Minimal working Behavior Changer (no Whisper, pure OpenAI)

app.py

@@ -8,30 +8,22 @@ import gradio as gr
 import yt_dlp
 from openai import OpenAI
 
-# opcjonalny fallback na lokalny Whisper z reels-agent
-try:
-    from modules import transcriber as local_transcriber  # transcribe_from_url(url)
-except Exception:
-    local_transcriber = None
-
-# opcjonalny summarizer z Nebiusa (reels-agent)
-try:
-    from modules import summarizer as nebius_summarizer  # summarize(text) -> {"insight","action"}
-except Exception:
-    nebius_summarizer = None
-
 # =====================================
 # CONFIG
 # =====================================
 
-DATA_DIR = "./storage/contracts"     # lokalnie
-# albo dla HF Spaces:
-# DATA_DIR = "/home/user/app/storage/contracts"
+# Zamiast /data (read-only lokalnie) używamy katalogu w repo
+BASE_DIR = os.path.dirname(__file__)
+DATA_DIR = os.path.join(BASE_DIR, "storage", "contracts")
 os.makedirs(DATA_DIR, exist_ok=True)
 
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 if not OPENAI_API_KEY:
-    raise RuntimeError("Brak OPENAI_API_KEY w secrets Spaces.")
+    raise RuntimeError(
+        "OPENAI_API_KEY nie jest ustawiony.\n"
+        "Lokalnie: export OPENAI_API_KEY='...'\n"
+        "HuggingFace: Settings → Repository secrets → OPENAI_API_KEY"
+    )
 
 client = OpenAI(api_key=OPENAI_API_KEY)
 
@@ -47,6 +39,7 @@ def _contract_path(uid: str) -> str:
 def save_contract(contract: Dict[str, Any]) -> None:
     uid = contract["uid"]
     path = _contract_path(uid)
+    os.makedirs(os.path.dirname(path), exist_ok=True)
     with open(path, "w", encoding="utf-8") as f:
         json.dump(contract, f, ensure_ascii=False, indent=2)
 
@@ -60,13 +53,17 @@ def load_contract(uid: str) -> Dict[str, Any]:
 
 
 # =====================================
-# TRANSKRYPCJA: OpenAI → fallback local Whisper
+# CORE: TRANSCRIBE
 # =====================================
 
-def _download_video_with_ytdlp(link: str) -> str:
+def transcribe_reel(link: str) -> str:
     """
-    Pobiera wideo/audio do /tmp i zwraca ścieżkę do pliku.
+    Download a reel/video from a link (e.g. Instagram/YouTube/TikTok)
+    and transcribe audio using OpenAI Whisper (gpt-4o-transcribe).
+
+    Zwraca czysty tekst (string).
     """
+    # 1) pobranie pliku przez yt-dlp
     tmp_id = str(uuid.uuid4())
     out_tmpl = f"/tmp/{tmp_id}.%(ext)s"
 
@@ -79,65 +76,41 @@ def _download_video_with_ytdlp(link: str) -> str:
     with yt_dlp.YoutubeDL(ydl_opts) as ydl:
         info = ydl.extract_info(link, download=True)
         filename = ydl.prepare_filename(info)
-    return filename
-
 
-def transcribe_reel(link: str) -> str:
-    """
-    1) Próbuje transkrypcji w OpenAI (gpt-4o-transcribe)
-    2) Jeśli to padnie i mamy local_transcriber → używa Whisper lokalnie
-    3) Jeśli wszystko padnie → zwraca 'TRANSCRIPTION_FAILED'
-    """
-    # --- krok 1: OpenAI audio.transcriptions ---
-    try:
-        filename = _download_video_with_ytdlp(link)
-        with open(filename, "rb") as f:
-            transcript = client.audio.transcriptions.create(
-                model="gpt-4o-transcribe",
-                file=f
-            )
-        text = transcript.text if hasattr(transcript, "text") else str(transcript)
-        if text and text.strip():
-            return text.strip()
-    except Exception as e:
-        print(f"[WARN] OpenAI audio transcription failed: {e}")
-
-    # --- krok 2: fallback – lokalny Whisper z reels-agent ---
-    if local_transcriber is not None and hasattr(local_transcriber, "transcribe_from_url"):
-        try:
-            text = local_transcriber.transcribe_from_url(link)  # type: ignore[attr-defined]
-            if text and text.strip():
-                return text.strip()
-        except Exception as e:
-            print(f"[WARN] Local Whisper transcription failed: {e}")
+    # 2) transkrypcja przez OpenAI
+    with open(filename, "rb") as f:
+        transcript = client.audio.transcriptions.create(
+            model="gpt-4o-transcribe",
+            file=f,
+        )
 
-    # --- krok 3: totalna porażka ---
-    return "TRANSCRIPTION_FAILED"
+    text = transcript.text if hasattr(transcript, "text") else str(transcript)
+    return text
 
 
 # =====================================
-# EXTRACT HABITS (OpenAI – 7 kroków)
+# CORE: EXTRACT HABITS (goal + 7 kroków)
 # =====================================
 
 def extract_habits(transcript: str, category: str = "general") -> Dict[str, Any]:
     """
-    Analizuje transkrypcję i produkuje:
-    - goal (one sentence)
-    - steps: 7 prostych kroków (list[str])
+    Z transkryptu robi:
+    - goal (jedno zdanie)
+    - steps: dokładnie 7 krótkich, wykonalnych kroków (lista stringów)
     """
-    if not transcript or transcript == "TRANSCRIPTION_FAILED":
-        # Fallback generic plan
+    if not transcript or not transcript.strip():
+        # Fallback gdy nie ma transkrypcji / błąd pobierania
         return {
-            "goal": f"Improve your {category} through one small action per day.",
+            "goal": f"Popraw swoją sferę: {category}, robiąc jeden mały krok dziennie.",
             "steps": [
-                "Pick one tiny action related to your goal and do it today.",
-                "Repeat the same action and make it slightly harder.",
-                "Share your progress with someone (message or note).",
-                "Add 10–15 minutes of focused deep work on this goal.",
-                "Remove one distraction that blocks this goal.",
-                "Create a simple checklist for next week.",
-                "Summarize what you learned in 3–5 sentences."
-            ]
+                "Zapisz dziś jeden konkretny cel związany z tym obszarem.",
+                "Zrób 10–15 minut skoncentrowanej pracy nad tym celem.",
+                "Usuń jedną oczywistą przeszkodę lub rozpraszacz.",
+                "Podziel swój cel na 3 mniejsze podcele i wybierz jeden.",
+                "Zrób mikro-wersję działania (np. 1 mail, 1 notatka, 1 telefon).",
+                "Podsumuj na kartce, czego nauczyłeś się z dzisiejszej próby.",
+                "Zaplanuj konkretny krok na jutro (godzina + miejsce).",
+            ],
         }
 
     system_msg = (
@@ -165,23 +138,24 @@ def extract_habits(transcript: str, category: str = "general") -> Dict[str, Any]
     )
 
     raw = resp.choices[0].message.content
-
-    # Try to parse JSON even if model wrapped it
     raw = raw.strip()
     start = raw.find("{")
     end = raw.rfind("}")
     if start == -1 or end == -1:
+        # Jeżeli model coś popierdoli z formatem
         raise ValueError(f"Cannot parse JSON from model output: {raw}")
-    json_str = raw[start:end + 1]
 
+    json_str = raw[start:end + 1]
     data = json.loads(json_str)
 
     goal = data.get("goal") or f"Improve your {category}."
     steps = data.get("steps") or []
     steps = [s for s in steps if isinstance(s, str)]
+
+    # Normalizacja liczby kroków
     if len(steps) < 7:
         while len(steps) < 7:
-            steps.append("Repeat a small action that moves you forward.")
+            steps.append("Powtórz mały krok, który realnie przesuwa Cię w tym obszarze.")
     else:
         steps = steps[:7]
 
@@ -189,73 +163,35 @@ def extract_habits(transcript: str, category: str = "general") -> Dict[str, Any]
 
 
 # =====================================
-# NEBIUS SUMMARY (INSIGHT + TODAY ACTION)
-# =====================================
-
-def summarize_with_nebius(transcript: str) -> Dict[str, Optional[str]]:
-    """
-    Używa modules/summarizer.py z reels-agent (Nebius).
-    Zwraca dict: {"insight": str | None, "action": str | None}
-    Jeśli coś padnie → zwraca domyślne fallbacki.
-    """
-    default_insight = "Mały krok dzisiaj zmienia trajektorię tygodnia."
-    default_action = "Obejrzyj materiał i zapisz 1 konkretną rzecz, którą dziś wdrożysz."
-
-    if not transcript or transcript == "TRANSCRIPTION_FAILED":
-        return {"insight": default_insight, "action": default_action}
-
-    if nebius_summarizer is None or not hasattr(nebius_summarizer, "summarize"):
-        return {"insight": default_insight, "action": default_action}
-
-    try:
-        res = nebius_summarizer.summarize(transcript)  # type: ignore[attr-defined]
-        insight = res.get("insight") if isinstance(res, dict) else None
-        action = res.get("action") if isinstance(res, dict) else None
-    except Exception as e:
-        print(f"[WARN] Nebius summarizer failed: {e}")
-        insight, action = None, None
-
-    if not insight or not insight.strip():
-        insight = default_insight
-    if not action or not action.strip():
-        action = default_action
-
-    return {"insight": insight.strip(), "action": action.strip()}
-
-
-# =====================================
-# CONTRACT API (MCP tools)
+# CONTRACT LOGIC
 # =====================================
 
 def create_contract(
     link: str,
     category: str = "general",
     uid: Optional[str] = None,
-    auto_transcribe: bool = True
+    auto_transcribe: bool = True,
 ) -> Dict[str, Any]:
     """
-    Tworzy kontrakt nawyku z linku:
-
-    - transkrypcja (OpenAI → Whisper fallback)
-    - Nebius: INSIGHT + TODAY ACTION
-    - OpenAI: goal + 7 kroków
-    - zapis do /data/contracts
+    Create a habit contract from a video link.
 
-    Zwraca skrócone podsumowanie kontraktu.
+    - (opcjonalnie) transkrybuje video
+    - wyciąga goal + 7 habit steps
+    - zapisuje kontrakt
+    - zwraca podsumowanie (uid, goal, pierwszy krok)
     """
     if uid is None or not uid.strip():
         uid = f"{category}_{uuid.uuid4().hex[:8]}"
 
     transcript = ""
     if auto_transcribe:
-        transcript = transcribe_reel(link)
-
-    # Nebius: INSIGHT + AKCJA DNIA
-    nebius_summary = summarize_with_nebius(transcript)
-    insight = nebius_summary["insight"]
-    today_action = nebius_summary["action"]
+        try:
+            transcript = transcribe_reel(link)
+        except Exception as e:
+            # nie zabijamy procesu – lecimy z fallbackiem w extract_habits()
+            print(f"[WARN] Transcription failed for {link}: {e}")
+            transcript = ""
 
-    # OpenAI: goal + 7 kroków
     habits = extract_habits(transcript, category=category)
 
     contract = {
@@ -267,10 +203,6 @@ def create_contract(
         "current_index": 0,
         "history": [],
         "created_at": datetime.datetime.utcnow().isoformat() + "Z",
-        "insight": insight,
-        "today_action": today_action,
-        # trzymamy tylko preview, żeby nie zabić storage
-        "transcript_preview": None if not transcript else transcript[:2000],
     }
 
     save_contract(contract)
@@ -282,15 +214,10 @@ def create_contract(
         "goal": contract["goal"],
         "first_step": contract["steps"][0],
         "total_steps": len(contract["steps"]),
-        "insight": insight,
-        "today_action": today_action,
     }
 
 
 def next_step(uid: str) -> Dict[str, Any]:
-    """
-    Zwraca kolejny krok dla danego kontraktu.
-    """
     contract = load_contract(uid)
     idx = contract.get("current_index", 0)
     steps = contract.get("steps", [])
@@ -301,7 +228,6 @@ def next_step(uid: str) -> Dict[str, Any]:
             "done": True,
             "message": "All steps completed.",
             "goal": contract.get("goal", ""),
-            "insight": contract.get("insight", ""),
         }
 
     return {
@@ -311,15 +237,10 @@ def next_step(uid: str) -> Dict[str, Any]:
         "step_index": idx,
         "step": steps[idx],
         "remaining_steps": len(steps) - idx,
-        "insight": contract.get("insight", ""),
-        "today_action": contract.get("today_action", ""),
     }
 
 
 def mark_done(uid: str) -> Dict[str, Any]:
-    """
-    Oznacza bieżący krok jako wykonany i przechodzi do kolejnego.
-    """
     contract = load_contract(uid)
     idx = contract.get("current_index", 0)
     steps = contract.get("steps", [])
@@ -338,9 +259,6 @@ def mark_done(uid: str) -> Dict[str, Any]:
 
 
 def report(uid: str) -> Dict[str, Any]:
-    """
-    Zwraca pełny raport z progresu.
-    """
     contract = load_contract(uid)
     steps = contract.get("steps", [])
     idx = contract.get("current_index", 0)
@@ -361,23 +279,18 @@ def report(uid: str) -> Dict[str, Any]:
         "progress_percent": round(progress, 1),
         "history": history,
         "current_step": steps[idx] if idx < total else None,
-        "insight": contract.get("insight", ""),
-        "today_action": contract.get("today_action", ""),
     }
 
 
 # =====================================
-# GRADIO UI + MCP
+# GRADIO UI + MCP EXPOSURE
 # =====================================
 
 with gr.Blocks() as demo:
     gr.Markdown(
         "# Behavior Changer – Habit Agent (MCP)\n"
-        "Kontrakty nawyków z linków do Reels / video:\n"
-        "- transkrypcja (OpenAI → Whisper fallback)\n"
-        "- Nebius INSIGHT + mikro-akcja\n"
-        "- 7 kroków z OpenAI\n"
-        "- MCP tools do użycia z Claude/Cursor."
+        "Tworzy kontrakty nawyków z linków do Reels / video, "
+        "rozbija na 7 kroków i udostępnia jako MCP tools."
     )
 
     with gr.Tab("Create Contract"):