- llm-python VS gpt-vector-agent
- llm-python VS learning-llms-and-genai-for-dev-sec-ops
- llm-python VS langcorn
- llm-python VS pandas-ai
- llm-python VS Large-Language-Models-Tutorial
- llm-python VS sample-agentic-frameworks-on-aws
- llm-python VS ProTaska-GPT
- llm-python VS OSGPT
- llm-python VS langchain-chatbot
- llm-python VS rag-implementation-for-own-data
Llm-python Alternatives
Similar projects and alternatives to llm-python
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gpt-vector-agent
🧩 Interfacing with different LLMs-chains, vectorstore databases, and autonomous agents.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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learning-llms-and-genai-for-dev-sec-ops
A set of lessons aimed at anyone learning LLM and generative AI concepts, with sections on operations and security, as well as development.
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pandas-ai
Discontinued Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG. [Moved to: https://github.com/Sinaptik-AI/pandas-ai] (by gventuri)
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sample-agentic-frameworks-on-aws
Build Agentic AI solutions on AWS, using latest OSS Agentic Frameworks.
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ProTaska-GPT
Unleash the Potential of Datasets with Intelligent Tasks, Tutorials, and Algorithm Recommendations.
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OSGPT
OSGPT is a powerful plugin designed to dynamically load documents from specified folders and create searchable vector databases. Not only does it offer a quick way to query from your documents, but it also allows you to execute CLI commands on the host system, be it Linux/Unix or Windows.
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langchain-chatbot
Discontinued AI Chatbot for analyzing/extracting information from data in conversational format.
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rag-implementation-for-own-data
RAG workflow using your own documents, Chroma vector storage, Gemini embeddings, and a local Docker-served LLM for offline-style inference
llm-python discussion
llm-python reviews and mentions
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Using LLMs without Burning Dollars - Different Database Query Strategies
Another sophisticated technique is to let the LLMs generate code to break down a question into multiple queries or API calls. This is a very natural way of solving complicated questions and unleashes the power of combining natural-language and underlying code.
Stats
onlyphantom/llm-python is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of llm-python is Jupyter Notebook.