fireworks-ai
The official Python library for the fireworks API
Decision gist · record as of 2026-08-14
Yes. The SDK is actively maintained (released 2 days ago), has low install friction, supports modern Python versions, carries a permissive Apache-2.0 license, and provides a well-typed, production-ready interface to Fireworks' API. No known vulnerabilities. Install it if you need to integrate Fireworks' LLM services into a Python application.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a valid FIREWORKS_API_KEY environment variable or explicit api_key parameter to authenticate with the Fireworks API.
- Low friction: pure Python wheel with 8 runtime dependencies (aiohttp, httpx, pydantic, and others) all widely maintained.
- Active maintenance—released 2 days ago with last commit 2026-08-14.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions. Safe for proprietary projects.
last release 2026-08-12 (2 days) · last repo commit 2026-08-14 · 10 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 4,447,706 downloads/mo, #2,300 on PyPI
Alternatives
Verify before relying
pip install fireworks-ai
import os
from fireworks import Fireworks
client = Fireworks(api_key=os.environ.get("FIREWORKS_API_KEY"))
completion = client.chat.completions.create(
messages=[{"role": "user", "content": "How do LLMs work?"}],
model="accounts/fireworks/models/kimi-k2-instruct-0905",
)
print(completion.choices[0].message.content)- Whether the optional [training] extra (for GRPO/DPO) is stable and production-ready on Python 3.11+
- Rate limits and quota behavior for the Fireworks API endpoints
- Performance characteristics of the async client under high concurrency
What it is and what it does
Fireworks AI is the official Python SDK for accessing Fireworks' REST API, enabling developers to call LLM inference endpoints and manage training jobs from Python applications. It provides both synchronous (httpx-based) and asynchronous (aiohttp-based) clients with full type hints, Pydantic response models, and automatic pagination support. The library handles authentication via API keys, supports streaming responses over Server-Sent Events, and includes convenience methods for common operations like chat completions, batch inference, and dataset management.
The SDK is actively maintained, supports modern Python versions (3.9–3.14), and has low install friction with standard HTTP and async dependencies. It is auto-generated by Stainless for API consistency, with the exception of training-specific code in src/fireworks/training/. Optional training extras are available for GRPO/DPO workflows on Python 3.11+, though training-scoped API keys are required for those features.
Use it for
- Build chat applications or LLM-powered services by calling Fireworks' hosted models via the chat completions API.
- Stream real-time LLM responses in web applications or CLIs using Server-Sent Events.
- Manage fine-tuning and training jobs (GRPO/DPO) with the optional training SDK on Python 3.11+.
- Automate batch inference workloads by submitting and monitoring batch inference jobs.
- Paginate through large result sets (datasets, jobs, deployments) without manual page handling.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The SDK is actively maintained (released 2 days ago), has low install friction, supports modern Python versions, carries a permissive Apache-2.0 license, and provides a well-typed, production-ready interface to Fireworks' API. No known vulnerabilities. Install it if you need to integrate Fireworks' LLM services into a Python application.
Install
fireworks-ai on PyPI
Before you install
Low friction: pure Python wheel with 8 runtime dependencies (aiohttp, httpx, pydantic, and others) all widely maintained. Active maintenance—released 2 days ago with last commit 2026-08-14. Supports Python 3.9 through 3.14.
Requires a valid FIREWORKS_API_KEY environment variable or explicit api_key parameter to authenticate with the Fireworks API.
License in practice
Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions. Safe for proprietary projects.
Quickstart
pip install fireworks-ai
import os
from fireworks import Fireworks
client = Fireworks(api_key=os.environ.get("FIREWORKS_API_KEY"))
completion = client.chat.completions.create(
messages=[{"role": "user", "content": "How do LLMs work?"}],
model="accounts/fireworks/models/kimi-k2-instruct-0905",
)
print(completion.choices[0].message.content)Verify before relying
- Whether the optional [training] extra (for GRPO/DPO) is stable and production-ready on Python 3.11+
- Rate limits and quota behavior for the Fireworks API endpoints
- Performance characteristics of the async client under high concurrency
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 8 packagesaiohttpanyiodistrohttpx-aiohttphttpxpydanticsniffiotyping-extensions |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 4,447,706 / month, #2,300 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: OS IndependentOperating System :: POSIXOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries :: Python ModulesTyping :: Typed |
Evidence: fireworks_ai-1.2.9-py3-none-any.whl
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See also mistralai · sambanova · langchain-fireworks · writer-sdk · perplexityai · llama-api-client · cerebras-cloud-sdk · llama-stack-client · hiddenlayer-sdk · FireWorks