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Updated Ollama part of local deployment (#1066)

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### What problem does this PR solve?

#720 

### Type of change

- [x] Documentation Update
This commit is contained in:
writinwaters
2024-06-07 09:06:46 +08:00
committed by GitHub
parent 722c342d56
commit f65d6a957b
6 changed files with 138 additions and 55 deletions
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21
docs/quickstart.mdx
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@@ -18,10 +18,10 @@ This quick start guide describes a general process from:
## Prerequisites
- CPU >= 4 cores
- RAM >= 16 GB
- Disk >= 50 GB
- Docker >= 24.0.0 & Docker Compose >= v2.26.1
- CPU ≥ 4 cores
- RAM ≥ 16 GB
- Disk ≥ 50 GB
- Docker ≥ 24.0.0 & Docker Compose ≥ v2.26.1
> If you have not installed Docker on your local machine (Windows, Mac, or Linux), see [Install Docker Engine](https://docs.docker.com/engine/install/).
@@ -30,11 +30,11 @@ This quick start guide describes a general process from:
This section provides instructions on setting up the RAGFlow server on Linux. If you are on a different operating system, no worries. Most steps are alike.
<details>
<summary>1. Ensure <code>vm.max_map_count</code> >= 262144:</summary>
<summary>1. Ensure <code>vm.max_map_count</code> &ge; 262144:</summary>
`vm.max_map_count`. This value sets the the maximum number of memory map areas a process may have. Its default value is 65530. While most applications require fewer than a thousand maps, reducing this value can result in abmornal behaviors, and the system will throw out-of-memory errors when a process reaches the limitation.
RAGFlow v0.7.0 uses Elasticsearch for multiple recall. Setting the value of `vm.max_map_count` correctly is crucial to the proper functioning the Elasticsearch component.
RAGFlow v0.7.0 uses Elasticsearch for multiple recall. Setting the value of `vm.max_map_count` correctly is crucial to the proper functioning of the Elasticsearch component.
<Tabs
defaultValue="linux"
@@ -168,7 +168,9 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
5. In your web browser, enter the IP address of your server and log in to RAGFlow.
> - With default settings, you only need to enter `http://IP_OF_YOUR_MACHINE` (**sans** port number) as the default HTTP serving port `80` can be omitted when using the default configurations.
:::caution WARNING
With default settings, you only need to enter `http://IP_OF_YOUR_MACHINE` (**sans** port number) as the default HTTP serving port `80` can be omitted when using the default configurations.
:::
## Configure LLMs
@@ -188,7 +190,7 @@ To add and configure an LLM:
1. Click on your logo on the top right of the page **>** **Model Providers**:
![2 add llm](https://github.com/infiniflow/ragflow/assets/93570324/10635088-028b-4b3d-add9-5c5a6e626814)
![add llm](https://github.com/infiniflow/ragflow/assets/93570324/10635088-028b-4b3d-add9-5c5a6e626814)
> Each RAGFlow account is able to use **text-embedding-v2** for free, a embedding model of Tongyi-Qianwen. This is why you can see Tongyi-Qianwen in the **Added models** list. And you may need to update your Tongyi-Qianwen API key at a later point.
@@ -286,4 +288,5 @@ Conversations in RAGFlow are based on a particular knowledge base or multiple kn
![question1](https://github.com/infiniflow/ragflow/assets/93570324/bb72dd67-b35e-4b2a-87e9-4e4edbd6e677)
![question2](https://github.com/infiniflow/ragflow/assets/93570324/7cc585ae-88d0-4aa2-817d-0370b2ad7230)
![question2](https://github.com/infiniflow/ragflow/assets/93570324/7cc585ae-88d0-4aa2-817d-0370b2ad7230)import { resetWarningCache } from 'prop-types';