Refactor project structure for modularity

Move model and pipeline components into dedicated modules
Extract utilities from CLI into shared helpers
Update imports throughout codebase
Refactor project structure for modularity

Move model configuration and hardware selection into `models/` package
Extract pipeline steps into `pipeline/` package
Add utility helpers in `utils/` package
Update CLI imports and references

src/audio_summary/pipeline/summarization.py

@@ -0,0 +1,39 @@
+"""Text summarization with Qwen3 on Apple Silicon via mlx-lm."""
+
+from mlx_lm import generate, load
+
+SYSTEM_PROMPT = "I would like for you to assume the role of a Technical Expert."
+
+USER_PROMPT_TEMPLATE = """Generate a concise summary of the text below.
+Text : {text}
+Add a title to the summary.
+Make sure your summary has useful and true information about the main points of the topic.
+Begin with a short introduction explaining the topic. If you can, use bullet points to list important details,
+and finish your summary with a concluding sentence."""
+
+
+def summarize_text(text: str, model_repo: str, max_tokens: int = 2048) -> str:
+    """Summarize ``text`` using the Qwen3 model at ``model_repo``."""
+    print(f"Loading summarization model: {model_repo}")
+    model, tokenizer = load(model_repo)
+
+    messages = [
+        {"role": "system", "content": SYSTEM_PROMPT},
+        {"role": "user", "content": USER_PROMPT_TEMPLATE.format(text=text)},
+    ]
+
+    # Qwen3 supports a "thinking" mode; disable it for clean, direct summaries.
+    prompt = tokenizer.apply_chat_template(
+        messages,
+        add_generation_prompt=True,
+        enable_thinking=False,
+    )
+
+    summary = generate(
+        model,
+        tokenizer,
+        prompt=prompt,
+        max_tokens=max_tokens,
+        verbose=False,
+    )
+    return summary.strip()