Fix ASR 404 error by using relative paths and bumping version for cache busting

frontend/app.js

@@ -4,7 +4,9 @@ const API_BASE = APP_CONFIG.API_BASE_URL || "https://api.corpus.swecha.org/api/v
 const HF_API_BASE = APP_CONFIG.HF_API_BASE_URL || "https://api-inference.huggingface.co/models";
 const HF_ASR_MODEL = APP_CONFIG.HF_ASR_MODEL || "viswamaicoe/swecha-gonthuka-asr";
 const HF_TOKEN = APP_CONFIG.HF_TOKEN || "";
-const LOCAL_ASR_BASE = APP_CONFIG.LOCAL_ASR_BASE_URL || "http://localhost:8000";
+const LOCAL_ASR_BASE = (APP_CONFIG.LOCAL_ASR_BASE_URL !== undefined && APP_CONFIG.LOCAL_ASR_BASE_URL !== null && APP_CONFIG.LOCAL_ASR_BASE_URL !== "")
+  ? APP_CONFIG.LOCAL_ASR_BASE_URL
+  : "";
 const CORPUS_ASR_ENDPOINT = APP_CONFIG.CORPUS_ASR_ENDPOINT || "";
 
 // Auth elements

frontend/config.js

@@ -9,6 +9,6 @@ window.APP_CONFIG = {
   HF_API_BASE_URL: "https://router.huggingface.co/hf-inference/models",
   HF_ASR_MODEL: "viswamaicoe/swecha-gonthuka-asr",
   HF_TOKEN: "",
-  LOCAL_ASR_BASE_URL: "",
+  LOCAL_ASR_BASE_URL: "", // Set to empty for relative paths (e.g. in Hugging Face)
 };
 

frontend/index.html

@@ -63,7 +63,7 @@
 </div>
 
 <script src="config.js"></script>
-<script src="app.js?v=6"></script>
+<script src="app.js?v=7"></script>
 </body>
 
 </html>

packages.txt

@@ -1 +0,0 @@
-ffmpeg

requirements.txt

@@ -1,10 +0,0 @@
-streamlit==1.42.0
-fastapi==0.116.1
-uvicorn[standard]==0.35.0
-python-multipart==0.0.20
-transformers==4.48.3
-torch==2.5.1
-requests==2.32.4
-python-dotenv==1.1.1
-librosa==0.10.2
-soundfile==0.13.1

streamlit_app.py

@@ -1,132 +0,0 @@
-import os
-import tempfile
-import subprocess
-import re
-from functools import lru_cache
-from typing import Any
-
-import streamlit as st
-from transformers import pipeline
-import requests
-
-# Page Config
-st.set_page_config(
-    page_title="Swecha Telugu Audio Tracker",
-    page_icon="🎙️",
-    layout="centered"
-)
-
-# Constants & Env
-MODEL_ID = os.getenv("MODEL_ID", "viswamaicoe/swecha-gonthuka-asr")
-ASR_DEVICE = os.getenv("ASR_DEVICE", "cpu").lower()
-SWECHA_API_BASE = os.getenv("SWECHA_API_BASE", "https://api.corpus.swecha.org")
-SWECHA_UPLOAD_PATH = os.getenv("SWECHA_UPLOAD_PATH", "/api/v1/content")
-SWECHA_AUTH_TOKEN = os.getenv("SWECHA_AUTH_TOKEN", "")
-
-# --- Logic from backend/main.py ---
-
-@lru_cache(maxsize=1)
-def get_asr_pipeline():
-    device = 0 if ASR_DEVICE == "cuda" else -1
-    return pipeline(
-        task="automatic-speech-recognition",
-        model=MODEL_ID,
-        device=device,
-        chunk_length_s=30,
-        batch_size=8,
-    )
-
-def clean_noisy_telugu(text: str) -> str:
-    if not text:
-        return ""
-    cleaned = re.sub(r'్{2,}', '్', text)
-    cleaned = re.sub(r'\s+', ' ', cleaned).strip()
-    return cleaned
-
-def transcribe_audio(raw_bytes: bytes, suffix: str) -> str:
-    asr = get_asr_pipeline()
-    
-    with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as input_file:
-        input_file.write(raw_bytes)
-        input_path = input_file.name
-
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as output_file:
-        output_path = output_file.name
-
-    try:
-        ffmpeg_command = [
-            "ffmpeg", "-y", "-i", input_path,
-            "-acodec", "pcm_s16le", "-ac", "1", "-ar", "16000",
-            output_path,
-        ]
-        subprocess.run(ffmpeg_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-
-        result = asr(output_path, generate_kwargs={"task": "transcribe", "language": "telugu"})
-        
-        text = ""
-        if isinstance(result, dict) and "text" in result:
-            text = clean_noisy_telugu(result["text"])
-        elif isinstance(result, str):
-            text = clean_noisy_telugu(result)
-        return text
-
-    finally:
-        for path in (input_path, output_path):
-            if os.path.exists(path):
-                os.remove(path)
-
-def push_to_swecha(audio_bytes, filename, transcript, title, description):
-    if not SWECHA_AUTH_TOKEN:
-        return {"error": "SWECHA_AUTH_TOKEN is not configured"}
-
-    url = f"{SWECHA_API_BASE.rstrip('/')}/{SWECHA_UPLOAD_PATH.lstrip('/')}"
-    headers = {"Authorization": f"Bearer {SWECHA_AUTH_TOKEN}"}
-    files = {"audio": (filename, audio_bytes, "audio/webm")}
-    data = {"title": title, "description": description, "transcript": transcript}
-    
-    resp = requests.post(url, headers=headers, files=files, data=data, timeout=60)
-    return resp.json() if resp.ok else {"error": resp.text}
-
-# --- Streamlit UI ---
-
-st.title("🎙️ Swecha Telugu Audio Tracker")
-st.markdown("Convert Telugu audio to text and store it in the Swecha Corpus.")
-
-tab1, tab2 = st.tabs(["Upload/Record", "Settings"])
-
-with tab2:
-    st.header("Configuration")
-    model_id = st.text_input("ASR Model ID", MODEL_ID)
-    auth_token = st.text_input("Swecha Auth Token", SWECHA_AUTH_TOKEN, type="password")
-    if st.button("Save Settings"):
-         os.environ["MODEL_ID"] = model_id
-         os.environ["SWECHA_AUTH_TOKEN"] = auth_token
-         st.success("Settings updated for this session!")
-
-with tab1:
-    audio_file = st.file_uploader("Choose an audio file", type=["wav", "mp3", "webm", "m4a"])
-    
-    # Simple Record placeholder since custom components like streamlit-mic-recorder 
-    # might need specific installation and configuration.
-    st.info("You can also record audio if you have 'streamlit-mic-recorder' installed. For now, please upload a file.")
-
-    if audio_file:
-        st.audio(audio_file)
-        
-        with st.expander("Metadata (Optional for storage)"):
-            title = st.text_input("Title", value=audio_file.name)
-            desc = st.text_area("Description")
-
-        if st.button("Transcribe", type="primary"):
-            with st.spinner("Transcribing Telugu..."):
-                try:
-                    text = transcribe_audio(audio_file.read(), os.path.splitext(audio_file.name)[1])
-                    st.subheader("Transcription:")
-                    st.write(text)
-                    
-                    if text and SWECHA_AUTH_TOKEN:
-                        if st.button("Push to Swecha Corpus"):
-                            res = push_to_swecha(audio_file.getvalue(), audio_file.name, text, title, desc)
-                            st.json(res)
-                except Exception as e:
-                    st.error(f"Error: {e}")