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optimclaw/.env.example
T
424a0366a9 feat: enable Anthropic prompt caching via automatic cache_control injection (#660)
* feat(llm): add Anthropic prompt caching and cache token tracking

- Inject cache_control via additional_params for Claude models in rig_adapter
- Add cache_read_input_tokens and cache_creation_input_tokens to
  CompletionResponse and ToolCompletionResponse
- Extract cached_input_tokens from rig-core unified Usage
- Add is_anthropic_model() detection helper with provider prefix support
- Log prompt cache hits at debug level (consistent with response_cache)
- Add 7 unit tests for cache injection and model detection
- Update all mock providers and test fixtures with new fields

* feat(cost): apply 90% cache discount to prompt-cached tokens in CostGuard

- Add cache_read_input_tokens to TokenUsage so cache counts flow from
  CompletionResponse through the reasoning layer to the dispatcher
- Update CostGuard::record_llm_call() to accept cache_read_input_tokens:
  cached tokens are billed at 10% of the normal input rate
- Thread cache_read_input_tokens from dispatcher into CostGuard
- Add test_cache_discount_reduces_cost verifying exact savings match
  90% of input cost for fully-cached requests
- Update all existing test callers with zero-cache parameter

* refactor(cache): scope cache_control to Anthropic backend and validate model support

- Replace model-name-based is_anthropic_model() with explicit
  enable_prompt_cache flag on RigAdapter, set only for the direct
  Anthropic backend via with_prompt_cache(true)
- Add supports_prompt_cache() to validate model names per Anthropic
  docs: only Claude 3+ models support caching; claude-2 and
  claude-instant are excluded to prevent 400 errors
- Warn when caching is enabled but model does not support it
- Replace is_anthropic_model tests with flag-based and model
  validation tests

* fix(cache): validate model at construction and propagate cache metrics through proxy

- Move supports_prompt_cache() check into with_prompt_cache() so
  unsupported models are detected once at construction, not per request
- Add cache_read_input_tokens and cache_creation_input_tokens to
  ProxyCompletionResponse and ProxyToolCompletionResponse with
  serde(default) for backward compatibility
- Pass cache metrics through orchestrator proxy instead of zeroing
- Use claude-opus-4-6 in cache discount test to match Anthropic
  semantics

* feat(llm): add configurable cache retention with write surcharge

- Add CacheRetention enum (none/short/long) to AnthropicDirectConfig
- Parse ANTHROPIC_CACHE_RETENTION env var (default: short)
- Inject TTL-aware cache_control (short=5m ephemeral, long=1h)
- Extract cache_creation_input_tokens from raw Anthropic response
- Add cache_write_multiplier() to LlmProvider trait (1.25x short, 2.0x long)
- Pipe dynamic write multiplier through dispatcher to CostGuard
- Add TokenUsage.cache_creation_input_tokens field
- Add tests for Long TTL injection, 5m and 1h write surcharges
- Document ANTHROPIC_CACHE_RETENTION in .env.example

* docs: fix stale cache_retention field comment

* fix: resolve CI failures after upstream merge

- Add missing cost_per_token arg to cache test callsites
- Apply cargo fmt to long lines in tests and tracing macros

* fix: address Copilot review feedback

- Use saturating_add for cache token sum to prevent u32 overflow
- Tighten supports_prompt_cache to explicitly match claude-3+/claude-4+
  and named families (claude-sonnet/claude-opus/claude-haiku)

* fix: adapt prompt caching to registry architecture and add missing cache fields

- Resolve merge conflicts: adapt CacheRetention and cache injection to
  the declarative provider registry (RegistryProviderConfig replaces
  AnthropicDirectConfig)
- Parse ANTHROPIC_CACHE_RETENTION env var in create_anthropic_from_registry()
- Use Anthropic automatic caching via top-level cache_control in
  additional_params (rig-core #[serde(flatten)] places it at request root)
- Add cache_read/creation_input_tokens fields to all mock LlmProviders
  added on main after PR #291 branched (response_cache, dispatcher,
  provider_chaos, trace_llm)
- Suppress clippy::too_many_arguments on record_llm_call and
  build_rig_request
- Add regression tests for cache injection (short/long/none) and
  cache_write_multiplier values

Co-Authored-By: Canvinus <[email protected]>

* fix: delegate cache_write_multiplier through provider wrappers and make cache_read_discount configurable

The 6 decorator providers (Retry, CircuitBreaker, Failover, SmartRouting,
CachedProvider, RecordingLlm) did not delegate cache_write_multiplier()
to their inner provider, causing it to always return 1.0 instead of the
actual 1.25x/2.0x from RigAdapter. This fix adds delegation for both
cache_write_multiplier() and the new cache_read_discount() method.

Also makes the cache read discount per-provider instead of hardcoding
Anthropic's 90% discount (÷10). OpenAI uses 50% (÷2), so the discount
is now returned by each provider via the LlmProvider trait.

Addresses review feedback on PR #660.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* style: cargo fmt

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* test: add CacheRetention FromStr/Display unit tests

Tests cover primary values, aliases (off/disabled/5m/ephemeral/1h),
case-insensitivity, invalid input error, and Display round-trip.

Addresses Copilot review feedback on PR #660.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

---------

Co-authored-by: Andrey <[email protected]>
Co-authored-by: Andrey Gruzdev <[email protected]>
Co-authored-by: Claude Opus 4.6 <[email protected]>
2026-03-07 09:10:05 +00:00

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# Database Configuration
DATABASE_URL=postgres://localhost/ironclaw
DATABASE_POOL_SIZE=10
# LLM Provider
# LLM_BACKEND=nearai # default
# Possible values: nearai, ollama, openai_compatible, openai, anthropic, tinfoil
# === NEAR AI (Chat Completions API) ===
# Two auth modes:
# 1. Session token (default): Uses browser OAuth (GitHub/Google) on first run.
# Session token stored in ~/.ironclaw/session.json automatically.
# Base URL defaults to https://private.near.ai
# 2. API key: Set NEARAI_API_KEY to use API key auth from cloud.near.ai.
# Base URL defaults to https://cloud-api.near.ai
NEARAI_MODEL=zai-org/GLM-5-FP8
NEARAI_BASE_URL=https://private.near.ai
NEARAI_AUTH_URL=https://private.near.ai
# NEARAI_SESSION_TOKEN=sess_... # hosting providers: set this
# NEARAI_SESSION_PATH=~/.ironclaw/session.json # optional, default shown
# NEARAI_API_KEY=... # API key from cloud.near.ai
# Local LLM Providers (Ollama, LM Studio, vLLM, LiteLLM)
# === Ollama ===
# OLLAMA_MODEL=llama3.2
# LLM_BACKEND=ollama
# OLLAMA_BASE_URL=http://localhost:11434 # default
# === OpenAI-compatible (LM Studio, vLLM, Anything-LLM) ===
# LLM_MODEL=llama-3.2-3b-instruct-q4_K_M
# LLM_BACKEND=openai_compatible
# LLM_BASE_URL=http://localhost:1234/v1
# LLM_API_KEY=sk-... # optional for local servers
# Custom HTTP headers for OpenAI-compatible providers
# Format: comma-separated key:value pairs
# LLM_EXTRA_HEADERS=HTTP-Referer:https://github.com/nearai/ironclaw,X-Title:ironclaw
# === OpenRouter (300+ models via OpenAI-compatible) ===
# LLM_MODEL=anthropic/claude-sonnet-4 # see openrouter.ai/models for IDs
# LLM_BACKEND=openai_compatible
# LLM_BASE_URL=https://openrouter.ai/api/v1
# LLM_API_KEY=sk-or-...
# LLM_EXTRA_HEADERS=HTTP-Referer:https://myapp.com,X-Title:MyApp
# === Together AI (via OpenAI-compatible) ===
# LLM_MODEL=meta-llama/Llama-3.3-70B-Instruct-Turbo
# LLM_BACKEND=openai_compatible
# LLM_BASE_URL=https://api.together.xyz/v1
# LLM_API_KEY=...
# === Fireworks AI (via OpenAI-compatible) ===
# LLM_MODEL=accounts/fireworks/models/llama4-maverick-instruct-basic
# LLM_BACKEND=openai_compatible
# LLM_BASE_URL=https://api.fireworks.ai/inference/v1
# LLM_API_KEY=fw_...
# === Anthropic Direct ===
# LLM_BACKEND=anthropic
# ANTHROPIC_MODEL=claude-sonnet-4-6
# ANTHROPIC_API_KEY=sk-ant-...
# ANTHROPIC_BASE_URL=https://api.anthropic.com # default
# Prompt cache retention — controls Anthropic server-side prompt caching:
# none = disabled (no cache_control injected)
# short = 5-minute TTL, 1.25× (125%) write surcharge (default)
# long = 1-hour TTL, 2.0× (200%) write surcharge
# ANTHROPIC_CACHE_RETENTION=short
# For full provider setup guide see docs/LLM_PROVIDERS.md
# Channel Configuration
# CLI is always enabled
# Slack Bot (optional)
SLACK_BOT_TOKEN=xoxb-...
SLACK_APP_TOKEN=xapp-...
SLACK_SIGNING_SECRET=...
# Telegram Bot (optional)
TELEGRAM_BOT_TOKEN=...
# HTTP Webhook Server (optional)
HTTP_HOST=0.0.0.0
HTTP_PORT=8080
HTTP_WEBHOOK_SECRET=your-webhook-secret
# Signal Channel (optional, requires signal-cli daemon --http)
# SIGNAL_HTTP_URL=http://127.0.0.1:8080
# SIGNAL_ACCOUNT=+1234567890
# SIGNAL_ALLOW_FROM=+1234567890,uuid:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx # comma-separated, * for all, empty = deny/require pairing
# SIGNAL_ALLOW_FROM_GROUPS= # comma-separated group IDs, * for all, empty = deny all groups
# SIGNAL_DM_POLICY=pairing # open | allowlist | pairing
# SIGNAL_GROUP_POLICY=allowlist # allowlist | open | disabled
# SIGNAL_GROUP_ALLOW_FROM= # comma-separated, empty = inherit from ALLOW_FROM
# SIGNAL_IGNORE_ATTACHMENTS=false
# SIGNAL_IGNORE_STORIES=true
# Agent Settings
AGENT_NAME=ironclaw
AGENT_MAX_PARALLEL_JOBS=5
AGENT_JOB_TIMEOUT_SECS=3600
AGENT_STUCK_THRESHOLD_SECS=300
# Enable planning phase before tool execution (default: true)
AGENT_USE_PLANNING=true
# Self-repair settings
SELF_REPAIR_CHECK_INTERVAL_SECS=60
SELF_REPAIR_MAX_ATTEMPTS=3
# Heartbeat settings (proactive periodic execution)
# When enabled, reads HEARTBEAT.md checklist and reports findings
HEARTBEAT_ENABLED=false
HEARTBEAT_INTERVAL_SECS=1800
HEARTBEAT_NOTIFY_CHANNEL=cli
HEARTBEAT_NOTIFY_USER=default
# Memory hygiene settings (automatic cleanup of stale workspace documents)
# Runs on each heartbeat tick; identity files (IDENTITY.md, SOUL.md) are never deleted
# MEMORY_HYGIENE_ENABLED=true
# MEMORY_HYGIENE_DAILY_RETENTION_DAYS=30 # delete daily/ docs older than this many days
# MEMORY_HYGIENE_CONVERSATION_RETENTION_DAYS=7 # delete conversations/ docs older than this many days
# MEMORY_HYGIENE_CADENCE_HOURS=12 # minimum hours between cleanup passes
# Safety settings
SAFETY_MAX_OUTPUT_LENGTH=100000
SAFETY_INJECTION_CHECK_ENABLED=true
# Restart Feature (Docker containers only)
# Set IRONCLAW_IN_DOCKER=true in the container entrypoint to enable the restart feature.
# Without this, the restart tool and /restart command will be disabled.
# IRONCLAW_IN_DOCKER=false
# IRONCLAW_RESTART_DELAY=5 # default wait before exit (seconds, range: 1-30)
# IRONCLAW_MAX_FAILURES=10 # max consecutive failures before container exits
# Logging
RUST_LOG=ironclaw=debug,tower_http=debug