This is one real, billable provider request — that is the point: real traffic, real measurement.

Read the response. Success = HTTP 200 with a usage block. Anything else = the matching failure template below.

Step 5 — Report

End with exactly this shape, values filled from what you actually did and saw:

Copy code
## Caveman is live in this repo

Wired: <n> callsite(s) in <n> file(s)
  - <file> — <one-line what changed>
App slug: <app> — spend for this app groups under it
Verified: HTTP 200 · model <model> · <in> in / <out> out tokens (one real request)
Mode: record — measured only. No model-visible bytes changed, no optimization
enabled. Verified savings are $0 until you turn an optimizer on and it passes
its eval gate. That honesty is the product.

See the dollars: <DASHBOARD>/traces — your request is the top row, priced from
the public catalog. <DASHBOARD>/getting-started flips to "First request received."

Want spend split by workflow (e.g. support-reply vs nightly-digest), not just
by app? Say "discover workflows" — I'll fetch <docs origin>/docs/discover-workflows.md
and label every callsite by the job it does.

Failure templates (use verbatim, filled in — never soften)

• Nothing to wire: "I found no LLM callsites in this repo (searched SDKs, raw provider HTTP, base-URL env vars). If this repo runs a coding agent rather than shipping LLM code, use caveman wrap <agent> instead — see /getting-started."
• Gateway unreachable: "The verification request could not reach GATEWAY (). Wiring is in place but unverified — nothing will be measured until the gateway is reachable. Check the URL and network, then re-run the verification curl above."
• 401 cave_invalid_api_key: "The gateway rejected CAVE_API_KEY. Mint a new key at /getting-started and update the env file; the wiring itself is unchanged."
• 404 cave_route_not_found: "The gateway matched no route — usually a malformed /w/ slug (lowercase [a-z0-9] first, then [a-z0-9._-], max 64) or a path that doesn't match the SDK's protocol. Fix the URL and re-verify."
• Provider error (4xx/5xx via gateway): report status + body verbatim; the gateway is reachable and auth passed, the upstream call failed — usually a provider key or model-name issue in the app itself.

Never report success on any of these. An unverified integration is reported as unverified.