Add support for Z.AI GLM-4.7, latest flagship model with enhanced reasoning capabilities.
Changes:
- Add zai/glm-4.7 to model pricing with /bin/bash.60/M input, .20/M output
- Add cached input pricing (/bin/bash.11/M) for GLM-4.7
- Add supports_reasoning flag to enable thinking parameter
- Update ZAIChatConfig to support thinking parameter for models with reasoning
- Update documentation with GLM-4.7 as latest flagship model
- Add cached input column to pricing table (GLM-4.7 only)
- Add tests for GLM-4.7 reasoning support and cost calculation
- Update all examples to use GLM-4.7
Model specifications:
- Context: 200K input, 128K output
- Supports: reasoning, function calling, tool choice, prompt caching
- Pricing: Same as GLM-4.6 with cache support
See: https://docs.z.ai/guides/llm/glm-4.7
Fix Vertex AI API error: "tools[0].tool_type: one_of 'tool_type' has more
than one initialized field"
The Vertex AI API requires each Tool object to contain exactly one type
of tool (e.g., FunctionDeclaration, GoogleSearch, CodeExecution).
Previously, all tool types were combined into a single Tool object,
causing INVALID_ARGUMENT errors when using multiple tools simultaneously.
This change creates separate Tool objects for each tool type:
- Function declarations in one Tool
- Google Search in its own Tool
- Code Execution in its own Tool
- etc.
Ref: https://cloud.google.com/vertex-ai/generative-ai/docs/reference/rest/v1beta1/Tool🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Fixes#18430
- Pass custom_llm_provider to anthropic_messages_pt instead of hardcoded 'anthropic'
- Add check for vertex_ai provider to force base64 conversion for image URLs
- Add tests to verify behavior for both Vertex AI and regular Anthropic
- Add get_vertex_base_url() helper function to handle regional vs global URLs
- Update _get_embedding_url() to support global location
- Update _get_vertex_url() chat, image_generation, and count_tokens modes
- Add comprehensive test suite with 38 tests covering all endpoint types
- Tests verify both regional and global URL construction
- Maintains 100% backward compatibility
- Add OAuth M2M (Machine-to-Machine) authentication via DATABRICKS_CLIENT_ID and DATABRICKS_CLIENT_SECRET
- Add Databricks SDK auto-auth with automatic credential discovery
- Add sensitive data redaction for secure logging (tokens, API keys, secrets)
- Add custom user_agent parameter for partner attribution in Databricks telemetry
- Support user_agent in LiteLLM Proxy via config.yaml litellm_params
- Add 49 mocked unit tests for all new functionality
- Add 13 E2E tests for real-world validation (skipped in CI)
- Update documentation with new features and examples
* fix(gemini): use JSON instead of form-data for image edit requests
Gemini's image edit API expects JSON body, not multipart/form-data.
The handler was sending form-encoded data which caused 400 errors:
"Invalid JSON payload received. Unexpected token."
Changes:
- Add use_multipart_form_data() method to BaseImageEditConfig (default True)
- Modify image_edit_handler to use json= when use_multipart_form_data() is False
- Override use_multipart_form_data() in GeminiImageEditConfig to return False
* test(gemini): add test for use_multipart_form_data
Claude 3.7 Sonnet's default max_output_tokens is 64000, not 128000.
The 128K output limit requires the beta header 'output-128k-2025-02-19'.
This fixes the integration test failure where requests with max_tokens=128000
were being rejected by the Anthropic API.
Fixes test_multiturn_tool_calls in test_anthropic_responses_api.py
