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Sequa 📼

Sequa is snapshot testing for LLM applications. Record once, replay forever.


The Magic

Before

from langchain_groq import ChatGroq

model = ChatGroq(model_name="llama-3.1-8b-instant")
response = model.invoke("Write a 3-word slogan for gravity.")
# ⏱️ Time taken: 2.3 seconds

After

from langchain_groq import ChatGroq
from sequa import cassette

model = ChatGroq(model_name="llama-3.1-8b-instant")

with cassette("tests/cassettes"):
    response = model.invoke("Write a 3-word slogan for gravity.")
    # ⏱️ First run: 2.3 seconds (recorded to tests/cassettes/)
    # ⏱️ Second run: 12 ms (replayed locally!)

Features

  • Record once, replay forever: Speed up integration test suites from minutes to milliseconds.
  • Multiple Execution Modes: Support replay, record, auto, and live modes.
  • Robust Key Sorting & Hashing: Recursively sorts request inputs to generate deterministic hashes.
  • Custom Ignored Fields: Easily ignore dynamic/unstable fields (e.g. temperature, max_tokens).
  • Custom Normalizers: Redact, replace, or clean requests prior to hashing.
  • CLI Utilities: Inspect, format, and calculate statistics of stored cassettes.

Installation

uv pip install -e .

Configuration & Advanced API

1. Execution Modes

Control Sequa behavior via the mode parameter:

with cassette("tests/cassettes", mode="replay"):
    # Will raise CassetteNotFoundError if no matching cassette is found.
    # Guaranteed to make zero external network requests.
  • auto (Default): Replays if a matching cassette exists, otherwise calls the live API and records it.
  • record: Always calls the live API and records/overwrites the cassette.
  • replay: Never calls the live API. Raises CassetteNotFoundError on cache misses.
  • live: Direct pass-through to the live API, bypassing cassettes entirely.

2. Ignore Fields

Strip request parameters before generating hashes:

with cassette("tests/cassettes", ignore_fields=["temperature", "max_tokens"]):
    # These two calls generate the exact same hash and match the same cassette:
    model.invoke("hello", temperature=0.2)
    model.invoke("hello", temperature=0.9)

3. Custom Normalizers

For complex normalization or content redaction:

def redact_dates(request_dict):
    # Redact dynamic inputs or strip timestamps
    return request_dict

with cassette("tests/cassettes", normalizer=redact_dates):
    model.invoke(...)

Command Line Interface (CLI)

Sequa comes with a CLI tool to manage your cassettes.

Stats

Show the number of cassettes, total size on disk, and estimated API latency saved:

sequa stats --path ./tests/cassettes

Inspect

List all stored cassettes, their model, provider, and when they were recorded:

sequa inspect --path ./tests/cassettes

Clean

Clean dynamic fields (latency, created_at) from cassettes to prevent noisy git diffs:

sequa clean --path ./tests/cassettes --remove-latency --remove-timestamps

License

MIT License.

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