🌿 Fern Regeneration -- April 2, 2026

.github/workflows/ci.yml

@@ -1,46 +1,60 @@
 name: ci
-
-on:
-  push:
-  workflow_dispatch:
-
+on: [push]
 jobs:
   compile:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repo
-        uses: actions/checkout@v6
-
+        uses: actions/checkout@v4
       - name: Set up python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v4
         with:
-          python-version: '3.8'
-
+          python-version: 3.8
       - name: Bootstrap poetry
-        run: curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
-
+        run: |
+          curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
       - name: Install dependencies
         run: poetry install
-
       - name: Compile
         run: poetry run mypy .
-
   test:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repo
-        uses: actions/checkout@v6
-
+        uses: actions/checkout@v4
       - name: Set up python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v4
         with:
-          python-version: '3.8'
-
+          python-version: 3.8
       - name: Bootstrap poetry
-        run: curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
-
+        run: |
+          curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
       - name: Install dependencies
         run: poetry install
 
       - name: Test
         run: poetry run pytest -rP .
+
+  publish:
+    needs: [compile, test]
+    if: github.event_name == 'push' && contains(github.ref, 'refs/tags/')
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v4
+      - name: Set up python
+        uses: actions/setup-python@v4
+        with:
+          python-version: 3.8
+      - name: Bootstrap poetry
+        run: |
+          curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
+      - name: Install dependencies
+        run: poetry install
+      - name: Publish to pypi
+        run: |
+          poetry config repositories.remote https://upload.pypi.org/legacy/
+          poetry --no-interaction -v publish --build --repository remote --username "$PYPI_USERNAME" --password "$PYPI_PASSWORD"
+        env:
+          PYPI_USERNAME: ${{ secrets.PYPI_USERNAME }}
+          PYPI_PASSWORD: ${{ secrets.PYPI_PASSWORD }}

README.md

@@ -1,7 +1,7 @@
-# Agora Agent Server SDK for Python
+# Agoraio Python Library
 
 [![fern shield](https://img.shields.io/badge/%F0%9F%8C%BF-Built%20with%20Fern-brightgreen)](https://buildwithfern.com?utm_source=github&utm_medium=github&utm_campaign=readme&utm_source=https%3A%2F%2Fgithub.com%2FAgoraIO-Conversational-AI%2Fagent-server-sdk-python)
-[![pypi](https://img.shields.io/pypi/v/agent-server-sdk-python)](https://pypi.python.org/pypi/agent-server-sdk-python)
+[![pypi](https://img.shields.io/pypi/v/agora-agent-server-sdk)](https://pypi.python.org/pypi/agora-agent-server-sdk)
 
 The Agora Conversational AI SDK provides convenient access to the Agora Conversational AI APIs, 
 enabling you to build voice-powered AI agents with support for both cascading flows (ASR -> LLM -> TTS) 
@@ -30,7 +30,7 @@ and multimodal flows (MLLM) for real-time audio processing.
 ## Installation
 
 ```sh
-pip install agent-server-sdk-python
+pip install agora-agent-server-sdk
 ```
 
 ## Quick Start
@@ -155,37 +155,36 @@ A full reference for this library is available [here](https://github.com/AgoraIO
 For real-time audio processing using OpenAI's Realtime API or Google Gemini Live, use the MLLM (Multimodal Large Language Model) flow instead of the cascading ASR -> LLM -> TTS flow. See the [MLLM Overview](https://docs.agora.io/en/conversational-ai/models/mllm/overview) for more details.
 
 ```python
-from agora_agent import Agora, Area
-from agora_agent.agentkit import (
-    AdvancedFeatures,
-    TurnDetectionConfig,
-    TurnDetectionTypeValues,
-)
-from agora_agent.agents import (
+from agora-agent-server-sdk import Agora
+from agora-agent-server-sdk.agents import (
     StartAgentsRequestProperties,
+    StartAgentsRequestPropertiesAdvancedFeatures,
     StartAgentsRequestPropertiesMllm,
     StartAgentsRequestPropertiesMllmVendor,
     StartAgentsRequestPropertiesTts,
     StartAgentsRequestPropertiesTtsVendor,
     StartAgentsRequestPropertiesLlm,
+    StartAgentsRequestPropertiesTurnDetection,
+    StartAgentsRequestPropertiesTurnDetectionType,
 )
 
 client = Agora(
-    area=Area.US,
-    app_id="YOUR_APP_ID",
-    app_certificate="YOUR_APP_CERTIFICATE",
+    customer_id="YOUR_CUSTOMER_ID",
+    customer_secret="YOUR_CUSTOMER_SECRET",
 )
 
 client.agents.start(
-    client.app_id,
+    appid="your_app_id",
     name="mllm_agent",
     properties=StartAgentsRequestProperties(
         channel="channel_name",
         token="your_token",
         agent_rtc_uid="1001",
         remote_rtc_uids=["1002"],
         idle_timeout=120,
-        advanced_features=AdvancedFeatures(enable_mllm=True),
+        advanced_features=StartAgentsRequestPropertiesAdvancedFeatures(
+            enable_mllm=True,
+        ),
         mllm=StartAgentsRequestPropertiesMllm(
             url="wss://api.openai.com/v1/realtime",
             api_key="<your_openai_api_key>",
@@ -198,8 +197,8 @@ client.agents.start(
             output_modalities=["text", "audio"],
             greeting_message="Hello! I'm ready to chat in real-time.",
         ),
-        turn_detection=TurnDetectionConfig(
-            type=TurnDetectionTypeValues.SERVER_VAD,  # deprecated; use config.end_of_speech instead
+        turn_detection=StartAgentsRequestPropertiesTurnDetection(
+            type=StartAgentsRequestPropertiesTurnDetectionType.SERVER_VAD,
             threshold=0.5,
             silence_duration_ms=500,
         ),
@@ -215,6 +214,7 @@ client.agents.start(
 )
 ```
 
+
 ## MLLM Flow (Multimodal)
 
 For real-time audio processing using OpenAI's Realtime API or Google Gemini Live, use the MLLM (Multimodal Large Language Model) flow instead of the cascading ASR -> LLM -> TTS flow. See the [MLLM Overview](https://docs.agora.io/en/conversational-ai/models/mllm/overview) for more details.