code-interpreter
DocsGPT
code-interpreter | DocsGPT | |
---|---|---|
14 | 35 | |
583 | 14,208 | |
62.6% | 1.0% | |
9.3 | 9.8 | |
1 day ago | 6 days ago | |
Python | Python | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
code-interpreter
- Open-source secure sandboxes for AI code execution
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Open-source SDK for adding custom code interpreters to AI apps
Hey everyone! I'm the CEO of the company that built this SDK.
We're a company called E2B [0]. We're building and open-source [1] secure environments for running untrusted AI-generated code and AI agents. We call these environments sandboxes and they are built on top of micro VM called Firecracker [2]. We specifically decided to use Firecrackers instead of containers because of their security and ability to do snapshots.
You can think of us as giving small cloud computers to LLMs.
We recently created a dedicated SDK for building custom code interpreters in Python or JS/TS. We saw this need after a lot of our users have been adding code execution capabilities to their AI apps with our core SDK [3]. These use cases were often centered around AI data analysis so code interpreter-like behavior made sense
The way our code interpret SDK works is by spawning an E2B sandbox with Jupyter Server. We then communicate with this Jupyter server through Jupyter Kernel messaging protocol [4]. We work with an LLM and AI framework. We have different examples on how to use the SDK with Llama models, Anthropic models, LangChain, LangGraph, and more in our cookbook [5].
We don't do any wrapping around LLM, any prompting, or any agent-like framework. We leave all of that to our users. We're really just a boring code execution layer that sits at the bottom. We're building for the future software that will be building another software.
Our long-term plan is to build an automated AWS for AI apps and agents where AI can build and deploy its own software while giving developers powerful observability into what's happening inside our sandboxes. With everything being open-source.
Happy to answer any questions and hear feedback!
[0] https://e2b.dev
[1] https://github.com/e2b-dev
[2] https://github.com/firecracker-microvm/firecracker
[3] https://e2b.dev/docs
[4] https://jupyter-client.readthedocs.io/en/latest/messaging.ht...
[5] https://github.com/e2b-dev/e2b-cookbook
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Ask HN: Who is hiring? (May 2024)
E2B | https://e2b.dev | San Francisco, CA | Full-time | In-person
[E2B](https://e2b.dev) is building a secure open-source runtime that will power next billion of AI apps & agents.
We found an early traction with making it easy for developers to add [code interpreting](https://github.com/e2b-dev/code-interpreter) to their AI apps with our SDK built on top of our [agentic runtime](https://github.com/e2b-dev/e2b). We have paying customers from seed to enterprise companies.
We're hiring:
- Frontend/Product Engineer
- Infrastructure Engineer
Check the roles here https://e2b.dev/careers
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Llama 3 with Function Calling and Code Interpreter
We will show how to build a code interpreter with Llama 3 on Groq, and powered by open-source Code Interpreter SDK by E2B. The E2B Code Interpreter SDK quickly creates a secure cloud sandbox powered by Firecracker. Inside this sandbox is a running Jupyter server that the LLM can use.
- Show HN: Open-source SDK for creating custom code interpreters with any LLM
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Show HN: Add AI code interpreter to any LLM via SDK
Hi, I'm the CEO of the company that built this SDK.
We're a company called E2B [0]. We're building and open-source [1] secure environments for running untrusted AI-generated code and AI agents. We call these environments sandboxes and they are built on top of micro VM called Firecracker [2].
You can think of us as giving small cloud computers to LLMs.
We recently created a dedicated SDK for building custom code interpreters in Python or JS/TS. We saw this need after a lot of our users have been adding code execution capabilities to their AI apps with our core SDK [3]. These use cases were often centered around AI data analysis so code interpreter-like behavior made sense
The way our code interpret SDK works is by spawning an E2B sandbox with Jupyter Server. We then communicate with this Jupyter server through Jupyter Kernel messaging protocol [4].
We don't do any wrapping around LLM, any prompting, or any agent-like framework. We leave all of that on users. We're really just a boring code execution layer that sats at the bottom that we're building specifically for the future software that will be building another software. We work with any LLM. Here's how we added code interpreter to Claude [5].
Our long-term plan is to build an automated AWS for AI apps and agents.
Happy to answer any questions and hear feedback!
[0] https://e2b.dev/
[1] https://github.com/e2b-dev
[2] https://github.com/firecracker-microvm/firecracker
[3] https://e2b.dev/docs
[4] https://jupyter-client.readthedocs.io/en/latest/messaging.ht...
[5] https://github.com/e2b-dev/e2b-cookbook/blob/main/examples/c...
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Open Source Python Code Interpreter for Any LLM
These use cases were often centered around AI data analysis so code interpreter-like behavior made sense
The way our code interpret SDK works is by spawning an E2B sandbox with Jupyter Server. We then communicate with this Jupyter server through Jupyter Kernel messaging protocol [4]
We don't do any wrapping around LLM, any prompting, or any agent-like framework. We leave all of that on users. We're really just a boring code execution layer that sats at the bottom that we're building specifically for the future software that will be building another software.
Our long-term plan is to build an automated AWS for AI apps and agents.
Happy to answer any questions and hear feedback!
[0] https://e2b.dev/
DocsGPT
- You can earn free shirt by contributing to DocsGPT
- GPT-powered chat for documentation (fully local)
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DocsGPT Live: building extensions and discussing fine tuning
Github: https://github.com/arc53/DocsGPT
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Large documents reader engine
chatpdf.com often comes up in the comments. It works pretty well, but obviously a chat is limited with the content of a single document, it doesn't match the information. You need an API key to test it. I'm looking for a similar project to host locally, tested many projects but still searching. I tried https://github.com/arc53/docsgpt and got decent results but not enough citation references.
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Free GPT-4 platform to train custom AI models + voice conversations
I briefly tried DocsGPT, but it appeared to be broken and ignore the given documents, acting like a normal GPT chatbot.
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Is there an easy way to "upload" textbooks/standards/manuals, etc into ChatGPT?
https://github.com/arc53/docsgpt. This should do it.
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LlamaIndex
DocsGPT: https://github.com/arc53/DocsGPT (hosting locally with manifest) (live preview with openai)
- Can someone suggest way to feed developer docs into gpt? Planning to launch chatgpt search for our developer docs
- How to use embeddings to query PDF doucments using NLP
- Open source tool to Chat with your documents (PDF, Markdown, RST, TXT)
What are some alternatives?
MindsDB - The platform for customizing AI from enterprise data
llama_index - LlamaIndex is a data framework for your LLM applications
E2B - Secure cloud runtime for AI apps & AI agents. Fully open-source.
llama - Inference code for Llama models
awesome-ai-agents - A list of AI autonomous agents
yolov7-segmentation-with-DeepSORT-Tracking - YOLOv7 Segmentation using OpenCV and PyTorch with DeepSORT Tracking (ID + TRAILS)
e2b-cookbook - Examples and guides for using the E2B API
devdocs - API Documentation Browser
infra - Infrastructure powering E2B - Secure Runtime for AI Agents & Apps
localsend - An open-source cross-platform alternative to AirDrop
jobs - Jobs @ Clusterfudge
Open-Assistant - OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.