LLMFlow
FreeSimple, Explicit and Transparent LLM Apps 
FreeFree tier
Inputs: textOutputs: text
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About LLMFlow
LLMFlows is an open-source Python framework for building simple, explicit, and transparent LLM applications. It provides minimal abstractions like LLM wrappers, prompt templates, chat LLM support, and flow classes to create well-structured apps such as chatbots, question-answering systems, and agents. The framework ensures full transparency by eliminating hidden prompts or LLM calls, making monitoring, maintenance, and debugging easier. It integrates with vector stores like Pinecone and is designed to give developers complete control over their LLM-powered workflows.
Key Features
Minimalistic set of abstractions for building LLM apps
LLM wrappers for OpenAI APIs with retry and formatting
PromptTemplate class for dynamic prompt generation
Chat LLM support with conversation history handling
Flow and FlowStep classes for constructing complex LLM pipelines
Explicit API with no hidden prompts or LLM calls
Traceable flows for full transparency and debugging
Integration with vector stores like Pinecone
Easy installation via pip
Comprehensive documentation and examples
Pros & Cons
Pros
- Simple and well-documented framework with minimal abstractions
- Explicit API ensures clean, readable code and full control
- Complete transparency with traceable flows per component
- Easy to monitor, maintain, and debug applications
- Open source and free to use
- Supports both regular LLMs and chat-based LLMs
Cons
- Primarily supports OpenAI's API; limited to a single provider out of the box
- Documentation and community resources are still growing
- Not as feature-rich as larger frameworks like LangChain or LlamaIndex
- Requires basic understanding of Python and LLM concepts
Best For
Building chatbots with structured conversation flowsDeveloping question-answering systems using LLMs and vector storesCreating AI agents with explicit, traceable stepsPowering educational or explanatory apps (e.g., LLM-99 demo)Rapid prototyping of any LLM-powered application
FAQ
What is LLMFlows?
LLMFlows is an open-source Python framework for building simple, explicit, and transparent LLM applications. It provides minimalistic abstractions such as LLM wrappers, prompt templates, chat LLMs, and flows to create well-structured apps.
Is LLMFlows free?
Yes, LLMFlows is completely free and open source under the MIT License.
What LLM providers does LLMFlows support?
Currently, LLMFlows wraps the OpenAI API, including both regular completions and chat models. Integration with other providers is not documented but may be added in the future.
How does LLMFlows ensure transparency?
LLMFlows provides traceable flows where each component (LLM call, prompt, etc.) has complete information, making it easy to monitor, maintain, and debug. There are no hidden prompts or LLM calls.