Update main.py

main.py

@@ -25,7 +25,7 @@ if not SPITCH_API_KEY:
 os.environ["SPITCH_API_KEY"] = SPITCH_API_KEY
 spitch_client = Spitch()
 
-# HuggingFace LLM
+# HuggingFace LLM (removed task="conversational" to avoid StopIteration bug)
 llm = HuggingFaceEndpoint(
     repo_id=HF_MODEL,
     temperature=0.7,
@@ -78,7 +78,6 @@ Code: {code}
 Documentation:
 """
 
-# 🔥 Fixed SME template with escaped curly braces
 sme_template = """
 You are a senior full-stack engineer specializing in modern front-end development.
 Your job is to generate **production-ready code** for websites and apps.
@@ -90,7 +89,6 @@ Guidelines:
 - JavaScript must add interactivity (animations, toggles, button actions)
 - Include hero, feature grid, testimonials, and footer
 - Use realistic content (no lorem ipsum, no placeholders)
-- Return ONLY valid JSON: {{ "files": {{ "index.html": "...", "styles.css": "...", "script.js": "..." }} }}
 
 Prompt: {user_prompt}
 Context: {context}
@@ -114,7 +112,7 @@ class AutoDocRequest(BaseModel):
 # ----------------- AUTH -----------------
 def check_auth(authorization: str | None):
     """Validate Bearer token against PROJECT_API_KEY"""
-    if not PROJECT_API_KEY:
+    if not PROJECT_API_KEY:  # If not set, skip auth
         return
     if not authorization or not authorization.startswith("Bearer "):
         raise HTTPException(status_code=401, detail="Missing bearer token")
@@ -193,10 +191,54 @@ async def sme_generate(payload: dict = Body(...), authorization: str | None = He
         context = "\n".join([doc.page_content for doc in context_docs]) if context_docs else "No extra context"
         response = sme_chain.invoke({"user_prompt": user_prompt, "context": context})
         return {"success": True, "data": response}
-    except HfHubHTTPError as e:
-        if "exceeded" in str(e).lower() or "quota" in str(e).lower():
-            return {"success": False, "error": "⚠️ Token quota for today has been used. Please come back in 24 hours."}
-        raise e
+    except Exception as e:
+        return {"success": False, "error": f"⚠️ LLM error: {str(e)}"}
+
+@app.post("/sme/speech-generate")
+async def sme_speech_generate(file: UploadFile = File(...), lang_hint: str | None = None, authorization: str | None = Header(None)):
+    check_auth(authorization)
+
+    suffix = os.path.splitext(file.filename)[1] or ".wav"
+    with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tf:
+        tf.write(await file.read())
+        tmp_path = tf.name
+
+    try:
+        if lang_hint:
+            resp = spitch_client.speech.transcribe(language=lang_hint, content=open(tmp_path, "rb").read())
+        else:
+            resp = spitch_client.speech.transcribe(content=open(tmp_path, "rb").read())
+    except Exception:
+        resp = spitch_client.speech.transcribe(language="en", content=open(tmp_path, "rb").read())
+
+    transcription = getattr(resp, "text", "") or (resp.get("text", "") if isinstance(resp, dict) else "")
+    detected_lang = "en"
+    try:
+        detected_lang = detect(transcription) if transcription.strip() else "en"
+    except Exception:
+        pass
+
+    translation = transcription
+    if detected_lang != "en":
+        try:
+            translation_resp = spitch_client.text.translate(text=transcription, source=detected_lang, target="en")
+            translation = getattr(translation_resp, "text", "") or translation_resp.get("text", "")
+        except Exception:
+            translation = transcription
+
+    try:
+        context_docs = retriever.get_relevant_documents(translation)
+        context = "\n".join([doc.page_content for doc in context_docs]) if context_docs else "No extra context"
+        sme_response = sme_chain.invoke({"user_prompt": translation, "context": context})
+        return {
+            "success": True,
+            "transcription": transcription,
+            "detected_language": detected_lang,
+            "translation": translation,
+            "sme_site": sme_response
+        }
+    except Exception as e:
+        return {"success": False, "error": f"⚠️ LLM error: {str(e)}"}
 
 # ----------------- MAIN -----------------
 if __name__ == "__main__":