TEN-framework / TEN-framework/ten-framework
[FEATURE] [OceanbaseDeveloperChallenge] a Memory-Enabled Voice AI UseCase with TEN + PowerMem
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- Dominant language
- Python
- Stars
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- Forks
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Description
Description
Using TEN Framework together with PowerMem, we invite you to build a practical voice AI use case in a specific real-world scenario, where long-term or contextual memory actually matters.
Reference:
What to contribute
- A concrete voice AI usecase (not just a demo)
- Memory should play a clear role (e.g. user preferences, conversation history, context accumulation)
Example scenarios (not limited to):
- Language tutor that remembers learning progress
- Emotional companion or journaling assistant
You can help developers with
- Clear example code or runnable workflow
- Brief explanation of the use case and memory design
- A screenshot or short demo showing the use case works
Severity
Critical
Additional Information
No response
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the referenced example at ai_agents/agents/examples/voice-assistant-with-PowerMem and understand how TEN Framework and PowerMem are combined. Choose a concrete real-world voice AI use case where long-term or contextual memory matters, then provide runnable example code or a workflow, a brief explanation of the memory design, and a screenshot or short demo showing it works.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, audio-video-rtc
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100