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HuggingFace --> Hugging Face

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Vivian Fang
2023-10-17 15:16:20 -07:00
parent 8759d78349
commit 4688bef36d
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6
README.md
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@@ -171,7 +171,7 @@ Enter your message: How old is Bob?
To run our example where you can search over the SEC 10-K filings of Uber, Lyft, and Airbnb,
1. Download the .txt files from [HuggingFace](https://huggingface.co/datasets/MemGPT/example-sec-filings/tree/main) and place them in `memgpt/personas/examples/preload_archival`.
1. Download the .txt files from [Hugging Face](https://huggingface.co/datasets/MemGPT/example-sec-filings/tree/main) and place them in `memgpt/personas/examples/preload_archival`.
2. In the root `MemGPT` directory, run
```bash
@@ -186,7 +186,7 @@ If you would like to load your own local files into MemGPT's archival memory, ru
MemGPT also enables you to chat with docs -- try running this example to talk to the LlamaIndex API docs!
1.
a. Download LlamaIndex API docs and FAISS index from [HuggingFace](https://huggingface.co/datasets/MemGPT/llamaindex-api-docs).
a. Download LlamaIndex API docs and FAISS index from [Hugging Face](https://huggingface.co/datasets/MemGPT/llamaindex-api-docs).
```bash
# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install
@@ -210,7 +210,7 @@ MemGPT also enables you to chat with docs -- try running this example to talk to
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 HuggingFace, it will be `memgpt/personas/docqa/llamaindex-api-docs`.
If you downloaded from Hugging Face, it will be `memgpt/personas/docqa/llamaindex-api-docs`.
If you built the index yourself, it will be `memgpt/personas/docqa`.
</details>

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memgpt/personas/examples/docqa/README.md
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@@ -3,7 +3,7 @@
MemGPT enables you to chat with your data -- try running this example to talk to the LlamaIndex API docs!
1.
a. Download LlamaIndex API docs and FAISS index from [HuggingFace](https://huggingface.co/datasets/MemGPT/llamaindex-api-docs).
a. Download LlamaIndex API docs and FAISS index from [Hugging Face](https://huggingface.co/datasets/MemGPT/llamaindex-api-docs).
```bash
# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install
@@ -26,7 +26,7 @@ MemGPT enables you to chat with your data -- try running this example to talk to
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 HuggingFace, it will be `memgpt/personas/docqa/llamaindex-api-docs`.
If you downloaded from Hugging Face, it will be `memgpt/personas/docqa/llamaindex-api-docs`.
If you built the index yourself, it will be `memgpt/personas/docqa`.
## Demo

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memgpt/personas/examples/preload_archival/README.md
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@@ -3,7 +3,7 @@ MemGPT enables you to chat with your data locally -- this example gives the work
To run our example where you can search over the SEC 10-K filings of Uber, Lyft, and Airbnb,
1. Download the .txt files from [HuggingFace](https://huggingface.co/datasets/MemGPT/example-sec-filings/tree/main) and place them in this directory.
1. Download the .txt files from [Hugging Face](https://huggingface.co/datasets/MemGPT/example-sec-filings/tree/main) and place them in this directory.
2. In the root `MemGPT` directory, run
```bash