ZapBot

ZapBot is the default runtime agent used by DZapSDK. It is not a chatbot. It is a deterministic NLP pipeline wired to DeFi execution primitives.

What the NLP Engine does

Category	Examples
Read	balances, prices, pools, docs retrieval, search
Plan	token resolution, route/calldata generation
Execute	session-gated zap execution and chain switching
Track	structured step logs and session history snapshots

NLP pipeline

User prompt
  → Tokenization & normalization
  → Intent classification
  → Entity extraction (tokens, amounts, chains, addresses)
  → Ambiguity resolution
  → Tool selection & orchestration
  → Structured result

Supported intent types

Intent	Example prompt
Swap	”Swap 100 USDC for WETH on Arbitrum”
Bridge	”Move 0.5 ETH from Base to Optimism”
Balance check	”What’s my USDC balance across all chains?”
Price lookup	”What’s the current price of stETH?”
Route discovery	”Find the best route to zap into the ETH/USDC pool”
Portfolio summary	”Show me my full portfolio breakdown”

Entity extraction

The engine identifies and resolves the following entity types from natural language:

Entity	Examples
Token	`USDC`, `wETH`, `stETH`, full names like “wrapped ether”
Amount	`100`, `0.5`, `all`, `half`, `max`
Chain	`Arbitrum`, `Base`, `chain ID 10`, `mainnet`
Address	raw `0x...` addresses, ENS names
Action	`swap`, `bridge`, `zap`, `check`, `move`, `send`

Ambiguous inputs (e.g. “ETH” could mean native or wrapped) are resolved using chain context and wallet metadata before tool dispatch.

Ambiguity resolution

When the NLP Engine detects an ambiguous or underspecified prompt, it:

Infers the most likely intent from session context
Uses wallet metadata (connected chain, token holdings) to narrow choices
Asks a clarifying question if the ambiguity cannot be resolved safely

Where it runs

SDK (DZapSDK.ask())
CLI (dzap, dzapai, DzapAI)
HTTP (/ask_stream)
MCP (/mcp)

Default behavior

Setting	Default	Override
Model	`gpt-4o-mini`	`DZAP_OPENAI_MODEL=...`
Max retries	`2`	`DZAP_MODEL_MAX_RETRIES`
Timeout	`4500000 ms`	`DZAP_MODEL_TIMEOUT_MS`
Max tool steps	`25`	code-level config

Runtime guarantees

Metadata is required on each query (metadata.accountInfo[]).
Prompt text excludes private keys.
Interactive actions need explicit confirmation flow.
Tool calls are captured in structured session logs.

How it works

Step-by-step request lifecycle.

Safety

Confirmation gates and execution boundaries.

Get Started

Concepts

NLP Engine

Surfaces

Tool Categories

Skills + Plugins

Agent Integration

What the NLP Engine does

NLP pipeline

Supported intent types

Entity extraction

Ambiguity resolution

Where it runs

Default behavior

Runtime guarantees

Next

How it works

Safety

​What the NLP Engine does

​NLP pipeline

​Supported intent types

​Entity extraction

​Ambiguity resolution

​Where it runs

​Default behavior

​Runtime guarantees

​Next

How it works

Safety

What the NLP Engine does

NLP pipeline

Supported intent types

Entity extraction

Ambiguity resolution

Where it runs

Default behavior

Runtime guarantees

Next