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fix: improve Claude message detection and block conversion
- Improve isClaudeStyleMessages() heuristic to check ALL messages for Claude-specific features (tool_result, image with source, tool_use) - Properly convert tool_use blocks to ResponsesOutputItemFunctionCall - Convert image blocks in user messages to OpenResponsesInputMessageItem - Handle assistant images via synthetic function call outputs - Add TODO comment for cache_read_input_tokens mapping - Add console.warn for JSON parsing failures in tool arguments - Add E2E tests for getClaudeMessage() output format 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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src/lib/stream-transformers.ts

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@@ -599,7 +599,9 @@ export function convertToClaudeMessage(
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try {
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parsedInput = JSON.parse(fnCall.arguments);
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} catch {
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} catch (e) {
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// JSON parsing failed - likely malformed arguments from model
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console.warn(`[OpenRouter SDK] Failed to parse tool arguments for ${fnCall.name}: ${e}`);
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parsedInput = {};
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}
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@@ -698,6 +700,8 @@ export function convertToClaudeMessage(
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input_tokens: response.usage?.inputTokens ?? 0,
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output_tokens: response.usage?.outputTokens ?? 0,
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cache_creation_input_tokens: response.usage?.inputTokensDetails?.cachedTokens ?? 0,
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// TODO: OpenResponses doesn't expose cache_read separately from cachedTokens.
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// Anthropic distinguishes cache creation vs read; OpenResponses combines them.
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cache_read_input_tokens: 0,
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},
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...(unsupportedContent.length > 0 && { unsupported_content: unsupportedContent }),

tests/e2e/call-model.test.ts

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@@ -280,6 +280,86 @@ describe('callModel E2E Tests', () => {
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});
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});
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describe('getClaudeMessage - Claude output format', () => {
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it('should return ClaudeMessage with correct structure', async () => {
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const response = client.callModel({
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model: 'meta-llama/llama-3.2-1b-instruct',
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input: "Say 'hello' and nothing else.",
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});
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const claudeMessage = await response.getClaudeMessage();
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expect(claudeMessage.type).toBe('message');
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expect(claudeMessage.role).toBe('assistant');
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expect(claudeMessage.content).toBeInstanceOf(Array);
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expect(claudeMessage.content.length).toBeGreaterThan(0);
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expect(claudeMessage.content[0]?.type).toBe('text');
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expect(claudeMessage.stop_reason).toBeDefined();
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expect(claudeMessage.usage).toBeDefined();
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expect(claudeMessage.usage.input_tokens).toBeGreaterThan(0);
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expect(claudeMessage.usage.output_tokens).toBeGreaterThan(0);
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}, 30000);
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it('should include text content in ClaudeMessage', async () => {
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const response = client.callModel({
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model: 'meta-llama/llama-3.2-1b-instruct',
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input: "Say the word 'banana' and nothing else.",
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});
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const claudeMessage = await response.getClaudeMessage();
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const textBlock = claudeMessage.content.find((b) => b.type === 'text');
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expect(textBlock).toBeDefined();
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if (textBlock && textBlock.type === 'text') {
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expect(textBlock.text.toLowerCase()).toContain('banana');
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}
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}, 30000);
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it('should include tool_use blocks when tools are called', async () => {
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const response = client.callModel({
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model: 'openai/gpt-4o-mini',
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input: "What's the weather in Paris?",
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tools: [
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{
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type: ToolType.Function,
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function: {
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name: 'get_weather',
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description: 'Get weather for a location',
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inputSchema: z.object({
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location: z.string(),
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}),
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},
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},
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],
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maxToolRounds: 0, // Don't execute tools, just get the tool call
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});
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const claudeMessage = await response.getClaudeMessage();
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const toolUseBlock = claudeMessage.content.find((b) => b.type === 'tool_use');
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expect(toolUseBlock).toBeDefined();
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expect(claudeMessage.stop_reason).toBe('tool_use');
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if (toolUseBlock && toolUseBlock.type === 'tool_use') {
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expect(toolUseBlock.name).toBe('get_weather');
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expect(toolUseBlock.id).toBeDefined();
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expect(toolUseBlock.input).toBeDefined();
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}
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}, 30000);
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it('should have correct model field in ClaudeMessage', async () => {
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const response = client.callModel({
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model: 'meta-llama/llama-3.2-1b-instruct',
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input: "Say 'test'",
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});
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const claudeMessage = await response.getClaudeMessage();
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expect(claudeMessage.model).toBeDefined();
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expect(typeof claudeMessage.model).toBe('string');
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}, 30000);
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});
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describe('response.text - Text extraction', () => {
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it('should successfully get text from a response', async () => {
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const response = client.callModel({

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