atropos/atroposlib/envs/server_handling/README.md

Server Handling

This module provides server abstraction layers for different LLM inference backends.

Reasoning Model Support

The ReasoningConfig class enables support for reasoning/thinking models across different providers.

Provider Differences

Feature	OpenAI	OpenRouter / Others
Format	{"reasoning_effort": "high"}	{"reasoning": {"enabled": true, "effort": "high"}}
Effort Levels	none, minimal, low, medium, high, xhigh	none, minimal, low, medium, high, xhigh
Max Tokens	Not supported	{"reasoning": {"max_tokens": 16000}}
Temperature	Must be 1.0	No restriction
Token Param	max_completion_tokens	max_tokens

Effort Level to Token Mapping

When providers don't support effort strings, effort levels map to approximate token budgets (based on 32k base):

Effort	Tokens	Percentage
none	1,024	Minimum
minimal	3,200	~10%
low	6,400	~20%
medium	16,000	~50%
high	25,600	~80%
xhigh	30,400	~95%

Provider Token Limits

• OpenRouter: Caps Anthropic reasoning at 1,024-32,000 tokens (docs)
• Native Anthropic: Supports up to 128k extended thinking tokens

Usage

Reasoning is only injected for chat completions (not completions or logprobs API).

# Via environment config
config = BaseEnvConfig(
    thinking_mode=True,
    reasoning_effort="high",
    max_reasoning_tokens=16000,
)

# Direct ReasoningConfig
reasoning_config = ReasoningConfig(
    enabled=True,
    effort="high",
    max_tokens=16000,
)

Bypassing Reasoning Injection

Pass skip_reasoning=True to any chat completion call:

await server.chat_completion(messages=messages, skip_reasoning=True)

Important Constraints

1. OpenRouter: Only accepts ONE of effort or max_tokens, not both. When both specified, effort takes priority.
2. OpenAI: All effort levels are passed through directly.
3. Auto-enable: Setting effort or max_tokens automatically enables reasoning mode.