feat(M3-003): OpenAI provider adapter for Codex gpt-5.4 (#310)

Co-authored-by: Jason Woltje <jason@diversecanvas.com>
Co-committed-by: Jason Woltje <jason@diversecanvas.com>

apps/gateway/src/agent/adapters/openai.adapter.ts

@@ -0,0 +1,201 @@
+import { Logger } from '@nestjs/common';
+import OpenAI from 'openai';
+import type { ModelRegistry } from '@mariozechner/pi-coding-agent';
+import type {
+  CompletionEvent,
+  CompletionParams,
+  IProviderAdapter,
+  ModelInfo,
+  ProviderHealth,
+} from '@mosaic/types';
+
+/**
+ * OpenAI provider adapter.
+ *
+ * Registers OpenAI models (including Codex gpt-5.4) with the Pi ModelRegistry.
+ * Configuration is driven by environment variables:
+ *   OPENAI_API_KEY — OpenAI API key (required; adapter skips registration when absent)
+ */
+export class OpenAIAdapter implements IProviderAdapter {
+  readonly name = 'openai';
+
+  private readonly logger = new Logger(OpenAIAdapter.name);
+  private registeredModels: ModelInfo[] = [];
+  private client: OpenAI | null = null;
+
+  /** Model ID used for Codex gpt-5.4 in the Pi registry. */
+  static readonly CODEX_MODEL_ID = 'codex-gpt-5-4';
+
+  constructor(private readonly registry: ModelRegistry) {}
+
+  async register(): Promise<void> {
+    const apiKey = process.env['OPENAI_API_KEY'];
+    if (!apiKey) {
+      this.logger.debug('Skipping OpenAI provider registration: OPENAI_API_KEY not set');
+      return;
+    }
+
+    this.client = new OpenAI({ apiKey });
+
+    const codexModel = {
+      id: OpenAIAdapter.CODEX_MODEL_ID,
+      name: 'Codex gpt-5.4',
+      /** OpenAI-compatible completions API */
+      api: 'openai-completions' as never,
+      reasoning: false,
+      input: ['text', 'image'] as ('text' | 'image')[],
+      cost: { input: 0.003, output: 0.012, cacheRead: 0.0015, cacheWrite: 0 },
+      contextWindow: 128_000,
+      maxTokens: 16_384,
+    };
+
+    this.registry.registerProvider('openai', {
+      apiKey,
+      baseUrl: 'https://api.openai.com/v1',
+      models: [codexModel],
+    });
+
+    this.registeredModels = [
+      {
+        id: OpenAIAdapter.CODEX_MODEL_ID,
+        provider: 'openai',
+        name: 'Codex gpt-5.4',
+        reasoning: false,
+        contextWindow: 128_000,
+        maxTokens: 16_384,
+        inputTypes: ['text', 'image'] as ('text' | 'image')[],
+        cost: { input: 0.003, output: 0.012, cacheRead: 0.0015, cacheWrite: 0 },
+      },
+    ];
+
+    this.logger.log(`OpenAI provider registered with model: ${OpenAIAdapter.CODEX_MODEL_ID}`);
+  }
+
+  listModels(): ModelInfo[] {
+    return this.registeredModels;
+  }
+
+  async healthCheck(): Promise<ProviderHealth> {
+    const apiKey = process.env['OPENAI_API_KEY'];
+    if (!apiKey) {
+      return {
+        status: 'down',
+        lastChecked: new Date().toISOString(),
+        error: 'OPENAI_API_KEY not configured',
+      };
+    }
+
+    const start = Date.now();
+    try {
+      // Lightweight call — list models to verify key validity
+      const res = await fetch('https://api.openai.com/v1/models', {
+        method: 'GET',
+        headers: {
+          Authorization: `Bearer ${apiKey}`,
+          'Content-Type': '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 from OpenAI using the chat completions API.
+   *
+   * Maps OpenAI streaming chunks to the Mosaic CompletionEvent format.
+   */
+  async *createCompletion(params: CompletionParams): AsyncIterable<CompletionEvent> {
+    if (!this.client) {
+      throw new Error(
+        'OpenAIAdapter: client not initialized. ' +
+          'Ensure OPENAI_API_KEY is set and register() was called.',
+      );
+    }
+
+    const stream = await this.client.chat.completions.create({
+      model: params.model,
+      messages: params.messages.map((m) => ({
+        role: m.role,
+        content: m.content,
+      })),
+      ...(params.temperature !== undefined && { temperature: params.temperature }),
+      ...(params.maxTokens !== undefined && { max_tokens: params.maxTokens }),
+      ...(params.tools &&
+        params.tools.length > 0 && {
+          tools: params.tools.map((t) => ({
+            type: 'function' as const,
+            function: {
+              name: t.name,
+              description: t.description,
+              parameters: t.parameters,
+            },
+          })),
+        }),
+      stream: true,
+      stream_options: { include_usage: true },
+    });
+
+    let inputTokens = 0;
+    let outputTokens = 0;
+
+    for await (const chunk of stream) {
+      const choice = chunk.choices[0];
+
+      // Accumulate usage when present (final chunk with stream_options.include_usage)
+      if (chunk.usage) {
+        inputTokens = chunk.usage.prompt_tokens;
+        outputTokens = chunk.usage.completion_tokens;
+      }
+
+      if (!choice) continue;
+
+      const delta = choice.delta;
+
+      // Text content delta
+      if (delta.content) {
+        yield { type: 'text_delta', content: delta.content };
+      }
+
+      // Tool call delta — emit when arguments are complete
+      if (delta.tool_calls) {
+        for (const toolCallDelta of delta.tool_calls) {
+          if (toolCallDelta.function?.name && toolCallDelta.function.arguments !== undefined) {
+            yield {
+              type: 'tool_call',
+              name: toolCallDelta.function.name,
+              arguments: toolCallDelta.function.arguments,
+            };
+          }
+        }
+      }
+
+      // Stream finished
+      if (choice.finish_reason === 'stop' || choice.finish_reason === 'tool_calls') {
+        yield {
+          type: 'done',
+          usage: { inputTokens, outputTokens },
+        };
+        return;
+      }
+    }
+
+    // Fallback done event when stream ends without explicit finish_reason
+    yield { type: 'done', usage: { inputTokens, outputTokens } };
+  }
+}