LLM Framework
To build leading AI products driven by Large Language Models with minimal effort.
- Introduces a layer of abstraction between the user and the hardware, significantly simplifying the way of use.
- Built by developers for developers.
- Integrated with knowledge base.
What LLM Framework is?
It is a set of tools and API functions that helps developers create, optimize, and deploy large language models at scale. In general, it simplifies tasks that would otherwise require lots of manual coding and multiple iterations to achieve similar results and solve hardware compatibility issues.
Powered by following models
Accuracy
LLM small
Application
- good for more advanced reasoning and function calling
Features:
- Max context window: 4-8k tokens
Leading languages
Speed
LLM mini
Application
- quite good for chat bot and augmented generation applications
Features
- Max context window: 4k tokens
Leading languages
Cost efficiency
LLM micro
Application
- useful for testing purposes how LLMs work in test environments
Features
- Max context window: 2k tokens
Leading languages
Key functions
Responses API: Supports text inputs, and text outputs. Creates stateful interactions with the model, using the output of previous responses as input. Extends the model’s capabilities with built-in tools for file search, web search, computer use, and more. Allows the model access to external systems and data using function calling.
- Responses API
- Conversations API
Platforms APIs: Creates an embedding vector representing the input text, creates and executes a batch from an uploaded file of requests, creates intermediate uploads object.
- Embeddings
- Batch
- Uploads
Vector stores: Powers semantic search for the retrieval API.
- Vector stores
Chat Completions: Generates a model response from a list of messages comprising a conversation.
- Chat Completions
Use cases
- Customer Support Automation: Enables businesses to create AI-powered chat bots that can handle a wide range of customer queries, reducing response times and freeing up human agents for more complex tasks
- Sentiment Analysis: Analyzes customer feedback and detects sentiment, helping businesses understand customer emotions and tailor their products and services accordingly.
- Demand Forecasting: By analyzing historical data and trends, can help enterprises predict future demand for products and services, enabling better inventory management and resources allocation.
- HR and Recruitment: Can streamline the recruitment process by automating resume screening and candidate shortlisting, reducing time and effort spent on hiring.
- Employee Performance Analysis: Can analyze employee performance data to identify areas of improvement and provide personalized training suggestions.
- Product Recommendations: Can offer personalized product recommendations to customers, increasing sales and customer satisfaction.
- Fraud Detection: By analyzing vast amount of data, can help businesses identify and prevent fraudulent transactions in real-time.
- Supply Chain Optimization: Can optimize supply chain management by identifying inefficiencies, predicting potential disruptions, and suggesting optimal routes.
- Document Analysis: Can analyze large volumes of documents, extracting valuable insights and automating manual data entry tasks.
- Natural Language Processing: Can analyze and process textual data from various sources, such as social media, emails, and news articles.
- Image Recognition: Can be used to automate quality control, detect defects in products, and analyze visual data.
- Financial Analysis: Can analyze financial data to identify trends and generate valuable insights, helping businesses make better-informed investment decisions.
- Personalized Learning: Can create personalized learning plans for employees, helping them acquire new skills and improve their performance.
- Competitive Analysis: By analyzing competitor data, can help businesses identify opportunities and threats, allowing them to stay ahead of the competition.
- Content Generation: Can generate high-quality, human-like content for blogs, articles, and social media posts, saving time and resources.
- Cybersecurity: Can detect and respond to cyber threats in real-time, protecting businesses from data breaches and malicious attacks.
- Market research: By analyzing market data, can help businesses identify trends and consumer preferences, enabling them to make data-driven decisions.
API Reference
LLM framework API is compatible with OpenAI’s API.
See the original OpenAI API reference