caesura-io-core 0.1.0

Framework-agnostic core for Caesura — analyze, inject, and credit-metering logic shared across SDK integrations.

caesura-io-core

Framework-agnostic core for Caesura — shared analyze, inject, and credit-metering logic used by all SDK integrations.

This package is not meant to be used directly. It is the shared engine consumed by:

• caesura-io-openai — OpenAI Python SDK wrapper

What's inside

Module	Purpose
CaesuraClient / AsyncCaesuraClient	HTTP client that calls the /api/analyze endpoint
MemoryCaesuraStore	In-memory conversation state with LRU + idle-time eviction
CaesuraEngine / AsyncCaesuraEngine	Orchestrator: cadence checks, observe/analyze cycle, buffering, event emission
create_credit_meter	Accumulates and queries credit-usage metrics
create_debug_logger	Structured on_event logger for debugging
Helpers	hash_message, select_active, render_analysis, render_block, build_analyze_messages
Types	CaesuraConfig, CaesuraEvent, InjectConfig, SendConfig, etc.

Install

pip install caesura-io-core

Usage

Most consumers should use the framework-specific wrappers. If you're building your own integration:

from caesura_core import create_caesura_engine, select_active, render_block

engine = create_caesura_engine(CaesuraConfig(
    base_url="https://dev.caesura.io",
    # api_key auto-read from CAESURA_API_KEY if omitted
))

# 1. Observe a conversation turn
engine.observe("conversation-id", [
    AnalyzeMessage(
        speaker_role="user",
        speaker_name="Customer",
        text="I need help preparing for the next meeting",
    ),
])

# 2. Retrieve buffered recommendations
state = engine.store.get("conversation-id")
active = select_active(state, engine.config.inject, time.time() * 1000)
blocks = render_block(active, engine.config.inject)
# → blocks contains rendered recommendation text ready for injection

License

Apache-2.0