compressa-perf 0.2.7

Performance Measurement tool by Compressa

Compressa Performance Measurement Tool

This tool is designed to measure the performance of Compressa models.
It uses the OpenAI API to run inference tasks and stores the results in a SQLite database.

Installation

git clone https://github.com/compressa-ai/compressa-perf.git
cd compressa-perf
poetry install
$(poetry env activate)

Install with Pip

pip install compressa-perf

Usage

1. Run experiment with prompts from a file

❯ compressa-perf measure \
    --db some_db.sqlite \
    --openai_url https://some-api-url.ru/ \
    --api_key "${OPENAI_API_KEY}" \
    --model_name Compressa-Qwen2.5-14B-Instruct \
    --experiment_name "File Prompts Run" \
    --prompts_file resources/prompts.csv \
    --num_tasks 1000 \
    --num_runners 100

2. Run experiment with generated prompts

❯ compressa-perf measure \
    --db some_db.sqlite \
    --openai_url https://some-api-url.ru/chat-2/v1/ \
    --api_key "${OPENAI_API_KEY}" \
    --model_name Compressa-Qwen2.5-14B-Instruct \
    --experiment_name "Generated Prompts Run" \
    --num_tasks 2 \
    --num_runners 2 \
    --generate_prompts \
    --num_prompts 1000 \
    --prompt_length 5000

Full parameter list can be obtained with compressa-perf measure -h.

3. Run set of experiments from YAML file

You can describe set of experiments in YAML file and run them on different services in one command:

❯ compressa-perf measure-from-yaml experiments.yaml \
    --db some_db.sqlite \

Example of YAML file:

- openai_url: http://localhost:5000/v1/
  api_key: ${OPENAI_API_KEY}
  model_name: Compressa-LLM
  experiment_name: "File Prompts Run 1"
  description: "Experiment using prompts from a file with 500 tasks and 5 runners"
  prompts_file: resources/prompts.csv
  num_tasks: 500
  num_runners: 5
  generate_prompts: false
  num_prompts: 0
  prompt_length: 0
  max_tokens: 1000 

- openai_url: https://some-api-url/v1/
  api_key: ${OPENAI_API_KEY}
  model_name: Compressa-LLM
  experiment_name: "File Prompts Run 2"
  description: "Experiment using prompts from a file with 20 tasks and 10 runners"
  prompts_file: resources/prompts.csv
  num_tasks: 20
  num_runners: 10
  generate_prompts: true
  num_prompts: 10
  prompt_length: 10000
  max_tokens: 100

List of Parameters

• openai_url - url to chat completion endpoint - REQUIRED
• serv_api_url - url to service handlers of the Compressa platform - default is http://localhost:5100/v1/ (if None - the inference only will run)
• api_key - API key - REQUIRED
• model_name - served model name - REQUIRED
• experiment_name - REQUIRED
• description
• prompts_file - path to the file with prompts
• report_file - path to the report file - default is results/experiment
• report_mode - report file extension (.csv, .md, .pdf) - default is .pdf
• num_tasks
• num_runners
• generate_prompts - true or false
• num_prompts
• prompt_length
• max_tokens

4. List experiments

You can select experiments by name, parameters or metrics (or substrings in these fields) via compressa-perf list command.

For example:

❯ compressa-perf list \
    --show-metrics \
    --param-filter openai_url=chat-2 \
    --param-filter avg_n_input=30

List of Experiments:
+----+----------------------------------------------------------------------------+---------------------+--------+-----------------------+
|    | ID                                                                         | Name                | Date   | Description           |
+====+============================================================================+=====================+========+=======================+
| 25 | Compressa-Qwen2.5-14B-Instruct-Int4 Long Input / Short Output | 5 runners  | 2024-10-03 06:21:45 |        | ttft: 25.0960         |
|    |                                                                            |                     |        | latency: 52.5916      |
|    |                                                                            |                     |        | tpot: 0.5530          |
|    |                                                                            |                     |        | throughput: 2891.0323 |
+----+----------------------------------------------------------------------------+---------------------+--------+-----------------------+
| 23 | Compressa-Qwen2.5-14B-Instruct-Int4 Long Input / Short Output | 4 runners  | 2024-10-03 06:14:57 |        | ttft: 17.1862         |
|    |                                                                            |                     |        | latency: 37.9612      |
|    |                                                                            |                     |        | tpot: 0.3954          |
|    |                                                                            |                     |        | throughput: 3230.8769 |
+----+----------------------------------------------------------------------------+---------------------+--------+-----------------------+

Full parameter list:

❯ compressa-perf list -h
usage: compressa-perf list [-h] [--db DB] [--show-parameters] [--show-metrics] [--name-filter NAME_FILTER] [--param-filter PARAM_FILTER]

options:
  -h, --help            show this help message and exit
  --db DB               Path to the SQLite database
  --show-parameters     Show all parameters for each experiment
  --show-metrics        Show metrics for each experiment
  --name-filter NAME_FILTER
                        Filter experiments by substring in the name
  --param-filter PARAM_FILTER
                        Filter experiments by parameter value (e.g., paramkey=value_substring)

5. Generate a report for an experiment

In addition to the .pdf, .csv or .md reports the text reports also can be generated with the command:

❯ compressa-perf report <EXPERIMENT_ID>

Output example:

❯ compressa-perf report 3

Experiment Details:
ID: 3
Name: My First Run
Date: 2024-09-24 07:10:39
Description: None

Experiment Parameters:
╒══════════════╤═══════════════════════════════════════════╕
│    Parameter │                                     Value │
╞══════════════╪═══════════════════════════════════════════╡
│  num_workers │                                         2 │
├──────────────┼───────────────────────────────────────────┤
│    num_tasks │                                         2 │
├──────────────┼───────────────────────────────────────────┤
│   openai_url │ https://some-api-url.ru/chat-2/v1/        │
├──────────────┼───────────────────────────────────────────┤
│  max_tokens  │                                      1000 │
├──────────────┼───────────────────────────────────────────┤
│  model_name  │                             Compressa-LLM │
├──────────────┼───────────────────────────────────────────┤
│  avg_n_input │                                        32 │
├──────────────┼───────────────────────────────────────────┤
│  std_n_input │                                    2.8284 │
├──────────────┼───────────────────────────────────────────┤
│ avg_n_output │                                  748.5000 │
├──────────────┼───────────────────────────────────────────┤
│ std_n_output │                                    2.1213 │
╘══════════════╧═══════════════════════════════════════════╛

Experiment Metrics:

╒══════════════════════════╤══════════╕
│ Metric                   │    Value │
╞══════════════════════════╪══════════╡
│ TTFT                     │   0.0622 │
├──────────────────────────┼──────────┤
│ TTFT_95                  │   0.0693 │
├──────────────────────────┼──────────┤
│ TOP_5_TTFT               │   0.0757 │
├──────────────────────────┼──────────┤
│ LATENCY                  │   0.4642 │
├──────────────────────────┼──────────┤
│ LATENCY_95               │   0.6452 │
├──────────────────────────┼──────────┤
│ TOP_5_LATENCY            │   0.7156 │
├──────────────────────────┼──────────┤
│ TPOT                     │   0.0265 │
├──────────────────────────┼──────────┤
│ THROUGHPUT               │ 100.162  │
├──────────────────────────┼──────────┤
│ THROUGHPUT_INPUT_TOKENS  │  62.4664 │
├──────────────────────────┼──────────┤
│ THROUGHPUT_OUTPUT_TOKENS │  37.6953 │
├──────────────────────────┼──────────┤
│ RPS                      │   2.154  │
├──────────────────────────┼──────────┤
│ LONGER_THAN_60_LATENCY   │   0      │
├──────────────────────────┼──────────┤
│ LONGER_THAN_120_LATENCY  │   0      │
├──────────────────────────┼──────────┤
│ LONGER_THAN_180_LATENCY  │   0      │
├──────────────────────────┼──────────┤
│ FAILED_REQUESTS          │   0      │
├──────────────────────────┼──────────┤
│ FAILED_REQUESTS_PER_HOUR │   0      │
╘══════════════════════════╧══════════╛

For more information on available commands and options, run:

compressa-perf --help

License

This project is licensed under the MIT License. See the LICENSE file for more details.