promptlayer
PromptLayer is a platform for prompt engineering and tracks your LLM requests.
Decision gist · record as of 2026-08-14
Yes, if you use LLMs in production and want centralized prompt management, request logging, and observability. The SDK is actively maintained, has low install friction, and integrates cleanly with major LLM providers via proxy or OpenTelemetry instrumentation. Requires a PromptLayer account and API key. No known vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a PromptLayer API key from https://www.promptlayer.com (set via api_key parameter or PROMPTLAYER_API_KEY environment variable).
- Low install friction with a pure-Python wheel.
- Active maintenance with a release 7 days ago and recent commits.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions.
last release 2026-08-07 (7 days) · last repo commit 2026-08-13 · 782 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 431,862 downloads/mo, #6,713 on PyPI
Alternatives
Verify before relying
pip install promptlayer
from promptlayer import PromptLayer
pl = PromptLayer(api_key="pl_xxxxx")
prompt = pl.templates.get("support-reply", {"input_variables": {"customer_name": "Ada"}})
print(prompt["prompt_template"])- Whether the 13 runtime dependencies (aiohttp, httpx, opentelemetry-*, etc.) are all required for basic usage or only for optional features like tracing.
- Performance characteristics when caching is enabled via cache_ttl_seconds parameter.
- Detailed behavior of throw_on_error=False when API errors occur.
What it is and what it does
PromptLayer is a Python SDK that connects your application to the PromptLayer platform for prompt engineering, versioning, and LLM observability. It provides a client interface to retrieve and manage prompt templates, log LLM requests, and optionally auto-instrument OpenAI, Anthropic, Google GenAI, and AWS Bedrock SDKs with OpenTelemetry tracing. Both sync and async APIs are available.
The package acts as a proxy around supported provider SDKs, allowing you to send requests through PromptLayer for logging and monitoring without rewriting your code. It includes utilities for template caching, request annotation, group organization, and skill management. When tracing is enabled, spans are exported to PromptLayer using OpenTelemetry, providing visibility into prompt execution and LLM provider calls across your application.
Use it for
- Retrieve and version-control prompt templates from PromptLayer for use in production applications.
- Auto-instrument OpenAI or Anthropic SDK calls to log and monitor all LLM requests without modifying provider client code.
- Export OpenTelemetry spans from your own functions and LLM provider calls to PromptLayer for centralized tracing and debugging.
- Test and evaluate prompt variations using PromptLayer's evals and regression sets via the SDK.
- Organize and annotate LLM requests with metadata, scores, and group associations for analysis and monitoring.
- Set up coding agents (Cursor, Claude Code) with PromptLayer docs and evaluation skills via the setup command.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you use LLMs in production and want centralized prompt management, request logging, and observability.
The SDK is actively maintained, has low install friction, and integrates cleanly with major LLM providers via proxy or OpenTelemetry instrumentation. Requires a PromptLayer account and API key. No known vulnerabilities.
Install
promptlayer on PyPI
Before you install
Low install friction with a pure-Python wheel. Active maintenance with a release 7 days ago and recent commits. Supports Python 3.9 through 3.14.
Requires a PromptLayer API key from https://www.promptlayer.com (set via api_key parameter or PROMPTLAYER_API_KEY environment variable).
License in practice
Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions.
Quickstart
pip install promptlayer
from promptlayer import PromptLayer
pl = PromptLayer(api_key="pl_xxxxx")
prompt = pl.templates.get("support-reply", {"input_variables": {"customer_name": "Ada"}})
print(prompt["prompt_template"])Verify before relying
- Whether the 13 runtime dependencies (aiohttp, httpx, opentelemetry-*, etc.) are all required for basic usage or only for optional features like tracing.
- Performance characteristics when caching is enabled via cache_ttl_seconds parameter.
- Detailed behavior of throw_on_error=False when API errors occur.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <4.0,>=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 13 packagesaiohttpcachetoolscentrifuge-pythonhttpxjinja2nest-asyncioopenrouteropentelemetry-apiopentelemetry-exporter-otlp-proto-httpopentelemetry-sdkrequestsrichtenacity |
| Maintenance | Actively maintained 7 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 431,862 / month, #6,713 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9 |
Evidence: promptlayer-1.5.14-py3-none-any.whl
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