LLM Chain
An AI toolkit for configuring, benchmarking, comparing, prompting, evaluating, fine-tuning, analyzing, and optimizing LLM workflows. Each command logs timestamped entries to local files with full export, search, and statistics support.
Commands
Core AI Operations
| Command | Description |
|---|
| INLINECODE0 | Record a configuration change (or view recent configs with no args) |
| INLINECODE1 |
Log a benchmark run and its results |
|
llm-chain compare <input> | Record a model or output comparison |
|
llm-chain prompt <input> | Log a prompt template or prompt engineering note |
|
llm-chain evaluate <input> | Record an evaluation result or metric |
|
llm-chain fine-tune <input> | Log a fine-tuning session or parameters |
|
llm-chain analyze <input> | Record an analysis observation |
|
llm-chain cost <input> | Log cost tracking data (tokens, dollars, etc.) |
|
llm-chain usage <input> | Record API usage metrics |
|
llm-chain optimize <input> | Log an optimization attempt and outcome |
|
llm-chain test <input> | Record a test case or test result |
|
llm-chain report <input> | Log a report entry or summary |
Utility Commands
| Command | Description |
|---|
| INLINECODE12 | Show summary statistics across all log files |
| INLINECODE13 |
Export all data in
json,
csv, or
txt format |
|
llm-chain search <term> | Search all entries for a keyword (case-insensitive) |
|
llm-chain recent | Show the 20 most recent activity log entries |
|
llm-chain status | Health check: version, entry count, disk usage, last activity |
|
llm-chain help | Display full command reference |
|
llm-chain version | Print current version (v2.0.0) |
How It Works
Every core command accepts free-text input. When called with arguments, LLM Chain:
- 1. Timestamps the entry (
YYYY-MM-DD HH:MM) - Appends it to the command-specific log file (e.g.
benchmark.log, cost.log) - Records the action in a central INLINECODE25
- Reports the saved entry and running total
When called with no arguments, each command displays the 20 most recent entries from its log file.
Data Storage
All data is stored locally in plain-text log files:
CODEBLOCK0
Each log uses pipe-delimited format: timestamp|value.
Requirements
- - Bash 4.0+ with INLINECODE27
- Standard Unix utilities:
wc, du, grep, tail, date, INLINECODE33 - No external dependencies — pure bash
When to Use
- 1. Tracking LLM experiments — log benchmark results, prompt variations, and evaluation scores as you iterate on model configurations
- Cost monitoring — record token usage, API costs, and billing data to keep spending under control across multiple models
- Comparing models side-by-side — use
compare and benchmark to log performance differences between GPT-4, Claude, Gemini, etc. - Fine-tuning documentation — capture fine-tuning parameters, dataset info, and results for reproducibility
- Generating operational reports — export all logged data to JSON/CSV for dashboards, audits, or stakeholder reviews
Examples
CODEBLOCK1
Configuration
Set the DATA_DIR variable in the script or modify the default path to change storage location. Default: ~/.local/share/llm-chain/
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