vertex-ai-samples
langchain
| vertex-ai-samples | langchain | |
|---|---|---|
| 24 | 152 | |
| 1,358 | 56,526 | |
| 4.0% | - | |
| 9.8 | 10.0 | |
| about 21 hours ago | 9 months ago | |
| Jupyter Notebook | 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.
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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.
vertex-ai-samples
- Gemini 1.5 outshines GPT-4-Turbo-128K on long code prompts, HVM author
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Let's build your first ML app in Google Cloud Run
Google Cloud Platform (GCP) provides a very befitting Machine Learning solution called Vertex Ai that handles Google Cloud's unified platform for building, deploying, and managing machine learning (ML) models. Our goal is to build a simple Machine Learning application that optimizes all that GCP provides plus an implementation of continuous integration and continuous development (CI/CD).
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Google Gemini Pro API Available Through AI Studio
Cross posting some links from another post that HNers found helpful
- https://cloud.google.com/vertex-ai (marketing page)
- https://cloud.google.com/vertex-ai/docs (docs entry point)
- https://console.cloud.google.com/vertex-ai (cloud console)
- https://console.cloud.google.com/vertex-ai/model-garden (all the models)
- https://console.cloud.google.com/vertex-ai/generative (studio / playground)
VertexAI is the umbrella for all of the Google models available through their cloud platform.
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Google Imagen 2
For the peer comments
- https://cloud.google.com/vertex-ai (main page)
- https://cloud.google.com/vertex-ai/docs/start/introduction-u... (docs entry point)
- https://console.cloud.google.com/vertex-ai (cloud console)
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Introducing Gemini: our largest and most capable AI model
Starting on December 13, developers and enterprise customers can access Gemini Pro via the Gemini API in Google AI Studio or Google Cloud Vertex AI.
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How to Use AI/ML Models for Your Projects
Google Cloud Platform (https://cloud.google.com/vertex-ai): Conversely, Google Cloud Platform (GCP) provides a comprehensive suite of AI and machine learning services, including APIs for vision, language, conversation, and structured data analysis. Whether you're analyzing images, interpreting human speech, or diving deep into data patterns, GCP has something for you.
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Create a ChatBot with VertexAI and LibreChat
VertexAI is a machine learning platform available on Google Cloud. It offers a variety of services to train and deploy AI models, including those for Generative AI.
- Tune PaLM 2 with your own RLHF training data
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Any better alternatives to fine-tuning GPT-3 yet to create a custom chatbot persona based on provided knowledge for others to use?
Depending on how much work you want to put into it, you can get started at HuggingFace with their models and datasets, but you'd need compute power, multiple MLOps, etc. I was introduced to the concept in this video, since Google has their Vertex AI tools on Google Cloud, and there's always LangChain but I'm not sure about anything recent.
- Google Cloud Learning Machine
langchain
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🗣️🤖 Ask to your Neo4J knowledge base in NLP & get KPIs
Langchain and the implementation of Custom Tools also is a great (and very efficient) way to setup a dedicated Q&A (for example for chat purpose) agent.
- LangChain – Some quick, high level thoughts on improvements/changes
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Claude 2 Internal API Client and CLI
We're using it via langchain talking to Amazon Bedrock which is hosting Claude 1.x. It's comparable to GPT3.x, not bad. The integration doesn't seem to be fully there though, I think langchain is expecting "Human:" and "AI:", but Claude uses "Assistant:".
https://github.com/hwchase17/langchain/issues/2638
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Any better alternatives to fine-tuning GPT-3 yet to create a custom chatbot persona based on provided knowledge for others to use?
Depending on how much work you want to put into it, you can get started at HuggingFace with their models and datasets, but you'd need compute power, multiple MLOps, etc. I was introduced to the concept in this video, since Google has their Vertex AI tools on Google Cloud, and there's always LangChain but I'm not sure about anything recent.
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langchain VS griptape - a user suggested alternative
2 projects | 11 Jul 20232 projects | 9 Jul 2023
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Vector storage is coming to Meilisearch to empower search through AI
a documentation chatbot proof of concept using GPT3.5 and LangChain
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ChatPDF: What ChatGPT Can't Do, This Can!
I encourage everyone to pay attention to the Langchain open-source project and leverage it to achieve tasks that ChatGPT cannot handle.
- LangChain Arbitrary Command Execution - CVE-2023-34541
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Langchain Is Pointless
Yeah I never know where memory goes exactly in langchain, it's not exactly clear all the time. But sure, the main insight I remember is this, take a look at their MULTI_PROMPT_ROUTER_TEMPLATE: https://github.com/hwchase17/langchain/blob/560c4dfc98287da1...
It's a lot of instructions for an LLM, they seem to forget an LLM is an auto-completion machine, and which data it is trained on. Using <<>> for sections is not a normal thing, it's not markdown, which probably the thing read way more often on the internet, instead of open json comments, why not type signatures, instead of so many rules, why not give it examples? It is an autocomplete machine!
They are relying too much on the LLM being smart because they probably only test stuff in GPT-4 and 3.5, but with GPT4All models this prompt was not working at all, so I had to rewrite it, for simple routing, we don't even need json, carying the `next_inputs` here is weird if you don't need it.
So this is my version of it: https://gist.github.com/rogeriochaves/b67676977eebb1936b9b5c...
It's so basic it's dumb, yet it is more powerful, as it does not rely on GPT-4 level intelligence, it's just what I needed
What are some alternatives?
mlops-with-vertex-ai - An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
awesome-mlops - A curated list of references for MLOps
llama_index - LlamaIndex is a data framework for your LLM applications
MLflow - Open source platform for the machine learning lifecycle
llama - Inference code for Llama models
VevestaX - 2 Lines of code to track ML experiments + EDA + check into Github
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
jina - ☁️ Build multimodal AI applications with cloud-native stack
gpt_index - LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]
rasa - 💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
AutoGPT - AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.