https://github.com/ruska-ai/a2a-langgraph
🤖💬🤖 Agent-to-Agent (A2A Protocol) built on top of LangGraph
https://github.com/ruska-ai/a2a-langgraph
a2a agentic-ai agents ai anthropic claude google jsonrpc langchain langgraph mcp openai protocol python uvicorn vertex
Last synced: 3 months ago
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🤖💬🤖 Agent-to-Agent (A2A Protocol) built on top of LangGraph
- Host: GitHub
- URL: https://github.com/ruska-ai/a2a-langgraph
- Owner: enso-labs
- Created: 2025-04-12T04:09:24.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-04-12T05:02:06.000Z (about 1 year ago)
- Last Synced: 2025-04-12T08:43:30.996Z (about 1 year ago)
- Topics: a2a, agentic-ai, agents, ai, anthropic, claude, google, jsonrpc, langchain, langgraph, mcp, openai, protocol, python, uvicorn, vertex
- Language: Python
- Homepage: https://a2a.enso.sh
- Size: 180 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🤖 A2A Protocol 💬 from Enso Labs 🤖
This sample demonstrates a currency conversion agent built with [LangGraph](https://langchain-ai.github.io/langgraph/) and exposed through the A2A protocol. It showcases conversational interactions with support for multi-turn dialogue and streaming responses. For more information checkout the OFFICIAL repo at https://github.com/google/A2A/tree/main
## Docker Deploy
```bash
# Pull Image
docker pull ghcr.io/enso-labs/a2a-langgraph
# Run Image
docker run -p 10000:10000 --name a2a \
-e GOOGLE_API_KEY=$GOOGLE_API_KEY \
ghcr.io/enso-labs/a2a-langgraph
# Check Logs
docker logs -f a2a
```
## Prerequisites
- Python 3.13 or higher
- UV
- Access to an LLM and API Key
## Setup & Running
1. Navigate to the samples directory:
```bash
cd samples/python/agents/langgraph
```
2. Create an environment file with your API key:
```bash
echo "GOOGLE_API_KEY=your_api_key_here" > .env
```
3. Run the agent:
```bash
# Basic run on default port 10000
uv run .
# On custom host/port
uv run . --host 0.0.0.0 --port 8080
```
4. In a separate terminal, run an A2A [client](/samples/python/hosts/README.md):
```bash
uv run hosts/cli
```
## Technical Implementation
- **LangGraph ReAct Agent**: Uses the ReAct pattern for reasoning and tool usage
- **Streaming Support**: Provides incremental updates during processing
- **Checkpoint Memory**: Maintains conversation state between turns
- **Push Notification System**: Webhook-based updates with JWK authentication
- **A2A Protocol Integration**: Full compliance with A2A specifications
## Limitations
- Only supports text-based input/output (no multi-modal support)
- Uses Frankfurter API which has limited currency options
- Memory is session-based and not persisted between server restarts
## Examples
**Synchronous request**
Request:
```
POST http://localhost:10000
Content-Type: application/json
{
"jsonrpc": "2.0",
"id": 11,
"method": "tasks/send",
"params": {
"id": "129",
"sessionId": "8f01f3d172cd4396a0e535ae8aec6687",
"acceptedOutputModes": [
"text"
],
"message": {
"role": "user",
"parts": [
{
"type": "text",
"text": "How much is the exchange rate for 1 USD to INR?"
}
]
}
}
}
```
Response:
```
{
"jsonrpc": "2.0",
"id": 11,
"result": {
"id": "129",
"status": {
"state": "completed",
"timestamp": "2025-04-02T16:53:29.301828"
},
"artifacts": [
{
"parts": [
{
"type": "text",
"text": "The exchange rate for 1 USD to INR is 85.49."
}
],
"index": 0
}
],
"history": []
}
}
```
**Multi-turn example**
Request - Seq 1:
```
POST http://localhost:10000
Content-Type: application/json
{
"jsonrpc": "2.0",
"id": 10,
"method": "tasks/send",
"params": {
"id": "130",
"sessionId": "a9bb617f2cd94bd585da0f88ce2ddba2",
"acceptedOutputModes": [
"text"
],
"message": {
"role": "user",
"parts": [
{
"type": "text",
"text": "How much is the exchange rate for 1 USD?"
}
]
}
}
}
```
Response - Seq 2:
```
{
"jsonrpc": "2.0",
"id": 10,
"result": {
"id": "130",
"status": {
"state": "input-required",
"message": {
"role": "agent",
"parts": [
{
"type": "text",
"text": "Which currency do you want to convert to? Also, do you want the latest exchange rate or a specific date?"
}
]
},
"timestamp": "2025-04-02T16:57:02.336787"
},
"history": []
}
}
```
Request - Seq 3:
```
POST http://localhost:10000
Content-Type: application/json
{
"jsonrpc": "2.0",
"id": 10,
"method": "tasks/send",
"params": {
"id": "130",
"sessionId": "a9bb617f2cd94bd585da0f88ce2ddba2",
"acceptedOutputModes": [
"text"
],
"message": {
"role": "user",
"parts": [
{
"type": "text",
"text": "CAD"
}
]
}
}
}
```
Response - Seq 4:
```
{
"jsonrpc": "2.0",
"id": 10,
"result": {
"id": "130",
"status": {
"state": "completed",
"timestamp": "2025-04-02T16:57:40.033328"
},
"artifacts": [
{
"parts": [
{
"type": "text",
"text": "The current exchange rate is 1 USD = 1.4328 CAD."
}
],
"index": 0
}
],
"history": []
}
}
```
**Streaming example**
Request:
```
{
"jsonrpc": "2.0",
"id": 12,
"method": "tasks/sendSubscribe",
"params": {
"id": "131",
"sessionId": "cebd704d0ddd4e8aa646aeb123d60614",
"acceptedOutputModes": [
"text"
],
"message": {
"role": "user",
"parts": [
{
"type": "text",
"text": "How much is 100 USD in GBP?"
}
]
}
}
}
```
Response:
```
data: {"jsonrpc":"2.0","id":12,"result":{"id":"131","status":{"state":"working","message":{"role":"agent","parts":[{"type":"text","text":"Looking up the exchange rates..."}]},"timestamp":"2025-04-02T16:59:34.578939"},"final":false}}
data: {"jsonrpc":"2.0","id":12,"result":{"id":"131","status":{"state":"working","message":{"role":"agent","parts":[{"type":"text","text":"Processing the exchange rates.."}]},"timestamp":"2025-04-02T16:59:34.737052"},"final":false}}
data: {"jsonrpc":"2.0","id":12,"result":{"id":"131","artifact":{"parts":[{"type":"text","text":"Based on the current exchange rate, 1 USD is equivalent to 0.77252 GBP. Therefore, 100 USD would be approximately 77.252 GBP."}],"index":0,"append":false}}}
data: {"jsonrpc":"2.0","id":12,"result":{"id":"131","status":{"state":"completed","timestamp":"2025-04-02T16:59:35.331844"},"final":true}}
```
## Learn More
- [A2A Protocol Documentation](https://google.github.io/A2A/#/documentation)
- [LangGraph Documentation](https://langchain-ai.github.io/langgraph/)
- [Frankfurter API](https://www.frankfurter.app/docs/)
- [Google Gemini API](https://ai.google.dev/gemini-api)