feat: add api key auth, devii agent, openai gateway, and admin service management

This commit introduces a comprehensive set of new features including API key authentication with CLI management commands (get, reset, backfill), a Devii agentic assistant with WebSocket terminal and session bootstrap, an OpenAI-compatible LLM gateway service, and an admin service management panel. It also adds Playwright browser automation for bot support, configures internal gateway URLs, refactors content editing/deletion to support JSON API responses, and updates documentation across AGENTS.md, README.md, and the developer docs site.

devplacepy/services/devii/llm.py

@@ -0,0 +1,105 @@
+# retoor <retoor@molodetz.nl>
+
+from __future__ import annotations
+
+import logging
+from typing import Any
+
+import httpx
+
+from .config import Settings
+from .cost import record_usage
+from .errors import LLMError
+
+logger = logging.getLogger("devii.llm")
+
+
+class LLMClient:
+    def __init__(self, settings: Settings) -> None:
+        self._settings = settings
+        self._client = httpx.AsyncClient(
+            timeout=settings.timeout_seconds,
+            headers={
+                "Authorization": f"Bearer {settings.ai_key}",
+                "Content-Type": "application/json",
+            },
+        )
+
+    async def aclose(self) -> None:
+        await self._client.aclose()
+
+    async def complete(
+        self,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]],
+    ) -> dict[str, Any]:
+        payload = {
+            "model": self._settings.ai_model,
+            "messages": messages,
+            "tools": tools,
+            "tool_choice": "auto",
+        }
+        try:
+            logger.debug("LLM request with %d messages", len(messages))
+            response = await self._client.post(self._settings.ai_url, json=payload)
+        except httpx.HTTPError as exc:
+            raise LLMError(f"Could not reach the model endpoint: {exc}") from exc
+
+        if response.status_code >= 400:
+            raise LLMError(
+                f"Model endpoint returned {response.status_code}: {self._reason(response)}",
+                status=response.status_code,
+                body=response.text[:500],
+            )
+
+        try:
+            data = response.json()
+        except ValueError as exc:
+            raise LLMError("Model endpoint returned invalid JSON.") from exc
+
+        choices = data.get("choices")
+        if not choices:
+            raise LLMError("Model response contained no choices.", body=str(data)[:500])
+
+        message = choices[0].get("message")
+        if message is None:
+            raise LLMError("Model response contained no message.", body=str(data)[:500])
+
+        record_usage(data.get("usage"))
+        logger.debug("LLM response received (tool_calls=%s)", bool(message.get("tool_calls")))
+        return message
+
+    async def summarize(self, text: str) -> str:
+        payload = {
+            "model": self._settings.ai_model,
+            "messages": [
+                {"role": "system", "content": "You are a precise technical summarizer."},
+                {"role": "user", "content": text},
+            ],
+            "temperature": 0.0,
+        }
+        try:
+            response = await self._client.post(self._settings.ai_url, json=payload)
+        except httpx.HTTPError as exc:
+            raise LLMError(f"Could not reach the model endpoint: {exc}") from exc
+        if response.status_code >= 400:
+            raise LLMError(f"Model endpoint returned {response.status_code}: {self._reason(response)}")
+        try:
+            data = response.json()
+            content = data["choices"][0]["message"]["content"] or ""
+        except (ValueError, KeyError, IndexError) as exc:
+            raise LLMError("Model summarization returned an unexpected response.") from exc
+        record_usage(data.get("usage"))
+        return content
+
+    @staticmethod
+    def _reason(response: httpx.Response) -> str:
+        try:
+            error = response.json().get("error")
+        except ValueError:
+            return response.text[:200] or response.reason_phrase
+        if isinstance(error, dict):
+            return str(error.get("message", error))
+        if error:
+            return str(error)
+        return response.reason_phrase