command line app STT, text to local LLM

python/tool-speechtotext/assistant.py

@@ -3,6 +3,7 @@ import numpy as np
 import pyperclip
 import requests
 import sys
+import argparse
 from faster_whisper import WhisperModel
 
 import os
@@ -10,12 +11,14 @@ os.environ["CT2_CUDA_ALLOW_FP16"] = "1"
 
 # --- Configuration ---
 MODEL_SIZE = "medium"  # Options: "base", "small", "medium", "large-v3"
-OLLAMA_URL = "http://localhost:11434/api/generate" # Default is 11434
-OLLAMA_MODEL = "qwen3:latest"
+OLLAMA_URL = "http://localhost:11434/api/generate"  # Default is 11434
+DEFAULT_OLLAMA_MODEL = "qwen3:latest"
 
-# Load Whisper on GPU 
+# Load Whisper on GPU
 # float16 is faster and uses less VRAM on NVIDIA cards
 print("Loading Whisper model...")
+
+
 try:
     model = WhisperModel(MODEL_SIZE, device="cuda", compute_type="float16")
 except Exception as e:
@@ -23,14 +26,15 @@ except Exception as e:
     print("Falling back to CPU (Check your CUDA/cuDNN installation)")
     model = WhisperModel(MODEL_SIZE, device="cuda", compute_type="int16")
 
+
 def record_audio():
-    fs = 16000 
+    fs = 16000
     print("\n[READY] Press Enter to START recording...")
     input()
     print("[RECORDING] Press Enter to STOP...")
-    
+
     recording = []
-    
+
     def callback(indata, frames, time, status):
         if status:
             print(status, file=sys.stderr)
@@ -38,42 +42,86 @@ def record_audio():
 
     with sd.InputStream(samplerate=fs, channels=1, callback=callback):
         input()
-        
+
     return np.concatenate(recording, axis=0)
 
+
 def main():
-    print(f"System active. Model: {OLLAMA_MODEL}")
+    # 1. Setup Parser
+    print(f"System active. Model: {DEFAULT_OLLAMA_MODEL}")
+    parser = argparse.ArgumentParser(description="Whisper + Ollama CLI")
+
+    # Known Arguments (Hardcoded logic)
+    parser.add_argument("--nollm", "-n", action='store_true',
+                        help="turn off llm")
+    parser.add_argument("--system", "-s", default=None,
+                        help="The system prompt for Ollama")
+    parser.add_argument("--model_size", default="base",
+                        help="Whisper model size: base, small, medium")
+    parser.add_argument(
+        "--ollama_model", default=DEFAULT_OLLAMA_MODEL, help="Ollama model name")
+    parser.add_argument(
+        "--num_ctx", default='5000', help="context length")
+    parser.add_argument(
+        "--temp", default='0.7', help="temperature")
+
+    # 2. Capture "Unknown" arguments
+    # args = known values, unknown = a list like ['--num_ctx', '4096', '--temp', '0.7']
+    args, unknown = parser.parse_known_args()
+
+    # Convert unknown list to a dictionary for the Ollama 'options' field
+    # This logic pairs ['--key', 'value'] into {key: value}
+    extra_options = {}
+    for i in range(0, len(unknown), 2):
+        key = unknown[i].lstrip('-')  # remove the '--'
+        val = unknown[i+1]
+        # Try to convert numbers to actual ints/floats
+        try:
+            val = float(val) if '.' in val else int(val)
+        except ValueError:
+            pass
+        extra_options[key] = val
+
     while True:
         try:
             audio_data = record_audio()
-            
+
             print("[TRANSCRIBING]...")
             segments, _ = model.transcribe(audio_data.flatten(), beam_size=5)
             text = "".join([segment.text for segment in segments]).strip()
-            
+
             if not text:
                 print("No speech detected. Try again.")
                 continue
 
-            print(f"You said: {text}")
+            # print(f"You said: {text}")
             pyperclip.copy(text)
 
-            # Send to Ollama
-            print(f"[OLLAMA] Thinking...")
-            response = requests.post(OLLAMA_URL, json={
-                "model": OLLAMA_MODEL,
-                "prompt": text,
-                "stream": False
-            })
-            
-            result = response.json().get("response", "")
-            print(f"\nLLM Response:\n{result}\n")
-            
+            if (args.nollm == False):
+                # Send to Ollama
+                print(f"[OLLAMA] Thinking...")
+                payload = {
+                    "model": args.ollama_model,
+                    "prompt": text,
+                    "stream": False,
+                    "options": extra_options,
+                }
+
+                if args.system:
+                    payload["system"] = args
+                response = requests.post(OLLAMA_URL, json=payload)
+
+                result = response.json().get("response", "")
+                print(f"\nLLM Response:\n{result}\n")
+            else:
+                print(f"\n{text}\n")
+
         except KeyboardInterrupt:
             print("\nExiting...")
             break
         except Exception as e:
             print(f"An error occurred: {e}")
 
+
 if __name__ == "__main__":
-    main()
+    main()