## Description
AI Gateway computes the cost of an interception from `ai_model_prices`,
which is seeded on every server start from a price book embedded in the
binary. A model the price book does not cover records a NULL cost, so
its spend is invisible to cost reporting and is not enforced against
budgets. The only fix was to wait for a Coder release that added the
model.
This adds an experimental CLI, backed by an experimental HTTP endpoint,
for pricing those models. Models the price book already covers are
rejected, because the seeder re-applies the book on every start and
would overwrite an operator price. Support for custom pricing will be
handled in
https://linear.app/codercom/issue/AIGOV-589/extend-experimental-cli-command-to-set-custom-ai-model-prices.
## Commands
```
coder exp ai-model-prices list [--provider] [--model]
coder exp ai-model-prices update [file|-] [--provider] [--model] [--input-price] [--output-price] [--cache-read-price] [--cache-write-price] [--yes]
```
## Changes
- Add `GET` and `POST /api/experimental/ai/model-prices`, gated behind
the AI Bridge entitlement and the existing `ai_model_price` RBAC
resource.
- Add a `GetAIModelPrices` query with optional `provider` and `model`
filters applied in SQL.
- Validate the whole request before writing anything, so one bad entry
cannot leave the table half updated, and report every problem at once.
- Reject prices for models the embedded price book already covers,
through a new `prices.IsDefaultPriced`.
- Add the `coder exp ai-model-prices` command with `list` and `update`.
`update` accepts a JSON document or the single-model flags and prints a
plan, asking to confirm unless the document is piped in or `--yes` is
passed.
- Consolidate the supported provider list into
`coderd/aibridge/prices/providers` so the price generator and the server
share one definition.
- Add `codersdk` types and client methods for both endpoints, and bound
the request body at 1 MiB.
- Document the command in the AI Gateway cost controls page.
Closes
https://linear.app/codercom/issue/AIGOV-567/experimental-cli-command-to-set-prices-for-unpriced-ai-models
> [!NOTE]
> Initially generated by Claude Opus 5, modified and reviewed by
@ssncferreira
Adds the full set of supported provider types to
`scripts/aibridgepricesgen` and updates stored model prices.
Notes:
* We need to rename a few keys from models.dev JSON to match our
internal provider types.
* `prices.json` is now marked as generated.
---------
Co-authored-by: Susana Ferreira <susana@coder.com>
- Regenerates `prices.json` from models.dev. The seeder only upserts, so
existing deployments keep delisted models.
- Generate the frontend known-models catalog instead of hand-writing it.
`make gen/aibridge-prices` fetches models.dev once
- Moved patches to model definitions to separate `overrides.jq` which
handles both `claude-sonnet-4-5` 200k context and 'aliasing' Fable 5
as Mythos 5.
- Editorial choices of selection, order, aliases, and reasoning defaults
live in `curation.json`.
- Adds golden join tests with one error case per validation, a
no-network drift test comparing curation to the checked-in artifact, and
pinned invariants for the Anthropic thinking-mode split (the wrong side
returns HTTP 400) and the sonnet-4-5 context pin.
Adding a model is now one `curation.json` entry plus `make
gen/aibridge-prices`, assuming it is present on models.dev.
> This PR was authored by Coder Agents on Cian's behalf.
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
# Summary
Implements
https://linear.app/codercom/issue/AIGOV-282/add-ai-model-price-table-and-seed-generator
This PR lays the groundwork for AI Bridge cost controls (per the AI
Governance RFC). It adds the foundation needed for future cost tracking:
a place to store per-model token prices, a way to keep those prices in
sync with upstream pricing data, and a startup mechanism that ensures
every deployment has prices loaded before AI Bridge starts processing
requests.
The price data comes from [models.dev](https://models.dev/), a
community-maintained catalogue of AI provider pricing. A generator
script fetches the latest prices, filters to Anthropic and OpenAI for
now, and produces a seed file checked into the repository.
On every server startup the seed is applied to the database, so new
releases automatically pick up any price corrections that landed since
the previous one. Existing rows are overwritten with the latest prices;
rows for models no longer in the seed are left untouched.
# Batching the AI model price seed: three approaches
Context: at server startup we seed the `ai_model_prices` table from an
embedded JSON price book (~70 rows today, will grow as we add providers,
potentially 4000+).
Each row is:
```text
(provider, model, input_price, output_price, cache_read_price, cache_write_price)
```
Any of the four price columns can be:
- `NULL` → “price unknown for this dimension”
- explicit `0` → “free”
The batch must be an UPSERT so re-running is idempotent and existing
rows pick up new prices.
We considered three implementations.
---
## Approach 1 — Per-row UPSERT in a Go loop
```go
for _, row := range rows {
if err := db.UpsertAIModelPrice(ctx, database.UpsertAIModelPriceParams{
Provider: row.Provider,
Model: row.Model,
InputPrice: nullInt64(row.InputPrice),
// ...
}); err != nil {
return err
}
}
```
### Pros
- Trivial.
- NULL handling falls out naturally from `sql.NullInt64`.
### Cons
- `N` round-trips per seed.
- With ~70 rows that means ~70 statement executions on every startup,
even inside a transaction.
- Doesn't scale gracefully as the price book grows, potentially 4000+.
---
## Approach 2 — `UNNEST` with parallel arrays
Pass each column as a separate Go slice. Postgres unnests them in
parallel into a virtual table, then `INSERT ... SELECT`.
```sql
INSERT INTO ai_model_prices (
provider,
model,
input_price,
output_price,
cache_read_price,
cache_write_price
)
SELECT
UNNEST(@providers::text[]),
UNNEST(@models::text[]),
NULLIF(UNNEST(@input_prices::bigint[]), -1),
NULLIF(UNNEST(@output_prices::bigint[]), -1),
NULLIF(UNNEST(@cache_read_prices::bigint[]), -1),
NULLIF(UNNEST(@cache_write_prices::bigint[]), -1)
ON CONFLICT (provider, model) DO UPDATE SET
input_price = EXCLUDED.input_price,
output_price = EXCLUDED.output_price,
cache_read_price = EXCLUDED.cache_read_price,
cache_write_price = EXCLUDED.cache_write_price,
updated_at = NOW();
```
Go side: flatten rows into six parallel slices.
Use a sentinel (`-1`) for “missing”, since `lib/pq` can't encode `NULL`
into a `bigint[]` element.
```go
providers := make([]string, len(rows))
models := make([]string, len(rows))
inputs := make([]int64, len(rows))
outputs := make([]int64, len(rows))
cacheR := make([]int64, len(rows))
cacheW := make([]int64, len(rows))
for i, r := range rows {
providers[i] = r.Provider
models[i] = r.Model
inputs[i] = -1
if r.InputPrice != nil {
inputs[i] = *r.InputPrice
}
outputs[i] = -1
if r.OutputPrice != nil {
outputs[i] = *r.OutputPrice
}
cacheR[i] = -1
if r.CacheReadPrice != nil {
cacheR[i] = *r.CacheReadPrice
}
cacheW[i] = -1
if r.CacheWritePrice != nil {
cacheW[i] = *r.CacheWritePrice
}
}
return db.UpsertAIModelPrices(ctx, database.UpsertAIModelPricesParams{
Providers: providers,
Models: models,
InputPrices: inputs,
OutputPrices: outputs,
CacheReadPrices: cacheR,
CacheWritePrices: cacheW,
})
```
### Pros
- Single round-trip.
### Cons
- The generated `sqlc` params become plain `[]int64`, which can't
represent `NULL`.
---
## Approach 3 — `jsonb_array_elements` over a single `@seed::jsonb`
(chosen)
Pass the raw seed JSON as one parameter; let Postgres expand and parse
it.
```sql
INSERT INTO ai_model_prices (
provider,
model,
input_price,
output_price,
cache_read_price,
cache_write_price
)
SELECT
elem->>'provider',
elem->>'model',
(elem->>'input_price')::bigint,
(elem->>'output_price')::bigint,
(elem->>'cache_read_price')::bigint,
(elem->>'cache_write_price')::bigint
FROM jsonb_array_elements(@seed::jsonb) AS elem
ON CONFLICT (provider, model) DO UPDATE SET
input_price = EXCLUDED.input_price,
output_price = EXCLUDED.output_price,
cache_read_price = EXCLUDED.cache_read_price,
cache_write_price = EXCLUDED.cache_write_price,
updated_at = NOW();
```
Go side reduces to:
```go
return db.UpsertAIModelPrices(ctx, seedJSON)
```
### Pros
- Single round-trip.
- NULLs fall out naturally:
- `(elem->>'cache_write_price')::bigint` becomes `NULL`
- no sentinels
- The seed is already JSON:
- Existing precedent:
- `jsonb_array_elements` is already used elsewhere in the codebase
### Cons
- Less type-safe at the SQL boundary than `UNNEST`
- Slightly less standard than `UNNEST`
- Readers need familiarity with:
- `jsonb_array_elements`
- `->>` extraction syntax
- Postgres pays JSON parse cost
- negligible at our scale
---
---
# Decision
We picked Approach 3.
It collapses the round-trips like `UNNEST` does, but without:
- nullable-array workarounds
- sentinel values
Susana Ferreira