docs/doc/developer/apps/PromptBased.mdx
Prompt-based apps let you customize how Omi thinks and responds without writing any backend code. Simply define your prompt and Omi's behavior changes accordingly.
<CardGroup cols={2}> <Card title="No Server Required" icon="cloud-slash"> Everything runs on Omi's infrastructure - just write your prompt </Card> <Card title="Instant Deployment" icon="bolt"> Create, test, and publish in minutes </Card> </CardGroup>Chat prompts alter Omi's conversational style and knowledge base. Create specialized versions of Omi for different contexts or expertise areas.
flowchart LR
U[User Message] --> O[Omi + Your Prompt]
O --> R[Customized Response]
style O fill:#e1f5fe
1. Your prompt is injected into the system context
2. Omi adopts the personality/expertise you defined
3. All responses reflect your customizations
The prompt persists for the entire conversation, creating a consistent experience.
Example - Fitness Coach Prompt:
You are an enthusiastic fitness coach named Alex. You:
- Provide encouraging, actionable fitness advice
- Ask about the user's goals and current fitness level
- Suggest specific exercises with proper form instructions
- Celebrate progress and motivate through setbacks
- Keep responses concise but informative
Example - Creative Writing Partner:
You are a creative writing mentor. You:
- Help brainstorm story ideas and plot structures
- Provide constructive feedback on writing samples
- Suggest techniques for improving prose
- Share examples from famous authors when relevant
- Encourage experimentation with different styles
Memory prompts analyze conversations and extract specific information based on your criteria. They run after each conversation is processed.
flowchart LR
C[Conversation Ends] --> M[Memory Processing]
M --> P[Your Prompt]
P --> E[Extracted Information]
style P fill:#e8f5e9
1. The full transcript is passed to your prompt
2. Your prompt extracts/summarizes specific information
3. The result is saved alongside the conversation
This creates structured data from unstructured conversations.
Example - Action Item Extractor:
Analyze this conversation and extract all action items.
For each action item, identify:
- The task description
- Who is responsible (if mentioned)
- Any deadline or timeframe mentioned
- Priority level (high/medium/low based on context)
Format as a numbered list. If no action items exist, respond with "No action items found."
Example - Meeting Summary:
Create a structured summary of this meeting:
1. **Attendees**: List people mentioned
2. **Main Topics**: Bullet points of key discussion areas
3. **Decisions Made**: Any conclusions or agreements
4. **Action Items**: Tasks assigned with owners
5. **Follow-ups**: Next steps or future meetings mentioned
Keep each section concise (2-3 sentences max).
Example - Project Manager App: