from typing import Any import pytest from free_claude_code.core.openai_responses import ( OpenAIResponsesAdapter, OpenAIResponsesRequest, ) _ADAPTER = OpenAIResponsesAdapter() _CONVERSION_ERROR = OpenAIResponsesAdapter.ConversionError def _to_anthropic_payload(request: dict[str, Any]) -> dict[str, Any]: return _ADAPTER.to_anthropic_payload(OpenAIResponsesRequest.model_validate(request)) def test_responses_string_input_converts_to_anthropic_message() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "instructions": "System instructions", "input": "Hello", "max_output_tokens": 64, "temperature": 0.2, "top_p": 0.9, "metadata": {"trace": "abc"}, } ) assert payload["model"] == "nvidia_nim/test-model" assert payload["system"] == "System instructions" assert payload["messages"] == [{"role": "user", "content": "Hello"}] assert payload["max_tokens"] == 64 assert payload["temperature"] == 0.2 assert payload["top_p"] == 0.9 assert payload["metadata"] == {"trace": "abc"} @pytest.mark.parametrize("effort", ["none", "low", "medium", "high", "xhigh"]) def test_responses_reasoning_effort_is_preserved_for_application_policy( effort: str, ) -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": "Hello", "reasoning": {"effort": effort}, } ) assert payload["output_config"] == {"effort": effort} assert "thinking" not in payload def test_responses_messages_tools_and_tool_results_convert() -> None: payload = _to_anthropic_payload( { "model": "deepseek/deepseek-chat", "input": [ { "type": "message", "role": "developer", "content": [{"type": "input_text", "text": "Developer rules"}], }, { "type": "message", "role": "user", "content": [{"type": "input_text", "text": "Use the tool"}], }, { "type": "function_call", "call_id": "call_1", "name": "echo", "arguments": '{"value":"FCC"}', }, { "type": "function_call_output", "call_id": "call_1", "output": "FCC", }, ], "tools": [ { "type": "function", "name": "echo", "description": "Echo a value", "parameters": { "type": "object", "properties": {"value": {"type": "string"}}, }, } ], "tool_choice": {"type": "function", "name": "echo"}, } ) assert payload["system"] == "Developer rules" assert payload["messages"] == [ {"role": "user", "content": [{"type": "text", "text": "Use the tool"}]}, { "role": "assistant", "content": [ { "type": "tool_use", "id": "call_1", "name": "echo", "input": {"value": "FCC"}, } ], }, { "role": "user", "content": [ { "type": "tool_result", "tool_use_id": "call_1", "content": "FCC", } ], }, ] assert payload["tools"] == [ { "name": "echo", "description": "Echo a value", "input_schema": { "type": "object", "properties": {"value": {"type": "string"}}, }, } ] assert payload["tool_choice"] == {"type": "tool", "name": "echo"} def test_responses_tool_choice_none_disables_forwarded_tools() -> None: payload = _to_anthropic_payload( { "model": "deepseek/deepseek-chat", "input": "Reply without tools", "tools": [ { "type": "function", "name": "echo", "parameters": { "type": "object", "properties": {"value": {"type": "string"}}, }, } ], "tool_choice": "none", } ) assert "tools" not in payload assert "tool_choice" not in payload def test_responses_namespace_tools_flatten_for_anthropic() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": "Use JS", "tools": [ { "type": "namespace", "name": "mcp__node_repl", "description": "Node tools", "tools": [ { "type": "function", "name": "js", "description": "Run JavaScript", "parameters": { "type": "object", "properties": {"code": {"type": "string"}}, "required": ["code"], }, } ], } ], "tool_choice": { "type": "function", "namespace": "mcp__node_repl", "name": "js", }, } ) assert payload["tools"] == [ { "name": "mcp__node_repl__js", "description": "Run JavaScript", "input_schema": { "type": "object", "properties": {"code": {"type": "string"}}, "required": ["code"], }, } ] assert payload["tool_choice"] == {"type": "tool", "name": "mcp__node_repl__js"} def test_responses_namespaced_tool_choice_type_tool_flattens_for_anthropic() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": "Use JS", "tools": [ { "type": "namespace", "name": "mcp__node_repl", "tools": [ { "type": "function", "name": "js", "parameters": {"type": "object", "properties": {}}, } ], } ], "tool_choice": { "type": "tool", "namespace": "mcp__node_repl", "name": "js", }, } ) assert payload["tool_choice"] == {"type": "tool", "name": "mcp__node_repl__js"} def test_responses_custom_tool_converts_to_anthropic_string_tool() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": "Use apply_patch", "tools": [ { "type": "custom", "name": "apply_patch", "description": "Apply a repo patch", "format": { "type": "grammar", "syntax": "lark", "definition": "start: /.+/", }, } ], "tool_choice": {"type": "custom", "name": "apply_patch"}, } ) assert payload["tools"] == [ { "name": "apply_patch", "description": ( "Apply a repo patch\n\n" "Custom tool input format: grammar (lark): start: /.+/" ), "input_schema": { "type": "object", "properties": { "input": { "type": "string", "description": "Free-form input for the custom tool.", } }, "required": ["input"], }, } ] assert payload["tool_choice"] == {"type": "tool", "name": "apply_patch"} def test_responses_namespaced_custom_tool_flattens_for_anthropic() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": "Use shell", "tools": [ { "type": "namespace", "name": "mcp__shell", "tools": [ { "type": "custom", "name": "exec", "description": "Run shell text", "format": {"type": "text"}, } ], } ], "tool_choice": { "type": "custom", "namespace": "mcp__shell", "custom": {"name": "exec"}, }, } ) assert payload["tools"][0]["name"] == "mcp__shell__exec" assert payload["tools"][0]["description"] == ( "Run shell text\n\nCustom tool input format: unconstrained text." ) assert payload["tool_choice"] == {"type": "tool", "name": "mcp__shell__exec"} def test_responses_passive_codex_built_in_tools_are_ignored() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": "Hello", "tools": [ {"type": "web_search", "external_web_access": True}, {"type": "image_generation", "output_format": "png"}, {"type": "tool_search"}, { "type": "function", "name": "echo", "parameters": {"type": "object", "properties": {}}, }, ], } ) assert payload["tools"] == [ {"name": "echo", "input_schema": {"type": "object", "properties": {}}} ] def test_responses_namespaced_prior_function_call_flattens_tool_use_name() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": [ { "type": "function_call", "call_id": "call_1", "namespace": "mcp__node_repl", "name": "js", "arguments": '{"code":"1+1"}', }, { "type": "function_call_output", "call_id": "call_1", "output": "2", }, ], } ) assert payload["messages"][0]["content"][0]["name"] == "mcp__node_repl__js" def test_responses_prior_custom_tool_call_flattens_tool_use_name() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": [ { "type": "custom_tool_call", "call_id": "call_1", "namespace": "mcp__shell", "name": "exec", "input": "printf FCC", }, { "type": "custom_tool_call_output", "call_id": "call_1", "output": "FCC", }, ], } ) assert payload["messages"] == [ { "role": "assistant", "content": [ { "type": "tool_use", "id": "call_1", "name": "mcp__shell__exec", "input": {"input": "printf FCC"}, } ], }, { "role": "user", "content": [ { "type": "tool_result", "tool_use_id": "call_1", "content": "FCC", } ], }, ] def test_responses_groups_consecutive_prior_tool_calls() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": [ { "type": "function_call", "call_id": "call_1", "name": "echo", "arguments": '{"value":"FCC"}', }, { "type": "custom_tool_call", "call_id": "call_2", "name": "apply_patch", "input": "*** Begin Patch", }, ], } ) assert payload["messages"] == [ { "role": "assistant", "content": [ { "type": "tool_use", "id": "call_1", "name": "echo", "input": {"value": "FCC"}, }, { "type": "tool_use", "id": "call_2", "name": "apply_patch", "input": {"input": "*** Begin Patch"}, }, ], } ] def test_responses_groups_consecutive_prior_tool_outputs() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": [ { "type": "function_call", "call_id": "call_1", "name": "echo", "arguments": '{"value":"FCC"}', }, { "type": "function_call", "call_id": "call_2", "name": "echo", "arguments": '{"value":"Codex"}', }, { "type": "function_call_output", "call_id": "call_1", "output": "FCC", }, { "type": "function_call_output", "call_id": "call_2", "output": "Codex", }, ], } ) assert len(payload["messages"]) == 2 assert payload["messages"][0]["role"] == "assistant" assert len(payload["messages"][0]["content"]) == 2 assert payload["messages"][1] == { "role": "user", "content": [ { "type": "tool_result", "tool_use_id": "call_1", "content": "FCC", }, { "type": "tool_result", "tool_use_id": "call_2", "content": "Codex", }, ], } def test_responses_reasoning_between_tool_call_and_output_attaches_to_tool_message() -> ( None ): payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": [ { "type": "function_call", "call_id": "call_1", "name": "echo", "arguments": '{"value":"FCC"}', }, { "type": "reasoning", "content": [{"type": "reasoning_text", "text": "Need the result."}], }, { "type": "function_call_output", "call_id": "call_1", "output": "FCC", }, ], } ) assert payload["messages"][0]["reasoning_content"] == "Need the result." assert payload["messages"][0]["content"][0]["id"] == "call_1" assert payload["messages"][1]["content"][0]["tool_use_id"] == "call_1" def test_responses_empty_reasoning_attaches_to_prior_tool_call() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": [ { "type": "function_call", "call_id": "call_1", "name": "echo", "arguments": '{"value":"FCC"}', }, { "type": "reasoning", "content": [{"type": "reasoning_text", "text": ""}], }, { "type": "function_call_output", "call_id": "call_1", "output": "FCC", }, ], } ) assert payload["messages"][0]["reasoning_content"] == "" def test_responses_unsupported_tool_type_is_clear() -> None: with pytest.raises(_CONVERSION_ERROR, match="Unsupported Responses tool type"): _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": "Hello", "tools": [{"type": "web_search_preview"}], } ) def test_responses_malformed_prior_function_call_is_quarantined() -> None: payload = _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": [ {"role": "user", "content": "hello"}, { "type": "function_call", "call_id": "call_bad", "name": "echo", "arguments": "{", }, { "type": "function_call_output", "call_id": "call_bad", "output": "stale output", }, { "type": "function_call", "call_id": "call_good", "name": "echo", "arguments": '{"value":"ok"}', }, { "type": "function_call_output", "call_id": "call_good", "output": "ok", }, {"role": "user", "content": "continue"}, ], } ) assert payload["messages"] == [ {"role": "user", "content": "hello"}, { "role": "assistant", "content": [ { "type": "tool_use", "id": "call_good", "name": "echo", "input": {"value": "ok"}, } ], }, { "role": "user", "content": [ { "type": "tool_result", "tool_use_id": "call_good", "content": "ok", } ], }, {"role": "user", "content": "continue"}, ] def test_responses_malformed_only_function_call_still_has_no_routable_message() -> None: with pytest.raises(_CONVERSION_ERROR, match="must contain a message"): _to_anthropic_payload( { "model": "nvidia_nim/test-model", "input": [ { "type": "function_call", "call_id": "call_bad", "name": "echo", "arguments": "{", }, { "type": "function_call_output", "call_id": "call_bad", "output": "stale output", }, ], } )