Genai Toolkit
Genai Toolkit v2.0.0 — an AI toolkit for managing generative AI workflows from the command line. Log configurations, benchmarks, prompts, evaluations, fine-tuning runs, cost tracking, and optimization notes. Each entry is timestamped and persisted locally. Works entirely offline — your data never leaves your machine.
Why Genai Toolkit?
- Works entirely offline — your data never leaves your machine
- Simple command-line interface with no GUI dependency
- Export to JSON, CSV, or plain text at any time for sharing or archival
- Automatic activity history logging across all commands
- Each domain command doubles as both a logger and a viewer
Commands
Domain Commands
Each domain command works in two modes: log mode (with arguments) saves a timestamped entry, view mode (no arguments) shows the 20 most recent entries.
| Command |
Description |
genai-toolkit configure <input> |
Log a configuration note such as model parameters, API keys, or environment settings. Use this to record setup changes and track which configurations were active during experiments. |
genai-toolkit benchmark <input> |
Log a benchmark result or performance observation. Record latency, throughput, accuracy, or other metrics to compare across runs and model versions. |
genai-toolkit compare <input> |
Log a comparison note between models, configurations, or approaches. Useful for side-by-side evaluations like GPT-4 vs Claude on specific tasks. |
genai-toolkit prompt <input> |
Log a prompt template or prompt engineering note. Track iterations on prompt design, record what worked, and document prompt versioning. |
genai-toolkit evaluate <input> |
Log an evaluation result or quality metric. Record accuracy scores, F1 metrics, human ratings, or any qualitative assessment of model outputs. |
genai-toolkit fine-tune <input> |
Log a fine-tuning run or hyperparameter note. Track epochs, learning rates, dataset sizes, and resulting model performance after fine-tuning. |
genai-toolkit analyze <input> |
Log an analysis observation or insight. Record patterns found in data, failure mode analysis, or trends across experiments. |
genai-toolkit cost <input> |
Log cost tracking data including API costs, compute expenses, and token consumption. Essential for budget monitoring across projects and providers. |
genai-toolkit usage <input> |
Log usage metrics or consumption data. Track request volumes, token counts, rate limit encounters, and daily/monthly consumption patterns. |
genai-toolkit optimize <input> |
Log optimization attempts or performance improvements. Record what was changed, the expected vs actual impact, and next steps. |
genai-toolkit test <input> |
Log test results or test case notes. Record pass/fail outcomes, edge cases discovered, and regression test results. |
genai-toolkit report <input> |
Log a report entry or summary finding. Capture weekly summaries, milestone reports, or executive-level findings from AI workflows. |
Utility Commands
| Command |
Description |
genai-toolkit stats |
Show summary statistics across all log files, including entry counts per category and total data size on disk. |
genai-toolkit export <fmt> |
Export all data to a file in the specified format. Supported formats: json, csv, txt. Output is saved to the data directory. |
genai-toolkit search <term> |
Search all log entries for a term using case-insensitive matching. Results are grouped by log category for easy scanning. |
genai-toolkit recent |
Show the 20 most recent entries from the unified activity log, giving a quick overview of recent work across all commands. |
genai-toolkit status |
Health check showing version, data directory path, total entry count, disk usage, and last activity timestamp. |
genai-toolkit help |
Show the built-in help message listing all available commands and usage information. |
genai-toolkit version |
Print the current version (v2.0.0). |
Data Storage
All data is stored locally at ~/.local/share/genai-toolkit/. Each domain command writes to its own log file (e.g., configure.log, benchmark.log). A unified history.log tracks all actions across commands. Use export to back up your data at any time.
Requirements
- Bash (4.0+)
- No external dependencies — pure shell script
- No network access required
When to Use
- Tracking AI model benchmarks and comparisons across different providers and versions over time
- Logging prompt engineering iterations to understand what improvements actually moved the needle
- Monitoring API costs and token usage across multiple projects and billing periods
- Evaluating fine-tuning experiments with detailed hyperparameter and metric tracking
- Building a searchable knowledge base of optimization attempts and analysis insights
Examples
# Log a benchmark result
genai-toolkit benchmark "GPT-4o latency: avg 1.2s, p99 3.8s on summarization task, 500 samples"
# Track a cost entry
genai-toolkit cost "March batch processing: $42.50 across 15k requests, avg $0.0028/req"
# Compare two models
genai-toolkit compare "Claude 3.5 vs GPT-4o on code generation — Claude 15% faster, GPT-4o 5% more accurate"
# Log a prompt iteration
genai-toolkit prompt "v3: Added chain-of-thought instruction, reduced hallucination rate from 12% to 3%"
# Record a fine-tuning run
genai-toolkit fine-tune "SQL-gen model epoch 5: accuracy=0.96, loss=0.12, lr=2e-5, dataset=50k rows"
# View all statistics
genai-toolkit stats
# Export everything to JSON
genai-toolkit export json
# Search for entries mentioning latency
genai-toolkit search latency
# Check recent activity
genai-toolkit recent
# Health check
genai-toolkit status
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1---2name: genai-toolbox-23description: Bridge AI models to databases through MCP with config and evaluation tools. Use when setting up DB tools, comparing engines, or evaluating prompt quality.4---5
6# Genai Toolkit
7
8Genai Toolkit v2.0.0 — an AI toolkit for managing generative AI workflows from the command line. Log configurations, benchmarks, prompts, evaluations, fine-tuning runs, cost tracking, and optimization notes. Each entry is timestamped and persisted locally. Works entirely offline — your data never leaves your machine.
9
10## Why Genai Toolkit?
11
12- Works entirely offline — your data never leaves your machine
13- Simple command-line interface with no GUI dependency
14- Export to JSON, CSV, or plain text at any time for sharing or archival
15- Automatic activity history logging across all commands
16- Each domain command doubles as both a logger and a viewer
17
18## Commands
19
20### Domain Commands
21
22Each domain command works in two modes: **log mode** (with arguments) saves a timestamped entry, **view mode** (no arguments) shows the 20 most recent entries.
23
24| Command | Description |
25|---------|-------------|
26| `genai-toolkit configure <input>` | Log a configuration note such as model parameters, API keys, or environment settings. Use this to record setup changes and track which configurations were active during experiments. |
27| `genai-toolkit benchmark <input>` | Log a benchmark result or performance observation. Record latency, throughput, accuracy, or other metrics to compare across runs and model versions. |
28| `genai-toolkit compare <input>` | Log a comparison note between models, configurations, or approaches. Useful for side-by-side evaluations like GPT-4 vs Claude on specific tasks. |
29| `genai-toolkit prompt <input>` | Log a prompt template or prompt engineering note. Track iterations on prompt design, record what worked, and document prompt versioning. |
30| `genai-toolkit evaluate <input>` | Log an evaluation result or quality metric. Record accuracy scores, F1 metrics, human ratings, or any qualitative assessment of model outputs. |
31| `genai-toolkit fine-tune <input>` | Log a fine-tuning run or hyperparameter note. Track epochs, learning rates, dataset sizes, and resulting model performance after fine-tuning. |
32| `genai-toolkit analyze <input>` | Log an analysis observation or insight. Record patterns found in data, failure mode analysis, or trends across experiments. |
33| `genai-toolkit cost <input>` | Log cost tracking data including API costs, compute expenses, and token consumption. Essential for budget monitoring across projects and providers. |
34| `genai-toolkit usage <input>` | Log usage metrics or consumption data. Track request volumes, token counts, rate limit encounters, and daily/monthly consumption patterns. |
35| `genai-toolkit optimize <input>` | Log optimization attempts or performance improvements. Record what was changed, the expected vs actual impact, and next steps. |
36| `genai-toolkit test <input>` | Log test results or test case notes. Record pass/fail outcomes, edge cases discovered, and regression test results. |
37| `genai-toolkit report <input>` | Log a report entry or summary finding. Capture weekly summaries, milestone reports, or executive-level findings from AI workflows. |
38
39### Utility Commands
40
41| Command | Description |
42|---------|-------------|
43| `genai-toolkit stats` | Show summary statistics across all log files, including entry counts per category and total data size on disk. |
44| `genai-toolkit export <fmt>` | Export all data to a file in the specified format. Supported formats: `json`, `csv`, `txt`. Output is saved to the data directory. |
45| `genai-toolkit search <term>` | Search all log entries for a term using case-insensitive matching. Results are grouped by log category for easy scanning. |
46| `genai-toolkit recent` | Show the 20 most recent entries from the unified activity log, giving a quick overview of recent work across all commands. |
47| `genai-toolkit status` | Health check showing version, data directory path, total entry count, disk usage, and last activity timestamp. |
48| `genai-toolkit help` | Show the built-in help message listing all available commands and usage information. |
49| `genai-toolkit version` | Print the current version (v2.0.0). |
50
51## Data Storage
52
53All data is stored locally at `~/.local/share/genai-toolkit/`. Each domain command writes to its own log file (e.g., `configure.log`, `benchmark.log`). A unified `history.log` tracks all actions across commands. Use `export` to back up your data at any time.
54
55## Requirements
56
57- Bash (4.0+)
58- No external dependencies — pure shell script
59- No network access required
60
61## When to Use
62
63- Tracking AI model benchmarks and comparisons across different providers and versions over time
64- Logging prompt engineering iterations to understand what improvements actually moved the needle
65- Monitoring API costs and token usage across multiple projects and billing periods
66- Evaluating fine-tuning experiments with detailed hyperparameter and metric tracking
67- Building a searchable knowledge base of optimization attempts and analysis insights
68
69## Examples
70
71```bash
72# Log a benchmark result
73genai-toolkit benchmark "GPT-4o latency: avg 1.2s, p99 3.8s on summarization task, 500 samples"
74
75# Track a cost entry
76genai-toolkit cost "March batch processing: $42.50 across 15k requests, avg $0.0028/req"
77
78# Compare two models
79genai-toolkit compare "Claude 3.5 vs GPT-4o on code generation — Claude 15% faster, GPT-4o 5% more accurate"
80
81# Log a prompt iteration
82genai-toolkit prompt "v3: Added chain-of-thought instruction, reduced hallucination rate from 12% to 3%"
83
84# Record a fine-tuning run
85genai-toolkit fine-tune "SQL-gen model epoch 5: accuracy=0.96, loss=0.12, lr=2e-5, dataset=50k rows"
86
87# View all statistics
88genai-toolkit stats
89
90# Export everything to JSON
91genai-toolkit export json
92
93# Search for entries mentioning latency
94genai-toolkit search latency
95
96# Check recent activity
97genai-toolkit recent
98
99# Health check
100genai-toolkit status
101```
102
103---
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