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Llm-app Alternatives
Similar projects and alternatives to llm-app
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pathway
Pathway is an open framework for high-throughput and low-latency real-time data processing.
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Onboard AI
Learn any GitHub repo in 59 seconds. Onboard AI learns any GitHub repo in minutes and lets you chat with it to locate functionality, understand different parts, and generate new code. Use it for free at www.getonboard.dev.
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llm-prompt-testing
Prompt Testing framework for LLMs (specifically OpenAI models). Compute NLP and Responsible AI metrics for each model-generated answer.
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falcongpt
Simple GPT app that uses the falcon-7b-instruct model with a Flask front-end.
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chatgpt-api-python-sales
Find real-time sales with AI-powered Python API using ChatGPT and LLM (Large Language Model) App.
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InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
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llm-app reviews and mentions
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How to use LLMs for real-time alerting
Answering queries and defining alerts: Our application running on Pathway LLM-App exposes the HTTP REST API endpoint to send queries and receive real-time responses. It is used by the Streamlit UI app. Queries are answered by looking up relevant documents in the index, as in the Retrieval-augmented generation (RAG) implementation. Next, queries are categorized for intent: an LLM probes them for natural language commands synonymous with notify or send an alert.
As we have seen in the example of the marketing campaign demo, real-time alerts with LLMs keep the entire team updated on critical changes and help teams stay agile, adjusting strategies as needed. LLM App’s alerting feature can also be used for monitoring model performance when LLMs can occasionally produce unexpected or undesirable outputs. In cases where LLMs are used for processing sensitive data, real-time alerting can be useful for security and compliance too.
- Show HN: Alerting in realtime RAG: spot changes to LLM answers, using few tokens
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How to build a custom GPT enabled full-stack app for real-time data
In this case, you need to build a custom LLM (Language Learning Model) app efficiently to give context to the answer process. A promising approach you find on the internet is utilizing LLMs with vector databases that come with costs like increased prep work, infrastructure, and complexity. Keeping source and vectors in sync is painful. Instead, you can use an open-source LLM App library in Python to implement real-time in-memory data indexing directly reading data from any compatible storage and showing this data on Streamlit UI.
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Show HN: LLM App – build a realtime LLM app in 30 lines, with no vector database
To quickly get to the application sources please go to:
- https://github.com/pathwaycom/llm-app/blob/main/llm_app/path... for the simplest contextless app
- https://github.com/pathwaycom/llm-app/blob/main/llm_app/path... for the default app that builds a reactive index of context documents
- https://github.com/pathwaycom/llm-app/blob/main/llm_app/path... for the contextful app reading data from s3
- https://github.com/pathwaycom/llm-app/blob/main/llm_app/path... for the app using locally available models
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LLM(Large Language Models) for better developer learning of your product
This article explores how LLMs(Large Language Models) and LLM apps such as Pathway can be leveraged for effective and efficient developer education, which can boost the utilization of your product.
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A note from our sponsor - #<SponsorshipServiceOld:0x00007f0f9b656d08>
www.saashub.com | 11 Dec 2023
Stats
pathwaycom/llm-app is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of llm-app is Python.