summarization-pydantic-ai
Automatic Conversation Summarization and History Management for Pydantic AI
Decision gist · record as of 2026-08-14
Yes, if you are building Pydantic AI agents that run for more than a few turns or handle long documents. The library is actively maintained, has no known vulnerabilities, and solves a real problem with two pragmatic strategies. Install with conditions only if you need accurate token counting—add the tiktoken extra for that. The MIT license poses no restrictions.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; optional tiktoken dependency for accurate token counting.
- Low friction: single runtime dependency (pydantic-ai-slim), pure Python wheel, active maintenance with recent release.
- Supports Python 3.10–3.13.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution in both open and closed projects with minimal attribution requirements.
last release 2026-07-24 (21 days) · last repo commit 2026-08-14 · 71 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 183,903 downloads/mo, #10,054 on PyPI
Alternatives
Verify before relying
pip install summarization-pydantic-ai
from pydantic_ai import Agent
from summarization_pydantic_ai import ContextManagerCapability
agent = Agent(
"anthropic:claude-sonnet-4-6",
capabilities=[ContextManagerCapability(max_tokens=100_000)],
)
result = await agent.run("Hello!")- Whether the library auto-detects context window size for all supported model providers or only specific ones.
- Performance characteristics of intelligent summarization versus sliding window in production workloads.
- Behavior when tool outputs exceed max_tool_output_tokens during truncation.
What it is and what it does
This library extends pydantic-ai-slim agents with automatic conversation history management, solving the problem of long-running agents hitting model context limits. It offers two strategies: intelligent LLM-based summarization that compresses older messages while preserving meaning, or a zero-cost sliding window that simply discards old messages. Both strategies protect tool call/response pairs from being broken mid-exchange.
The library integrates via Pydantic AI's native Capabilities API, providing automatic token tracking, threshold-based compression triggers, and optional agent-controlled compression through a compact_conversation tool. You can configure triggers by message count, token count, or fraction of context window, and choose what to keep using the same flexible trigger system. It also offers standalone processors for custom integration and a LimitWarnerCapability to alert agents before hitting iteration or token caps.
Use it for
- Long-running customer support bots that need to preserve key details across hundreds of exchanges without exceeding context limits.
- Code assistant agents that keep recent code context while summarizing older design discussions to stay within token budgets.
- High-throughput applications using zero-cost sliding window to trim history with minimal latency overhead.
- Cost-sensitive deployments choosing between intelligent summarization (higher quality, LLM cost) and sliding window (free, lossy).
- Multi-turn agents that let the model decide when to compress via the compact_conversation tool with a focus topic.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building Pydantic AI agents that run for more than a few turns or handle long documents.
The library is actively maintained, has no known vulnerabilities, and solves a real problem with two pragmatic strategies. Install with conditions only if you need accurate token counting—add the tiktoken extra for that. The MIT license poses no restrictions.
Install
summarization-pydantic-ai on PyPI
Before you install
Low friction: single runtime dependency (pydantic-ai-slim), pure Python wheel, active maintenance with recent release. Supports Python 3.10–3.13.
Requires Python 3.10 or later; optional tiktoken dependency for accurate token counting.
License in practice
MIT license permits unrestricted use, modification, and distribution in both open and closed projects with minimal attribution requirements.
Quickstart
pip install summarization-pydantic-ai
from pydantic_ai import Agent
from summarization_pydantic_ai import ContextManagerCapability
agent = Agent(
"anthropic:claude-sonnet-4-6",
capabilities=[ContextManagerCapability(max_tokens=100_000)],
)
result = await agent.run("Hello!")Verify before relying
- Whether the library auto-detects context window size for all supported model providers or only specific ones.
- Performance characteristics of intelligent summarization versus sliding window in production workloads.
- Behavior when tool outputs exceed max_tool_output_tokens during truncation.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagepydantic-ai-slim |
| Maintenance | Actively maintained 21 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 183,903 / month, #10,054 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Software Development :: Libraries :: Python ModulesTyping :: Typed |
Evidence: summarization_pydantic_ai-0.1.11-py3-none-any.whl
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See also pydantic-ai-todo · pydantic-ai-backend · pydantic-deep · subagents-pydantic-ai · pydantic-ai · pydantic-ai-slim · pydantic-ai-shields · headroom-ai · pydantic-ai-harness · pydantic-ai-skills