{"repo": "abdrsl/vibebridge", "files": {"src/vibebridge/providers/openrouter.py": {"b9d8d20882fa994eccef9e11cdfd3edbb9d4a645": {"t": 1785746501.6504695, "n": 11709, "h": "09a13f35d989448f", "c": "\"\"\"OpenRouter provider for VibeBridge.\"\"\"\n\nfrom __future__ import annotations\n\nimport asyncio\nimport json\nimport logging\nimport os\nfrom typing import AsyncIterator\n\nimport httpx\n\nfrom .base import BaseProvider, StreamEvent, StreamEventType\n\nlogger = logging.getLogger(__name__)\n\n\nclass OpenRouterProvider(BaseProvider):\n    \"\"\"OpenRouter provider using their API.\"\"\"\n\n    name = \"openrouter\"\n    display_name = \"OpenRouter\"\n\n    def __init__(\n        self,\n        api_key: str | None = None,\n        default_model: str = \"openai/gpt-4o\",\n        base_url: str = \"https://openrouter.ai/api/v1\",\n    ):\n        self.api_key = api_key or os.getenv(\"OPENROUTER_API_KEY\", \"\")\n        self.default_model = default_model\n        self.base_url = base_url\n        self._client: httpx.AsyncClient | None = None\n        self._tasks: dict[str, asyncio.Task] = {}\n        self._task_contexts: dict[str, dict[str, str]] = {}\n\n    async def _get_client(self) -> httpx.AsyncClient:\n        \"\"\"Get or create HTTP client.\"\"\"\n        if self._client is None:\n            headers = {\n                \"Authorization\": f\"Bearer {self.api_key}\",\n                \"Content-Type\": \"application/json\",\n                \"HTTP-Referer\": \"https://vibebridge.ai\",\n                \"X-Title\": \"VibeBridge\",\n            }\n            self._client = httpx.AsyncClient(\n                headers=headers, timeout=httpx.Timeout(300.0, connect=10.0)\n            )\n        return self._client\n\n    async def health_check(self) -> tuple[bool, str]:\n        \"\"\"Check if OpenRouter API is accessible.\"\"\"\n        if not self.api_key:\n            return False, \"OpenRouter API key not configured\"\n\n        try:\n            client = await self._get_client()\n            response = await client.get(f\"{self.base_url}/models\")\n            if response.status_code == 200:\n                return True, \"OpenRouter API is accessible\"\n            else:\n                return False, f\"OpenRouter API returned status {response.status_code}\"\n        except Exception as e:\n            return False, f\"OpenRouter API error: {str(e)}\"\n\n    async def create_task(\n        self,\n        prompt: str,\n        workdir: str,\n        session_id: str,\n        chat_id: str | None = None,\n    ) -> str:\n        \"\"\"Create a task and return task_id.\"\"\"\n        task_id = f\"openrouter_{session_id}_{hash(prompt) & 0xFFFFFFFF}\"\n        \n        # Store task context so stream_task can access the original prompt\n        self._task_contexts[task_id] = {\n            \"prompt\": prompt,\n            \"workdir\": workdir,\n            \"session_id\": session_id,\n            \"chat_id\": chat_id or \"\",\n        }\n        \n        # Start the task in background\n        task = asyncio.create_task(self._execute_task(task_id, prompt, workdir))\n        self._tasks[task_id] = task\n        \n        return task_id\n\n    async def _execute_task(self, task_id: str, prompt: str, workdir: str):\n        \"\"\"Execute the task and store result.\"\"\"\n        try:\n            logger.info(f\"OpenRouter task {task_id} created for prompt: {prompt[:100]}...\")\n        except Exception as e:\n            logger.error(f\"Error in OpenRouter task {task_id}: {e}\")\n\n    async def stream_task(self, task_id: str) -> AsyncIterator[StreamEvent]:\n        \"\"\"Stream task execution using OpenRouter API.\"\"\"\n        # Retrieve the original prompt from task context\n        ctx = self._task_contexts.get(task_id, {})\n        prompt = ctx.get(\"prompt\", \"\")\n        if not prompt:\n            logger.warning(f\"OpenRouter task {task_id}: no prompt found in context, using fallback\")\n            prompt = \"Execute the user's request\"\n        \n        try:\n            client = await self._get_client()\n            \n            # Send initial status\n            yield StreamEvent(\n                type=StreamEventType.STATUS,\n                content=\"Starting OpenRouter task...\",\n                task_id=task_id,\n            )\n            \n            # Prepare the request\n            messages = [\n                {\n                    \"role\": \"system\",\n                    \"content\": \"You are an AI assistant that helps with coding tasks. Provide clear, executable solutions.\"\n                },\n                {\n                    \"role\": \"user\",\n                    \"content\": prompt\n                }\n            ]\n            \n            data = {\n                \"model\": self.default_model,\n                \"messages\": messages,\n                \"stream\": True,\n                \"temperature\": 0.7,\n                \"max_tokens\": 4000,\n            }\n            \n            # Make streaming request\n            async with client.stream(\n                \"POST\",\n                f\"{self.base_url}/chat/completions\",\n                json=data,\n            ) as response:\n                response.raise_for_status()\n                \n                buffer = \"\"\n                async for chunk in response.aiter_bytes():\n                    chunk_str = chunk.decode(\"utf-8\")\n                    lines = chunk_str.split(\"\\n\")\n                    \n                    for line in lines:\n                        line = line.strip()\n                        if not line or line == \"data: [DONE]\":\n                            continue\n                            \n                        if line.startswith(\"data: \"):\n                            data_str = line[6:]\n                            try:\n                                data_obj = json.loads(data_str)\n                                choices = data_obj.get(\"choices\", [])\n                                if choices:\n                                    delta = choices[0].get(\"delta\", {})\n                                    content = delta.get(\"content\", \"\")\n                                    if content:\n                                        buffer += content\n                                        # Yield text in chunks\n                                        if len(buffer) > 100 or \"\\n\" in content:\n                                            yield StreamEvent(\n                                                type=StreamEventType.TEXT,\n                                                content=buffer,\n                                                task_id=task_id,\n                                            )\n                                            buffer = \"\"\n                            except json.JSONDecodeError:\n                                continue\n                \n                # Yield any remaining buffer\n                if buffer:\n                    yield StreamEvent(\n                        type=StreamEventType.TEXT,\n                        content=buffer,\n                        task_id=task_id,\n                    )\n                \n                # Yield completion\n                yield StreamEvent(\n                    type=StreamEventType.DONE,\n                    content=\"Task completed successfully\",\n                    task_id=task_id,\n                )\n                \n        except Exception as e:\n            logger.error(f\"Error streaming OpenRouter task {task_id}: {e}\")\n            yield StreamEvent(\n                type=StreamEventType.ERROR,\n                content=f\"OpenRouter API error: {str(e)}\",\n                task_id=task_id,\n            )\n        finally:\n            # Clean up task and context\n            if task_id in self._tasks:\n                del self._tasks[task_id]\n            if task_id in self._task_contexts:\n                del self._task_contexts[task_id]\n\n    async def cancel_task(self, task_id: str) -> bool:\n        \"\"\"Cancel a running task.\"\"\"\n        if task_id in self._tasks:\n            task = self._tasks[task_id]\n            task.cancel()\n            try:\n                await task\n            except asyncio.CancelledError:\n                pass\n            del self._tasks[task_id]\n            return True\n        return False\n\n    def default_workdir(self) -> str:\n        \"\"\"Return the suggested default working directory.\"\"\"\n        return os.path.expanduser(\"~/workspace\")\n\n    async def close(self):\n        \"\"\"Close the HTTP client.\"\"\"\n        if self._client:\n            await self._client.aclose()\n            self._client = None\n\n    async def test_all_models(self) -> dict:\n        \"\"\"Test all available models on OpenRouter.\"\"\"\n        if not self.api_key:\n            return {\"error\": \"OpenRouter API key not configured\"}\n        \n        try:\n            client = await self._get_client()\n            response = await client.get(f\"{self.base_url}/models\")\n            \n            if response.status_code != 200:\n                return {\"error\": f\"Failed to fetch models: {response.status_code}\"}\n            \n            models_data = response.json()\n            models = models_data.get(\"data\", [])\n            \n            results = {\n                \"total_models\": len(models),\n                \"available_models\": [],\n                \"test_results\": {}\n            }\n            \n            # Test a subset of popular models\n            popular_models = [\n                \"openai/gpt-4o\",\n                \"openai/gpt-4-turbo\",\n                \"anthropic/claude-3.5-sonnet\",\n                \"anthropic/claude-3-opus\",\n                \"google/gemini-2.0-flash-exp\",\n                \"meta-llama/llama-3.3-70b-instruct\",\n                \"mistralai/mistral-large-2411\",\n                \"deepseek/deepseek-chat\",\n                \"deepseek/deepseek-reasoner\",\n                \"qwen/qwen-2.5-72b-instruct\",\n            ]\n            \n            for model in popular_models:\n                # Check if model is available\n                model_available = any(m.get(\"id\") == model for m in models)\n                \n                if model_available:\n                    # Test the model with a simple prompt\n                    test_result = await self._test_model(client, model)\n                    results[\"test_results\"][model] = test_result\n                    results[\"available_models\"].append(model)\n                else:\n                    results[\"test_results\"][model] = {\"available\": False, \"error\": \"Model not found\"}\n            \n            return results\n            \n        except Exception as e:\n            return {\"error\": f\"Error testing models: {str(e)}\"}\n\n    async def _test_model(self, client: httpx.AsyncClient, model: str) -> dict:\n        \"\"\"Test a specific model with a simple prompt.\"\"\"\n        try:\n            messages = [\n                {\n                    \"role\": \"user\",\n                    \"content\": \"Hello! Please respond with 'OK' if you can hear me.\"\n                }\n            ]\n            \n            data = {\n                \"model\": model,\n                \"messages\": messages,\n                \"max_tokens\": 10,\n                \"temperature\": 0.1,\n            }\n            \n            response = await client.post(\n                f\"{self.base_url}/chat/completions\",\n                json=data,\n                timeout=10.0\n            )\n            \n            if response.status_code == 200:\n                result = response.json()\n                content = result[\"choices\"][0][\"message\"][\"content\"].strip()\n                return {\n                    \"available\": True,\n                    \"response\": content,\n                    \"tokens\": result.get(\"usage\", {}).get(\"total_tokens\", 0)\n                }\n            else:\n                return {\n                    \"available\": False,\n                    \"error\": f\"API error: {response.status_code}\",\n                    \"details\": response.text[:200]\n                }\n                \n        except Exception as e:\n            return {\n                \"available\": False,\n                \"error\": f\"Test failed: {str(e)}\"\n            }"}, "4fde75c0641efce8bbaccb9cc1214dd542db7dfe": {"t": 1785765004.5854676, "n": 11709, "h": "09a13f35d989448f", "c": "\"\"\"OpenRouter provider for VibeBridge.\"\"\"\n\nfrom __future__ import annotations\n\nimport asyncio\nimport json\nimport logging\nimport os\nfrom typing import AsyncIterator\n\nimport httpx\n\nfrom .base import BaseProvider, StreamEvent, StreamEventType\n\nlogger = logging.getLogger(__name__)\n\n\nclass OpenRouterProvider(BaseProvider):\n    \"\"\"OpenRouter provider using their API.\"\"\"\n\n    name = \"openrouter\"\n    display_name = \"OpenRouter\"\n\n    def __init__(\n        self,\n        api_key: str | None = None,\n        default_model: str = \"openai/gpt-4o\",\n        base_url: str = \"https://openrouter.ai/api/v1\",\n    ):\n        self.api_key = api_key or os.getenv(\"OPENROUTER_API_KEY\", \"\")\n        self.default_model = default_model\n        self.base_url = base_url\n        self._client: httpx.AsyncClient | None = None\n        self._tasks: dict[str, asyncio.Task] = {}\n        self._task_contexts: dict[str, dict[str, str]] = {}\n\n    async def _get_client(self) -> httpx.AsyncClient:\n        \"\"\"Get or create HTTP client.\"\"\"\n        if self._client is None:\n            headers = {\n                \"Authorization\": f\"Bearer {self.api_key}\",\n                \"Content-Type\": \"application/json\",\n                \"HTTP-Referer\": \"https://vibebridge.ai\",\n                \"X-Title\": \"VibeBridge\",\n            }\n            self._client = httpx.AsyncClient(\n                headers=headers, timeout=httpx.Timeout(300.0, connect=10.0)\n            )\n        return self._client\n\n    async def health_check(self) -> tuple[bool, str]:\n        \"\"\"Check if OpenRouter API is accessible.\"\"\"\n        if not self.api_key:\n            return False, \"OpenRouter API key not configured\"\n\n        try:\n            client = await self._get_client()\n            response = await client.get(f\"{self.base_url}/models\")\n            if response.status_code == 200:\n                return True, \"OpenRouter API is accessible\"\n            else:\n                return False, f\"OpenRouter API returned status {response.status_code}\"\n        except Exception as e:\n            return False, f\"OpenRouter API error: {str(e)}\"\n\n    async def create_task(\n        self,\n        prompt: str,\n        workdir: str,\n        session_id: str,\n        chat_id: str | None = None,\n    ) -> str:\n        \"\"\"Create a task and return task_id.\"\"\"\n        task_id = f\"openrouter_{session_id}_{hash(prompt) & 0xFFFFFFFF}\"\n        \n        # Store task context so stream_task can access the original prompt\n        self._task_contexts[task_id] = {\n            \"prompt\": prompt,\n            \"workdir\": workdir,\n            \"session_id\": session_id,\n            \"chat_id\": chat_id or \"\",\n        }\n        \n        # Start the task in background\n        task = asyncio.create_task(self._execute_task(task_id, prompt, workdir))\n        self._tasks[task_id] = task\n        \n        return task_id\n\n    async def _execute_task(self, task_id: str, prompt: str, workdir: str):\n        \"\"\"Execute the task and store result.\"\"\"\n        try:\n            logger.info(f\"OpenRouter task {task_id} created for prompt: {prompt[:100]}...\")\n        except Exception as e:\n            logger.error(f\"Error in OpenRouter task {task_id}: {e}\")\n\n    async def stream_task(self, task_id: str) -> AsyncIterator[StreamEvent]:\n        \"\"\"Stream task execution using OpenRouter API.\"\"\"\n        # Retrieve the original prompt from task context\n        ctx = self._task_contexts.get(task_id, {})\n        prompt = ctx.get(\"prompt\", \"\")\n        if not prompt:\n            logger.warning(f\"OpenRouter task {task_id}: no prompt found in context, using fallback\")\n            prompt = \"Execute the user's request\"\n        \n        try:\n            client = await self._get_client()\n            \n            # Send initial status\n            yield StreamEvent(\n                type=StreamEventType.STATUS,\n                content=\"Starting OpenRouter task...\",\n                task_id=task_id,\n            )\n            \n            # Prepare the request\n            messages = [\n                {\n                    \"role\": \"system\",\n                    \"content\": \"You are an AI assistant that helps with coding tasks. Provide clear, executable solutions.\"\n                },\n                {\n                    \"role\": \"user\",\n                    \"content\": prompt\n                }\n            ]\n            \n            data = {\n                \"model\": self.default_model,\n                \"messages\": messages,\n                \"stream\": True,\n                \"temperature\": 0.7,\n                \"max_tokens\": 4000,\n            }\n            \n            # Make streaming request\n            async with client.stream(\n                \"POST\",\n                f\"{self.base_url}/chat/completions\",\n                json=data,\n            ) as response:\n                response.raise_for_status()\n                \n                buffer = \"\"\n                async for chunk in response.aiter_bytes():\n                    chunk_str = chunk.decode(\"utf-8\")\n                    lines = chunk_str.split(\"\\n\")\n                    \n                    for line in lines:\n                        line = line.strip()\n                        if not line or line == \"data: [DONE]\":\n                            continue\n                            \n                        if line.startswith(\"data: \"):\n                            data_str = line[6:]\n                            try:\n                                data_obj = json.loads(data_str)\n                                choices = data_obj.get(\"choices\", [])\n                                if choices:\n                                    delta = choices[0].get(\"delta\", {})\n                                    content = delta.get(\"content\", \"\")\n                                    if content:\n                                        buffer += content\n                                        # Yield text in chunks\n                                        if len(buffer) > 100 or \"\\n\" in content:\n                                            yield StreamEvent(\n                                                type=StreamEventType.TEXT,\n                                                content=buffer,\n                                                task_id=task_id,\n                                            )\n                                            buffer = \"\"\n                            except json.JSONDecodeError:\n                                continue\n                \n                # Yield any remaining buffer\n                if buffer:\n                    yield StreamEvent(\n                        type=StreamEventType.TEXT,\n                        content=buffer,\n                        task_id=task_id,\n                    )\n                \n                # Yield completion\n                yield StreamEvent(\n                    type=StreamEventType.DONE,\n                    content=\"Task completed successfully\",\n                    task_id=task_id,\n                )\n                \n        except Exception as e:\n            logger.error(f\"Error streaming OpenRouter task {task_id}: {e}\")\n            yield StreamEvent(\n                type=StreamEventType.ERROR,\n                content=f\"OpenRouter API error: {str(e)}\",\n                task_id=task_id,\n            )\n        finally:\n            # Clean up task and context\n            if task_id in self._tasks:\n                del self._tasks[task_id]\n            if task_id in self._task_contexts:\n                del self._task_contexts[task_id]\n\n    async def cancel_task(self, task_id: str) -> bool:\n        \"\"\"Cancel a running task.\"\"\"\n        if task_id in self._tasks:\n            task = self._tasks[task_id]\n            task.cancel()\n            try:\n                await task\n            except asyncio.CancelledError:\n                pass\n            del self._tasks[task_id]\n            return True\n        return False\n\n    def default_workdir(self) -> str:\n        \"\"\"Return the suggested default working directory.\"\"\"\n        return os.path.expanduser(\"~/workspace\")\n\n    async def close(self):\n        \"\"\"Close the HTTP client.\"\"\"\n        if self._client:\n            await self._client.aclose()\n            self._client = None\n\n    async def test_all_models(self) -> dict:\n        \"\"\"Test all available models on OpenRouter.\"\"\"\n        if not self.api_key:\n            return {\"error\": \"OpenRouter API key not configured\"}\n        \n        try:\n            client = await self._get_client()\n            response = await client.get(f\"{self.base_url}/models\")\n            \n            if response.status_code != 200:\n                return {\"error\": f\"Failed to fetch models: {response.status_code}\"}\n            \n            models_data = response.json()\n            models = models_data.get(\"data\", [])\n            \n            results = {\n                \"total_models\": len(models),\n                \"available_models\": [],\n                \"test_results\": {}\n            }\n            \n            # Test a subset of popular models\n            popular_models = [\n                \"openai/gpt-4o\",\n                \"openai/gpt-4-turbo\",\n                \"anthropic/claude-3.5-sonnet\",\n                \"anthropic/claude-3-opus\",\n                \"google/gemini-2.0-flash-exp\",\n                \"meta-llama/llama-3.3-70b-instruct\",\n                \"mistralai/mistral-large-2411\",\n                \"deepseek/deepseek-chat\",\n                \"deepseek/deepseek-reasoner\",\n                \"qwen/qwen-2.5-72b-instruct\",\n            ]\n            \n            for model in popular_models:\n                # Check if model is available\n                model_available = any(m.get(\"id\") == model for m in models)\n                \n                if model_available:\n                    # Test the model with a simple prompt\n                    test_result = await self._test_model(client, model)\n                    results[\"test_results\"][model] = test_result\n                    results[\"available_models\"].append(model)\n                else:\n                    results[\"test_results\"][model] = {\"available\": False, \"error\": \"Model not found\"}\n            \n            return results\n            \n        except Exception as e:\n            return {\"error\": f\"Error testing models: {str(e)}\"}\n\n    async def _test_model(self, client: httpx.AsyncClient, model: str) -> dict:\n        \"\"\"Test a specific model with a simple prompt.\"\"\"\n        try:\n            messages = [\n                {\n                    \"role\": \"user\",\n                    \"content\": \"Hello! Please respond with 'OK' if you can hear me.\"\n                }\n            ]\n            \n            data = {\n                \"model\": model,\n                \"messages\": messages,\n                \"max_tokens\": 10,\n                \"temperature\": 0.1,\n            }\n            \n            response = await client.post(\n                f\"{self.base_url}/chat/completions\",\n                json=data,\n                timeout=10.0\n            )\n            \n            if response.status_code == 200:\n                result = response.json()\n                content = result[\"choices\"][0][\"message\"][\"content\"].strip()\n                return {\n                    \"available\": True,\n                    \"response\": content,\n                    \"tokens\": result.get(\"usage\", {}).get(\"total_tokens\", 0)\n                }\n            else:\n                return {\n                    \"available\": False,\n                    \"error\": f\"API error: {response.status_code}\",\n                    \"details\": response.text[:200]\n                }\n                \n        except Exception as e:\n            return {\n                \"available\": False,\n                \"error\": f\"Test failed: {str(e)}\"\n            }"}, "609080ba9d33964707f6ffe15534c2ad8908c71a": {"t": 1785765005.8294215, "n": 11203, "h": "057f1d926e3d1ada", "c": "\"\"\"OpenRouter provider for VibeBridge.\"\"\"\n\nfrom __future__ import annotations\n\nimport asyncio\nimport json\nimport logging\nimport os\nfrom typing import AsyncIterator\n\nimport httpx\n\nfrom .base import BaseProvider, StreamEvent, StreamEventType\n\nlogger = logging.getLogger(__name__)\n\n\nclass OpenRouterProvider(BaseProvider):\n    \"\"\"OpenRouter provider using their API.\"\"\"\n\n    name = \"openrouter\"\n    display_name = \"OpenRouter\"\n\n    def __init__(\n        self,\n        api_key: str | None = None,\n        default_model: str = \"openai/gpt-4o\",\n        base_url: str = \"https://openrouter.ai/api/v1\",\n    ):\n        self.api_key = api_key or os.getenv(\"OPENROUTER_API_KEY\", \"\")\n        self.default_model = default_model\n        self.base_url = base_url\n        self._client: httpx.AsyncClient | None = None\n        self._tasks: dict[str, asyncio.Task] = {}\n\n    async def _get_client(self) -> httpx.AsyncClient:\n        \"\"\"Get or create HTTP client.\"\"\"\n        if self._client is None:\n            headers = {\n                \"Authorization\": f\"Bearer {self.api_key}\",\n                \"Content-Type\": \"application/json\",\n                \"HTTP-Referer\": \"https://vibebridge.ai\",\n                \"X-Title\": \"VibeBridge\",\n            }\n            self._client = httpx.AsyncClient(\n                headers=headers, timeout=httpx.Timeout(300.0, connect=10.0)\n            )\n        return self._client\n\n    async def health_check(self) -> tuple[bool, str]:\n        \"\"\"Check if OpenRouter API is accessible.\"\"\"\n        if not self.api_key:\n            return False, \"OpenRouter API key not configured\"\n\n        try:\n            client = await self._get_client()\n            response = await client.get(f\"{self.base_url}/models\")\n            if response.status_code == 200:\n                return True, \"OpenRouter API is accessible\"\n            else:\n                return False, f\"OpenRouter API returned status {response.status_code}\"\n        except Exception as e:\n            return False, f\"OpenRouter API error: {str(e)}\"\n\n    async def create_task(\n        self,\n        prompt: str,\n        workdir: str,\n        session_id: str,\n        chat_id: str | None = None,\n    ) -> str:\n        \"\"\"Create a task and return task_id.\"\"\"\n        task_id = f\"openrouter_{session_id}_{hash(prompt) & 0xFFFFFFFF}\"\n        \n        # Start the task in background\n        task = asyncio.create_task(self._execute_task(task_id, prompt, workdir))\n        self._tasks[task_id] = task\n        \n        return task_id\n\n    async def _execute_task(self, task_id: str, prompt: str, workdir: str):\n        \"\"\"Execute the task and store result.\"\"\"\n        try:\n            # This is a placeholder - actual execution would happen in stream_task\n            logger.info(f\"OpenRouter task {task_id} created for prompt: {prompt[:100]}...\")\n        except Exception as e:\n            logger.error(f\"Error in OpenRouter task {task_id}: {e}\")\n\n    async def stream_task(self, task_id: str) -> AsyncIterator[StreamEvent]:\n        \"\"\"Stream task execution using OpenRouter API.\"\"\"\n        # Get the prompt from task context (in real implementation, we'd store it)\n        # For now, we'll use a dummy prompt\n        prompt = \"Execute the user's request\"\n        \n        try:\n            client = await self._get_client()\n            \n            # Send initial status\n            yield StreamEvent(\n                type=StreamEventType.STATUS,\n                content=\"Starting OpenRouter task...\",\n                task_id=task_id,\n            )\n            \n            # Prepare the request\n            messages = [\n                {\n                    \"role\": \"system\",\n                    \"content\": \"You are an AI assistant that helps with coding tasks. Provide clear, executable solutions.\"\n                },\n                {\n                    \"role\": \"user\",\n                    \"content\": prompt\n                }\n            ]\n            \n            data = {\n                \"model\": self.default_model,\n                \"messages\": messages,\n                \"stream\": True,\n                \"temperature\": 0.7,\n                \"max_tokens\": 4000,\n            }\n            \n            # Make streaming request\n            async with client.stream(\n                \"POST\",\n                f\"{self.base_url}/chat/completions\",\n                json=data,\n            ) as response:\n                response.raise_for_status()\n                \n                buffer = \"\"\n                async for chunk in response.aiter_bytes():\n                    chunk_str = chunk.decode(\"utf-8\")\n                    lines = chunk_str.split(\"\\n\")\n                    \n                    for line in lines:\n                        line = line.strip()\n                        if not line or line == \"data: [DONE]\":\n                            continue\n                            \n                        if line.startswith(\"data: \"):\n                            data_str = line[6:]\n                            try:\n                                data_obj = json.loads(data_str)\n                                choices = data_obj.get(\"choices\", [])\n                                if choices:\n                                    delta = choices[0].get(\"delta\", {})\n                                    content = delta.get(\"content\", \"\")\n                                    if content:\n                                        buffer += content\n                                        # Yield text in chunks\n                                        if len(buffer) > 100 or \"\\n\" in content:\n                                            yield StreamEvent(\n                                                type=StreamEventType.TEXT,\n                                                content=buffer,\n                                                task_id=task_id,\n                                            )\n                                            buffer = \"\"\n                            except json.JSONDecodeError:\n                                continue\n                \n                # Yield any remaining buffer\n                if buffer:\n                    yield StreamEvent(\n                        type=StreamEventType.TEXT,\n                        content=buffer,\n                        task_id=task_id,\n                    )\n                \n                # Yield completion\n                yield StreamEvent(\n                    type=StreamEventType.DONE,\n                    content=\"Task completed successfully\",\n                    task_id=task_id,\n                )\n                \n        except Exception as e:\n            logger.error(f\"Error streaming OpenRouter task {task_id}: {e}\")\n            yield StreamEvent(\n                type=StreamEventType.ERROR,\n                content=f\"OpenRouter API error: {str(e)}\",\n                task_id=task_id,\n            )\n        finally:\n            # Clean up task\n            if task_id in self._tasks:\n                del self._tasks[task_id]\n\n    async def cancel_task(self, task_id: str) -> bool:\n        \"\"\"Cancel a running task.\"\"\"\n        if task_id in self._tasks:\n            task = self._tasks[task_id]\n            task.cancel()\n            try:\n                await task\n            except asyncio.CancelledError:\n                pass\n            del self._tasks[task_id]\n            return True\n        return False\n\n    def default_workdir(self) -> str:\n        \"\"\"Return the suggested default working directory.\"\"\"\n        return os.path.expanduser(\"~/workspace\")\n\n    async def close(self):\n        \"\"\"Close the HTTP client.\"\"\"\n        if self._client:\n            await self._client.aclose()\n            self._client = None\n\n    async def test_all_models(self) -> dict:\n        \"\"\"Test all available models on OpenRouter.\"\"\"\n        if not self.api_key:\n            return {\"error\": \"OpenRouter API key not configured\"}\n        \n        try:\n            client = await self._get_client()\n            response = await client.get(f\"{self.base_url}/models\")\n            \n            if response.status_code != 200:\n                return {\"error\": f\"Failed to fetch models: {response.status_code}\"}\n            \n            models_data = response.json()\n            models = models_data.get(\"data\", [])\n            \n            results = {\n                \"total_models\": len(models),\n                \"available_models\": [],\n                \"test_results\": {}\n            }\n            \n            # Test a subset of popular models\n            popular_models = [\n                \"openai/gpt-4o\",\n                \"openai/gpt-4-turbo\",\n                \"anthropic/claude-3.5-sonnet\",\n                \"anthropic/claude-3-opus\",\n                \"google/gemini-2.0-flash-exp\",\n                \"meta-llama/llama-3.3-70b-instruct\",\n                \"mistralai/mistral-large-2411\",\n                \"deepseek/deepseek-chat\",\n                \"deepseek/deepseek-reasoner\",\n                \"qwen/qwen-2.5-72b-instruct\",\n            ]\n            \n            for model in popular_models:\n                # Check if model is available\n                model_available = any(m.get(\"id\") == model for m in models)\n                \n                if model_available:\n                    # Test the model with a simple prompt\n                    test_result = await self._test_model(client, model)\n                    results[\"test_results\"][model] = test_result\n                    results[\"available_models\"].append(model)\n                else:\n                    results[\"test_results\"][model] = {\"available\": False, \"error\": \"Model not found\"}\n            \n            return results\n            \n        except Exception as e:\n            return {\"error\": f\"Error testing models: {str(e)}\"}\n\n    async def _test_model(self, client: httpx.AsyncClient, model: str) -> dict:\n        \"\"\"Test a specific model with a simple prompt.\"\"\"\n        try:\n            messages = [\n                {\n                    \"role\": \"user\",\n                    \"content\": \"Hello! Please respond with 'OK' if you can hear me.\"\n                }\n            ]\n            \n            data = {\n                \"model\": model,\n                \"messages\": messages,\n                \"max_tokens\": 10,\n                \"temperature\": 0.1,\n            }\n            \n            response = await client.post(\n                f\"{self.base_url}/chat/completions\",\n                json=data,\n                timeout=10.0\n            )\n            \n            if response.status_code == 200:\n                result = response.json()\n                content = result[\"choices\"][0][\"message\"][\"content\"].strip()\n                return {\n                    \"available\": True,\n                    \"response\": content,\n                    \"tokens\": result.get(\"usage\", {}).get(\"total_tokens\", 0)\n                }\n            else:\n                return {\n                    \"available\": False,\n                    \"error\": f\"API error: {response.status_code}\",\n                    \"details\": response.text[:200]\n                }\n                \n        except Exception as e:\n            return {\n                \"available\": False,\n                \"error\": f\"Test failed: {str(e)}\"\n            }"}}, "src/vibebridge/legacy/secure_config.py": {"b9d8d20882fa994eccef9e11cdfd3edbb9d4a645": {"t": 1785746896.8498871, "n": 10283, "h": "954aa47d912a2321", "c": "\"\"\"\nSecure configuration management with optional encryption for sensitive values.\n\nUsage:\n1. Set a master key via environment variable: AI_MASTER_KEY or in ~/.ai-product-lab/master.key\n2. Encrypt sensitive values using the encrypt_value() function\n3. Store encrypted values in .env with prefix ENC_\n4. Use get_secret() to automatically decrypt values\n\nExample:\n    Before: DEEPSEEK_API_KEY=sk-abc123\n    After:  DEEPSEEK_API_KEY_ENC=ENC:gAAAAABm... (encrypted)\n\n    In code: api_key = get_secret(\"DEEPSEEK_API_KEY\")\n\"\"\"\n\nimport base64\nimport binascii\nimport hashlib\nimport os\nfrom pathlib import Path\nfrom typing import Optional\n\nimport os\nfrom cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes\nfrom cryptography.hazmat.primitives import padding\nfrom cryptography.hazmat.backends import default_backend\n\n# Constants\nMASTER_KEY_ENV_VAR = \"AI_MASTER_KEY\"\nMASTER_KEY_FILE = Path.home() / \".ai-product-lab\" / \"master.key\"\nENCRYPTED_PREFIX = \"ENC:\"\nDEFAULT_SENSITIVE_KEYS = [\n    \"DEEPSEEK_API_KEY\",\n    \"MOONSHOT_API_KEY\",\n    \"FEISHU_APP_SECRET\",\n    \"FEISHU_ENCRYPT_KEY\",\n    \"FEISHU_VERIFICATION_TOKEN\",\n    \"NGROK_AUTHTOKEN\",\n    \"OPENAI_API_KEY\",\n    \"ANTHROPIC_API_KEY\",\n    \"GEMINI_API_KEY\",\n    \"OPENROUTER_API_KEY\",\n    \"LITELLM_MASTER_KEY\",\n    \"POSTGRES_PASSWORD\",\n    \"REDIS_PASSWORD\",\n    \"QDRANT_API_KEY\",\n]\n\n\nclass SecureConfigError(Exception):\n    \"\"\"Secure configuration error.\"\"\"\n\n    pass\n\n\ndef _get_master_key() -> bytes:\n    \"\"\"Get master key from environment variable or file.\"\"\"\n    # Try environment variable first\n    master_key = os.getenv(MASTER_KEY_ENV_VAR)\n    if master_key:\n        # Ensure it's 32 bytes for AES-256\n        key_hash = hashlib.sha256(master_key.encode()).digest()\n        return key_hash\n\n    # Try key file\n    if MASTER_KEY_FILE.exists():\n        try:\n            key_data = MASTER_KEY_FILE.read_bytes()\n            # File can contain raw bytes or base64 encoded string\n            if len(key_data) == 32:\n                return key_data\n            else:\n                # Try to decode as base64\n                try:\n                    decoded = base64.b64decode(key_data)\n                    if len(decoded) == 32:\n                        return decoded\n                    else:\n                        # Hash to 32 bytes\n                        return hashlib.sha256(decoded).digest()[:32]\n                except (binascii.Error, ValueError):\n                    # Hash the raw bytes\n                    return hashlib.sha256(key_data).digest()[:32]\n        except Exception as e:\n            raise SecureConfigError(f\"Failed to read master key file: {e}\")\n\n    # No master key found - in development, we can fall back to a default\n    # but warn loudly. In production, this should fail.\n    if os.getenv(\"APP_ENV\") == \"dev\":\n        print(\"⚠️  WARNING: No master key found. Using default development key.\")\n        print(f\"   Set {MASTER_KEY_ENV_VAR} or create {MASTER_KEY_FILE}\")\n        # Generate deterministic key from string for development\n        dev_key = \"dev-master-key-insecure-change-in-production\"\n        return hashlib.sha256(dev_key.encode()).digest()\n\n    raise SecureConfigError(\n        f\"Master key required. Set {MASTER_KEY_ENV_VAR} environment variable \"\n        f\"or create {MASTER_KEY_FILE} with 32-byte key.\"\n    )\n\n\ndef _create_cipher(key: bytes, iv: bytes) -> Cipher:\n    \"\"\"Create AES cipher in CBC mode.\"\"\"\n    return Cipher(algorithms.AES(key), modes.CBC(iv), backend=default_backend())\n\n\ndef encrypt_value(plaintext: str) -> str:\n    \"\"\"\n    Encrypt a plaintext string.\n\n    Returns:\n        Base64 encoded string with format: ENC:<base64(iv + ciphertext)>\n    \"\"\"\n    if not plaintext:\n        return \"\"\n\n    master_key = _get_master_key()\n    iv = os.urandom(16)\n    cipher = _create_cipher(master_key, iv)\n    encryptor = cipher.encryptor()\n\n    # Encrypt with PKCS7 padding\n    padder = padding.PKCS7(128).padder()\n    padded_data = padder.update(plaintext.encode(\"utf-8\")) + padder.finalize()\n    ciphertext = encryptor.update(padded_data) + encryptor.finalize()\n\n    # Combine IV and ciphertext\n    encrypted = iv + ciphertext\n    encoded = base64.b64encode(encrypted).decode(\"utf-8\")\n\n    return f\"{ENCRYPTED_PREFIX}{encoded}\"\n\n\ndef decrypt_value(encrypted_str: str) -> str:\n    \"\"\"\n    Decrypt an encrypted string.\n\n    Args:\n        encrypted_str: String with format ENC:<base64(iv + ciphertext)>\n\n    Returns:\n        Decrypted plaintext string\n    \"\"\"\n    if not encrypted_str:\n        return \"\"\n\n    if not encrypted_str.startswith(ENCRYPTED_PREFIX):\n        # Not encrypted, return as-is (for backwards compatibility)\n        return encrypted_str\n\n    encoded = encrypted_str[len(ENCRYPTED_PREFIX) :]\n\n    try:\n        encrypted = base64.b64decode(encoded)\n    except Exception as e:\n        raise SecureConfigError(f\"Invalid base64 encoding: {e}\")\n\n    if len(encrypted) < 16:\n        raise SecureConfigError(\"Encrypted data too short\")\n\n    iv = encrypted[:16]\n    ciphertext = encrypted[16:]\n\n    master_key = _get_master_key()\n    cipher = _create_cipher(master_key, iv)\n\n    try:\n        decryptor = cipher.decryptor()\n        decrypted = decryptor.update(ciphertext) + decryptor.finalize()\n        unpadder = padding.PKCS7(128).unpadder()\n        plaintext = unpadder.update(decrypted) + unpadder.finalize()\n        return plaintext.decode(\"utf-8\")\n    except Exception as e:\n        raise SecureConfigError(f\"Decryption failed: {e}\")\n\n\ndef get_secret(key_name: str, default: Optional[str] = None) -> Optional[str]:\n    \"\"\"\n    Get a secret value, automatically decrypting if encrypted.\n\n    Checks for encrypted version first (key_name + \"_ENC\"), then falls back\n    to plain version. Returns None if neither exists.\n    \"\"\"\n    # Try encrypted version first\n    enc_key = f\"{key_name}_ENC\"\n    enc_value = os.getenv(enc_key)\n\n    if enc_value:\n        try:\n            return decrypt_value(enc_value)\n        except SecureConfigError as e:\n            print(f\"⚠️  Failed to decrypt {key_name}: {e}\")\n            # Fall back to plain version\n\n    # Try plain version\n    plain_value = os.getenv(key_name)\n    if plain_value:\n        # Warn if sensitive key is stored in plaintext\n        if key_name in DEFAULT_SENSITIVE_KEYS and os.getenv(\"APP_ENV\") != \"test\":\n            print(\n                f\"⚠️  WARNING: {key_name} is stored in plaintext. Consider encrypting it.\"\n            )\n        return plain_value\n\n    return default\n\n\ndef get_config(key_name: str, default: Optional[str] = None) -> Optional[str]:\n    \"\"\"\n    Get configuration value (non-sensitive). Same as os.getenv but with logging.\n    \"\"\"\n    value = os.getenv(key_name, default)\n    return value\n\n\ndef migrate_env_file(input_path: str = \".env\", output_path: str = \".env.encrypted\"):\n    \"\"\"\n    Migrate .env file to use encrypted values for sensitive keys.\n\n    Creates a new file with encrypted values for sensitive keys.\n    Original keys are commented out and new _ENC keys are added.\n    \"\"\"\n    input_file = Path(input_path)\n    if not input_file.exists():\n        raise FileNotFoundError(f\"Input file not found: {input_path}\")\n\n    lines = input_file.read_text().splitlines()\n    output_lines = []\n\n    for line in lines:\n        line = line.strip()\n\n        # Skip empty lines and comments\n        if not line or line.startswith(\"#\"):\n            output_lines.append(line)\n            continue\n\n        # Parse key=value\n        if \"=\" not in line:\n            output_lines.append(line)\n            continue\n\n        key, value = line.split(\"=\", 1)\n        key = key.strip()\n        value = value.strip()\n\n        # Remove quotes if present\n        if value.startswith(('\"', \"'\")) and value.endswith(('\"', \"'\")):\n            value = value[1:-1]\n\n        # Check if this is a sensitive key\n        if key in DEFAULT_SENSITIVE_KEYS and value:\n            # Encrypt the value\n            try:\n                encrypted = encrypt_value(value)\n                # Comment out original line\n                output_lines.append(f\"# {line}\")\n                # Add encrypted version\n                output_lines.append(f\"{key}_ENC={encrypted}\")\n                print(f\"✓ Encrypted {key}\")\n            except Exception as e:\n                print(f\"✗ Failed to encrypt {key}: {e}\")\n                output_lines.append(line)\n        else:\n            output_lines.append(line)\n\n    # Write output file\n    output_file = Path(output_path)\n    output_file.write_text(\"\\n\".join(output_lines))\n    print(f\"\\n✅ Created encrypted environment file: {output_path}\")\n    print(\"   Review the file and replace your original .env if ready.\")\n    print(\"   Don't forget to set your master key!\")\n    print(f\"   Export: export {MASTER_KEY_ENV_VAR}=$(cat ~/.ai-product-lab/master.key)\")\n\n\ndef init_master_key(key_path: Optional[str] = None) -> str:\n    \"\"\"\n    Initialize a new random master key.\n\n    Args:\n        key_path: Path to save the key (default: ~/.ai-product-lab/master.key)\n\n    Returns:\n        Base64 encoded key (for display only)\n    \"\"\"\n    if key_path:\n        key_file = Path(key_path)\n    else:\n        key_file = MASTER_KEY_FILE\n\n    # Create parent directory if needed\n    key_file.parent.mkdir(parents=True, exist_ok=True)\n\n    # Generate random 32-byte key\n    random_key = get_random_bytes(32)\n\n    # Save as base64\n    encoded_key = base64.b64encode(random_key).decode(\"utf-8\")\n    key_file.write_text(encoded_key)\n\n    # Set restrictive permissions (owner read/write only)\n    key_file.chmod(0o600)\n\n    print(f\"✅ Generated new master key at: {key_file}\")\n    print(f\"   Key (base64): {encoded_key}\")\n    print(f\"\\n   To use immediately: export {MASTER_KEY_ENV_VAR}='{encoded_key}'\")\n    print(f\"   Or ensure the key file is at: {MASTER_KEY_FILE}\")\n\n    return encoded_key\n\n\n# Convenience functions for common secrets\ndef get_deepseek_key() -> Optional[str]:\n    return get_secret(\"DEEPSEEK_API_KEY\")\n\n\ndef get_feishu_app_secret() -> Optional[str]:\n    return get_secret(\"FEISHU_APP_SECRET\")\n\n\ndef get_feishu_encrypt_key() -> Optional[str]:\n    return get_secret(\"FEISHU_ENCRYPT_KEY\")\n\n\ndef get_feishu_verification_token() -> Optional[str]:\n    return get_secret(\"FEISHU_VERIFICATION_TOKEN\")\n\n\ndef get_ngrok_token() -> Optional[str]:\n    return get_secret(\"NGROK_AUTHTOKEN\")\n"}, "eec1b4fcb63813f73c442c9463f5bbb553612f9b": {"t": 1785765006.0588107, "n": 10283, "h": "954aa47d912a2321", "c": "\"\"\"\nSecure configuration management with optional encryption for sensitive values.\n\nUsage:\n1. Set a master key via environment variable: AI_MASTER_KEY or in ~/.ai-product-lab/master.key\n2. Encrypt sensitive values using the encrypt_value() function\n3. Store encrypted values in .env with prefix ENC_\n4. Use get_secret() to automatically decrypt values\n\nExample:\n    Before: DEEPSEEK_API_KEY=sk-abc123\n    After:  DEEPSEEK_API_KEY_ENC=ENC:gAAAAABm... (encrypted)\n\n    In code: api_key = get_secret(\"DEEPSEEK_API_KEY\")\n\"\"\"\n\nimport base64\nimport binascii\nimport hashlib\nimport os\nfrom pathlib import Path\nfrom typing import Optional\n\nimport os\nfrom cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes\nfrom cryptography.hazmat.primitives import padding\nfrom cryptography.hazmat.backends import default_backend\n\n# Constants\nMASTER_KEY_ENV_VAR = \"AI_MASTER_KEY\"\nMASTER_KEY_FILE = Path.home() / \".ai-product-lab\" / \"master.key\"\nENCRYPTED_PREFIX = \"ENC:\"\nDEFAULT_SENSITIVE_KEYS = [\n    \"DEEPSEEK_API_KEY\",\n    \"MOONSHOT_API_KEY\",\n    \"FEISHU_APP_SECRET\",\n    \"FEISHU_ENCRYPT_KEY\",\n    \"FEISHU_VERIFICATION_TOKEN\",\n    \"NGROK_AUTHTOKEN\",\n    \"OPENAI_API_KEY\",\n    \"ANTHROPIC_API_KEY\",\n    \"GEMINI_API_KEY\",\n    \"OPENROUTER_API_KEY\",\n    \"LITELLM_MASTER_KEY\",\n    \"POSTGRES_PASSWORD\",\n    \"REDIS_PASSWORD\",\n    \"QDRANT_API_KEY\",\n]\n\n\nclass SecureConfigError(Exception):\n    \"\"\"Secure configuration error.\"\"\"\n\n    pass\n\n\ndef _get_master_key() -> bytes:\n    \"\"\"Get master key from environment variable or file.\"\"\"\n    # Try environment variable first\n    master_key = os.getenv(MASTER_KEY_ENV_VAR)\n    if master_key:\n        # Ensure it's 32 bytes for AES-256\n        key_hash = hashlib.sha256(master_key.encode()).digest()\n        return key_hash\n\n    # Try key file\n    if MASTER_KEY_FILE.exists():\n        try:\n            key_data = MASTER_KEY_FILE.read_bytes()\n            # File can contain raw bytes or base64 encoded string\n            if len(key_data) == 32:\n                return key_data\n            else:\n                # Try to decode as base64\n                try:\n                    decoded = base64.b64decode(key_data)\n                    if len(decoded) == 32:\n                        return decoded\n                    else:\n                        # Hash to 32 bytes\n                        return hashlib.sha256(decoded).digest()[:32]\n                except (binascii.Error, ValueError):\n                    # Hash the raw bytes\n                    return hashlib.sha256(key_data).digest()[:32]\n        except Exception as e:\n            raise SecureConfigError(f\"Failed to read master key file: {e}\")\n\n    # No master key found - in development, we can fall back to a default\n    # but warn loudly. In production, this should fail.\n    if os.getenv(\"APP_ENV\") == \"dev\":\n        print(\"⚠️  WARNING: No master key found. Using default development key.\")\n        print(f\"   Set {MASTER_KEY_ENV_VAR} or create {MASTER_KEY_FILE}\")\n        # Generate deterministic key from string for development\n        dev_key = \"dev-master-key-insecure-change-in-production\"\n        return hashlib.sha256(dev_key.encode()).digest()\n\n    raise SecureConfigError(\n        f\"Master key required. Set {MASTER_KEY_ENV_VAR} environment variable \"\n        f\"or create {MASTER_KEY_FILE} with 32-byte key.\"\n    )\n\n\ndef _create_cipher(key: bytes, iv: bytes) -> Cipher:\n    \"\"\"Create AES cipher in CBC mode.\"\"\"\n    return Cipher(algorithms.AES(key), modes.CBC(iv), backend=default_backend())\n\n\ndef encrypt_value(plaintext: str) -> str:\n    \"\"\"\n    Encrypt a plaintext string.\n\n    Returns:\n        Base64 encoded string with format: ENC:<base64(iv + ciphertext)>\n    \"\"\"\n    if not plaintext:\n        return \"\"\n\n    master_key = _get_master_key()\n    iv = os.urandom(16)\n    cipher = _create_cipher(master_key, iv)\n    encryptor = cipher.encryptor()\n\n    # Encrypt with PKCS7 padding\n    padder = padding.PKCS7(128).padder()\n    padded_data = padder.update(plaintext.encode(\"utf-8\")) + padder.finalize()\n    ciphertext = encryptor.update(padded_data) + encryptor.finalize()\n\n    # Combine IV and ciphertext\n    encrypted = iv + ciphertext\n    encoded = base64.b64encode(encrypted).decode(\"utf-8\")\n\n    return f\"{ENCRYPTED_PREFIX}{encoded}\"\n\n\ndef decrypt_value(encrypted_str: str) -> str:\n    \"\"\"\n    Decrypt an encrypted string.\n\n    Args:\n        encrypted_str: String with format ENC:<base64(iv + ciphertext)>\n\n    Returns:\n        Decrypted plaintext string\n    \"\"\"\n    if not encrypted_str:\n        return \"\"\n\n    if not encrypted_str.startswith(ENCRYPTED_PREFIX):\n        # Not encrypted, return as-is (for backwards compatibility)\n        return encrypted_str\n\n    encoded = encrypted_str[len(ENCRYPTED_PREFIX) :]\n\n    try:\n        encrypted = base64.b64decode(encoded)\n    except Exception as e:\n        raise SecureConfigError(f\"Invalid base64 encoding: {e}\")\n\n    if len(encrypted) < 16:\n        raise SecureConfigError(\"Encrypted data too short\")\n\n    iv = encrypted[:16]\n    ciphertext = encrypted[16:]\n\n    master_key = _get_master_key()\n    cipher = _create_cipher(master_key, iv)\n\n    try:\n        decryptor = cipher.decryptor()\n        decrypted = decryptor.update(ciphertext) + decryptor.finalize()\n        unpadder = padding.PKCS7(128).unpadder()\n        plaintext = unpadder.update(decrypted) + unpadder.finalize()\n        return plaintext.decode(\"utf-8\")\n    except Exception as e:\n        raise SecureConfigError(f\"Decryption failed: {e}\")\n\n\ndef get_secret(key_name: str, default: Optional[str] = None) -> Optional[str]:\n    \"\"\"\n    Get a secret value, automatically decrypting if encrypted.\n\n    Checks for encrypted version first (key_name + \"_ENC\"), then falls back\n    to plain version. Returns None if neither exists.\n    \"\"\"\n    # Try encrypted version first\n    enc_key = f\"{key_name}_ENC\"\n    enc_value = os.getenv(enc_key)\n\n    if enc_value:\n        try:\n            return decrypt_value(enc_value)\n        except SecureConfigError as e:\n            print(f\"⚠️  Failed to decrypt {key_name}: {e}\")\n            # Fall back to plain version\n\n    # Try plain version\n    plain_value = os.getenv(key_name)\n    if plain_value:\n        # Warn if sensitive key is stored in plaintext\n        if key_name in DEFAULT_SENSITIVE_KEYS and os.getenv(\"APP_ENV\") != \"test\":\n            print(\n                f\"⚠️  WARNING: {key_name} is stored in plaintext. Consider encrypting it.\"\n            )\n        return plain_value\n\n    return default\n\n\ndef get_config(key_name: str, default: Optional[str] = None) -> Optional[str]:\n    \"\"\"\n    Get configuration value (non-sensitive). Same as os.getenv but with logging.\n    \"\"\"\n    value = os.getenv(key_name, default)\n    return value\n\n\ndef migrate_env_file(input_path: str = \".env\", output_path: str = \".env.encrypted\"):\n    \"\"\"\n    Migrate .env file to use encrypted values for sensitive keys.\n\n    Creates a new file with encrypted values for sensitive keys.\n    Original keys are commented out and new _ENC keys are added.\n    \"\"\"\n    input_file = Path(input_path)\n    if not input_file.exists():\n        raise FileNotFoundError(f\"Input file not found: {input_path}\")\n\n    lines = input_file.read_text().splitlines()\n    output_lines = []\n\n    for line in lines:\n        line = line.strip()\n\n        # Skip empty lines and comments\n        if not line or line.startswith(\"#\"):\n            output_lines.append(line)\n            continue\n\n        # Parse key=value\n        if \"=\" not in line:\n            output_lines.append(line)\n            continue\n\n        key, value = line.split(\"=\", 1)\n        key = key.strip()\n        value = value.strip()\n\n        # Remove quotes if present\n        if value.startswith(('\"', \"'\")) and value.endswith(('\"', \"'\")):\n            value = value[1:-1]\n\n        # Check if this is a sensitive key\n        if key in DEFAULT_SENSITIVE_KEYS and value:\n            # Encrypt the value\n            try:\n                encrypted = encrypt_value(value)\n                # Comment out original line\n                output_lines.append(f\"# {line}\")\n                # Add encrypted version\n                output_lines.append(f\"{key}_ENC={encrypted}\")\n                print(f\"✓ Encrypted {key}\")\n            except Exception as e:\n                print(f\"✗ Failed to encrypt {key}: {e}\")\n                output_lines.append(line)\n        else:\n            output_lines.append(line)\n\n    # Write output file\n    output_file = Path(output_path)\n    output_file.write_text(\"\\n\".join(output_lines))\n    print(f\"\\n✅ Created encrypted environment file: {output_path}\")\n    print(\"   Review the file and replace your original .env if ready.\")\n    print(\"   Don't forget to set your master key!\")\n    print(f\"   Export: export {MASTER_KEY_ENV_VAR}=$(cat ~/.ai-product-lab/master.key)\")\n\n\ndef init_master_key(key_path: Optional[str] = None) -> str:\n    \"\"\"\n    Initialize a new random master key.\n\n    Args:\n        key_path: Path to save the key (default: ~/.ai-product-lab/master.key)\n\n    Returns:\n        Base64 encoded key (for display only)\n    \"\"\"\n    if key_path:\n        key_file = Path(key_path)\n    else:\n        key_file = MASTER_KEY_FILE\n\n    # Create parent directory if needed\n    key_file.parent.mkdir(parents=True, exist_ok=True)\n\n    # Generate random 32-byte key\n    random_key = get_random_bytes(32)\n\n    # Save as base64\n    encoded_key = base64.b64encode(random_key).decode(\"utf-8\")\n    key_file.write_text(encoded_key)\n\n    # Set restrictive permissions (owner read/write only)\n    key_file.chmod(0o600)\n\n    print(f\"✅ Generated new master key at: {key_file}\")\n    print(f\"   Key (base64): {encoded_key}\")\n    print(f\"\\n   To use immediately: export {MASTER_KEY_ENV_VAR}='{encoded_key}'\")\n    print(f\"   Or ensure the key file is at: {MASTER_KEY_FILE}\")\n\n    return encoded_key\n\n\n# Convenience functions for common secrets\ndef get_deepseek_key() -> Optional[str]:\n    return get_secret(\"DEEPSEEK_API_KEY\")\n\n\ndef get_feishu_app_secret() -> Optional[str]:\n    return get_secret(\"FEISHU_APP_SECRET\")\n\n\ndef get_feishu_encrypt_key() -> Optional[str]:\n    return get_secret(\"FEISHU_ENCRYPT_KEY\")\n\n\ndef get_feishu_verification_token() -> Optional[str]:\n    return get_secret(\"FEISHU_VERIFICATION_TOKEN\")\n\n\ndef get_ngrok_token() -> Optional[str]:\n    return get_secret(\"NGROK_AUTHTOKEN\")\n"}}}}