From 4c37d113cac1f0205294d199c9bb9ad9cf5da7ff Mon Sep 17 00:00:00 2001 From: Dobromir Popov Date: Tue, 26 Mar 2024 23:13:00 +0200 Subject: [PATCH 1/2] text segmentation prompt --- _doc/_notes/PROMPTS.md | 8 ++++++++ 1 file changed, 8 insertions(+) create mode 100644 _doc/_notes/PROMPTS.md diff --git a/_doc/_notes/PROMPTS.md b/_doc/_notes/PROMPTS.md new file mode 100644 index 0000000..fcdaa54 --- /dev/null +++ b/_doc/_notes/PROMPTS.md @@ -0,0 +1,8 @@ +You are an expert in extracting new information from text sorting it out in existing categories or creating new categoty (We're using Neo4j as graph database). +This is multi-step process: +1. Divide the text into paragraph simmilar chunks that have the same toppic. Add a summary to the paragraph. +2. Create Memory object for each summary +3. Extract facts from each paragraph and add them as knowledge linked to the paragraph as separate memory object linked to the first one. Look into verbs, ajectives and nouns to extract the plain information from the text. If there is a source code, do not interpret it, but remember it as linked Memory as it is, while adding summary and link it to the main "Memory". +4. Assign possible category and scientific field labels to the information by adding them as tags. +This systematization and segmentation will allow you to remember the text and store it in your long-term memory as knowledge graph, while providing easy access later. Respond in json format with the extracted and restructured data. +Here's the source text: From 3ad33c96654fd5603e3e821aa3128586f012acac Mon Sep 17 00:00:00 2001 From: Dobromir Popov Date: Sun, 7 Apr 2024 17:26:58 +0300 Subject: [PATCH 2/2] devika test prompt --- _doc/_notes/PROMPTS.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/_doc/_notes/PROMPTS.md b/_doc/_notes/PROMPTS.md index fcdaa54..3b7bf8f 100644 --- a/_doc/_notes/PROMPTS.md +++ b/_doc/_notes/PROMPTS.md @@ -6,3 +6,8 @@ This is multi-step process: 4. Assign possible category and scientific field labels to the information by adding them as tags. This systematization and segmentation will allow you to remember the text and store it in your long-term memory as knowledge graph, while providing easy access later. Respond in json format with the extracted and restructured data. Here's the source text: + + + +------------ +create a web app that has a button to start recording sends it to latest whisper llm for STT, translates it to target language and shows the result in realtime. it should be streaming text with minimal lag. \ No newline at end of file