190proof opinionated unified interface to interact with multiple AI providers

A new npm package called 190proof provides a unified interface for calling models from OpenAI, Anthropic, Google, Groq, OpenRouter, and AWS Bedrock through a single `provider:model-id` string format. The package handles retries, streaming by default, function/tool calling, message alternation, and image normalization across providers, and it degrades images to inline text references for text-only providers such as Groq or when OpenRouter rejects a request with a routing-layer 404. It is installed via `npm install 190proof` and exposes a `callWithRetries` function alongside a `GenericPayload` type.

An opinionated unified interface for interacting with multiple AI providers including OpenAI , Anthropic , Google , Groq , OpenRouter , and AWS Bedrock . This package provides a consistent API for making requests to different LLM providers while handling retries, streaming, and multimodal inputs. Fully-local unified interface across multiple AI providers that includes: - 🛠️ Consistent function/tool calling across all providers - 💬 Consistent message alternation & system instructions - 🖼️ Image format & size normalization - 🔄 Automatic retries with configurable attempts - 📡 Streaming by default - ☁️ Cloud service providers supported Azure, AWS Bedrock - 🔌 Provider prefix strings for any model without waiting for package updates npm install 190proof Use any model from any provider with the provider:model-id format: js import { callWithRetries, GenericPayload } from "190proof"; const payload: GenericPayload = { model: "openai:gpt-4o-mini", messages: { role: "user", content: "Tell me a joke.", }, , }; const response = await callWithRetries "my-request-id", payload ; console.log response.content ; js import { callWithRetries, GenericPayload } from "190proof"; // OpenAI const openaiPayload: GenericPayload = { model: "openai:gpt-5", messages: { role: "user", content: "Hello " } , }; // Anthropic const claudePayload: GenericPayload = { model: "anthropic:claude-sonnet-4-5", messages: { role: "user", content: "Hello " } , }; // Google const geminiPayload: GenericPayload = { model: "google:gemini-2.0-flash", messages: { role: "user", content: "Hello " } , }; // Groq const groqPayload: GenericPayload = { model: "groq:llama-3.3-70b-versatile", messages: { role: "user", content: "Hello " } , }; // OpenRouter const openRouterPayload: GenericPayload = { model: "openrouter:google/gemma-4-31b-it:free", messages: { role: "user", content: "Hello " } , }; const response = await callWithRetries "request-id", claudePayload ; js const payload: GenericPayload = { model: "openai:gpt-4o", messages: { role: "user", content: "What is the capital of France?", }, , functions: { name: "get country capital", description: "Get the capital of a given country", parameters: { type: "object", properties: { country name: { type: "string", description: "The name of the country", }, }, required: "country name" , }, }, , }; const response = await callWithRetries "function-call-example", payload ; // response.function call contains { name: string, arguments: Record<string, any } js const payload: GenericPayload = { model: "anthropic:claude-sonnet-4-5", messages: { role: "user", content: "What's in this image?", files: { mimeType: "image/jpeg", url: "https://example.com/image.jpg", }, , }, , }; const response = await callWithRetries "image-example", payload ; How images reach the model depends on the provider. OpenAI, Anthropic, and Google get native image blocks. Groq is text-only: images degrade to an inline Image url text reference. OpenRouter sends OpenAI-style image url content parts the remote URL when present, else a data: URI — but if the model has no vision-capable endpoints, OpenRouter rejects the request with a routing-layer 404, so the retry loop resends the payload with images degraded to the same inline text references Groq gets, and remembers the model in-process, until restart so later calls degrade up front. Messages without image attachments serialize identically either way. js const payload: GenericPayload = { model: "google:gemini-2.0-flash", messages: { role: "system", content: "You are a helpful assistant that speaks in a friendly tone.", }, { role: "user", content: "Tell me about yourself.", }, , }; const response = await callWithRetries "system-message-example", payload ; Use parseModelString to see how a model string will be routed: js import { parseModelString } from "190proof"; parseModelString "openai:gpt-7" ; // → { provider: "openai", modelId: "gpt-7" } parseModelString "openrouter:org/model-name:free" ; // → { provider: "openrouter", modelId: "org/model-name:free" } The model string format is provider:model-id , where the provider prefix is one of: | Prefix | Provider | |---|---| | openai | OpenAI | | anthropic | Anthropic | | google | Google Gemini | | groq | Groq | | openrouter | OpenRouter | The prefix is stripped before sending to the API, so the model ID should be exactly what the provider expects e.g. "openai:gpt-4o" sends "gpt-4o" to OpenAI . These models are tested. You can use any model with the provider:model-id format. - openai:gpt-5 - openai:gpt-5-mini - openai:gpt-4.1 - openai:gpt-4.1-mini - openai:gpt-4.1-nano - openai:gpt-4o - openai:gpt-4o-mini - openai:o3-mini - openai:o1-preview - openai:o1-mini - anthropic:claude-opus-4-5 - anthropic:claude-sonnet-4-5 - anthropic:claude-haiku-4-5 - anthropic:claude-opus-4-1 - anthropic:claude-opus-4-20250514 - anthropic:claude-sonnet-4-20250514 - anthropic:claude-3-5-sonnet-20241022 - anthropic:claude-3-5-haiku-20241022 - google:gemini-3.1-flash-lite-preview - google:gemini-3-flash-preview - google:gemini-2.5-flash-preview-04-17 - google:gemini-2.0-flash - google:gemini-2.0-flash-exp-image-generation - google:gemini-1.5-pro-latest - groq:llama-3.3-70b-versatile - groq:llama3-70b-8192 - groq:qwen/qwen3-32b - groq:deepseek-r1-distill-llama-70b - openrouter:google/gemma-4-31b-it:free - openrouter:google/gemma-4-31b-it Set the following environment variables for the providers you want to use: OpenAI OPENAI API KEY=your-openai-api-key Anthropic ANTHROPIC API KEY=your-anthropic-api-key Google GEMINI API KEY=your-gemini-api-key Groq GROQ API KEY=your-groq-api-key OpenRouter OPENROUTER API KEY=your-openrouter-api-key AWS Bedrock for Anthropic via Bedrock AWS ACCESS KEY ID=your-aws-access-key AWS SECRET ACCESS KEY=your-aws-secret-key Main function to make requests to any supported AI provider. - identifier : string | string - Unique identifier for the request used for logging - payload : GenericPayload - Request payload containing model, messages, and optional functions - config : OpenAIConfig | AnthropicAIConfig - Optional configuration for the specific provider - retries : number - Number of retry attempts default: 5 - chunkTimeoutMs : number - Timeout for streaming chunks in ms default: 15000 Optional per-request knobs live on payload GenericPayload : - payload.requestTimeoutMs : number - Per-attempt HTTP timeout in ms default: 120000 , honored by every adapter — except streaming OpenRouter attempts, which it deliberately does NOT bound see below . For OpenRouter's non-streaming transport the default is 180000. - payload.streaming : boolean - OpenRouter-only default: true . Streams the completion over SSE. A streaming attempt is bounded by two independent timers instead of requestTimeoutMs : streamTimeoutMs total wall clock, default 600000 and the per-useful-chunk stall timeout chunkTimeoutMs argument, default 15000 . A chunk is "useful" only if it advances content, reasoning, tool-call fragments, finish reason, or usage — SSE comment keep-alives : OPENROUTER PROCESSING and role-only deltas don't reset the stall timer, so a hung provider dies within one stall window while a healthy long generation can run to the total budget. Set streaming: false for the old single-JSON-body transport. - payload.streamTimeoutMs : number - OpenRouter-only: total wall-clock budget per streaming attempt default: 600000 . - payload.streamDeadlineAt : number - OpenRouter-only: absolute deadline epoch ms for the whole call including retries — the caller's turn budget. Each attempt gets min streamTimeoutMs, deadline - now , and once under 10s remain the call fails fast instead of starting a generation that cannot be delivered. Use it whenever the caller has its own timeout: a per-attempt budget alone is re-granted on every retry and can outlive that timeout. - payload.thinkingConfig : Record<string, unknown - Google-only: forwarded verbatim as generationConfig.thinkingConfig on the Gemini request — e.g. { thinkingBudget: 0 } to disable thinking, { thinkingLevel: "HIGH" } on models that take a level. Ignored by all other adapters; shapes are model-specific and validated by Google, not the SDK. - payload.reasoningEffort : string - OpenAI and OpenRouter reasoning effort. Valid values are model-dependent none / minimal / low / medium / high / xhigh / max . OpenRouter: sent as the nested reasoning: { effort } object — the canonical form, and the only one that accepts max the flat reasoning effort field caps at xhigh . Direct OpenAI: sent flat as reasoning effort ; max is rejected there, and reasoning-by-default models the gpt-5.6 family reject function tools on /chat/completions with a 400 unless this is explicitly "none" — their implicit default is medium . Via OpenRouter the same models accept tools at any effort OpenRouter fronts /v1/responses , so omitting this runs them at their native default. Ignored by all other adapters. When a streaming attempt is cut at its total deadline and prose has already arrived, the partial answer is returned with truncated: true on the response rather than discarded — those tokens were generated and billed, so throwing them away costs money and gives the user nothing. Surface such a reply as incomplete. Salvage never applies to tool-call turns half-streamed arguments are unparseable JSON , to stalls the provider died mid-thought , or to caller aborts. When nothing is salvageable, the discard is logged with an approximate token count — aborted attempts never receive OpenRouter's usage chunk, so that log line is the only record of the wasted spend. OpenRouter retries also perform moderation eviction : a provider content-moderation rejection e.g. "Upstream error from Alibaba: Output data may contain inappropriate content." is deterministic for a given payload, so on the first one the refusing provider is removed from the request's provider preferences ignore += slug, order -= slug and every remaining attempt reroutes to the next provider. Non-moderation errors retry with unchanged preferences, and fallbackModel still applies if the whole pool refuses. - payload.signal : AbortSignal - Caller-supplied cancellation. When it aborts, the in-flight provider request is cancelled and callWithRetries rejects immediately — it does not retry or fall back both the retry loop and the fallback branch bail on signal.aborted . Threaded to the underlying fetch/axios/SDK call of each provider. Promise<ParsedResponseMessage : interface ParsedResponseMessage { role: "assistant"; content: string | null; function call: FunctionCall | null; function calls: FunctionCall ; files: File ; // For models that return files e.g., image generation // Who actually served the response: OpenRouter's upstream provider from the // response body e.g. "Baidu" , or the SDK provider name "anthropic", ... // for direct providers. On fallback, reflects the model that answered. provider?: string; usage: { prompt tokens: number; completion tokens: number; total tokens: number; // Reasoning/thinking tokens spent before the visible answer; currently // populated from Google's usageMetadata.thoughtsTokenCount. thoughts tokens?: number; } | null; // null when streaming } Parses a model string into its provider and model ID components. - model : string - A model string in "provider:model-id" format { provider: Provider, modelId: string } interface OpenAIConfig { service: "azure" | "openai"; apiKey: string; / Optional base URL. Defaults to https://api.openai.com/v1 . Set to point at any OpenAI-compatible endpoint e.g. a self-hosted proxy . The path /chat/completions is appended automatically. Ignored for Azure. / baseUrl?: string; orgId?: string; modelConfigMap?: Record< string, { resource: string; deployment: string; apiVersion: string; apiKey: string; endpoint?: string; } ; } To talk to an OpenAI-compatible server instead of OpenAI itself: await callWithRetries "my-identifier", { model: "openai:gpt-4o-mini", messages: { role: "user", content: "hi" } , }, { service: "openai", apiKey: process.env.SOME SERVER API KEY, baseUrl: "https://your-proxy.example.com/v1", }, ; interface AnthropicAIConfig { service: "anthropic" | "bedrock"; } ISC