| Name | nichirin JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | None |
| Summary | TODO |
| upload_time | 2024-04-13 21:04:57 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.6 |
| license | MIT License Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files, to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
retrieval augmentation
vector database
natural language processing
machine learning
deep learning
artificial intelligence
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Nichirin: A custom search framework featuring augmented generation with retrieval capabilities.
## Overview
**Nichirin** serves as an advanced layer atop Apache Solr, facilitating seamless data indexing operations.
1. **What is Nichirin?**
- **Nichirin** acts as a surface or layer on top of **Apache Solr**, making data indexing a breeze.
- It abstracts away the complexities of Solr indexing, allowing users to focus on providing their data without worrying about the nitty-gritty details.
2. **Key Features:**
- **Multi-level Crawling**: Performs multi-level web crawling utilizing a depth-first search methodology, with text indexing and retrieval facilitated through Apache Solr.
- **Efficient Indexing**: Integrated Apache Spark for parallel processing of URLs, improving the scalability and efficiency of both web crawling and text indexing.
- **Python package**: Available as a Python package on PyPI for easy installation and integration
<!-- '''3. **Getting Started:**
- **Installation**: Clone this repository and follow the installation instructions in the Installation Guide.
- **Usage**:
- Execute `nichirin.py`.
- Input your data or specify the data source.
- Follow the provided commands to initiate indexing.
- Sit back and let Nichirin handle the rest!
4. **Example Usage:**
```bash
$ python nichirin.py
Welcome to Nichirin!
Please provide your data source (CSV, JSON, or database connection string):
> data.csv
Data source accepted. Initializing indexing...
Indexing complete! Your data is now searchable via Solr. -->
## Commands
* `install-solr` to install solr
* `create-core --core <core name>` to create solr core,
* `partition-data --path <path to the dataset>` to partition the data
* `pipeline --path <path to the dataset>` generate embeddings of the partition data
* `index-solr --data-path <path to dataset> --core <core to which the data needs to be sent>` index the data
* `query-solr --input_sen <input sen> --core_name <core name to query from>` query the data from solr
* `seed-urls --core <core name> --urls <urls separted with commas>` to add the seed urls
* `start-crawler` to start the web crawler
* `start-serve` to start the web server
## Quickstart
1. Begin by executing the `install-solr` command to install the Solr application.
2. Next, create the cores using the `create-core` command.
3. After setting up Solr and creating the cores, add seed URLs by running the `seed-urls` command.
4. Once the seed URLs are added, initiate the crawling process with the `start-crawler` command. Be patient, as this step may take some time.
5. Finally, to view the results, launch the Flask web app using the `start-serve` command.
<!-- * Run `install-solr` to install the solr application.
* To create the cores, run `create-core` command.
* Once after setting up the solr, creating cores run `seed-urls` command to add seed urls.
* Now that you have added seed urls, run `start-crawler` commad, this might take a while.
* Once the crawling is completed, to view the results run the command `start-serve` this will start the flask web app. -->
Contributing and Feedback:
We welcome contributions! If you’d like to enhance Nichirin or report issues, feel free to submit a pull request.
For feedback or questions, open an issue on our GitHub repository.
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