Product
The execution layer for AI agents.
Paprika is production infrastructure that makes agent execution traceable, governable, and replayable. It wraps your runtime — it doesn't replace it.
Structured trace capture
Every LLM call and tool invocation is recorded as a typed, audit-ready event. Timestamps, token counts, input hashes, and durations — for every run.
Runtime policy enforcement
Configure max_steps, max_tokens, and max_repeat_hashes. Paprika halts execution with a structured PolicyViolationError before damage is done.
Safe deterministic replay
Re-execute any prior run using recorded outputs. LLM and tool calls return cached results. No live APIs, no side effects. Mismatches surface immediately.
Inspection and diffing
List runs, inspect traces step-by-step, diff two runs to see where execution diverged. CLI and API for operational workflows.
Platform
Minimal surface, maximum control.
Wrap your agent in minutes. Paprika injects a context object that traces every LLM and tool call automatically.
#a3d95f]">"text-[#9ecbff]">from paprika "text-[#9ecbff]">import PaprikaRuntime, PolicyConfig
runtime = PaprikaRuntime(
policy=PolicyConfig(
max_steps=20,
max_tokens=20000,
max_repeat_hashes=3,
)
)
@runtime.agent()
#a3d95f]">"text-[#9ecbff]">def support_agent(ctx, user_input):
analysis = ctx.llm.call(
provider=#a3d95f]">"openai",
model=#a3d95f]">"gpt-4.1-mini",
input={#a3d95f]">"messages": [{"role": "user", "content": user_input}]},
)
customer = ctx.tools.call(
name=#a3d95f]">"lookup_customer",
args={#a3d95f]">"email": "alice@example.com"},
)
#a3d95f]">"text-[#9ecbff]">return ctx.llm.call(
provider=#a3d95f]">"openai",
model=#a3d95f]">"gpt-4.1-mini",
input={#a3d95f]">"messages": [
{#a3d95f]">"role": "user", "content": f"Summarize: {customer}"}
]},
)Trace format
Audit-ready execution records.
Ready to add execution control?
Book a demo to see how teams are using Paprika for production agent workflows.