# 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
Registers a new aibridge provider for ChatGPT by reusing the existing
OpenAI provider with a different `Name` and `BaseURL`
(https://chatgpt.com/backend-api/codex). The ChatGPT backend API is
OpenAI-compatible, so no new provider type is needed.
ChatGPT authenticates exclusively via per-user OAuth JWTs (BYOK mode) —
no centralized API key is configured. The OpenAI provider already
handles this: when no key is set, it falls through to the bearer token
from the request's Authorization header.
Depends on #23811
## Description
Adds support for multiple Copilot provider instances to route requests to different Copilot upstreams (individual, business, enterprise). Each instance has its own name and base URL, enabling per-upstream metrics, logs, circuit breakers, API dump, and routing.
## Changes
* Add Copilot business and enterprise provider names and host constants
* Register three Copilot provider instances in aibridged (default, business, enterprise)
* Update `defaultAIBridgeProvider` in `aibridgeproxy` to route new Copilot hosts to their corresponding providers
## Related
* Depends on: https://github.com/coder/aibridge/pull/240
* Closes: https://github.com/coder/aibridge/issues/152
Note: documentation changes will be added in a follow-up PR.
_Disclaimer: initially produced by Claude Opus 4.6, heavily modified and reviewed by @ssncferreira ._
## Problem
`aibridgeproxyd` sends `X-AI-Bridge-Request-Id` on every MITM request to
`aibridged` for cross-service log correlation, but aibridged never reads
it. The header is silently forwarded to upstream LLM providers.
## Changes
* Renamed the header to `X-Coder-AI-Governance-Request-Id` to match the
existing `X-Coder-AI-Governance-*` convention.
* `aibridged` now extracts the header, logs it and strips it before
forwarding upstream.
* Added `TestServeHTTP_StripInternalHeaders` to verify no `X-Coder-*`
headers leak to upstream
### Changes
**coder/coder:**
- `coderd/aibridge/aibridge.go` — Added `HeaderCoderBYOKToken` constant,
`IsBYOK()` helper, and updated `ExtractAuthToken` to check the BYOK
header first.
- `enterprise/aibridged/http.go` — BYOK-aware header stripping: in BYOK
mode only the BYOK header is stripped (user's LLM credentials
preserved); in centralized mode all auth headers are stripped.
<hr/>
**NOTE**: `X-Coder-Token` was removed! As of now `ExtractAuthToken`
retrieves token either from `X-Coder-AI-Governance-BYOK-Token` or from
`Authorization`/`X-Api-Key`.
---------
Co-authored-by: Susana Ferreira <susana@coder.com>
Co-authored-by: Danny Kopping <danny@coder.com>
## Description
Introduces a new `X-Coder-Token` header for authenticating requests from
AI Proxy to AI Bridge. Previously, the proxy overwrote the
`Authorization` header with the Coder token, which prevented the
original authentication headers from flowing through to upstream
providers.
With this change, AI Proxy sets the Coder token in a separate header,
preserving the original `Authorization` and `X-Api-Key` headers. AI
Bridge uses this header for authentication and removes it before
forwarding requests to upstream providers. For requests that don't come
through AI Proxy, AI Bridge continues to use `Authorization` and
`X-Api-Key` for authentication.
## Changes
* Add `HeaderCoderAuth` constant and update `ExtractAuthToken` to check
headers in the following order: `X-Coder-Token` > `Authorization` >
`X-Api-Key`
* Update AI Proxy to set `X-Coder-Token` instead of overwriting
`Authorization`
* Remove `X-Coder-Token` in AI Bridge before forwarding to upstream
providers
* Add tests for header handling and token extraction priority
Related to: https://github.com/coder/internal/issues/1235
## Summary
This adds configurable overload protection to the AI Bridge daemon to
prevent the server from being overwhelmed during periods of high load.
Partially addresses coder/internal#1153 (rate limits and concurrency
control; circuit breakers are deferred to a follow-up).
## New Configuration Options
| Option | Environment Variable | Description | Default |
|--------|---------------------|-------------|---------|
| `--aibridge-max-concurrency` | `CODER_AIBRIDGE_MAX_CONCURRENCY` |
Maximum number of concurrent AI Bridge requests. Set to 0 to disable
(unlimited). | `0` |
| `--aibridge-rate-limit` | `CODER_AIBRIDGE_RATE_LIMIT` | Maximum number
of AI Bridge requests per second. Set to 0 to disable rate limiting. |
`0` |
## Behavior
When limits are exceeded:
- **Concurrency limit**: Returns HTTP `503 Service Unavailable` with
message "AI Bridge is currently at capacity. Please try again later."
- **Rate limit**: Returns HTTP `429 Too Many Requests` with
`Retry-After` header.
Both protections are optional and disabled by default (0 values).
## Implementation
The overload protection is implemented as reusable middleware in
`coderd/httpmw/ratelimit.go`:
1. **`RateLimitByAuthToken`**: Per-user rate limiting that uses
`APITokenFromRequest` to extract the authentication token, with fallback
to `X-Api-Key` header for AI provider compatibility (e.g., Anthropic).
Falls back to IP-based rate limiting if no token is present. Includes
`Retry-After` header for backpressure signaling.
2. **`ConcurrencyLimit`**: Uses an atomic counter to track in-flight
requests and reject when at capacity.
The middleware is applied in `enterprise/coderd/aibridge.go` via
`r.Group` in the following order:
1. Concurrency check (faster rejection for load shedding)
2. Rate limit check
**Note**: Rate limiting currently applies to all AI Bridge requests,
including pass-through requests. Ideally only actual interceptions
should count, but this would require changes in the aibridge library.
## Testing
Added comprehensive tests for:
- Rate limiting by auth token (Bearer token, X-Api-Key, no token
fallback to IP)
- Different tokens not rate limited against each other
- Disabled when limit is zero
- Retry-After header is set on 429 responses
- Concurrency limiting (allows within limit, rejects over limit,
disabled when zero)
Yevhenii Shcherbina