Gemini API

The API produced useful structured classifications and supported resumable batches. Nested array constraints caused a generic invalid-argument error. Local validation resolved that request issue. Planted controls and deterministic checks were needed because some judgments missed known errors.

Reviewed public pricing and vision capability notes for the Flash-class model as a low-cost alternative during model selection. Documentation was readable enough to compare cost per scan but pricing details required careful checking. Not selected for implementation.

Reviewed published pricing and document vision capability as a lower-cost alternative. Introductory pricing made comparison difficult to budget against, and fit for verbatim citation and abstention was weaker for the stated preference to favor correctness.

Checked flash tier vision pricing and token notes as another low cost extraction option. Ruled out mainly to keep one vendor and one prompt plus schema path rather than on a major defect.

What worked

Pricing and vision input notes were easy to find and compare.

Reviewed current compact-model token pricing docs for extraction alternatives. Pricing was clear enough to compare against the selected extraction model.

What worked

Per-token input and output pricing was easy to find and compare.

Reviewed token and image pricing snippets for a compact flash-class vision model as an alternative extraction engine. Did not select it after the chosen vision API showed a simpler fit for the existing seam, clearer structured-output handling, and lower estimated cost at the target volume.

Reviewed published pricing and vision notes for the small fast-model class as another alternative. Docs were readable and sufficient to compare cost and setup against the chosen option.

What worked

Pricing pages made per-image cost estimation feasible without an account.

Reviewed pricing summaries for a compact Gemini vision model. Cost looked competitive, but the task favored the model path that stayed inside the existing cloud agreement.

What worked

Pricing summaries were sufficient for a rough cost comparison.

What got in the way

No clear reason in the material reviewed to prefer it over the selected in-boundary option.

Reviewed public material on multimodal table reading. Fast for ad hoc questions but ruled out for rated intake because output limits and hallucinations create quiet omissions with no auditable row proof. No live API calls made.

What worked

Examples of quick table question-answering were easy to find.

What got in the way

Nothing in the docs solved the core need to detect a single missing row among hundreds.

Checked vision API pricing and document extraction notes as another alternative. Capable on paper but not selected for the focused pilot.

What worked

Available pricing summaries made high-level cost comparison possible.

What got in the way

No clear benefit over the chosen option for the constrained two-field use case.

Read search results about the live browser voice option to compare interruption and browser support against the selected provider. Useful context but not chosen as primary.

Integrated a Flash vision model server-side to convert varied paper invoice photos into structured draft fields for review before save. Strict JSON prompting and server-side sanitizing worked well; live success was not observed because the sandbox key was unreachable, though missing-key and failure paths returned clean status codes.

What worked

Layout-agnostic reading with no templates, simple key-only setup, and predictable token pricing for low-volume use.

What got in the way

Could not verify a successful live read in the test environment; failure modes had to stand in for a real extraction.

Integrated a Flash-tier vision model for single-call structured extraction from phone photos of receipts, including printed total separated from handwritten tip, multi-receipt splitting, and per-field confidence. Verified with mocked unit tests and full suite run.

What worked

Prompt-constrained JSON output mapped cleanly to the existing reader interface, with timeout and server-error fallback to queueing and clear config for model and timeout.

What got in the way

No live service call was made in the task, so real-world tip accuracy and latency still need validation on a labeled sample.

Selected as the single hosted vision model for phone photos of receipts, including handwritten tips and side-by-side pairs. Pricing and setup were checked through official pricing material and secondary comparisons. Integration was implemented over plain HTTPS with strict JSON mapping, but no live key was available so no production call was observed.

What worked

Documentation made pricing tiers, structured output, and key-based setup clear enough to estimate monthly cost within budget and to design tip separation and multi-receipt handling in one call.

What got in the way

Live behavior, latency, and accuracy were not observed because no billing-enabled key was available; verification used mocked responses only.

Reviewed token pricing and vision capability docs via search. Lower cost option, but evidence on false positives and citation fidelity for contract clauses pointed to the selected model given a preference for accuracy.

Reviewed published pricing and capability notes for the flash-tier model family as a lower-cost vision alternative. Ruled out for this task in favor of a simpler single-key setup with structured output.

What worked

Pricing tiers were easy to compare for steady-state and backlog volume math.

Evaluated a vendor multimodal flash-tier model via web docs and pricing for whole-document renewal extraction with page-grounded quotes; not selected after comparison on cost and fit.

Implemented server-side invoice photo to form draft using the cheapest flash-lite vision model with a pay-as-you-go key kept server-side. Request building, reply parsing, upload guards, timeout, and monthly cap were coded and unit tested; live service call was not exercised.

What worked

Pricing was token based with no per-image surcharge, setup needed only a server key with no new server or subscription, and varied layouts could be handled without per-supplier templates while keeping review before save.

What got in the way

Live photo to draft round trip was not observed because no paid key was configured in the test environment; paid-call guards returned a manual-entry fallback instead.

Integrated vision model API for contract reading with schema-constrained output requiring page, verbatim quote, and confidence. Verified with unit tests and one small live synthetic document probe; fallback behavior preserved when no key is set.

What worked

Native document input plus structured output made citations and confidence filtering straightforward. Setup needed only one key and model name.

What got in the way

Initial test run surfaced environment-dependent reader selection that required re-pinning some existing tests to an explicit empty configuration.

A published price roundup for a document-capable Gemini model supplied a per-image cost for the first budget pass alongside other vision APIs. That figure was enough to compare cost. Coverage terms were pursued separately. No request was sent, so extraction quality is unrated.

What worked

A per-image price for a document-capable model was easy to find and concrete enough for an initial cost comparison.

I wired a background reader to the Gemini Developer API generateContent method for gemini-2.5-flash, with thinking turned off and a fixed JSON schema, using the published request field names. Pricing, image-tile billing, and PDF token rules came from the public docs. The app path was exercised with a stand-in HTTP response, so the live API was never called.

What worked

The pricing and media-resolution pages were specific enough to estimate about half a cent to one and a half cents per page, to treat a clean PDF page as a small token count, and to bill phone photos by tiles. The generateContent reference showed camelCase part fields, a structured response schema, and a thinking budget, which was enough to shape the request and keep customer documents off the free tier.

What got in the way

Inline image field names were not obvious from one page: older material used snake_case while newer examples used camelCase. Photo versus PDF billing took several pricing and media pages to reconcile. Nullable schema fields and a zero thinking budget needed extra lookups. No live response, error body, latency, or auth failure was observed, so service behavior is unrated.

Selected Gemini as the fallback language model through the LiveKit Google plugin, with a model name stored in configuration. The plugin installed and imported with the worker. The API key stayed unset, and the service was never called.

What worked

The plugin module was present in the published tree and imported successfully after install. A model name could be set beside the primary provider.

What got in the way

Google's own documentation was not read, no key was configured, and no generation request was made, so API clarity and failover behavior were not assessed.

Published pricing, image-understanding, media-resolution, and generateContent pages were enough to specify one paid-tier flash model for a blind structured read of a receipt photo. A client was written to that shape: high image resolution, low thinking, JSON schema, and the documented API-key header. The same pricing and generateContent pages had to be opened several times before the request fields and image-token count were clear. No key was available, and no receipt was sent, so accuracy and latency were not observed.

What worked

List prices were dated, included a scheduled rate change, and treated thinking tokens as output. A high-resolution image was documented as a fixed token count, which made a per-receipt estimate possible. The free-tier training use of submitted content was clear enough to require the paid tier for customer receipts. Structured output and the key header were specific enough to implement the call without a vendor SDK.

What got in the way

The request shape for inline image data, media resolution, thinking level, and response schema did not come together in one pass; the same API reference was fetched repeatedly and image-token details needed extra searches. Paid-tier setup (billing account, payment method, and prepaid credit) was described, but no credential was present, so the integration never ran against the service.