story-writing
S
Story Writing
Overview :
story-writing is an application built on LangGraph Cloud, designed to showcase the features of LangGraph Cloud in an engaging and interactive manner. The app enables users to write stories with the help of the LangGraph agent, allowing them to edit existing chapters or continue writing the next one. Users can create multiple versions of the same chapter and choose their preferred version to continue the story. At the start, users provide a story summary, desired writing style, and any other relevant details. From that point, they only need to provide editing and continuation commands to guide the agent in the desired direction. Note: This application is a prototype and is not yet ready for deployment; it may contain bugs or yield suboptimal results from the agent.
Target Users :
The target audience includes writers and enthusiasts who wish to create stories in an innovative and interactive way. This product is particularly suited for users looking for technological assistance to inspire creativity and enhance writing efficiency.
Total Visits: 474.6M
Top Region: US(19.34%)
Website Views : 53.3K
Use Cases
Writers use story-writing to outline and draft various chapters of their novels.
Educators leverage this tool in the classroom to guide students through creative writing exercises.
Writing enthusiasts use the application to experiment with different storylines and styles.
Features
Allows users to edit or continue writing story chapters
Supports users in creating multiple versions of the same chapter
Users can select their preferred chapter to continue the story
Provides story summary, writing style, and details to guide the agent
Run the application locally via Streamlit
If users self-host the graph, they will need to change the URL to match the deployed graph
How to Use
First, clone the repository to your local machine.
Navigate to the repository directory and run App_Information.py using Streamlit.
If users self-host the graph, they need to change the URL in the get_client function call within pages/Story_Writing.py to match the deployed graph's URL.
After running App_Information.py, go to http://localhost:8501 to view the application.
Use the interface provided by the application to edit or continue writing the story as needed.
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