feat: use timestamps in file names

This allows us to run multiple recordings at once.

.gitignore

@@ -0,0 +1,3 @@
+*.json
+*.txt
+*.wav

README.md

@@ -1,20 +1,10 @@
-# New Repository Template
+# Meeting Minutes
 
-This template contains all of our basic files for a new GitHub repository. There is also a handy workflow that will create an issue on a new repository made from this template, with a checklist for the steps we usually take in setting up a new repository.
+This is a local recording, transcription, and summarisation script that listens to your meeting and generates a summary. This is completely offline, to protect your data privacy.
-
-If you're starting a Node.JS project with TypeScript, we have a [specific template](https://github.com/naomi-lgbt/nodejs-typescript-template) for that purpose.
-
-## Readme
-
-Delete all of the above text (including this line), and uncomment the below text to use our standard readme template.
-
-<!-- # Project Name
-
-Project Description
 
 ## Live Version
 
-This page is currently deployed. [View the live website.]
+Gotta run it locally. Sorry!
 
 ## Feedback and Bugs
 
@@ -36,4 +26,4 @@ Copyright held by Naomi Carrigan.
 
 ## Contact
 
-We may be contacted through our [Chat Server](http://chat.nhcarrigan.com) or via email at `contact@nhcarrigan.com`. -->
+We may be contacted through our [Chat Server](http://chat.nhcarrigan.com) or via email at `contact@nhcarrigan.com`.

main.py

@@ -0,0 +1,84 @@
+import subprocess
+import json
+import datetime
+
+# === CONFIG ===
+# Use current timestamp for file naming
+TIMESTAMP = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+MEETING_FILE = f"meeting_audio_{TIMESTAMP}.wav"
+WHISPER_MODEL = "small.en"
+DURATION = 36000  # seconds (10 hour max)
+OUTPUT_TRANSCRIPT = f"meeting_audio_{TIMESTAMP}.json"
+OUTPUT_SUMMARY = f"summary_{TIMESTAMP}.txt"
+
+def record_audio():
+    print("🎙 Recording meeting audio... (q to stop early)")
+    subprocess.run([
+        "ffmpeg",
+        "-f", "pulse",              # Linux (change for Windows/macOS)
+        "-i", "default",            # capture default input/output mix
+        "-t", str(DURATION),
+        "-ac", "2",
+        "-ar", "44100",
+        MEETING_FILE
+    ], check=True)
+
+def transcribe_audio():
+    print("🔠 Transcribing with WhisperX...")
+    subprocess.run([
+        # "pipenv run python3 -m whisperx",
+        "whisper",
+        MEETING_FILE,
+        "--device", "cpu",  # Use CPU
+        "--language", "en",
+        # "--diarize", Put back when whisperX works.
+        "--model", WHISPER_MODEL,
+        "--output_format", "json",
+        "--output_dir", "."
+    ], check=True)
+
+def summarize_with_local_model():
+    print("🧾 Summarizing locally with Ollama...")
+    with open(OUTPUT_TRANSCRIPT, "r", encoding="utf-8") as f:
+        transcript = json.load(f)
+
+    text = "\n".join(
+        seg["text"]
+        for seg in transcript["segments"]
+    )
+
+    prompt = f"""Summarize this meeting transcript into clear bullet points with:
+    - Key decisions
+    - Action items
+    - Notable discussion points
+    
+    Transcript:
+    {text}
+    """
+
+    result = subprocess.run(
+        ["ollama", "run", "llama3:8b"],
+        input=prompt.encode(),
+        capture_output=True,
+        check=True
+    )
+
+    summary = result.stdout.decode()
+
+    with open(OUTPUT_SUMMARY, "w", encoding="utf-8") as f:
+        f.write(summary)
+
+    print("✅ Summary written to", OUTPUT_SUMMARY)
+
+def cleanup():
+    import os
+    if os.path.exists(MEETING_FILE):
+        os.remove(MEETING_FILE)
+    if os.path.exists(OUTPUT_TRANSCRIPT):
+        os.remove(OUTPUT_TRANSCRIPT)
+
+if __name__ == "__main__":
+    record_audio()
+    transcribe_audio()
+    summarize_with_local_model()
+    cleanup()