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Merge remote-tracking branch 'origin/main'
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‎.github/workflows/release.yml‎

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name: Build and Release
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on:
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push:
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tags:
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- "v*"
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permissions:
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contents: write
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jobs:
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build-x86_64:
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name: Build (x86_64)
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runs-on: ubuntu-latest
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steps:
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- name: Install base dependencies
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shell: bash
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run: |
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set -euo pipefail
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export DEBIAN_FRONTEND=noninteractive
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sudo apt-get update
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sudo apt-get install -y --no-install-recommends \
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ca-certificates \
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pkg-config \
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libssl-dev \
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build-essential \
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git \
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curl \
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unzip
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- name: Check out repository
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uses: actions/checkout@v4
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- name: Set up Rust toolchain
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uses: dtolnay/rust-toolchain@stable
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- name: Add Rust target
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run: rustup target add x86_64-unknown-linux-gnu
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- name: Build binary
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run: cargo build --release --target x86_64-unknown-linux-gnu
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- name: Package release artifact
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id: package
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shell: bash
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run: |
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set -euo pipefail
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binary_path="target/x86_64-unknown-linux-gnu/release/echokit_server"
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if [ ! -f "$binary_path" ]; then
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echo "Release binary not found at $binary_path" >&2
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exit 1
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fi
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archive_name="echokit_server-${{ github.ref_name }}-x86_64-unknown-linux-gnu.tar.gz"
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mkdir -p dist
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cp "$binary_path" dist/echokit_server
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chmod +x dist/echokit_server
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tar -C dist -czf "$archive_name" echokit_server
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rm dist/echokit_server
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echo "archive=$archive_name" >> "$GITHUB_OUTPUT"
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- name: Upload artifact
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uses: actions/upload-artifact@v4
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with:
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name: echokit_server-x86_64-unknown-linux-gnu
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path: ${{ steps.package.outputs.archive }}
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build-aarch64:
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name: Build (aarch64)
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runs-on: ubuntu-latest
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container:
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image: debian:bookworm-slim
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steps:
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- name: Install base dependencies
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shell: bash
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run: |
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set -euo pipefail
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export DEBIAN_FRONTEND=noninteractive
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dpkg --add-architecture arm64
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apt-get update
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apt-get install -y --no-install-recommends \
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ca-certificates \
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pkg-config \
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libssl-dev \
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libssl-dev:arm64 \
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gcc-aarch64-linux-gnu \
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libc6-dev-arm64-cross \
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build-essential \
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git \
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curl \
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unzip
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- name: Check out repository
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uses: actions/checkout@v4
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- name: Set up Rust toolchain
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uses: dtolnay/rust-toolchain@stable
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- name: Add Rust target
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run: rustup target add aarch64-unknown-linux-gnu
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- name: Build binary
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env:
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CC_aarch64_unknown_linux_gnu: aarch64-linux-gnu-gcc
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AR_aarch64_unknown_linux_gnu: aarch64-linux-gnu-ar
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CARGO_TARGET_AARCH64_UNKNOWN_LINUX_GNU_LINKER: aarch64-linux-gnu-gcc
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PKG_CONFIG_ALLOW_CROSS: "1"
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PKG_CONFIG_PATH: /usr/lib/aarch64-linux-gnu/pkgconfig
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run: cargo build --release --target aarch64-unknown-linux-gnu
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- name: Package release artifact
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id: package
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shell: bash
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run: |
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set -euo pipefail
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binary_path="target/aarch64-unknown-linux-gnu/release/echokit_server"
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if [ ! -f "$binary_path" ]; then
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echo "Release binary not found at $binary_path" >&2
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exit 1
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fi
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archive_name="echokit_server-${{ github.ref_name }}-aarch64-unknown-linux-gnu.tar.gz"
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mkdir -p dist
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cp "$binary_path" dist/echokit_server
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chmod +x dist/echokit_server
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tar -C dist -czf "$archive_name" echokit_server
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rm dist/echokit_server
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echo "archive=$archive_name" >> "$GITHUB_OUTPUT"
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- name: Upload artifact
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uses: actions/upload-artifact@v4
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with:
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name: echokit_server-aarch64-unknown-linux-gnu
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path: ${{ steps.package.outputs.archive }}
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release:
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name: Publish release
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runs-on: ubuntu-latest
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needs:
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- build-x86_64
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- build-aarch64
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steps:
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- name: Download artifacts
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uses: actions/download-artifact@v4
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with:
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pattern: echokit_server-*
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path: artifacts
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merge-multiple: true
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- name: Prepare release files
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id: prepare
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shell: bash
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run: |
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set -euo pipefail
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mapfile -t archives < <(find artifacts -name '*.tar.gz' -type f)
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if [ "${#archives[@]}" -eq 0 ]; then
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echo "No release archives found" >&2
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exit 1
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fi
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{
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echo "files<<EOF"
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for archive in "${archives[@]}"; do
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echo "$archive"
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done
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echo "EOF"
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} >> "$GITHUB_OUTPUT"
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- name: Publish GitHub release
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uses: softprops/action-gh-release@v1
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with:
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tag_name: ${{ github.ref_name }}
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name: Echokit Server ${{ github.ref_name }}
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files: ${{ steps.prepare.outputs.files }}
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

‎README.md‎

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# Setup the EchoKit server
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# EchoKit Server
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EchoKit Server is the central component that manages communication between the EchoKit device and AI services. It can be deployed locally or connected to preset servers, allowing developers to customize LLM endpoints, plan the LLM prompt, configure speech models, and integrate additional AI features like MCP servers.
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EchoKit Server is the central component that manages communication between the [EchoKit device](https://echokit.dev/) and AI services. It can be deployed locally or connected to preset servers, allowing developers to customize LLM endpoints, plan the LLM prompt, configure speech models, and integrate additional AI features like MCP servers.
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<br>
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<div align="center">
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</div>
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</br>
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You will need an EchoKit device, or create your own ESP32 device with the [EchoKit firmware](https://github.com/second-state/echokit_box).
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You will need an [EchoKit device](https://echokit.dev/), or create your own ESP32 device with the [EchoKit firmware](https://github.com/second-state/echokit_box).
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## Features
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## Build
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EchoKit Server powers the full voice–AI interaction loop, making it easy for developers to run end-to-end speech pipelines with flexible model choices and custom integrations.
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### ASR → LLM → TTS Pipeline
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Seamlessly connect **ASR → LLM → TTS** for real-time, natural conversations.
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Each stage can be configured independently with your preferred models or APIs.
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#### Model Compatibility
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* **ASR (Speech Recognition):** Works with any API that’s *OpenAI-compatible*.
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* **LLM (Language Model):** Connect to any *OpenAI-spec* endpoint — local or cloud.
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* **TTS (Text-to-Speech):** Use any *OpenAI-spec* voice model for flexible deployment.
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* ElevenLabs (Streaming Mode)
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### End-to-End Model Pipelines
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Out-of-the-box support for:
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* **Gemini** — Google’s multimodal model
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* **Qwen Real-Time** — Alibaba’s powerful open LLM
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### Developer Customization
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* Deploy **locally** or connect to **remote inference servers**
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* Define your own **LLM prompts** and **response workflows**
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* Configure **speech and voice models** for different personas or use cases
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* Integrate **MCP servers** for extended functionality
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## Set up the EchoKit server
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### Build
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```
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git clone https://github.com/second-state/echokit_server
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cargo build --release
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```
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## Configure AI services
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### Configure AI services
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The `config.toml` can use any combination of open-source or proprietary AI services, as long as they offer OpenAI-compatible API endpoints. Here are instructions to start open source AI servers for the EchoKit server.
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You can also [configure MCP servers](examples/gaia/mcp/config.toml) to give the EchoKit server tool use capabilities.
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## Configure the voice prompt
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### Configure the voice prompt
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The `hello.wav` file on the server is sent to the EchoKit device when it connects. It is the voice prompt the device will say to tell the user that it is ready.
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## Run the EchoKit server
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### Run the EchoKit server
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```
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export RUST_LOG=debug
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nohup target/release/echokit_server &
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```
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## Test on a web page
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### Test on a web page
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Go here: https://echokit.dev/chat/
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In the web page, set the URL to your own EchoKit server address, and start chatting!
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## Configure a new device
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### Configure a new device
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Go to web page: https://echokit.dev/setup/ and use Bluetooth to connect to the `GAIA ESP332` device.
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![Configure Wifi](https://hackmd.io/_uploads/HJkh5ZjVee.png)
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## Use the device
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### Use the device
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**Chat:** press the `K0` button once or multiple times util the screen shows "Listening ...". You can now speak and it will answer.
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**Chat:** press the `K0` button once or multiple times until the screen shows "Listening ...". You can now speak and it will answer.
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**Record:** long press the `K0` until the screen shows "Recording ...". You can now speak and the audio will be recorded on the server.
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