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Guilherme Segantini
e335dd70f8
* (sap) ensure tool parameters have type='object' for SAP compatibility Fix SAP GenAI Hub Orchestration Service rejecting tool calls with error: "400 - LLM Module: tools.0.custom.input_schema.type: Input should be 'object'" Root cause: When Claude Code uses tools (like web_search) with the SAP provider through LiteLLM's Anthropic experimental pass-through adapter, Anthropic's input_schema format doesn't always include the required type="object" field. The adapter's translate_anthropic_tools_to_openai() function was directly copying input_schema to OpenAI's parameters field without ensuring the type="object" requirement that SAP's API strictly enforces. Changes: - Modified translate_anthropic_tools_to_openai() to check if input_schema is missing the type field and add type="object" if absent - Preserves existing type field if already present - Added comprehensive test suite (6 tests) covering: - Missing type field scenario (now adds type="object") - Existing type preservation - Empty input_schema handling - Multiple tools transformation - Additional schema properties preservation - SAP-specific compatibility regression test Testing: - All new tests pass (6/6 in test_anthropic_tool_schema_fix.py) - All existing Anthropic tool tests pass (57/57 tool-related tests) - SAP tool parameter validation tests pass (9/9 in test_sap_tool_parameters.py) * (sap) enable native response_format for anthropic models * (sap) filter strict param from model_params for GPT models only * (sap) revert Anthropic adapter type='object' fix The SAP FunctionTool Pydantic validator in litellm/llms/sap/chat/models.py already ensures type='object' is added to all tool parameters for SAP API compatibility. The Anthropic adapter change affected ALL consumers, not just SAP, which was broader scope than intended for this PR. - Revert input_schema modification in Anthropic adapter - Remove Anthropic-specific test file (SAP tests still cover this case) * (sap) gate markdown stripping to Anthropic models only SAP GenAI Hub with Anthropic models sometimes returns JSON wrapped in markdown code blocks. GPT/Gemini/Mistral models don't exhibit this behavior, so stripping is now gated to avoid accidentally modifying valid responses that may contain markdown in JSON string values.