History Injection

History injection is enabled via memory presets like memory="history" or memory=MemoryConfig(history=True).

Session history is preserved even across long conversations — see Retention Policies for how overflow is summarised and archived.

Overview

History injection automatically loads previous conversation messages from a session and includes them in the agent’s context. This enables:

Multi-turn conversations across sessions
Context continuity when users return
Persistent memory without complex setup

from praisonaiagents import Agent

agent = Agent(
    name="assistant",
    instructions="Continue our conversation with prior turns in context",
    memory="history",
)

agent.start("What did we decide yesterday?")

The user returns to a session; prior messages are injected before the model runs.

Quick Start

Simple Usage

Preset (Simple)
Chat Preset
Custom Limit

from praisonaiagents import Agent

# Enable history with defaults (last 10 messages)
agent = Agent(
    name="assistant",
    instructions="Be helpful",
    memory="history"
)

from praisonaiagents import Agent

# Conversational preset (last 20 messages)
agent = Agent(
    name="assistant",
    instructions="Be helpful",
    memory="chat"
)

from praisonaiagents import Agent
from praisonaiagents import MemoryConfig

# Custom history limit
agent = Agent(
    name="assistant",
    instructions="Be helpful",
    memory=MemoryConfig(history=True, history_limit=5)
)

With Configuration

Switch presets (memory=“chat”) or use a MemoryConfig for token limits and injection rules — see the remaining tabs.

Memory Presets

Enable history via memory presets:

Preset	History Limit	Description
`memory="history"`	10 messages	Standard history injection
`memory="session"`	10 messages	Alias for “history”
`memory="chat"`	20 messages	Conversational (more context)

# Enable history via memory preset
agent = Agent(
    name="assistant",
    memory="history"  # Enables history with file backend
)

# Alias for history preset
agent = Agent(
    name="assistant",
    memory="session"  # Same as "history"
)

# Conversational preset with higher limit
agent = Agent(
    name="assistant",
    memory="chat"  # history_limit=20
)

MemoryConfig

For full control, use MemoryConfig:

from praisonaiagents import Agent
from praisonaiagents import MemoryConfig

agent = Agent(
    name="assistant",
    instructions="Be helpful",
    memory=MemoryConfig(
        history=True,       # Enable history injection
        history_limit=15    # Last 15 messages
    )
)

Show MemoryConfig History Fields

bool

default:"False"

Whether history injection is enabled

int

default:"10"

Maximum number of messages to inject (most recent)

Default sessions are workspace-scoped — the same agent name in a different project is a different session. See Where sessions live for details and the PRAISONAI_GLOBAL_SESSIONS opt-out.

With auto_save

When using auto_save, the session ID is automatically used for history:

MemoryConfig (Recommended)
Legacy (Deprecated)

from praisonaiagents import Agent
from praisonaiagents import MemoryConfig

agent = Agent(
    name="assistant",
    memory=MemoryConfig(auto_save="my-session", history=True)
)

agent.start("Hello!")

# Later, same session continues
agent2 = Agent(
    name="assistant",
    memory=MemoryConfig(auto_save="my-session", history=True)
)
agent2.start("What did I say before?")  # Has context!

from praisonaiagents import Agent

agent = Agent(
    name="assistant",
    auto_save="my-session",  # Deprecated standalone param
    memory="history"
)

How It Works

The user sends a message; the agent loads prior turns from the session store and prepends them to the messages array before calling the model.

Agent Initialization

History settings are resolved from memory parameter:

memory="history" → enabled with limit=10
memory="chat" → enabled with limit=20
memory=MemoryConfig(history=True, history_limit=N) → custom limit

Message Building

When _build_messages() is called:

System prompt is added
Session history is injected (if enabled)
In-memory chat history is added
User prompt is added

Session Store

History is loaded from the session store using get_working_history(session_id, max_messages=limit) when the store supports it — this replays a compacted summary + retained tail if a compaction checkpoint exists. Stores that implement only get_chat_history fall back to raw history automatically. See Compacted Session Resume.

Per-turn persistence is exact. When memory="history" (or MemoryConfig(history=True)) is combined with auto_save, each agent turn persists exactly the user message and the assistant response — no duplicates, even on repeated save_state() calls. Fixed in PraisonAI PR #1897.

Auto-derived session ids are workspace-scoped. When history is enabled without an explicit session_id, the id now folds in a workspace identity so same-named agents in different projects don’t share history. Opt out with PRAISONAI_GLOBAL_SESSIONS=true. See Session Resume.

Best Practices

Set reasonable limits

Use memory="history" (10 messages) to avoid token bloat. More history means more tokens and higher cost.

Use meaningful session IDs

Always use session IDs like user-{user_id} for multi-user apps via auto_save.

Combine with auto_save

Use auto_save to persist conversations and memory="history" to reload them. Repeated turns persist incrementally.

Monitor token usage

Monitor token usage when enabling history to ensure costs stay reasonable.

Comparison

Feature	`memory=True`	`memory="history"`	`memory="chat"`
Enables memory backend	✅	✅	✅
Injects session history	❌	✅ (10 msgs)	✅ (20 msgs)
Long-term memory	✅	✅	✅

Use memory="history" for conversation continuity with reasonable context. Use memory="chat" for longer conversational context.

Memory

Full memory system with backends

Sessions

Session management and persistence

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Getting Started (No Code)

Overview

Quick Start

Memory Presets

MemoryConfig

With auto_save

How It Works

Best Practices

Comparison

Memory

Sessions

​Overview

​Quick Start

​Memory Presets

​MemoryConfig

​With auto_save

​How It Works

​Best Practices

​Comparison

​Related

Memory

Sessions

Overview

Quick Start

Memory Presets

MemoryConfig

With auto_save

How It Works

Best Practices

Comparison

Related