Skip to main content

matrx-batch

Cost-shield foundation for AI workloads in the Matrx ecosystem.

Three primitives:

  1. OpenAI Batch API + Anthropic Message Batches — submit JSONL, poll status, fetch results. Async wrappers over the provider SDKs.
  2. Urgency routerBatchRouter.submit(job) routes a job to live inference, to the provider's Batch API (50% discount, 24h SLA), or makes a cost-based decision automatically.
  3. Embedding cache — content-addressable (SHA256 of model || text) reuse of embedding vectors across the org. Backed by rag.embedding_cache via a host-supplied asyncpg pool.

Dependency posture

matrx-batch sits one notch above matrx-utils in the dependency graph and is consumed by matrx-rag (embedding cache) and matrx-ai (urgency router, future). It MUST NOT import from aidream/ or from any other matrx-* sibling — every cross-boundary dependency comes in via matrx_batch.configure(...).

Usage (host-side wiring)

import matrx_batch
from openai import AsyncOpenAI
from anthropic import AsyncAnthropic

matrx_batch.configure(
    openai_client=AsyncOpenAI(api_key=settings.OPENAI_API_KEY),
    anthropic_client=AsyncAnthropic(api_key=settings.ANTHROPIC_API_KEY),
    pool_factory=lambda: get_async_pg_pool(),
    cost_check=_aidream_budget_precheck,
)

# Wire the cache into matrx-rag's embed() funnel
import matrx_rag
matrx_rag.configure(embedding_cache=matrx_batch.get_embedding_cache())

Usage (consumer)

from matrx_batch import BatchRouter, BatchableJob

router = BatchRouter()
receipt = await router.submit(
    BatchableJob(
        kind="chat",
        provider="anthropic",
        urgency="auto",
        payload={"model": "claude-haiku-4-5", "messages": [...]},
        estimated_tokens_in=8200,
    )
)

See also

  • CLAUDE.md — package rules and injection-point contract.
  • matrx_batch/embedding_cache.py — chunk-level embedding reuse.
  • matrx_batch/router.py — urgency routing decisions.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

matrx_batch-0.2.81.tar.gz (74.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

matrx_batch-0.2.81-py3-none-any.whl (66.5 kB view details)

Uploaded Python 3

File details

Details for the file matrx_batch-0.2.81.tar.gz.

File metadata

  • Download URL: matrx_batch-0.2.81.tar.gz
  • Upload date:
  • Size: 74.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for matrx_batch-0.2.81.tar.gz
Algorithm Hash digest
SHA256 709ee44143adee52d3292f688ea3e27a7a7c3a6b517f1e2d139670c6ca4f9196
MD5 136ee2e4b31e02a9c24aa77129325e23
BLAKE2b-256 5ca87f404d5edc54ed69a1217f0367d7fa8bbe2cfc2996a09899d418a7168ad7

See more details on using hashes here.

Provenance

The following attestation bundles were made for matrx_batch-0.2.81.tar.gz:

Publisher: publish-package.yml on AI-Matrix-Engine/aidream

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file matrx_batch-0.2.81-py3-none-any.whl.

File metadata

  • Download URL: matrx_batch-0.2.81-py3-none-any.whl
  • Upload date:
  • Size: 66.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for matrx_batch-0.2.81-py3-none-any.whl
Algorithm Hash digest
SHA256 4f832b41d5179e174ddd94d90958a3da9cdd6ea1a36cb1cb52273f28a9c73c94
MD5 cb7aaf97260a79620c119b52e7618a5c
BLAKE2b-256 75de5f1e80136a23d969b7a4e826554a4b9c545fe21ca6c08abfc6e3a2043dcc

See more details on using hashes here.

Provenance

The following attestation bundles were made for matrx_batch-0.2.81-py3-none-any.whl:

Publisher: publish-package.yml on AI-Matrix-Engine/aidream

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

0.2.86

2 files

0.2.84

2 files

0.2.83

2 files

0.2.82

2 files

This release

0.2.81 This release

2 files

0.2.80

2 files

0.2.79

2 files

0.2.78

2 files

0.2.77

2 files

0.2.76

2 files

0.2.75

2 files

0.2.74

2 files

0.2.73

2 files

0.2.72

2 files

0.2.71

2 files

0.2.70

2 files

0.2.69

2 files

0.2.68

2 files

0.2.67

2 files

0.2.66

2 files

0.2.65

2 files

0.2.64

2 files

0.2.63

2 files

0.2.62

2 files

0.2.61

2 files

0.2.60

2 files

0.2.59

2 files

0.2.58

2 files

0.2.57

2 files

0.2.56

2 files

0.2.55

2 files

0.2.54

2 files

0.2.53

2 files

0.2.52

2 files

0.2.51

2 files

0.2.50

2 files

0.2.49

2 files

0.2.48

2 files

0.2.47

2 files

0.2.46

2 files

0.2.45

2 files

0.2.44

2 files

0.2.43

2 files

0.2.42

2 files

0.2.41

2 files

0.2.40

2 files

0.2.39

2 files

0.2.38

2 files

0.2.37

2 files

0.2.36

2 files

0.2.35

2 files

0.2.34

2 files

0.2.33

2 files

0.2.32

2 files

0.2.31

2 files

0.2.30

2 files

0.2.29

2 files

0.2.28

2 files

0.2.27

2 files

0.2.26

2 files

0.2.25

2 files

0.2.24

2 files

0.2.23

2 files

0.2.22

2 files

0.2.21

2 files

0.2.20

2 files

0.2.19

2 files

0.2.18

2 files

0.2.17

2 files

0.2.16

2 files

0.2.15

2 files

0.2.14

2 files

0.2.13

2 files

0.2.12

2 files

0.2.11

2 files

0.2.10

2 files

0.2.9

2 files

0.2.8

2 files

0.2.7

2 files

0.2.6

2 files

0.2.5

2 files

0.2.4

2 files

0.2.3

2 files

0.2.2

2 files

0.2.1

2 files

0.2.0

2 files

0.1.1

2 files

0.1.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page