style: fix ruff lint and formatting issues

- tts.py: rename ambiguous variable 'l' to 'line' (E741)
- tts.py, llm.py: apply ruff formatter

llm.py

@@ -168,10 +168,12 @@ async def chat_stream(
         messages.append({"role": "system", "content": system_prompt})
 
     for entry in history:
-        messages.append({
+        messages.append(
+            {
                 "role": entry["role"],
                 "content": _extract_content(entry["content"]),
-        })
+            }
+        )
 
     messages.append({"role": "user", "content": message})
 
@@ -214,7 +216,9 @@ async def chat_stream(
                         continue
 
                 latency = time.time() - start_time
-                logger.info("LLM streamed response: %d chars in %.1fs", len(full_text), latency)
+                logger.info(
+                    "LLM streamed response: %d chars in %.1fs", len(full_text), latency
+                )
 
                 # Best-effort metrics from the final SSE payload
                 _log_llm_metrics(
@@ -229,9 +233,7 @@ async def chat_stream(
                 # Non-streaming fallback (endpoint doesn't support stream)
                 body = await response.aread()
                 result = json.loads(body)
-                text = _extract_content(
+                text = _extract_content(result["choices"][0]["message"]["content"])
-                    result["choices"][0]["message"]["content"]
-                )
                 latency = time.time() - start_time
                 usage = result.get("usage", {})
 

tts.py

@@ -132,8 +132,16 @@ LANGUAGES = {
 _SENTENCE_RE = re.compile(r"(?<=[.!?;])\s+|(?<=\n)\s*", re.MULTILINE)
 
 _DIGIT_WORDS = {
-    "0": "zero", "1": "one", "2": "two", "3": "three", "4": "four",
+    "0": "zero",
-    "5": "five", "6": "six", "7": "seven", "8": "eight", "9": "nine",
+    "1": "one",
+    "2": "two",
+    "3": "three",
+    "4": "four",
+    "5": "five",
+    "6": "six",
+    "7": "seven",
+    "8": "eight",
+    "9": "nine",
 }
 
 
@@ -190,6 +198,7 @@ def _split_sentences(text: str) -> list[str]:
 
 # ─── Audio helpers ───────────────────────────────────────────────────────
 
+
 def _read_wav_bytes(data: bytes) -> tuple[int, np.ndarray]:
     """Read WAV audio from bytes, handling scipy wavfile and standard WAV.
 
@@ -211,7 +220,9 @@ def _read_wav_bytes(data: bytes) -> tuple[int, np.ndarray]:
         elif sampwidth == 4:
             audio = np.frombuffer(raw, dtype=np.int32).astype(np.float32) / 2147483648.0
         elif sampwidth == 1:
-            audio = (np.frombuffer(raw, dtype=np.uint8).astype(np.float32) - 128.0) / 128.0
+            audio = (
+                np.frombuffer(raw, dtype=np.uint8).astype(np.float32) - 128.0
+            ) / 128.0
         else:
             raise ValueError(f"Unsupported sample width: {sampwidth}")
 
@@ -237,7 +248,8 @@ def _read_wav_bytes(data: bytes) -> tuple[int, np.ndarray]:
     # Last resort: raw 16-bit PCM at 22050 Hz
     logger.warning(
         "Could not parse WAV header (len=%d, first 4 bytes=%r); raw PCM decode",
-        len(data), data[:4],
+        len(data),
+        data[:4],
     )
     audio = np.frombuffer(data, dtype=np.int16).astype(np.float32) / 32768.0
     return 22050, audio
@@ -272,6 +284,7 @@ def _concat_audio(
 
 # ─── TTS synthesis ───────────────────────────────────────────────────────
 
+
 def _synthesize_chunk(text: str, lang_code: str, speed: float = 1.0) -> bytes:
     """Synthesize a single text chunk via the TTS backend.
 
@@ -303,7 +316,9 @@ def _synthesize_chunk(text: str, lang_code: str, speed: float = 1.0) -> bytes:
         # Non-JSON response — treat as raw audio bytes
         return resp.content
     except Exception:
-        logger.debug("POST endpoint failed, falling back to GET /api/tts", exc_info=True)
+        logger.debug(
+            "POST endpoint failed, falling back to GET /api/tts", exc_info=True
+        )
 
     # Fallback: Coqui-compatible GET (no speed control)
     resp = client.get(
@@ -426,11 +441,16 @@ in multiple languages. Long text is automatically split into sentences for bette
                             label="Language",
                         )
                         speed = gr.Slider(
-                            minimum=0.5, maximum=2.0, value=1.0,
+                            minimum=0.5,
-                            step=0.1, label="Speed",
+                            maximum=2.0,
+                            value=1.0,
+                            step=0.1,
+                            label="Speed",
                         )
                         synthesize_btn = gr.Button(
-                            "🔊 Synthesize", variant="primary", scale=2,
+                            "🔊 Synthesize",
+                            variant="primary",
+                            scale=2,
                         )
                 with gr.Column(scale=1):
                     status_output = gr.Textbox(label="Status", interactive=False)
@@ -446,9 +466,21 @@ in multiple languages. Long text is automatically split into sentences for bette
 
             gr.Examples(
                 examples=[
-                    ["Hello! Welcome to Davies Tech Labs. This is a demonstration of our text-to-speech system.", "English", 1.0],
+                    [
-                    ["The quick brown fox jumps over the lazy dog. This sentence contains every letter of the alphabet.", "English", 1.0],
+                        "Hello! Welcome to Davies Tech Labs. This is a demonstration of our text-to-speech system.",
-                    ["Bonjour! Bienvenue au laboratoire technique de Davies.", "French", 1.0],
+                        "English",
+                        1.0,
+                    ],
+                    [
+                        "The quick brown fox jumps over the lazy dog. This sentence contains every letter of the alphabet.",
+                        "English",
+                        1.0,
+                    ],
+                    [
+                        "Bonjour! Bienvenue au laboratoire technique de Davies.",
+                        "French",
+                        1.0,
+                    ],
                     ["Hola! Bienvenido al laboratorio de tecnología.", "Spanish", 1.0],
                     ["Guten Tag! Willkommen im Techniklabor.", "German", 1.0],
                 ],
@@ -462,9 +494,15 @@ in multiple languages. Long text is automatically split into sentences for bette
                 label="Text to Compare", value="Hello, how are you today?", lines=2
             )
             with gr.Row():
-                lang1 = gr.Dropdown(choices=list(LANGUAGES.keys()), value="English", label="Language 1")
+                lang1 = gr.Dropdown(
-                lang2 = gr.Dropdown(choices=list(LANGUAGES.keys()), value="Spanish", label="Language 2")
+                    choices=list(LANGUAGES.keys()), value="English", label="Language 1"
-                compare_speed = gr.Slider(minimum=0.5, maximum=2.0, value=1.0, step=0.1, label="Speed")
+                )
+                lang2 = gr.Dropdown(
+                    choices=list(LANGUAGES.keys()), value="Spanish", label="Language 2"
+                )
+                compare_speed = gr.Slider(
+                    minimum=0.5, maximum=2.0, value=1.0, step=0.1, label="Speed"
+                )
 
             compare_btn = gr.Button("Compare Languages", variant="primary")
 
@@ -497,15 +535,23 @@ in multiple languages. Long text is automatically split into sentences for bette
                 placeholder="Enter multiple texts, one per line...",
                 lines=6,
             )
-            batch_lang = gr.Dropdown(choices=list(LANGUAGES.keys()), value="English", label="Language")
+            batch_lang = gr.Dropdown(
-            batch_speed = gr.Slider(minimum=0.5, maximum=2.0, value=1.0, step=0.1, label="Speed")
+                choices=list(LANGUAGES.keys()), value="English", label="Language"
+            )
+            batch_speed = gr.Slider(
+                minimum=0.5, maximum=2.0, value=1.0, step=0.1, label="Speed"
+            )
             batch_btn = gr.Button("Synthesize All", variant="primary")
 
             batch_status = gr.Textbox(label="Status", interactive=False)
             batch_audio = gr.Audio(label="Combined Audio", type="numpy")
 
             def batch_synthesize(texts_raw: str, lang: str, spd: float):
-                lines = [l.strip() for l in texts_raw.strip().splitlines() if l.strip()]
+                lines = [
+                    line.strip()
+                    for line in texts_raw.strip().splitlines()
+                    if line.strip()
+                ]
                 if not lines:
                     return "❌ Please enter at least one line of text", None
                 combined = "\n".join(lines)