LlamaIndex Embeddings Integration: Fireworks
This integration provides support for Fireworks AI embedding models with LlamaIndex.
Fireworks AI offers fast and efficient inference for embedding models. Sign up at fireworks.ai to get an API key.
Installation
pip install llama-index-embeddings-fireworks
Usage
from llama_index.embeddings.fireworks import FireworksEmbedding
# Initialize the embedding model
embed_model = FireworksEmbedding(
api_key="your-api-key", # or set FIREWORKS_API_KEY env var
model_name="nomic-ai/nomic-embed-text-v1.5",
)
# Get embedding for a single text
embedding = embed_model.get_text_embedding("Hello, world!")
# Get embeddings for multiple texts
embeddings = embed_model.get_text_embedding_batch(
["Hello, world!", "How are you?"]
)
# Get query embedding
query_embedding = embed_model.get_query_embedding("What is machine learning?")
Configuration
| Parameter | Description | Default |
|---|---|---|
api_key |
Fireworks API key (or set FIREWORKS_API_KEY env var) |
None |
model_name |
Embedding model to use | nomic-ai/nomic-embed-text-v1.5 |
dimensions |
Output embedding dimensions (if supported by model) | None |
embed_batch_size |
Batch size for embedding requests | 10 |
timeout |
Request timeout in seconds | 60.0 |
max_retries |
Maximum number of retries | 10 |
Environment Variables
FIREWORKS_API_KEY: Your Fireworks API keyFIREWORKS_API_BASE: Custom API base URL (optional)
1 maintainer
Metadata
1 maintainer
Release files for llama-index-embeddings-fireworks 0.6.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| llama_index_embeddings_fireworks-0.6.0.tar.gz | 4.5 kB | Without provenance | Details for llama_index_embeddings_fireworks-0.6.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| llama_index_embeddings_fireworks-0.6.0-py3-none-any.whl | Python 3 | none | any | Details for llama_index_embeddings_fireworks-0.6.0-py3-none-any.whl |
Total release size: 9.1 kB
Release files / llama_index_embeddings_fireworks-0.6.0.tar.gz
| Download URL | llama_index_embeddings_fireworks-0.6.0.tar.gz |
|---|---|
| Size | 4.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
bb43788402fed87d0c027e50457d99b44d76827c8e1f461dc497afa30148474c
|
|
BLAKE2b-256 checksum How to use checksums |
8366caf98e19cfb2965ea1c3b263b8cd6bac97eb5f1dcf4f11bd1f4c839868a5
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.12.7 {"installer":{"name":"uv","version":"0.12.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Release files / llama_index_embeddings_fireworks-0.6.0-py3-none-any.whl
| Download URL | llama_index_embeddings_fireworks-0.6.0-py3-none-any.whl |
|---|---|
| Size | 4.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
d08449d634d74d1b1f37d36e1fb5621b18a15cfb817beb86e28e29c6ea076c53
|
|
BLAKE2b-256 checksum How to use checksums |
d7b872ffbff63f2fc0e4b5c2dfad2292e149d449391a8a8db762fc39f2862dd0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.12.7 {"installer":{"name":"uv","version":"0.12.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Security for llama-index-embeddings-fireworks 0.6.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
