feat(llm): enable Bedrock/Anthropic prompt caching for Claude models (#772)

Co-authored-by: Sean Turner <sean.turner@zerohash.com>
Co-authored-by: Ahmed Allam <ahmed39652003@gmail.com>

strix/core/inputs.py

@@ -10,6 +10,9 @@ from openai.types.shared import Reasoning
 
 from strix.config.models import (
     DEFAULT_MODEL_RETRY,
+    bedrock_route_supports_prompt_caching,
+    is_bedrock_route,
+    is_claude_model,
     is_known_openai_bare_model,
     model_supports_reasoning,
     request_timeout_extra_args,
@@ -128,6 +131,7 @@ def make_model_settings(
     model_name: str,
     force_required_tool_choice: bool = False,
     request_timeout: float | None = None,
+    prompt_cache: bool = True,
 ) -> ModelSettings:
     model_settings = ModelSettings(
         parallel_tool_calls=False,
@@ -145,9 +149,38 @@ def make_model_settings(
         )
     if force_required_tool_choice and _accepts_required_tool_choice(model_name):
         model_settings = model_settings.resolve(ModelSettings(tool_choice="required"))
+
+    cache_extra_args = _prompt_cache_extra_args(model_name) if prompt_cache else None
+    if cache_extra_args:
+        model_settings = model_settings.resolve(
+            ModelSettings(
+                extra_args={**(model_settings.extra_args or {}), **cache_extra_args},
+            ),
+        )
     return model_settings
 
 
+def _prompt_cache_extra_args(model_name: str) -> dict[str, Any] | None:
+    """LiteLLM ``cache_control_injection_points`` for Claude prompt caching.
+
+    System prompt + rolling last-message breakpoint everywhere; ``tool_config``
+    only on Bedrock Converse (the only route whose LiteLLM transform consumes
+    it — elsewhere it leaks onto the wire and native Anthropic 400s). Unmapped
+    Bedrock models get no points at all: Bedrock rejects the passed-through
+    field outright.
+    """
+    if not is_claude_model(model_name):
+        return None
+    if is_bedrock_route(model_name) and not bedrock_route_supports_prompt_caching(model_name):
+        return None
+
+    points: list[dict[str, Any]] = [{"location": "message", "role": "system"}]
+    if is_bedrock_route(model_name):
+        points.append({"location": "tool_config"})
+    points.append({"location": "message", "index": -1})
+    return {"cache_control_injection_points": points}
+
+
 def child_initial_input(
     *,
     name: str,

strix/core/runner.py

@@ -236,6 +236,7 @@ async def run_strix_scan(
             model_name=resolved_model,
             force_required_tool_choice=settings.llm.force_required_tool_choice,
             request_timeout=settings.llm.timeout,
+            prompt_cache=settings.llm.prompt_cache,
         )
         run_config = RunConfig(
             model=resolved_model,