# Solar-QA-CLI
This repository contains the command-line tool for [solar-qa pipepine](https://github.com/oeg-upm/solar-qa-eval)

## Requirement

### Requirement for Paper Extraction

- [Grobid](https://grobid.readthedocs.io/en/latest/)

### Requirement for Generation

All required libraries are detailed in requirement.txt. 

```console
pip install -r requirement.txt
```


### Usage

1. Install [GROBID](https://grobid.readthedocs.io/en/latest/) in your computing device
2. Start running GROBID server in your local device following the instruction from [GROBID WEBSITE](https://grobid.readthedocs.io/en/latest/).
3. With the running GROBID server, upload the configuration of GROBID in sub-folder `.../CLI/setting/config.json`. The file is given below:

```json
{
  "grobid_server": "http://localhost:8070",
  "batch_size": 1000,
  "sleep_time": 5,
  "timeout": 60,
  "coordinates": ["persName", "figure", "ref", "biblStruct", "formula", "s"]
}
```


4. Run the entire command-line tool by running the `cli.py` in the directory `.../CLI/code/cli.py`. The command line to run the `cli.py` is given below:
```json
{
    "--use_platform": the parameter of whether use online platform or local model for the llm(generation model). option = ["True", "False"]
    "--user_key": the user key or token for the online platform, type="str"
    "--llm_id": the reference id for the llm(generation model), type="str"
    "--hf_key": your huggingface token, this is required to use the similarity model, type="str"
    "--llm_platform": indication of which llm online platform you wish to use, option=["grob"]
    "--sim_model_id": the reference id for the similarity model, type="str"
    "--input_file_path": the directory for the pdf fild that you wish to analysis, type="str", file type=.pdf
    "--prompt_file_path": the directory for the json file that contains your prompt, file type=.json
    "--context_file_path": the directory for where you wish to save the output file, file type=.json
}
```
*Example not use online platform:*
```console
python cli.py --use_platform False --hf_key YOUR_HF_KEY --llm_id meta-llama/Llama-3.2-3B-Instruct --sim_model_id Salesforce/SFR-Embedding-Mistral --pdf_file_path .../test.pdf --prompt_file .../prompts.json --context_file_path .../context.json
```
*Example use online platform:*
```console
python cli.py --use_platform True --user_key YOUR_USER_KEY --hf_key YOUR_HF_KEY --llm_id llama-3.1-70b-versatile --llm_platform grob --sim_model_id Salesforce/SFR-Embedding-Mistral --pdf_file_path .../test.pdf --prompt_file .../prompts.json --context_file_path .../context.json
```

5. Result format is given at `Result_Spec.md`