---
title: 'General FAQ'
weight: 1
type: docs
---
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# General FAQ

This page describes the solutions to some common questions for Flink Agents users.

## Q1: What are the Python environment considerations when running Flink Agents jobs?

To ensure stability and compatibility when running Flink Agents jobs, please be aware of the following Python environment guidelines:

- **Recommended Python versions**: It is advised to use officially supported Python versions such as Python 3.10, 3.11 or 3.12. These versions have been thoroughly tested and offer the best compatibility with Flink Agents.

  {{< hint info >}}
  **Note**: Python 3.12 must work with Flink above 2.1 (including 2.1).
  {{< /hint >}}

- **Installation recommendations**:
    - **For Linux users**: We recommend installing Python via your system package manager (e.g., using `apt`: `sudo apt install python3`).
    - **For macOS users**: Use Homebrew to install Python (e.g., `brew install python`).
    - **For Windows users**: Download and install the official version from the [Python website](https://www.python.org/downloads/).

- **Avoid using Python installed via uv**: Currently, it is not recommended to run Flink Agents jobs with a Python interpreter installed via the `uv` tool, as this may lead to potential compatibility issues or instability. For example, you may encounter the following gRPC-related error:

    ```
    Logging client failed: <_MultiThreadedRendezvous of RPC that terminated with:
        status = StatusCode.UNAVAILABLE
        details = "Socket closed"
        debug_error_string = "UNKNOWN:Error received from peer ipv6:%5B::1%5D:58663 {grpc_message:"Socket closed", grpc_status:14}"
    >... resetting
    Exception in thread read_grpc_client_inputs:
    ...
    py4j.protocol.Py4JError: An error occurred while calling o12.execute
    ```

  If you see an error like this, switch immediately to one of the officially recommended installation methods and confirm that you're using a supported Python version.

## Q2: Why do cross-language resources not work in local development mode?

Cross-language resources, such as using Java resources from Python or vice versa, are currently supported only when running in Flink. Local development mode does not support cross-language resources.

This limitation exists because cross-language communication requires the Flink runtime environment to effectively bridge Java and Python processes. In local development mode, this bridge is unavailable.

To use cross-language resources, please test the functionality by deploying to a Flink standalone cluster.

## Q3: Should I choose Java or Python?

When choosing between Flink Agents' Java API and Python API, consider the following factors:

1. **Team experience and preferences**
2. **JDK version** (for Java users)
3. **Integration supports**

### Understanding Async Execution and JDK Versions

Async execution can significantly improve performance by allowing multiple operations to run concurrently. However, async execution support varies by language and JDK version:

| Environment | Async Execution Support |
|-------------|------------------------|
| Python | ✅ Supported |
| Java (JDK 21+) | ✅ Supported (via Continuation API) |
| Java (JDK < 21) | ❌ Not supported (falls back to synchronous execution) |

This is important because:

- **For Python users**: Async execution is always available.
- **For Java users on JDK 21+**: Async execution is available.
- **For Java users on JDK < 21**: Async execution is not available and falls back to synchronous execution.

> **Cross-language async note**: Async execution for cross-language resources requires the pemja 0.5.7 fix, available in Flink 1.20.5+ / 2.0.2+ / 2.1.3+ / 2.2.1+ / 2.3+. Current builds target Flink 2.3.0, which includes the fix, so cross-language async is enabled by default; on older Flink versions it falls back to synchronous execution automatically.

### Native Integration Support Matrix

Flink Agents provides built-in integrations for many ecosystem providers. Some integrations are only available in one language. For those marked as ❌, you can still use them from the other language via cross-language support.

**Chat Models**

| Provider | Python | Java |
|---|---|---|
| [Amazon Bedrock]({{< ref "docs/development/chat_models#amazon-bedrock" >}}) | ❌ | ✅ |
| [Anthropic]({{< ref "docs/development/chat_models#anthropic" >}}) | ✅ | ✅ |
| [Azure AI]({{< ref "docs/development/chat_models#azure-ai" >}}) | ❌ | ✅ |
| [Azure OpenAI]({{< ref "docs/development/chat_models#azure-openai" >}}) | ✅ | ✅ |
| [Ollama]({{< ref "docs/development/chat_models#ollama" >}}) | ✅ | ✅ |
| [OpenAI]({{< ref "docs/development/chat_models#openai" >}}) | ✅ | ✅ |
| [Tongyi (DashScope)]({{< ref "docs/development/chat_models#tongyi-dashscope" >}}) | ✅ | ❌ |

**Embedding Models**

| Provider | Python | Java |
|---|---|---|
| [Amazon Bedrock]({{< ref "docs/development/embedding_models#amazon-bedrock" >}}) | ❌ | ✅ |
| [Ollama]({{< ref "docs/development/embedding_models#ollama" >}}) | ✅ | ✅ |
| [OpenAI]({{< ref "docs/development/embedding_models#openai" >}}) | ✅ | ❌ |
| [Tongyi (DashScope)]({{< ref "docs/development/embedding_models#tongyi-dashscope" >}}) | ✅ | ❌ |

**Vector Stores**

| Provider | Python | Java |
|---|---|---|
| [Amazon OpenSearch]({{< ref "docs/development/vector_stores#amazon-opensearch" >}}) | ❌ | ✅ |
| [Amazon S3 Vectors]({{< ref "docs/development/vector_stores#amazon-s3-vectors" >}}) | ❌ | ✅ |
| [Chroma]({{< ref "docs/development/vector_stores#chroma" >}}) | ✅ | ❌ |
| [Elasticsearch]({{< ref "docs/development/vector_stores#elasticsearch" >}}) | ❌ | ✅ |
| [Mem0]({{< ref "docs/development/vector_stores#mem0" >}}) | ✅ | ❌ |
| [Milvus]({{< ref "docs/development/vector_stores#milvus" >}}) | ❌ | ✅ |

**MCP Server**

| Provider | Python | Java |
|---|---|---|
| [MCP Server]({{< ref "docs/development/mcp" >}}) | ✅ | ✅ |

> **Note**: Java native MCP support requires **JDK 17+**. For JDK 11-16, the framework automatically uses the Python SDK via cross-language support, which works seamlessly without additional configuration. See [MCP]({{< ref "docs/development/mcp" >}}) for details.

## Q4: How to run agent in IDE.

To avoid potential conflict with Flink cluster, the scope of the dependencies related to Flink and Flink Agents for agent job are provided. See [Maven Dependencies]({{< ref "docs/get-started/installation#maven-dependencies-for-java" >}}) for details.

To run the examples in IDE, users must enable the IDE feature: `add dependencies with provided scope to classpath`.
* For **IDEA**, edit the **`Run/Debug Configuration`** and enable **`add dependencies with provided scope to classpath`**. See [Run/Debug Configuration](https://www.jetbrains.com/help/idea/run-debug-configuration-scala.html) for details.
