Basic message list context manager for conversation state.
- Python 3.11+
- UV - Fast Python package manager
# macOS/Linux/WSL
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"Provides straightforward in-memory conversation context management. This is the reference implementation and default context manager.
Module Type: Context
Mount Point: contexts
Entry Point: amplifier_module_context_simple:mount
- In-memory message list
- No persistence across sessions
- Automatic compaction when approaching token limit (keeps system messages + last 10 messages)
- Preserves tool pairs as atomic units during compaction (data integrity guarantee)
[[contexts]]
module = "context-simple"
name = "simple"
config = {
max_messages = 100 # Optional limit
}# In amplifier configuration
[session]
context = "context-simple"Perfect for:
- Development and testing
- Short conversations
- Stateless applications
Not suitable for:
- Cross-session persistence
- Custom compaction strategies
The SimpleContextManager uses ephemeral compaction - get_messages_for_request() returns a compacted VIEW without modifying the internal message history. The full history is always preserved in memory.
Compaction triggers when token usage reaches the configured threshold (default: 92% of max_tokens):
- System messages: All system messages are always preserved
- First user message: The original task/request is always protected (prevents losing context about what was originally asked)
- Last user message: The most recent user input is always preserved
- Recent messages: Last N% of messages (configurable via
protected_recent) - Tool pairs: Tool_use and tool_result messages are treated as atomic units
- Phase 1 - Tool Result Truncation: Older tool results are truncated to reduce token usage
- Phase 2 - Message Removal: Older non-protected messages are removed if still over budget
Anthropic API requires that every tool_use in message N has a matching tool_result in message N+1. The context manager preserves these pairs as atomic units during compaction to maintain conversation state integrity and prevent API errors.
Critical implementation detail: When an assistant message has multiple tool_calls, there are multiple consecutive tool_result messages after it. The compaction logic walks backwards through these tool results to find the originating assistant message, ensuring the entire tool group is preserved as an atomic unit. This prevents orphaned tool results that would cause API validation errors.
amplifier-core>=1.0.0
Note
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