add batch transcription playground

Author: ks6088ts

.env.template

@@ -20,6 +20,7 @@ AZURE_OPENAI_API_VERSION="2025-04-01-preview"
 AZURE_OPENAI_MODEL_CHAT="gpt-5"
 AZURE_OPENAI_MODEL_EMBEDDING="text-embedding-3-small"
 AZURE_OPENAI_MODEL_REASONING="o4-mini"
+AZURE_OPENAI_MODEL_STT="whisper"
 
 ## Azure AI Foundry
 AZURE_AI_FOUNDRY_INFERENCE_ENDPOINT="https://xxx.services.ai.azure.com/api/projects/xxx"

pyproject.toml

@@ -5,6 +5,7 @@ description = "A GitHub template repository for Python"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
+    "audio-recorder-streamlit>=0.0.10",
     "azure-ai-projects>=1.0.0",
     "azure-cosmos>=4.9.0",
     "azure-identity>=1.23.1",

template_langgraph/services/streamlits/pages/playground_batch_transcription.py

@@ -0,0 +1,80 @@
+import tempfile
+from os import getenv
+
+import streamlit as st
+from audio_recorder_streamlit import audio_recorder
+from dotenv import load_dotenv
+from langchain_community.document_loaders.parsers.audio import AzureOpenAIWhisperParser
+from langchain_core.documents.base import Blob
+
+from template_langgraph.loggers import get_logger
+
+load_dotenv(override=True)
+logger = get_logger(__name__)
+logger.setLevel("DEBUG")
+
+with st.sidebar:
+    "# Common Settings"
+    azure_openai_endpoint = st.text_input(
+        label="AZURE_OPENAI_ENDPOINT",
+        value=getenv("AZURE_OPENAI_ENDPOINT"),
+        key="AZURE_OPENAI_ENDPOINT",
+        type="default",
+    )
+    azure_openai_api_key = st.text_input(
+        label="AZURE_OPENAI_API_KEY",
+        value=getenv("AZURE_OPENAI_API_KEY"),
+        key="AZURE_OPENAI_API_KEY",
+        type="password",
+    )
+    azure_openai_api_version = st.text_input(
+        label="AZURE_OPENAI_API_VERSION",
+        value=getenv("AZURE_OPENAI_API_VERSION"),
+        key="AZURE_OPENAI_API_VERSION",
+        type="default",
+    )
+    azure_openai_model_stt = st.text_input(
+        label="AZURE_OPENAI_MODEL_STT",
+        value=getenv("AZURE_OPENAI_MODEL_STT"),
+        key="AZURE_OPENAI_MODEL_STT",
+        type="default",
+    )
+    "### Documents"
+    "[Azure OpenAI Whisper Parser](https://python.langchain.com/docs/integrations/document_loaders/parsers/azure_openai_whisper_parser/)"
+
+st.title("🎤 Batch Transcription Playground")
+
+audio_bytes = audio_recorder(
+    text="Click to record",
+    recording_color="red",
+    neutral_color="gray",
+    icon_name="microphone",
+    icon_size="6x",
+)
+
+if audio_bytes:
+    st.audio(audio_bytes, format="audio/wav")
+    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as temp_audio_file:
+        temp_audio_file.write(audio_bytes)
+        temp_audio_file_path = temp_audio_file.name
+    st.write(f"Audio saved to temporary file: {temp_audio_file_path}")
+
+if st.button("Transcribe", disabled=audio_bytes is None):
+    with st.spinner("Transcribing..."):
+        try:
+            audio_blob = Blob(path=temp_audio_file_path)
+            parser = AzureOpenAIWhisperParser(
+                api_key=azure_openai_api_key,
+                azure_endpoint=azure_openai_endpoint,
+                api_version=azure_openai_api_version,
+                deployment_name=azure_openai_model_stt,
+            )
+            documents = parser.lazy_parse(
+                blob=audio_blob,
+            )
+            results = [doc.page_content for doc in documents]
+            st.success("Transcription completed!")
+            st.text_area("Transcription Result", value="\n".join(results), height=200)
+        except Exception as e:
+            logger.error(f"Error during transcription: {e}")
+            st.error(f"Error during transcription: {e}")