kiri 0.3.4

Kiri Natural Language Engine

Kiri Natural Language Engine

Kiri Natural Language Engine is a high level Python library that makes using state-of-the-art language models easy, accessible and scalable.

With Kiri, no experience in AI is needed to solve valuable real world problems using:

• Semantic search (for ecommerce, documentation, etc.)
• Conversational question answering (for FAQ chatbots, text analysis, etc.)
• Zero-shot classification (for email sorting, intent detection, etc.)
• Summarisation (TLDRs for long documents)
• Emotion detection (for customer satisfaction, text analysis, etc.)

Run everything locally or take your code to production using our free, optimised inference API.

⚡ Getting started	Installation, few minute introduction
💡 Examples	Sample problems solved using Kiri
📙 Docs	In-depth documentation for advanced usage

Getting started

Installation

Install Kiri via PyPi:

pip install kiri

Basic usage

from kiri import Kiri, Document

# Unprocessed documents
documents = [
    Document("Look at examples to see awesome use cases!"),
    Document("Check out the docs to see what's possible!")
]

# Use our inference API
kiri = Kiri(api_key="abc")
# Or run locally
kiri = Kiri(local=True)

# Process documents
kiri.upload(documents)

# Start building!
search_results = kiri.search("What are some cool apps that have been built?")

print(search_results.to_json())

# Prints
{
   "max_score": 0.3804888461635889,
   "total_results": 2,
   "results": [
      {
         "document": {
            "id":"LzhtWcpV2eoMk8GJwaw7na",
            "content":"Look at examples to see awesome use cases!"
         },
         "score": 0.3804888461635889,
         "preview":" Look at examples to see awesome use cases!"
      },
      {
         "document": {
            "id":"bcLb8xUK585Zm6rZrwj89A",
            "content":"Check out the docs to see what's possible!"
         },
         "score": 0.1742559312454076,
         "preview":" Check out the docs to see what's possible!"
      }
   ]
}

Why Kiri?

1. No experience needed

   • Entrance to practical AI should be simple
   • Get state-of-the-art performance in your task without being an expert

2. There is an overwhelming amount of models

   • We implement the best ones for various use cases
   • A few general models can accomplish more with less optimisation

3. Deploying models cost effectively is hard work

   • If our models suit your use case, no deployment is needed
   • Our API scales, is always available, and you only pay for usage

Examples

Take a look at the examples folder.

Documentation

Check out our docs.