48 lines
2.0 KiB
Markdown
48 lines
2.0 KiB
Markdown
# Add Dynamic Agent API (Type=1) with Database Integration
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I will implement the Dynamic Agent feature by integrating it with the existing `agent_cards` system. Dynamic Agents will be distinguished by `type=1` and will store their extended data (videos, knowledge base) in a new linked table.
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## 1. Database Schema Extension
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I will create a new table `dynamic_agent_details` to store the specialized data for dynamic agents.
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* **Table Name**: `dynamic_agent_details`
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* **Columns**:
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* `id`: `SERIAL PRIMARY KEY`
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* `card_id`: `INTEGER` (Foreign Key linking to `agent_cards.card_id`)
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* `videos`: `JSONB` (Stores list of `{url, emotion}`, min 1, max 7)
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* `kb_id`: `VARCHAR` (Knowledge Base ID)
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* `kb_config`: `JSONB` (Additional Knowledge Base fields)
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* `created_at`: `TIMESTAMP`
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## 2. Code Implementation (`main.py`)
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### Pydantic Models
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I will define:
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* `VideoItem`: `{url: str, emotion: str}`
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* `DynamicAgentCreate`: Inherits/Includes fields from `AgentCard` (name, avatar, etc.) PLUS:
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* `videos`: List[VideoItem] (validated length 1-7)
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* `kb_id`: str
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* `kb_config`: dict
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### API Endpoints
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1. **Create Dynamic Agent**
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* `POST /dynamic_agent/`
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* **Logic**:
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1. Insert the base agent info into `agent_cards` with `type=1` and `RETURNING card_id`.
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2. Insert the extended info (videos, kb details) into `dynamic_agent_details` using the returned `card_id`.
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3. Return the new `card_id`.
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2. **Get Dynamic Agent Details**
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* `GET /dynamic_agent/{card_id}`
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* **Logic**:
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1. Fetch base info from `agent_cards`.
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2. Fetch extended info from `dynamic_agent_details`.
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3. Return combined result.
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### Helper Functions
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* `init_dynamic_agent_db()`: Checks/Creates the `dynamic_agent_details` table on startup.
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## 3. Verification
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* Create a dynamic agent via the new API.
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* Verify it appears in the `agent_cards` table (as type 1).
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* Verify extended data is in `dynamic_agent_details`.
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