LlamaIndex Selectors Integration: NotDiamond
Not Diamond offers an AI-powered model router that automatically determines which LLM is best suited to respond to any query, improving LLM output quality by combining multiple LLMs into a meta-model that learns when to call each LLM.
Not Diamond supports cost and latency tradeoffs, customized router training, and real-time router personalization. Learn more via the documentation.
Installation
pip install llama-index-selectors-notdiamond
Configuration
- API keys: You need API keys from Not Diamond and any LLM you want to use.
Quick Start
import os
from typing import List
from llama_index.core import (
SimpleDirectoryReader,
VectorStoreIndex,
SummaryIndex,
Settings,
)
from llama_index.core.query_engine import RouterQueryEngine
from llama_index.core.tools import QueryEngineTool
from llama_index.selectors.notdiamond.base import NotDiamondSelector
from notdiamond import NotDiamond
# Set up your API keys
os.environ["OPENAI_API_KEY"] = "sk-..."
os.environ["ANTHROPIC_API_KEY"] = "sk-ant-..."
os.environ["NOTDIAMOND_API_KEY"] = "sk-..."
# Create indexes
documents = SimpleDirectoryReader("data/paul_graham").load_data()
nodes = Settings.node_parser.get_nodes_from_documents(documents)
vector_index = VectorStoreIndex.from_documents(documents)
summary_index = SummaryIndex.from_documents(documents)
query_text = "What was Paul Graham's role at Yahoo?"
# Set up Tools for the QueryEngine
list_query_engine = summary_index.as_query_engine(
response_mode="tree_summarize",
use_async=True,
)
vector_query_engine = vector_index.as_query_engine()
list_tool = QueryEngineTool.from_defaults(
query_engine=list_query_engine,
description=(
"Useful for summarization questions related to Paul Graham eassy on"
" What I Worked On."
),
)
vector_tool = QueryEngineTool.from_defaults(
query_engine=vector_query_engine,
description=(
"Useful for retrieving specific context from Paul Graham essay on What"
" I Worked On."
),
)
# Create a NotDiamondSelector and RouterQueryEngine
client = NotDiamond(
api_key=os.environ["NOTDIAMOND_API_KEY"],
llm_configs=["openai/gpt-4o", "anthropic/claude-3-5-sonnet-20240620"],
)
preference_id = client.create_preference_id()
client.preference_id = preference_id
nd_selector = NotDiamondSelector(client=client)
query_engine = RouterQueryEngine(
selector=nd_selector,
query_engine_tools=[
list_tool,
vector_tool,
],
)
# Use Not Diamond to Query Indexes
response = query_engine.query(
"Please summarize Paul Graham's working experience."
)
print(str(response))
Metadata
Release files for llama-index-selectors-notdiamond 0.5.0
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_selectors_notdiamond-0.5.0.tar.gz | 5.8 kB | Without provenance | Details for llama_index_selectors_notdiamond-0.5.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| llama_index_selectors_notdiamond-0.5.0-py3-none-any.whl | Python 3 | none | any | Details for llama_index_selectors_notdiamond-0.5.0-py3-none-any.whl |
Total release size: 11.1 kB
Release files / llama_index_selectors_notdiamond-0.5.0.tar.gz
| Download URL | llama_index_selectors_notdiamond-0.5.0.tar.gz |
|---|---|
| Size | 5.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
cfcace922fa5dcc8aa71985dddfe50a612d1be4013c541546ce90df9737bd131
|
|
BLAKE2b-256 checksum How to use checksums |
8342cb56a3a917a74832170d340caf5a901143f2daceb3166c20a26485a9acff
|
| 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_selectors_notdiamond-0.5.0-py3-none-any.whl
| Download URL | llama_index_selectors_notdiamond-0.5.0-py3-none-any.whl |
|---|---|
| Size | 5.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
c107f0dae36ec3ea14789823d544481210c3cc3b6d97414ded77f0aee2c6d955
|
|
BLAKE2b-256 checksum How to use checksums |
1a367f3d8491883df50bfac8304cad978bdf0d759182e8b31eb47c2f730a8605
|
| 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-selectors-notdiamond 0.5.0
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.