feat(providers): OpenRouter adapter + Ollama embedding support — M3-004/006 (#311)
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Co-authored-by: Jason Woltje <jason@diversecanvas.com>
Co-committed-by: Jason Woltje <jason@diversecanvas.com>
This commit was merged in pull request #311.
This commit is contained in:
2026-03-21 21:38:09 +00:00
committed by jason.woltje
parent 08da6b76d1
commit 10761f3e47
4 changed files with 295 additions and 4 deletions

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@@ -1,3 +1,4 @@
export { OllamaAdapter } from './ollama.adapter.js';
export { AnthropicAdapter } from './anthropic.adapter.js';
export { OpenAIAdapter } from './openai.adapter.js';
export { OpenRouterAdapter } from './openrouter.adapter.js';

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@@ -8,11 +8,28 @@ import type {
ProviderHealth,
} from '@mosaic/types';
/** Embedding models that Ollama ships with out of the box */
const OLLAMA_EMBEDDING_MODELS: ReadonlyArray<{
id: string;
contextWindow: number;
dimensions: number;
}> = [
{ id: 'nomic-embed-text', contextWindow: 8192, dimensions: 768 },
{ id: 'mxbai-embed-large', contextWindow: 512, dimensions: 1024 },
];
interface OllamaEmbeddingResponse {
embedding?: number[];
}
/**
* Ollama provider adapter.
*
* Registers local Ollama models with the Pi ModelRegistry via the OpenAI-compatible
* completions API. Configuration is driven by environment variables:
* completions API. Also exposes embedding models and an `embed()` method for
* vector generation (used by EmbeddingService / M3-009).
*
* Configuration is driven by environment variables:
* OLLAMA_BASE_URL or OLLAMA_HOST — base URL of the Ollama instance
* OLLAMA_MODELS — comma-separated list of model IDs (default: llama3.2,codellama,mistral)
*/
@@ -52,7 +69,8 @@ export class OllamaAdapter implements IProviderAdapter {
})),
});
this.registeredModels = modelIds.map((id) => ({
// Chat / completion models
const completionModels: ModelInfo[] = modelIds.map((id) => ({
id,
provider: 'ollama',
name: id,
@@ -63,8 +81,24 @@ export class OllamaAdapter implements IProviderAdapter {
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
}));
// Embedding models (tracked in registeredModels but not in Pi registry,
// which only handles completion models)
const embeddingModels: ModelInfo[] = OLLAMA_EMBEDDING_MODELS.map((em) => ({
id: em.id,
provider: 'ollama',
name: em.id,
reasoning: false,
contextWindow: em.contextWindow,
maxTokens: 0,
inputTypes: ['text'] as ('text' | 'image')[],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
}));
this.registeredModels = [...completionModels, ...embeddingModels];
this.logger.log(
`Ollama provider registered at ${ollamaUrl} with models: ${modelIds.join(', ')}`,
`Ollama provider registered at ${ollamaUrl} with models: ${modelIds.join(', ')} ` +
`and embedding models: ${OLLAMA_EMBEDDING_MODELS.map((em) => em.id).join(', ')}`,
);
}
@@ -110,6 +144,44 @@ export class OllamaAdapter implements IProviderAdapter {
}
}
/**
* Generate an embedding vector for the given text using Ollama's /api/embeddings endpoint.
*
* Defaults to 'nomic-embed-text' when no model is specified.
* Intended for use by EmbeddingService (M3-009).
*
* @param text - The input text to embed.
* @param model - Optional embedding model ID (default: 'nomic-embed-text').
* @returns A float array representing the embedding vector.
*/
async embed(text: string, model = 'nomic-embed-text'): Promise<number[]> {
const ollamaUrl = process.env['OLLAMA_BASE_URL'] ?? process.env['OLLAMA_HOST'];
if (!ollamaUrl) {
throw new Error('OllamaAdapter: OLLAMA_BASE_URL not configured');
}
const embeddingUrl = `${ollamaUrl}/api/embeddings`;
const res = await fetch(embeddingUrl, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ model, prompt: text }),
signal: AbortSignal.timeout(30000),
});
if (!res.ok) {
throw new Error(`OllamaAdapter.embed: request failed with HTTP ${res.status}`);
}
const json = (await res.json()) as OllamaEmbeddingResponse;
if (!Array.isArray(json.embedding)) {
throw new Error('OllamaAdapter.embed: unexpected response — missing embedding array');
}
return json.embedding;
}
/**
* createCompletion is reserved for future direct-completion use.
* The current integration routes completions through Pi SDK's ModelRegistry/AgentSession.

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@@ -0,0 +1,212 @@
import { Logger } from '@nestjs/common';
import OpenAI from 'openai';
import type {
CompletionEvent,
CompletionParams,
IProviderAdapter,
ModelInfo,
ProviderHealth,
} from '@mosaic/types';
const OPENROUTER_BASE_URL = 'https://openrouter.ai/api/v1';
interface OpenRouterModel {
id: string;
name?: string;
context_length?: number;
top_provider?: {
max_completion_tokens?: number;
};
pricing?: {
prompt?: string | number;
completion?: string | number;
};
architecture?: {
input_modalities?: string[];
};
}
interface OpenRouterModelsResponse {
data?: OpenRouterModel[];
}
/**
* OpenRouter provider adapter.
*
* Routes completions through OpenRouter's OpenAI-compatible API.
* Configuration is driven by the OPENROUTER_API_KEY environment variable.
*/
export class OpenRouterAdapter implements IProviderAdapter {
readonly name = 'openrouter';
private readonly logger = new Logger(OpenRouterAdapter.name);
private client: OpenAI | null = null;
private registeredModels: ModelInfo[] = [];
async register(): Promise<void> {
const apiKey = process.env['OPENROUTER_API_KEY'];
if (!apiKey) {
this.logger.debug('Skipping OpenRouter provider registration: OPENROUTER_API_KEY not set');
return;
}
this.client = new OpenAI({
apiKey,
baseURL: OPENROUTER_BASE_URL,
defaultHeaders: {
'HTTP-Referer': 'https://mosaic.ai',
'X-Title': 'Mosaic',
},
});
try {
this.registeredModels = await this.fetchModels(apiKey);
this.logger.log(`OpenRouter provider registered with ${this.registeredModels.length} models`);
} catch (err) {
this.logger.warn(
`OpenRouter model discovery failed: ${err instanceof Error ? err.message : String(err)}. Registering with empty model list.`,
);
this.registeredModels = [];
}
}
listModels(): ModelInfo[] {
return this.registeredModels;
}
async healthCheck(): Promise<ProviderHealth> {
const apiKey = process.env['OPENROUTER_API_KEY'];
if (!apiKey) {
return {
status: 'down',
lastChecked: new Date().toISOString(),
error: 'OPENROUTER_API_KEY not configured',
};
}
const start = Date.now();
try {
const res = await fetch(`${OPENROUTER_BASE_URL}/models`, {
method: 'GET',
headers: {
Authorization: `Bearer ${apiKey}`,
Accept: 'application/json',
},
signal: AbortSignal.timeout(5000),
});
const latencyMs = Date.now() - start;
if (!res.ok) {
return {
status: 'degraded',
latencyMs,
lastChecked: new Date().toISOString(),
error: `HTTP ${res.status}`,
};
}
return { status: 'healthy', latencyMs, lastChecked: new Date().toISOString() };
} catch (err) {
const latencyMs = Date.now() - start;
const error = err instanceof Error ? err.message : String(err);
return { status: 'down', latencyMs, lastChecked: new Date().toISOString(), error };
}
}
/**
* Stream a completion through OpenRouter's OpenAI-compatible API.
*/
async *createCompletion(params: CompletionParams): AsyncIterable<CompletionEvent> {
if (!this.client) {
throw new Error('OpenRouterAdapter is not initialized. Ensure OPENROUTER_API_KEY is set.');
}
const stream = await this.client.chat.completions.create({
model: params.model,
messages: params.messages.map((m) => ({ role: m.role, content: m.content })),
temperature: params.temperature,
max_tokens: params.maxTokens,
stream: true,
});
let inputTokens = 0;
let outputTokens = 0;
for await (const chunk of stream) {
const choice = chunk.choices[0];
if (!choice) continue;
const delta = choice.delta;
if (delta.content) {
yield { type: 'text_delta', content: delta.content };
}
if (choice.finish_reason === 'stop') {
const usage = (chunk as { usage?: { prompt_tokens?: number; completion_tokens?: number } })
.usage;
if (usage) {
inputTokens = usage.prompt_tokens ?? 0;
outputTokens = usage.completion_tokens ?? 0;
}
}
}
yield {
type: 'done',
usage: { inputTokens, outputTokens },
};
}
// ---------------------------------------------------------------------------
// Private helpers
// ---------------------------------------------------------------------------
private async fetchModels(apiKey: string): Promise<ModelInfo[]> {
const res = await fetch(`${OPENROUTER_BASE_URL}/models`, {
method: 'GET',
headers: {
Authorization: `Bearer ${apiKey}`,
Accept: 'application/json',
},
signal: AbortSignal.timeout(10000),
});
if (!res.ok) {
throw new Error(`OpenRouter models endpoint returned HTTP ${res.status}`);
}
const json = (await res.json()) as OpenRouterModelsResponse;
const data = json.data ?? [];
return data.map((model): ModelInfo => {
const inputPrice = model.pricing?.prompt
? parseFloat(String(model.pricing.prompt)) * 1000
: 0;
const outputPrice = model.pricing?.completion
? parseFloat(String(model.pricing.completion)) * 1000
: 0;
const inputModalities = model.architecture?.input_modalities ?? ['text'];
const inputTypes = inputModalities.includes('image')
? (['text', 'image'] as const)
: (['text'] as const);
return {
id: model.id,
provider: 'openrouter',
name: model.name ?? model.id,
reasoning: false,
contextWindow: model.context_length ?? 4096,
maxTokens: model.top_provider?.max_completion_tokens ?? 4096,
inputTypes: [...inputTypes],
cost: {
input: inputPrice,
output: outputPrice,
cacheRead: 0,
cacheWrite: 0,
},
};
});
}
}

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@@ -8,7 +8,12 @@ import type {
ProviderHealth,
ProviderInfo,
} from '@mosaic/types';
import { AnthropicAdapter, OllamaAdapter, OpenAIAdapter } from './adapters/index.js';
import {
AnthropicAdapter,
OllamaAdapter,
OpenAIAdapter,
OpenRouterAdapter,
} from './adapters/index.js';
import type { TestConnectionResultDto } from './provider.dto.js';
/** Default health check interval in seconds */
@@ -46,6 +51,7 @@ export class ProviderService implements OnModuleInit, OnModuleDestroy {
new OllamaAdapter(this.registry),
new AnthropicAdapter(this.registry),
new OpenAIAdapter(this.registry),
new OpenRouterAdapter(),
];
// Run all adapter registrations first (Ollama, Anthropic, and any future adapters)