https://github.com/benderscript/agenticdb
GenAI Agent DB
https://github.com/benderscript/agenticdb
agents database genai openai ratings
Last synced: 2 months ago
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GenAI Agent DB
- Host: GitHub
- URL: https://github.com/benderscript/agenticdb
- Owner: BenderScript
- License: apache-2.0
- Created: 2024-07-14T23:13:52.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-06T03:36:08.000Z (12 months ago)
- Last Synced: 2025-07-06T14:05:52.021Z (3 months ago)
- Topics: agents, database, genai, openai, ratings
- Language: Python
- Homepage:
- Size: 3.84 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# AgenticDB
The world of GenAI agents is fragmented, with frameworks like LangGraph, AWS Bedrock, and Semantic Kernel each operating in their own silos. This lack of interoperability creates hurdles for developers and enterprises needing to integrate agents across different platforms, APIs, or legacy systems.
AgenticDB emerges as the solution to unify this scattered landscape. It's a database specifically designed to store and manage GenAI agent and application manifests. With AgenticDB, you can effortlessly add, search, invoke, and rate agents, all from a centralized repository. Advanced features like Docker-based agent management and remote execution expand its versatility, making it adaptable for a wide array of GenAI workflows.
By streamlining the way we handle agents, AgenticDB not only saves time but also fosters innovation by making it easier to find and utilize the right agent for any task. It's the bridge that connects disparate frameworks, enabling seamless collaboration and accelerating progress in the GenAI ecosystem.
With **AgenticDB**, you can:
- **Store** and manage agent manifests.
- **Search** for agents using similarity search.
- **Invoke** agents via local and remote execution models.
- **Rate** agents based on performance and interaction results.
---
## Table of Contents
- [AgenticDB](#agenticdb)
- [Table of Contents](#table-of-contents)
- [Run Server](#run-server)
- [Add an Agent](#add-an-agent)
- [Search for Agents (Similarity Search)](#search-for-agents-similarity-search)
- [Add an Application](#add-an-application)
- [Delete All Collections](#delete-all-collections)
- [cURL Command](#curl-command)
- [Response](#response)
- [Example Response](#example-response)
- [Explanation](#explanation)
- [Rate an Agent](#rate-an-agent)
- [Retrieve Ratings](#retrieve-ratings)
---
## Run Server
To start the AgenticDB server locally, run the following command:
```bash
python server.py
```
The API will be available at `http://127.0.0.1:8000`.
Here's an updated version of the **Delete All Collections** section in the README, reflecting the actual JSON response format from the provided Python code.
---
## Add an Agent
You can add an agent to the database using the following `curl` command. This example sends a JSON request to add a new agent called `code-gen-chart-agent`.
```bash
curl -X POST "http://127.0.0.1:8000/agents" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '[
{
"metadata": {
"name": "code-gen-chart-agent",
"namespace": "agents",
"description": "Requests for a javascript code generator to plot a chart with supplied free-form data."
},
"spec": {
"type": "agent",
"lifecycle": "dev",
"owner": "admin@company.com",
"access_level": "Public",
"category": "Travel Agent",
"url": "https://api.example.com/code-gen-chart-agent/agent",
"parameters": {
"type": "object",
"properties": {
"message": {
"type": "string",
"description": "The request message for the chart code generator agent."
},
"thread": {
"type": "string",
"description": "The id to separate parallel message threads."
}
},
"required": ["message", "thread"],
"additionalProperties": false
},
"output": {
"type": "string",
"description": "The result of the request, including any generated image location."
}
}
}
]'
```
This will add the agent manifest to AgenticDB, making it available for future searches and invocations.
---
## Search for Agents (Similarity Search)
To search for agents based on a natural language query, use the following `curl` command. This example searches for agents related to "Natural Language."
```bash
curl -G "http://127.0.0.1:8000/agents" \
-H "Accept: application/json" \
--data-urlencode "query=Which agents can book travel?"
```
AgenticDB will perform a similarity search and return a list of matching agents based on the query.
---
## Add an Application
You can also add an agentic application to AgenticDB using a similar `curl` command. Here’s an example for adding a "Stock Price Charting Application" that tracks stock prices and generates charts.
```bash
curl -X POST "http://127.0.0.1:8000/applications" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '[
{
"metadata": {
"name": "Stock Price Charting Application",
"namespace": "production",
"description": "Provides access to daily open, high, low, close stock prices over time and the ability to generate charts for the requested data"
},
"spec": {
"type": "application",
"lifecycle": "dev",
"owner": "admin@company.com",
"access_level": "PUBLIC",
"category": "Finance",
"setup": {
"compose": {
"compose_url": "https://ipfs.filebase.io/ipfs/somehash",
"run_command": "gunzip docker-compose.yml.gz && docker compose -f ./docker-compose.yml up -d"
}
},
"url": "http://localhost:3000/agent",
"method": "POST",
"example": "http://localhost:3000/agent 'Content-Type':'application/json' {'input':'what was the Nvidia close price on August 22nd 2024', 'thread':'nvidia'}",
"parameters": {
"type": "object",
"properties": {
"input": {
"type": "string",
"description": "natural language request for stock price data and charting of the data as required"
},
"thread": {
"type": "string",
"description": "thread context id for the request"
}
},
"required": ["input"],
"additionalProperties": false
},
"output": {
"type": "object",
"properties": {
"content": {
"type": "string",
"description": "the natural language response and the Final Answer to the request with a chart location if requested"
}
},
"description": "the answer to the request"
}
}
}
]'
```
---
## Delete All Collections
You can delete all agent, application, and rating collections from AgenticDB with a single `DELETE` request. This operation will attempt to remove the stored collections: `agents`, `applications`, and `ratings`. Each collection deletion is handled separately, and the results will reflect whether each collection was successfully deleted.
### cURL Command
```bash
curl -X DELETE "http://127.0.0.1:8000/collections"
```
### Response
The response will provide the status of each deletion attempt in the form of a JSON object. If a collection is successfully deleted, the value will be `0`. If there was an error, the value will contain the corresponding error message.
#### Example Response
```json
{
"agents": 0,
"applications": 0,
"ratings": "Failed to delete ratings collection: some_error_message"
}
```
### Explanation
- **agents**: `0` indicates the `agents` collection was successfully deleted.
- **applications**: `0` indicates the `applications` collection was successfully deleted.
- **ratings**: Contains an error message if the deletion failed (replace `"some_error_message"` with the actual error encountered).
---
## Rate an Agent
After interacting with an agent, you can submit a rating for the agent using this `curl` command. Replace `placeholder_agent_id` and `placeholder_some_id` with the actual agent and rating IDs.
```bash
curl -X POST "http://127.0.0.1:8000/ratings" \
-H "Content-Type: application/json" \
-d '{
"ratings": {
"agent_id": "placeholder_agent_id",
"id": "placeholder_some_id",
"data": {
"score": 4
}
}
}'
```
---
## Retrieve Ratings
You can retrieve agent ratings using this `curl` command. Replace `` with the actual ratings ID.
```bash
curl -X GET "http://127.0.0.1:8000/ratings?ratings_id="
```
AgenticDB will return the score and feedback associated with the provided ratings ID.