ObsiGate/backend/ai_routes.py

"""ObsiGate AI — API routes for AI-powered editor features."""

import logging

from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field

from backend.ai import (
    DEFAULT_PROVIDER,
    PROVIDERS,
    ai_change_tone,
    ai_continue_writing,
    ai_convert_to_canvas,
    ai_convert_to_list,
    ai_convert_to_table,
    ai_custom_rewrite,
    ai_explain,
    ai_fix_spelling,
    ai_generate_frontmatter,
    ai_improve_writing,
    ai_inline_complete,
    ai_make_longer,
    ai_make_shorter,
    ai_simplify,
    ai_summarize,
    ai_translate,
)

logger = logging.getLogger("obsigate.ai_routes")
router = APIRouter(prefix="/api/ai", tags=["AI"])


@router.get("/status")
async def api_status():
    """Check if AI is configured and which providers are available.

    Reads environment variables at runtime so that changes to
    .env or Docker environment are reflected immediately.
    """
    from backend.ai import get_ai_key
    provider_keys = {
        "deepseek": "DEEPSEEK_API_KEY",
        "openrouter": "OPENROUTER_API_KEY",
        "gemini": "GEMINI_API_KEY",
    }
    providers = {}
    for name, env_var in provider_keys.items():
        has_key = bool(get_ai_key(env_var))
        providers[name] = {
            "available": has_key,
            "model": PROVIDERS[name]["model"] if has_key else None,
        }

    # ---- Autocomplete (Ollama) status ----
    ollama_cfg = PROVIDERS.get("ollama", {})
    ollama_url = (ollama_cfg.get("base_url") or "").rstrip("/v1").rstrip("/")
    ollama_model = ollama_cfg.get("model", "")
    autocomplete = {
        "available": False,
        "server_ok": False,
        "model_loaded": False,
        "model": ollama_model,
        "error": None,
    }
    if ollama_url:
        try:
            import httpx
            async with httpx.AsyncClient(timeout=5.0) as client:
                # Check server health + list loaded models
                r = await client.get(f"{ollama_url}/api/tags")
                if r.status_code == 200:
                    autocomplete["server_ok"] = True
                    data = r.json()
                    models = [m.get("name", "") for m in data.get("models", [])]
                    # Check if our model (with or without tag) is loaded
                    model_base = ollama_model.split(":")[0]
                    autocomplete["model_loaded"] = any(
                        m == ollama_model or m.startswith(model_base + ":")
                        for m in models
                    )
                    autocomplete["available"] = autocomplete["model_loaded"]
                else:
                    autocomplete["error"] = f"HTTP {r.status_code}"
        except Exception as e:
            autocomplete["error"] = str(e)

    return {
        "configured": any(p["available"] for p in providers.values()),
        "default_provider": DEFAULT_PROVIDER,
        "providers": providers,
        "autocomplete": autocomplete,
    }


class AIRequest(BaseModel):
    text: str = Field(..., description="Input text to process", min_length=1)
    instruction: str | None = Field(None, description="Custom instruction for rewrite")
    target_lang: str | None = Field(None, description="Target language for translation")
    tone: str | None = Field(None, description="Target tone (professional, casual, etc.)")
    provider: str | None = Field(None, description="AI provider override")


class AIResponse(BaseModel):
    result: str = Field(..., description="Processed text result")
    provider: str = Field(..., description="AI provider used")


async def _handle(action, request: AIRequest):
    """Wrapper with error handling."""
    try:
        result = await action(request.text, request.provider)
        return AIResponse(result=result, provider=request.provider or "default")
    except ValueError as e:
        raise HTTPException(status_code=400, detail=str(e))
    except Exception as e:
        logger.error(f"AI error: {e}")
        raise HTTPException(status_code=500, detail=f"AI service error: {e!s}")


@router.post("/improve", response_model=AIResponse)
async def api_improve(req: AIRequest):
    """Improve writing quality."""
    return await _handle(ai_improve_writing, req)


@router.post("/fix-spelling", response_model=AIResponse)
async def api_fix_spelling(req: AIRequest):
    """Fix spelling and grammar."""
    return await _handle(ai_fix_spelling, req)


@router.post("/make-shorter", response_model=AIResponse)
async def api_make_shorter(req: AIRequest):
    """Make text more concise."""
    return await _handle(ai_make_shorter, req)


@router.post("/make-longer", response_model=AIResponse)
async def api_make_longer(req: AIRequest):
    """Expand text with more detail."""
    return await _handle(ai_make_longer, req)


@router.post("/simplify", response_model=AIResponse)
async def api_simplify(req: AIRequest):
    """Simplify language."""
    return await _handle(ai_simplify, req)


@router.post("/tone", response_model=AIResponse)
async def api_tone(req: AIRequest):
    """Change text tone. Requires `tone` field (e.g., 'professional', 'casual')."""
    if not req.tone:
        raise HTTPException(status_code=400, detail="Field 'tone' is required (e.g., 'professional', 'casual')")
    return await _handle(lambda text, p: ai_change_tone(text, req.tone, p), req)


@router.post("/translate", response_model=AIResponse)
async def api_translate(req: AIRequest):
    """Translate text. Requires `target_lang` field (e.g., 'French', 'English', 'Japanese')."""
    if not req.target_lang:
        raise HTTPException(status_code=400, detail="Field 'target_lang' is required")
    return await _handle(lambda text, p: ai_translate(text, req.target_lang, p), req)


@router.post("/explain", response_model=AIResponse)
async def api_explain(req: AIRequest):
    """Explain the selected text."""
    return await _handle(ai_explain, req)


@router.post("/summarize", response_model=AIResponse)
async def api_summarize(req: AIRequest):
    """Summarize text."""
    return await _handle(ai_summarize, req)


@router.post("/continue", response_model=AIResponse)
async def api_continue(req: AIRequest):
    """Continue writing from the selected text."""
    return await _handle(ai_continue_writing, req)


@router.post("/rewrite", response_model=AIResponse)
async def api_rewrite(req: AIRequest):
    """Custom rewrite with instruction. Requires `instruction` field."""
    if not req.instruction:
        raise HTTPException(status_code=400, detail="Field 'instruction' is required")
    return await _handle(lambda text, p: ai_custom_rewrite(text, req.instruction, p), req)


@router.post("/to-list", response_model=AIResponse)
async def api_to_list(req: AIRequest):
    """Convert text to a markdown list."""
    return await _handle(ai_convert_to_list, req)


@router.post("/to-table", response_model=AIResponse)
async def api_to_table(req: AIRequest):
    """Convert text to a markdown table."""
    return await _handle(ai_convert_to_table, req)


@router.post("/frontmatter", response_model=AIResponse)
async def api_frontmatter(req: AIRequest):
    """Generate YAML frontmatter."""
    return await _handle(ai_generate_frontmatter, req)


@router.post("/inline-complete", response_model=AIResponse)
async def api_inline_complete(req: AIRequest):
    """Inline completion."""
    return await _handle(ai_inline_complete, req)


@router.post("/to-canvas", response_model=AIResponse)
async def api_to_canvas(req: AIRequest):
    """Convert to Mermaid diagram or outline."""
    return await _handle(ai_convert_to_canvas, req)