diff --git a/README.md b/README.md
index ae521929..04d3048a 100644
--- a/README.md
+++ b/README.md
@@ -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`.