WIP: add ai speech sample

.env.template

@@ -31,6 +31,7 @@ AZURE_BLOB_CONTAINER_NAME="audio"
 # Azure AI Speech
 AZURE_AI_SPEECH_API_ENDPOINT="https://<speech-api-name>.cognitiveservices.azure.com/"
 AZURE_AI_SPEECH_API_SUBSCRIPTION_KEY="<speech-api-subscription-key>"
+AZURE_AI_SPEECH_API_REGION="eastus"
 
 # Bing search resource
 BING_SUBSCRIPTION_KEY="<bing-subscription-key>"

.gitignore

@@ -167,3 +167,5 @@ generated/
 *.jpg
 *.jpeg
 .chroma
+.stop
+.transcribed.txt

apps/14_streamlit_azure_ai_speech/README.md

@@ -0,0 +1,26 @@
+# Realtime transcription with Azure AI Speech Service
+
+This app demonstrates how to use Azure AI Speech Service for realtime transcription.
+
+## Prerequisites
+
+- Python 3.10 or later
+- Azure AI Speech Service
+- Azure OpenAI Service
+
+## Overview
+
+```shell
+# Speech to Text script
+poetry run python apps/14_streamlit_azure_ai_speech/speech_to_text.py --help
+
+# WIP: Streamlit app
+poetry run python -m streamlit run apps/14_streamlit_azure_ai_speech/main.py
+```
+
+# References
+
+- [How to recognize speech](https://learn.microsoft.com/azure/ai-services/speech-service/how-to-recognize-speech?pivots=programming-language-python)
+- [Quickstart: Create real-time diarization](https://learn.microsoft.com/azure/ai-services/speech-service/get-started-stt-diarization?tabs=windows&pivots=programming-language-python)
+- [Speech to text containers with Docker](https://learn.microsoft.com/azure/ai-services/speech-service/speech-container-stt?tabs=container&pivots=programming-language-python)
+- [AzureSpeechService でリアルタイム議事録](https://zenn.dev/o_ken_surprise/articles/991f5b592b91ee)

apps/14_streamlit_azure_ai_speech/main.py

@@ -0,0 +1,210 @@
+import pathlib
+import subprocess
+from os import getenv
+
+import streamlit as st
+from dotenv import load_dotenv
+from openai import AzureOpenAI
+
+load_dotenv()
+
+# Initialize the session state
+if "transcribed_result" not in st.session_state:
+    st.session_state["transcribed_result"] = ""
+
+with st.sidebar:
+    inference_type = st.selectbox(
+        label="INEFERENCE_TYPE",
+        options=[
+            "azure",
+            "local",
+        ],
+        key="INEFERENCE_TYPE",
+    )
+    azure_ai_speech_api_language = st.selectbox(
+        label="AZURE_AI_SPEECH_API_LANGUAGE",
+        options=[
+            "en-US",
+            "ja-JP",
+        ],
+        key="AZURE_AI_SPEECH_API_LANGUAGE",
+    )
+    if inference_type == "local":
+        path_to_model = st.text_input(
+            label="PATH_TO_MODEL",
+            value="./model",
+            key="PATH_TO_MODEL",
+            type="default",
+        )
+        stt_host = st.text_input(
+            label="STT_HOST",
+            value="ws://localhost:5000",
+            key="STT_HOST",
+            type="default",
+        )
+        st.warning("yet to be implemented")
+    if inference_type == "azure":
+        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_gpt_model = st.text_input(
+            label="AZURE_OPENAI_GPT_MODEL",
+            value=getenv("AZURE_OPENAI_GPT_MODEL"),
+            key="AZURE_OPENAI_GPT_MODEL",
+            type="default",
+        )
+        azure_ai_speech_api_subscription_key = st.text_input(
+            label="AZURE_AI_SPEECH_API_SUBSCRIPTION_KEY",
+            value=getenv("AZURE_AI_SPEECH_API_SUBSCRIPTION_KEY"),
+            key="AZURE_AI_SPEECH_API_SUBSCRIPTION_KEY",
+            type="password",
+        )
+        azure_ai_speech_api_region = st.text_input(
+            label="AZURE_AI_SPEECH_API_REGION",
+            value=getenv("AZURE_AI_SPEECH_API_REGION"),
+            key="AZURE_AI_SPEECH_API_REGION",
+            type="default",
+        )
+    "[Azure Portal](https://portal.azure.com/)"
+    "[Azure OpenAI Studio](https://oai.azure.com/resource/overview)"
+    "[View the source code](https://github.com/ks6088ts-labs/workshop-azure-openai/blob/main/apps/14_streamlit_azure_ai_speech/main.py)"
+
+
+def is_configured():
+    if inference_type == "local":
+        return path_to_model and stt_host
+    if inference_type == "azure":
+        return azure_openai_api_key and azure_openai_endpoint and azure_openai_api_version and azure_openai_gpt_model
+
+
+st.title("transcribe text")
+
+if not is_configured():
+    st.warning("Please fill in the required fields at the sidebar.")
+
+st.info("This is a sample to transcribe text.")
+
+# ---
+# 2 column layout
+
+# 1st row
+row1_left, row1_right = st.columns(2)
+with row1_left:
+    input = st.text_area(
+        "Transcribed text",
+        height=400,
+        placeholder="Please enter the text to transcribe.",
+        key="input",
+        value=st.session_state["transcribed_result"],
+    )
+
+with row1_right:
+    start_transcribe_button = st.button("start", disabled=not is_configured())
+    stop_transcribe_button = st.button("stop", disabled=not is_configured())
+    transcription_status = st.empty()
+
+# line break horizontal line
+st.markdown("---")
+
+# 2nd row
+row2_left, row2_right = st.columns(2)
+
+with row2_left:
+    selected_task = st.selectbox(
+        "Task",
+        [
+            "Create summaries from the following text",
+            "Extract 3 main points from the following text",
+            # Add more tasks here
+        ],
+        key="selected_task",
+        index=0,
+    )
+
+with row2_right:
+    run_task_button = st.button("run_task", disabled=not is_configured())
+
+path_to_transcribed_text = ".transcribed.txt"
+
+
+def start_recognition():
+    global process
+    if inference_type == "local":
+        command = f"python apps/14_streamlit_azure_ai_speech/speech_to_text.py --output {path_to_transcribed_text} --endpoint {stt_host} --language {azure_ai_speech_api_language} --type local --verbose"  # noqa
+        process = subprocess.Popen(command, shell=True)
+        st.warning("Local inference is not yet implemented.")
+        return
+    if inference_type == "azure":
+        command = f"python apps/14_streamlit_azure_ai_speech/speech_to_text.py --output {path_to_transcribed_text} --subscription {azure_ai_speech_api_subscription_key} --region {azure_ai_speech_api_region} --language {azure_ai_speech_api_language} --type azure --verbose"  # noqa
+        process = subprocess.Popen(command, shell=True)
+
+
+def run_task(selected_task: str, input: str) -> str:
+    if inference_type == "local":
+        st.warning("Local inference is not yet implemented.")
+        return
+    if inference_type == "azure":
+        client = AzureOpenAI(
+            api_key=azure_openai_api_key,
+            api_version=azure_openai_api_version,
+            azure_endpoint=azure_openai_endpoint,
+        )
+
+        response = client.chat.completions.create(
+            model=azure_openai_gpt_model,
+            messages=[
+                {
+                    "role": "system",
+                    "content": f"""
+                        Task: {selected_task}.
+                        ---
+                        {input}
+                        ---
+                    """,
+                },
+            ],
+        )
+        return response.choices[0].message.content
+    raise ValueError(f"Inference type is not supported: {inference_type}")
+
+
+def load_transcribed_text():
+    with open(path_to_transcribed_text) as f:
+        return f.read()
+
+
+if start_transcribe_button:
+    if not st.session_state.get("process"):
+        transcription_status.info(f"Transcribing... (language={azure_ai_speech_api_language})")
+        start_recognition()
+    else:
+        transcription_status.warning("Transcription is already running.")
+
+if stop_transcribe_button:
+    pathlib.Path(".stop").touch()
+    output = load_transcribed_text()
+    st.session_state.transcribed_result = output
+    st.rerun()
+
+if run_task_button:
+    with st.spinner("Running..."):
+        output = run_task(
+            selected_task=selected_task,
+            input=input,
+        )
+        st.write(output)