Spaces:
Running
Running
| title: Demo App | |
| emoji: 📚 | |
| colorFrom: green | |
| colorTo: pink | |
| sdk: streamlit | |
| sdk_version: 1.25.0 | |
| app_file: app.py | |
| pinned: false | |
| license: other | |
| # Product Description Generator | |
| Generate SEO-compliant product descriptions using product titles and meta-keywords provided by the user. | |
| Implemented custom LLMChain function from the Langchain and few-shot prompting technique to generate multi-paragraph rich text product description for each product name and its corresponding keywords. Built a gradio app as a frontend demo to showcase the process. | |
| ## Steps:- | |
| - Provide the product name and keywords separated by commas | |
| - Using the custom prompt template and ChatOpenAI model, call the custom LLM chain to generate a product description | |
| ## How to run it locally:- | |
| To run this app locally, first clone this repo using `git clone`.<br><br> | |
| Now, install all libraries by running the following command in the terminal:<br> | |
| ```python | |
| pip install -r requirements.txt | |
| ``` | |
| <br><br> | |
| Now, run the app from the terminal:<br> | |
| ```python | |
| gradio app.py | |
| ``` | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |