litellm - 💡(How to fix) Fix Anthropic reasoning_effort silently dropped when passed as Reasoning(effort, summary) dict (regression in v1.85.0) [2 pull requests]

reasoning_param = responses_api_request.get("reasoning")
if reasoning_param:
    if isinstance(reasoning_param, dict):
        if "summary" in reasoning_param:
            reasoning_effort = reasoning_param        # ← keeps WHOLE DICT
        elif "effort" in reasoning_param:
            reasoning_effort = reasoning_param.get("effort")  # ← extracts string

---

elif param == "reasoning_effort" and isinstance(value, str):  # ← isinstance fails
    mapped_thinking = AnthropicConfig._map_reasoning_effort(...)

---

if isinstance(value, str):
    return value
if isinstance(value, dict) and "effort" in value:
    return value["effort"]

---

import asyncio
import litellm

async def main():
    # Both calls request reasoning_effort="low" against the same model.
    # Only the first produces reasoning_tokens.

    r1 = await litellm.aresponses(
        model="anthropic/claude-sonnet-4-6",
        input=[{"role": "user", "content": "Think carefully: what is 17 * 23?"}],
        reasoning_effort="low",                          # string ← works
    )
    print("string form:", r1.usage.output_tokens_details)
    # → reasoning_tokens > 0, "reasoning" item in r1.output

    r2 = await litellm.aresponses(
        model="anthropic/claude-sonnet-4-6",
        input=[{"role": "user", "content": "Think carefully: what is 17 * 23?"}],
        reasoning=litellm.Reasoning(effort="low", summary="concise"),  # dict ← broken
    )
    print("Reasoning(summary) form:", r2.usage.output_tokens_details)
    # → reasoning_tokens == 0, no "reasoning" item in r2.output

asyncio.run(main())

---

string form:                 OutputTokensDetails(reasoning_tokens=187, ...)
Reasoning(summary) form:     OutputTokensDetails(reasoning_tokens=0, ...)

---

-            elif param == "reasoning_effort" and isinstance(value, str):
+            elif param == "reasoning_effort":
+                effort_value = value
+                if isinstance(effort_value, dict):
+                    effort_value = effort_value.get("effort")
+                if not isinstance(effort_value, str):
+                    continue
                 mapped_thinking = AnthropicConfig._map_reasoning_effort(
-                    reasoning_effort=value,
+                    reasoning_effort=effort_value,
                     model=model,
                     llm_provider=self.custom_llm_provider or "anthropic",
                 )
                 ...
                     if AnthropicConfig._is_adaptive_thinking_model(model):
                         mapped_effort = REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT.get(
-                            value
+                            effort_value
                         )