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roll back readme (revert me when pypi package is updated)

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Vivian Fang
2023-10-24 00:56:48 -07:00
parent f80a9bbcc1
commit 8bc81ff12d
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README.md
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@@ -71,15 +71,10 @@ Memory-GPT (or MemGPT in short) is a system that intelligently manages different
## Running MemGPT locally
Install MemGPT:
Install dependencies:
```sh
pip install pymemgpt
```
To update the package, run
```sh
pip install pymemgpt -U
pip install -r requirements.txt
```
Add your OpenAI API key to your environment:
@@ -94,37 +89,12 @@ export OPENAI_API_KEY=YOUR_API_KEY
set OPENAI_API_KEY=YOUR_API_KEY
```
To run MemGPT for as a conversation agent in CLI mode, simply run `memgpt`:
To run MemGPT for as a conversation agent in CLI mode, simply run `main.py`:
```sh
memgpt
python3 main.py
```
<details>
<summary><strong>Debugging command not found</strong></summary>
If you get `command not found` (Linux/MacOS), or a `CommandNotFoundException` (Windows), the directory where pip installs scripts is not in your PATH. You can either add that directory to your path (`pip show pip | grep Scripts`) or instead just run:
```sh
python -m memgpt
```
</details>
<details>
<summary><strong>Building from source</strong></summary>
Clone this repo: `git clone https://github.com/cpacker/MemGPT.git`
Using poetry:
1. Install poetry: `pip install poetry`
2. Run `poetry install`
3. Run `poetry run memgpt`
Using pip:
1. Run `pip install -e .`
2. Run `python3 main.py`
</details>
If you're using Azure OpenAI, set these variables instead:
```sh
@@ -135,31 +105,31 @@ export AZURE_OPENAI_VERSION = ...
export AZURE_OPENAI_DEPLOYMENT = ...
# then use the --use_azure_openai flag
memgpt --use_azure_openai
python main.py --use_azure_openai
```
To create a new starter user or starter persona (that MemGPT gets initialized with), create a new `.txt` file in `~/.memgpt/humans` or `~/.memgpt/personas`, then use the `--persona` or `--human` flag when running `main.py`. For example:
To create a new starter user or starter persona (that MemGPT gets initialized with), create a new `.txt` file in [/memgpt/humans/examples](/memgpt/humans/examples) or [/memgpt/personas/examples](/memgpt/personas/examples), then use the `--persona` or `--human` flag when running `main.py`. For example:
```sh
# assuming you created a new file ~/.memgpt/humans/me.txt
memgpt
# assuming you created a new file /memgpt/humans/examples/me.txt
python main.py
# Select me.txt during configuration process
```
-- OR --
```sh
# assuming you created a new file ~/.memgpt/humans/me.txt
memgpt --human me.txt
# assuming you created a new file /memgpt/humans/examples/me.txt
python main.py --human me.txt
```
You can also specify any of the starter users in [/memgpt/humans/examples](/memgpt/humans/examples) or any of the starter personas in [/memgpt/personas/examples](/memgpt/personas/examples).
### GPT-3.5 support
You can run MemGPT with GPT-3.5 as the LLM instead of GPT-4:
```sh
memgpt
python main.py
# Select gpt-3.5 during configuration process
```
-- OR --
```sh
memgpt --model gpt-3.5-turbo
python main.py --model gpt-3.5-turbo
```
**Note that this is experimental gpt-3.5-turbo support. It's quite buggy compared to gpt-4, but it should be runnable.**
@@ -240,7 +210,7 @@ id | name | age
To talk to this database, run:
```sh
memgpt --archival_storage_sqldb=memgpt/personas/examples/sqldb/test.db
python main.py --archival_storage_sqldb=memgpt/personas/examples/sqldb/test.db
```
And then you can input the path to your database, and your query.
@@ -263,7 +233,7 @@ To run our example where you can search over the SEC 10-K filings of Uber, Lyft,
2. In the root `MemGPT` directory, run
```bash
memgpt --archival_storage_files="memgpt/personas/examples/preload_archival/*.txt" --persona=memgpt_doc --human=basic
python3 main.py --archival_storage_files="memgpt/personas/examples/preload_archival/*.txt" --persona=memgpt_doc --human=basic
```
If you would like to load your own local files into MemGPT's archival memory, run the command above but replace `--archival_storage_files="memgpt/personas/examples/preload_archival/*.txt"` with your own file glob expression (enclosed in quotes).
@@ -271,7 +241,7 @@ If you would like to load your own local files into MemGPT's archival memory, ru
#### Enhance with embeddings search
In the root `MemGPT` directory, run
```bash
memgpt main.py --archival_storage_files_compute_embeddings="<GLOB_PATTERN>" --persona=memgpt_doc --human=basic
python3 main.py --archival_storage_files_compute_embeddings="<GLOB_PATTERN>" --persona=memgpt_doc --human=basic
```
This will generate embeddings, stick them into a FAISS index, and write the index to a directory, and then output:
@@ -282,7 +252,7 @@ This will generate embeddings, stick them into a FAISS index, and write the inde
If you want to reuse these embeddings, run
```bash
memgpt --archival_storage_faiss_path="<DIRECTORY_WITH_EMBEDDINGS>" --persona=memgpt_doc --human=basic
python3 main.py --archival_storage_faiss_path="<DIRECTORY_WITH_EMBEDDINGS>" --persona=memgpt_doc --human=basic
```
@@ -314,7 +284,7 @@ MemGPT also enables you to chat with docs -- try running this example to talk to
3. In the root `MemGPT` directory, run
```bash
memgpt --archival_storage_faiss_path=<ARCHIVAL_STORAGE_FAISS_PATH> --persona=memgpt_doc --human=basic
python3 main.py --archival_storage_faiss_path=<ARCHIVAL_STORAGE_FAISS_PATH> --persona=memgpt_doc --human=basic
```
where `ARCHIVAL_STORAGE_FAISS_PATH` is the directory where `all_docs.jsonl` and `all_docs.index` are located.
If you downloaded from Hugging Face, it will be `memgpt/personas/docqa/llamaindex-api-docs`.