KeyCall

One consistent interface for validating AI-provider API keys, listing and filtering the models available to them, and making normalized calls, so every product stops rebuilding the same model-picker filters and provider wrappers.

Status: 1.0. Key validation, model listing and filtering, text generation, streaming, tool calling, native web search with normalized citations, structured JSON output, embeddings, image, speech, realtime voice, and video generation, and image, audio, and document input all work and are live-verified against every provider that supports them. The API is stable.

Docs: USAGE.md for the full API and CLI reference · ARCHITECTURE.md for the layer diagram and component contracts · CHANGELOG.md for version history.

Install

pip install keycall

See it work in 30 seconds

No config file, no signup, nothing to write. Export a key you already have and point KeyCall at the variable:

export OPENAI_API_KEY=...

keycall verify --provider openai --source env:OPENAI_API_KEY --generate

✓ OPENAI_API_KEY (openai): key accepted, 79 text model(s), list digest 6d356bc3f4c24389, selection rule v4
✓ OPENAI_API_KEY: generated with gpt-5.6-luna (filtered position 0, provider-list position 123, 830 ms, total tokens: 18)

That is one command telling you the key is valid, how many text models it can reach, and that a generation came back — including which model answered and where it sat in the provider's own list. Swap openai for anthropic, gemini, deepseek, perplexity, moonshot, or xai and it works the same way.

Prefer to click around? Same key, one word different:

keycall view --provider openai --source env:OPENAI_API_KEY

That opens a local web app in your browser with your key already loaded: a dashboard that checks it live, a browsable model list with category filters, and a Playground where you can chat, show a model a picture, record a voice message straight from the page, attach a PDF, offer it a tool, or have it draw you something. Keys stay in the local server process and never reach the browser.

Got several keys? Put them in a file and load them all at once — see keycall-test-keys.example.toml for the format:

keycall view --source ./keys.toml

From a fresh clone with no Python set up at all, double-click a launcher instead: launch.command (macOS), launch.sh (Linux/macOS), launch.bat (Windows). Each creates the venv, installs KeyCall, finds your key file, and opens the viewer.

Use it from Python

from keycall import KeyCall, Message, ModelCategory, TextInput

with KeyCall(provider="openai", api_key=secret) as client:
    discovery = client.list_models(categories={ModelCategory.TEXT_GENERATION})

    result = client.generate_text(
        model=discovery.models[0].id,
        messages=[Message(role="user", content=[TextInput(text="Hello.")])],
    )

print(result.text)
print(result.usage.total_tokens)
print(result.round_trip_duration_ms)

What you get

• Explicit provider, always. KeyCall never guesses which vendor issued a key and never sends a credential to more than the one provider you name.
• No credential storage. Keys live in memory for the client's lifetime, wrapped in a redacting type that keeps them out of reprs, logs, traces, exceptions, and pickles. Your app decides how to store them.
• Model filtering built in. Text-generation models by default; embeddings, image, audio, and other categories on request; unknown models never silently enter the default picker.
• Typed errors. Invalid key, rate limit, provider outage, timeout, and malformed response are distinguishable, never collapsed into "invalid key."
• Streaming. stream_text() yields typed events (text increments, visible reasoning progress, citations, tool calls, finish) across all four wire protocols, and refuses to call a stream complete without the provider's own terminal signal.
• Tool calling. Define tools once and KeyCall normalizes all four call/result wire shapes, streamed or not, carrying the provider echo data some models require back verbatim. It never executes a tool.
• Image generation. generate_image() returns the picture as bytes with the media type the provider produced, on OpenAI and Gemini; the rest refuse before the network.
• Speech generation. generate_speech() speaks text aloud on OpenAI and Gemini, the only providers with a public API for it — Anthropic's voice mode runs on a third-party subcontractor behind a consumer app, not a callable endpoint. The result carries the media type the provider sent, including Gemini's raw PCM, never a container the provider didn't produce.
• Video generation. start_video() returns a job handle, check_video() polls it, fetch_video() downloads the finished MP4 — or generate_video() runs all three against a timeout you choose. Gemini (Veo) and xAI (Grok Imagine) support it; the rest refuse before the network. A timeout hands back the still-valid job, so a slow render is never lost.
• Embeddings. embed() returns one vector per input, in input order, on OpenAI and Gemini; providers without an embeddings endpoint refuse before the network instead of 404ing.
• Images, audio, and documents. Pass bytes (or a URL where the provider fetches one) beside your text; KeyCall maps each provider's shape and detects the media type from the content. Support varies by provider and by form, so a refusal happens before the network and names who does accept that kind.
• Web search with citations. web_search=True turns on the provider's native search tool (OpenAI, Anthropic, Gemini, xAI, Moonshot; Perplexity always searches) and returns sources normalized to one Citation shape (Moonshot reports none).
• Reasoning effort control. reasoning_effort="low" (or "medium" / "high") maps to the provider's native thinking control on OpenAI, Anthropic, Gemini, Perplexity, and xAI — each verified live to move reasoning-token spend. Providers that accept the parameter without honoring it refuse instead of silently ignoring it.
• Realtime voice sessions. realtime() opens a live WebSocket conversation on OpenAI, xAI, or Gemini — text or microphone audio up, normalized audio/transcript/turn events down, sync and async. The credential rides the handshake headers and never enters a URL.
• Structured output. response_schema=<JSON Schema> is enforced provider-side on OpenAI, Anthropic, Gemini, Moonshot, and Perplexity; on providers without enforcement (DeepSeek, unverified custom targets) KeyCall falls back to guaranteed-valid-JSON mode and adds a result warning rather than claiming a guarantee it can't back. result.text is always the JSON string, regardless of which mechanism produced it.
• Hardened transport. TLS always verified, redirects refused, response sizes capped, SSRF and DNS-rebinding guards on custom endpoints, and generation is never silently retried.

Provider support

Live-verified 2026-08-10. Every release re-runs a model list, a bounded generation, a stream, a full tool round (streamed and not), an image, sound, and document read, embeddings, image generation, an async round trip, and a probe that each provider still reaches a working model well inside the attempt budget, against every provider that supports them, and blocks publishing if any of it fails:

OpenAI advertises -latest aliases its own account can't invoke, and is retiring that family wholesale. On 2026-08-10 all four were dead: gpt-5-chat-latest and gpt-5.1-chat-latest returned "Model not found", and gpt-5.2-chat-latest and gpt-5.3-chat-latest were newly deprecated hours after both had worked. The numbered models were healthy throughout. This is the same failure as Gemini's retired models, on a provider people assume is tidier, and it is why verify walks the candidates and reports every attempt rather than trusting the first listed model.

Because of that, candidate order follows the provider's own dates where it publishes them. OpenAI, Anthropic, and Moonshot date every model they list, and a model a provider published recently is one it hasn't yet retired, so KeyCall tries the newest first. Gemini and DeepSeek publish no dates, and there maintained -latest aliases lead instead, which is right for Gemini because it keeps those aimed at a live model. Sorting aliases first everywhere was the earlier rule, and on OpenAI it put the four worst candidates at the front of every walk. A release probe now checks each provider still reaches a working model well inside the attempt budget, so this kind of drift is caught before it reaches a key.

Two further provider quirks worth knowing, both handled:

Gemini keeps retired models in its list endpoint with no lifecycle field to pre-filter on, and withdraws them per account ahead of the published shutdown date: on 2026-08-09 the first six text models it advertised to a new key were all refused, gemini-2.5-* with "no longer available to new users" months before its documented shutdown. Gemini dates none of its models, so KeyCall tries its maintained -latest aliases first there, and verification reaches a model that works instead of walking a list of withdrawn ones; the error for a retired model names those aliases. It also meters quota per model and tier, so one model's 429 says nothing about the next. Its supportedGenerationMethods is a transport signal rather than a modality claim: TTS variants advertise generateContent and then refuse a text response, and so do the Interactions-only, computer-use, and music families, so KeyCall lets the identifier outrank it and keeps those out of the default text picker.

Perplexity's GET /v1/models is scoped to the Agent API and returns vendor-prefixed router models (anthropic/..., perplexity/sonar) that the Sonar route rejects. Sonar's own models aren't API-discoverable, so KeyCall maintains them in its catalog and uses the list call purely as a credential check. Note the version prefix: the unversioned https://api.perplexity.ai/models returns 404 for every key, valid or not, so anything validating a key against that path rejects good credentials. /v1/models answers 401 for a bad key and 200 for a good one, which is what makes it usable as a check (verified 2026-08-09).

Structured output notes, per provider

• OpenAI requires additionalProperties: false on every object level of the schema for its strict json_schema mode, or the request 400s. This is an OpenAI requirement, not a KeyCall one — write schemas with it from the start.
• Anthropic implements structured output by forcing a single synthetic tool call; it can't be combined with web_search=True in the same request (forcing one tool prevents the model calling a different one), and KeyCall rejects that combination before any network call.
• Gemini's equivalent combination (web_search=True with response_schema) isn't gated — no live-verified evidence either way that Gemini rejects it, so KeyCall passes it through rather than guessing.
• DeepSeek hard-requires the literal word "json" somewhere in the prompt for its json_object fallback mode, or it 400s. KeyCall detects this and injects a short system instruction automatically when needed, and always says so via a result warning.
• Moonshot/Kimi reasoning-capable models can spend the entire max_output_tokens budget on a visible reasoning trace and never emit a final answer if the budget is too small. KeyCall detects the resulting empty-content-with-reasoning-trace response and adds a warning rather than returning a silent empty result; give these models a larger budget than you'd expect a short answer to need.

Because of quirks like these, keycall verify --generate walks the filtered models in provider order and prints the outcome of every attempt until one succeeds, so drift stays visible rather than being masked by a silent retry.

The viewer and the verify CLI in full

The viewer is token-protected and binds 127.0.0.1. Opening the printed link trades its token for an httpOnly, SameSite=Strict session cookie and strips it from the address bar, so the secret never reaches page script or browser history, and state-changing requests are CSRF-checked. Inside: a dashboard with live key checks, a sortable model browser, a Playground (text, pictures in and out, recordings, documents, tool calling, web search), and a verify report that walks every key. An attachment the selected key can't send is turned off with a line naming a key that can.

keycall verify takes the same sources as the viewer — TXT, JSON, or TOML files, an env:VAR_NAME reference, or an interactive prompt — and --generate adds one small bounded call per target. Keys never appear in output, and KeyCall never writes to or deletes your credential file. Full reference in USAGE.md.

Development

pip install -e ".[dev]"
pytest

Author

Built by Mo Shehu.

License

AGPL-3.0-or-later. See LICENSE.