You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
:warning:**On Ubuntu 24.04, replace `libasound2` with `libasound2t64`. You may also need to add the repository for Ubuntu 20.04 focal to have access to a few of the sources (e.g. create `/etc/apt/sources.list.d/mmore.list` with the contents `deb http://cz.archive.ubuntu.com/ubuntu focal main universe`).**
37
+
36
38
#### Step 1 – Install MMORE
37
39
38
40
To install the package simply run:
39
41
40
42
```bash
41
-
pip install -e .
43
+
pip install mmore
42
44
```
43
45
44
46
> :warning: This is a big package with a lot of dependencies, so we recommend to use `uv` to handle `pip` installations. [Check our tutorial on uv](./docs/uv.md).
Upload your multimodal documents (PDFs, videos, spreadsheets, and m(m)ore) into the pipeline.
90
92
91
-
2.[**:mag: Process**](./docs/process.md)
93
+
2.[**:mag: Process**](./docs/process.md)
92
94
Extracts and standardizes text, metadata, and multimedia content from diverse file formats. Easily extensible! You can add your own processors to handle new file types.
93
95
*Supports fast processing for specific types.*
94
96
95
-
3.[**:file_folder: Index**](./docs/index.md)
97
+
3.[**:file_folder: Index**](./docs/index.md)
96
98
Organizes extracted data into a **hybrid retrieval-ready Vector Store DB**, combining dense and sparse indexing through [Milvus](https://milvus.io/). Your vector DB can also be remotely hosted and then you only have to provide a standard API. There is also an [HTTP Index API](./docs/index_api.md) for adding new files on the fly with HTTP requests.
97
99
98
-
4.[**:robot: RAG**](./docs/rag.md)
100
+
4.[**:robot: RAG**](./docs/rag.md)
99
101
Use the indexed documents inside a **Retrieval-Augmented Generation (RAG) system** that provides a [LangChain](https://www.langchain.com/) interface. Plug in any LLM with a compatible interface or add new ones through an easy-to-use interface.
100
102
*Supports API hosting or local inference.*
101
103
102
-
5.**:tada: Evaluation**
104
+
5.**:tada: Evaluation**
103
105
*Coming soon*
104
106
An easy way to evaluate the performance of your RAG system using Ragas.
105
107
106
108
See [the `/docs` directory](./docs) for additional details on each modules and hands-on tutorials on parts of the pipeline.
0 commit comments