796c33f1a6
* Update README.md * fix: 'ollama run' should be 'ollama pull' * fix: linting, syntax, spelling corrections for all docs * fix: markdown linting rules and missed fixes * fix: readded space to block * fix: changed sh blocks to text * docs: added exception for bare urls in markdown * docs: added exception for in-line html (MD033/no-inline-html) * docs: made python indentation level consistent (4 space tabs) even though I prefer 2. --------- Co-authored-by: Charles Packer <packercharles@gmail.com>
55 lines
3.5 KiB
Markdown
55 lines
3.5 KiB
Markdown
---
|
|
title: Ollama
|
|
excerpt: Setting up MemGPT with Ollama
|
|
category: 6580da9a40bb410016b8b0c3
|
|
---
|
|
|
|
> ⚠️ Make sure to use tags when downloading Ollama models!
|
|
>
|
|
> Don't do **`ollama pull dolphin2.2-mistral`**, instead do **`ollama pull dolphin2.2-mistral:7b-q6_K`**.
|
|
>
|
|
> If you don't specify a tag, Ollama may default to using a highly compressed model variant (e.g. Q4). We highly recommend **NOT** using a compression level below Q5 when using GGUF (stick to Q6 or Q8 if possible). In our testing, certain models start to become extremely unstable (when used with MemGPT) below Q6.
|
|
|
|
1. Download + install [Ollama](https://github.com/jmorganca/ollama) and the model you want to test with
|
|
2. Download a model to test with by running `ollama pull <MODEL_NAME>` in the terminal (check the [Ollama model library](https://ollama.ai/library) for available models)
|
|
|
|
For example, if we want to use Dolphin 2.2.1 Mistral, we can download it by running:
|
|
|
|
```sh
|
|
# Let's use the q6_K variant
|
|
ollama pull dolphin2.2-mistral:7b-q6_K
|
|
```
|
|
|
|
```sh
|
|
pulling manifest
|
|
pulling d8a5ee4aba09... 100% |█████████████████████████████████████████████████████████████████████████| (4.1/4.1 GB, 20 MB/s)
|
|
pulling a47b02e00552... 100% |██████████████████████████████████████████████████████████████████████████████| (106/106 B, 77 B/s)
|
|
pulling 9640c2212a51... 100% |████████████████████████████████████████████████████████████████████████████████| (41/41 B, 22 B/s)
|
|
pulling de6bcd73f9b4... 100% |████████████████████████████████████████████████████████████████████████████████| (58/58 B, 28 B/s)
|
|
pulling 95c3d8d4429f... 100% |█████████████████████████████████████████████████████████████████████████████| (455/455 B, 330 B/s)
|
|
verifying sha256 digest
|
|
writing manifest
|
|
removing any unused layers
|
|
success
|
|
```
|
|
|
|
In your terminal where you're running MemGPT, run `memgpt configure` to set the default backend for MemGPT to point at Ollama:
|
|
|
|
```sh
|
|
# if you are running Ollama locally, the default IP address + port will be http://localhost:11434
|
|
# IMPORTANT: with Ollama, there is an extra required "model name" field
|
|
? Select LLM inference provider: local
|
|
? Select LLM backend (select 'openai' if you have an OpenAI compatible proxy): ollama
|
|
? Enter default endpoint: http://localhost:11434
|
|
? Enter default model name (required for Ollama, see: https://memgpt.readme.io/docs/ollama): dolphin2.2-mistral:7b-q6_K
|
|
...
|
|
```
|
|
|
|
If you have an existing agent that you want to move to the Ollama backend, add extra flags to `memgpt run`:
|
|
|
|
```sh
|
|
# use --model to switch Ollama models (always include the full Ollama model name with the tag)
|
|
# use --model-wrapper to switch model wrappers
|
|
memgpt run --agent your_agent --model dolphin2.2-mistral:7b-q6_K --model-endpoint-type ollama --model-endpoint http://localhost:11434
|
|
```
|