Roadmap#
db-ally is actively developed and maintained by a core team at deepsense.ai and a community of contributors.
We are constantly working on new features and improvements. If you have any ideas or suggestions, feel free to open an issue or a pull request.
Below you can find a list of planned features and integrations.
Planned Features#
- Support analytical queries: support for exposing operations beyond filtering.
- Few-shot prompting configuration: allow users to configure the few-shot prompting in View definition to improve IQL generation accuracy.
- Request contextualization: allow to provide extra context for db-ally runs, such as user asking the question.
- OpenAI Assistants API adapter: allow to embed db-ally into OpenAI's Assistants API to easily extend the capabilities of the assistant.
- Langchain adapter: allow to embed db-ally into Langchain applications.
Integrations#
Being agnostic to the underlying technology is one of the main goals of db-ally. Below you can find a list of planned integrations.
Data sources#
- Sqlalchemy
- Pandas DataFrame
- HTTP REST Endpoints
- GraphQL Endpoints
LLM Providers#
- OpenAI
- Anthropic
- VertexAI
- Hugging Face
- Bedrock
- Azure
And many more, the full list can be found in the LiteLLM documentation
Vector stores#
- FAISS
- Chroma
- Elasticsearch
- Weaviate
- Qdrant
- VertexAI Vector Search
- Milvus
Query tracking#
- LangSmith
- OpenTelemetry