Add structured tool event propagation from Lingma stream/finish metadata and map it to OpenAI tool_calls and Anthropic tool_use/tool_result in both streaming and non-streaming responses. Add focused bridge tests and update docs/design notes to match current behavior.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Add a wire-compatible Anthropic endpoint alongside the existing OpenAI one
so Claude Code / anthropic-sdk / Cursor Agent can hit Lingma directly.
- app/anthropic_schema.py (new): request model + content-block flattener
+ internal-messages adapter + affinity key helper. Handles text / image /
tool_use / tool_result blocks; unknown types degrade gracefully.
- app/auth.py: add require_anthropic_key (x-api-key, Bearer fallback)
and AnthropicAuthError so auth failures render in Anthropic's error
envelope instead of FastAPI's {detail:...} wrapper.
- app/main.py: POST /v1/messages. Shares LingmaPool / SessionCache /
InFlightGuard / StatsCollector with the OpenAI path — same api_key +
same conversation prefix hits the same upstream sessionId across both
protocols (KV cache carries over). Streaming emits the named Anthropic
event sequence (message_start / content_block_start / content_block_delta
/ content_block_stop / message_delta / message_stop). No claude-*
model mapping table: resolve_model's default fallback handles it.
- README.md / DESIGN.md: document the new endpoint, add decision 5.12,
iteration history M5, and a 4.3b streaming flow diagram.
- Bump FastAPI app version to 0.4.0.
Made-with: Cursor
