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Progressive algorithmization toolchain — from LLM to deterministic code, from proxy to tickets

Project description

algitex

Progressive algorithmization toolchain — from LLM to deterministic code, from proxy to tickets.

The only framework that automates the path from "LLM handles everything" to "most traffic runs deterministically, LLM only for edge cases."

pip install algitex
algitex init ./my-app
algitex go

Why "algitex"?

The name reflects the core cycle: analyze → plan → execute → validate → repeat. Each iteration makes your codebase healthier and your LLM usage cheaper. The progressive algorithmization loop gradually replaces LLM calls with deterministic rules.

Name alternatives considered

Name Why it works Why we picked algitex
algitex Core concept: the continuous improvement loop Clear, memorable, tech-neutral
prollama "progressive" + llama vibes Ties too much to one model family
codefact Code + factory/fact Sounds like a trivia app
algopact Algorithm + Propact Hard to pronounce
loopcode Loop + code Reverse reads awkward
prodev Progressive + dev Too generic, SEO nightmare

Three layers, one command

Layer 1: Code Quality Loop

from algitex import Project

p = Project("./my-app")
p.analyze()    # code2llm + vallm + redup → health report
p.plan()       # auto-generate tickets from analysis
p.execute()    # LLM handles tasks via proxym
p.status()     # health + tickets + budget + cost ledger

Layer 2: Progressive Algorithmization

from algitex import Loop

loop = Loop("./my-app")
loop.discover()        # Stage 1: collect all LLM traces
loop.extract()         # Stage 2: find repeating patterns
loop.generate_rules()  # Stage 3: AI writes its own replacement
loop.route()           # Stage 4: rules vs LLM by confidence
loop.optimize()        # Stage 5: monitor, minimize LLM usage
print(loop.report())   # "42% deterministic, $12.50 saved"

Layer 3: Propact Workflows

from algitex import Workflow

wf = Workflow("./refactor-v1.md")
wf.execute()   # runs propact:shell, propact:rest, propact:llm blocks

CLI

# Core loop
algitex init ./my-app         # initialize project
algitex analyze               # health check
algitex plan --sprints 3      # generate sprint strategy + tickets
algitex go                    # full pipeline
algitex status                # dashboard

# Progressive algorithmization
algitex algo discover         # start trace collection
algitex algo extract          # find patterns in traces
algitex algo rules            # generate deterministic replacements
algitex algo report           # show % deterministic vs LLM

# Propact workflows
algitex workflow run fix.md   # execute Markdown workflow
algitex workflow validate f.md

# Tickets
algitex ticket add "Fix auth" --priority high
algitex ticket list
algitex ticket board
algitex sync                  # push to GitHub/Jira

# Quick queries
algitex ask "Explain this race condition" --tier premium
algitex tools                 # show installed tools

The 5-Stage Progressive Algorithmization

Stage 1: Discovery     → LLM handles 100%, collect traces
Stage 2: Extraction    → identify hot paths + repeating patterns
Stage 3: Rules         → AI generates deterministic replacements
Stage 4: Hybrid        → confidence-based: known patterns → rules, unknown → LLM
Stage 5: Optimization  → most traffic deterministic, LLM for edge cases only

No existing framework automates this path. DSPy goes LLM→smaller LLM. algitex goes LLM→algorithm.

Propact: Markdown as Workflow

# Fix Authentication Module

Analyze current state:

```propact:shell
code2llm ./src/auth -f toon --json

Ask LLM for a fix plan:

POST http://localhost:4000/v1/chat/completions
{"model": "balanced", "messages": [{"role": "user", "content": "Fix auth"}]}

Validate the result:

vallm batch ./src/auth --recursive

## Planfile-Aware Proxy Headers

Every LLM request through algitex carries context:

X-Planfile-Ref: my-project/current/DLP-0042 X-Workflow-Ref: refactor-v1.md X-Task-Tier: complex X-Inject-Context: true


Proxym logs cost/model/latency **per ticket**. The cost ledger shows exactly what each task costs.

## Installation

```bash
pip install algitex                # core
pip install algitex[all]           # + all tools
pip install algitex[proxy]         # + proxym
pip install algitex[analysis]      # + code2llm, vallm, redup
pip install algitex[tickets]       # + planfile
pip install algitex[routing]       # + llx

Architecture

src/algitex/
├── __init__.py           # Project, Loop, Workflow, Config, Pipeline
├── config.py             # Unified config (env + YAML)
├── project.py            # Main Project class (expanded)
├── cli.py                # Typer CLI (all commands)
├── algo/                 # Progressive algorithmization
│   ├── __init__.py       # Loop, TraceEntry, Pattern, Rule, LoopState
│   └── loop.py           # Re-export
├── propact/              # Markdown workflow engine
│   ├── __init__.py       # Workflow, WorkflowStep, WorkflowResult
│   └── workflow.py       # Re-export
├── tools/
│   ├── __init__.py       # Tool discovery
│   ├── proxy.py          # proxym wrapper + planfile headers
│   ├── analysis.py       # code2llm + vallm + redup
│   └── tickets.py        # planfile wrapper + cost ledger
└── workflows/
    ├── __init__.py        # Pipeline (composable steps)
    └── pipeline.py        # Re-export

How it connects to the ecosystem

┌─────────────────────────────────────────────────────┐
│                     algitex                         │
│            (orchestration layer)                    │
├─────────────────────────────────────────────────────┤
│                                                     │
│  analyze()   plan()   execute()   algo.discover()   │
│     │          │         │            │             │
│  code2llm   planfile   proxym      trace →          │
│  vallm      tickets    llx         patterns →       │
│  redup      strategy   models      rules →          │
│                                    hybrid routing    │
│                                                     │
│  run_workflow("fix.md")                             │
│     │                                               │
│  propact:shell → subprocess                         │
│  propact:rest  → httpx                              │
│  propact:llm   → proxym                             │
│  propact:mcp   → MCP tool call                      │
│                                                     │
└─────────────────────────────────────────────────────┘

Tool Roles

Tool What Install
proxym LLM gateway, 10 providers, routing, budget pip install proxym
planfile Sprint planning, tickets, GitHub/Jira sync pip install planfile
llx Metric-driven model selection, MCP server pip install llx
code2llm Static analysis → .toon diagnostics pip install code2llm
vallm 4-tier code validation pip install vallm
redup Duplication detection pip install redup

License

Licensed under Apache-2.0.

Licensed under Apache-2.0.

Licensed under Apache-2.0.

Apache License 2.0

Author

Tom Sapletta

Tom Sapletta

Tom Sapletta

Created by Tom Saplettatom@sapletta.com

Part of the semcod / wronai ecosystem.

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