File size: 1,554 Bytes
20b3cb0 493728d 20b3cb0 493728d 20b3cb0 493728d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 |
---
title: LongCePO Chatbot (Sambanova)
emoji: 🤖
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.27.1
app_file: app.py
pinned: false
---
# LongCePO Chatbot with Sambanova Backend
This is a simple chatbot interface demonstrating the LongCePO (Long-Context Planning and Optimization) method using a Sambanova model (`Llama-4-Maverick-17B-128E-Instruct`) as the backend LLM.
## How it works
The LongCePO method is designed to handle long contexts (potentially millions of tokens) by:
1. **Planning:** Decomposing the initial query into sub-questions.
2. **MapReduce:** Answering each sub-question by processing chunks of the long context, summarizing relevant information, and aggregating results.
This application takes a long text context and a query based on that context. It then uses the modified `longcepo` plugin (originally from the `optillm` repository) to generate an answer using the Sambanova API.
## How to use
1. **(Optional)** Enter a system prompt to guide the chatbot's behavior.
2. Paste the long text document into the **Context** box.
3. Enter your question based on the provided context into the **Query** box.
4. Click **Submit**.
The chatbot will process the request using the LongCePO pipeline and display the final answer.
**Note:** Processing long contexts can take some time depending on the length of the context and the complexity of the query.
## API Key
This application requires a Sambanova API key to function. The key should be stored as a Hugging Face Space Secret named `SAMBANOVA_API_KEY`.
|