Adding code to transcribe long audio files using streaming analyze content

dialogflow/analyze_content_stream.py

@@ -0,0 +1,114 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Google Cloud Dialogflow API sample code using the StreamingAnalyzeContent
+API.
+
+Also please contact Google to get credentials of this project and set up the
+credential file json locations by running:
+export GOOGLE_APPLICATION_CREDENTIALS=<cred_json_file_location>
+
+Example usage:
+    export GOOGLE_CLOUD_PROJECT='cloud-contact-center-ext-demo'
+    export CONVERSATION_PROFILE='FnuBYO8eTBWM8ep1i-eOng'
+    export GOOGLE_APPLICATION_CREDENTIALS='/Users/ruogu/Desktop/keys/cloud-contact-center-ext-demo-78798f9f9254.json'
+    export AUDIO_FILE_PATH='/Users/ruogu/Desktop/book_a_room.wav'
+
+    python analyze_content_stream.py
+
+"""
+
+import os
+import conversation_management
+import participant_management
+from pydub import AudioSegment
+import math
+
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+AUDIO_FILE_PATH = os.getenv("AUDIO_FILE_PATH")
+CONVERSATION_PROFILE_ID = os.getenv("CONVERSATION_PROFILE")
+
+
+def split_audio(audio_file_path, max_length_ms=5_000):
+    """Splits audio into chunks under max_length_ms."""
+    audio = AudioSegment.from_file(audio_file_path)
+    chunks = []
+    num_chunks = math.ceil(len(audio) / max_length_ms)
+    base_filename = os.path.splitext(audio_file_path)[0]
+
+    for i in range(num_chunks):
+        start = i * max_length_ms
+        end = min((i + 1) * max_length_ms, len(audio))
+        chunk = audio[start:end]
+        chunk_path = f"{base_filename}_part{i}.wav"
+        chunk.export(chunk_path, format="wav", parameters=["-ac", "1"])
+        chunks.append(chunk_path)
+
+    return chunks
+
+def run_analyze_content_streaming(conversation_profile_id, audio_file_path, project_id):
+    # Create conversation
+    conversation = conversation_management.create_conversation(
+        project_id=project_id,
+        conversation_profile_id=conversation_profile_id
+    )
+    conversation_id = conversation.name.split("conversations/")[1]
+
+    # Create participant
+    participant = participant_management.create_participant(
+        project_id=project_id,
+        conversation_id=conversation_id,
+        role="END_USER"
+    )
+    participant_id = participant.name.split("participants/")[1]
+
+    class stream_generator:
+        def __init__(self, audio_file_path):
+            self.audio_file_path = audio_file_path
+
+        def generator(self):
+            with open(self.audio_file_path, "rb") as audio_file:
+                while True:
+                    chunk = audio_file.read(10000)
+                    if not chunk:
+                        break
+                    # The later requests contains audio data.
+                    yield chunk
+
+    results = participant_management.analyze_content_audio_stream(
+        conversation_id=conversation_id,
+        participant_id=participant_id,
+        sample_rate_herz=48000,
+        stream=stream_generator(audio_file_path),
+        language_code="en-US",
+        timeout=300,
+    )
+
+    out = " ".join([result.message.content for result in results])    
+
+    print(f"🔊 Transcription: {out}")
+
+    # Complete conversation
+    conversation_management.complete_conversation(project_id, conversation_id)
+    return out
+
+if __name__ == "__main__":
+    audio_chunks = split_audio(AUDIO_FILE_PATH)
+    results = []
+    for chunk_path in audio_chunks:
+        print(f"Processing {chunk_path}...")
+        partial_result = run_analyze_content_streaming(CONVERSATION_PROFILE_ID, chunk_path, PROJECT_ID)
+        results.extend(partial_result)
+
+    print("Final Transcript: {}".format(''.join(results).strip()))

dialogflow/requirements.txt

@@ -4,3 +4,4 @@ pyaudio==0.2.14
 termcolor==3.0.0
 functions-framework==3.8.2
 Werkzeug==3.0.6
+pydub==0.25.1