An AI framework for building cool things.
- LLMs are fantastic for knowledge generation and reasoning as they're pre-trained on large amounts of publicly available data.
- In practice, we need LLMs to be able to reason about our own data. Fine-tuning them is often impractical. Embedding data into LLMs is a viable alternative, but requires domain expertise, and considerable effort to dealing with prompt limitations
- Botastic aims to make it easy to embed your own data into LLMs.
- Botastic also aims to provide out-of-the-box solutions to satisfy common use cases.
- It would to be easily integrated into existing systems and scalable to meet business requirements.
- We're building AI-based applications, we need Botastic to simplify the process.
- 🔌 Connect to OpenAI's LLM
- 💾 Store and manage your own data as LLM's external brain
- 🌐 Restful APIs
- 💬 Conversations management to help you build dialogue interface based applications
- 🤖 Bot/Avatar management and builtin useful bots: emotion recognition, sentiment analysis, spam checker, etc. Please refer to [TBD].
- 🧩 Customize Middlewares to extend Botastic's functionality
- 💾 Store vectors in Postgres and other databases
- 📦 Better strategies to split the data and build text chunks
- 📤 Export data
- 🙋♂️ Support other LLMs
- 📚 Fine-tune own models
- visit https://developers.pando.im/console/botastic to get your API key/secret, and create a new bot.
- run the following command to talk to Botastic
curl --location --request POST 'https://botastic-api.pando.im/api/conversations/oneway' \
--header 'X-BOTASTIC-APPID: YOUR_BOTASTIC_APP_ID' \
--header 'Content-Type: application/json' \
--data-raw '{
"bot_id": YOUR_BOT_ID,
"content": "How do you view the future of blockchain, and what benefits does it have for human being? Respond as short as possible like a Zen Master.",
"category": "plain-text"
}'Please refer to Guide and API Reference for more details.
- Ask Vitalik: A digital avatar of Vitalik Buterin.
- Ask Scott Alexander: A digital avatar of Scott Alexander.
- The author also wrote a blog post about how she built it.
Please refer to docs/install.md for manual installation.
TBD