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ObsiGate/backend/bookslm_routes.py
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feat(bookslm): v2.2.0 - BooksLM chat AI contextuel par répertoire + 4 providers AI
BooksLM (#76):
- Panneau chat slide-in 450px, clic-droit répertoire → 🧠 BooksLM
- Collecte récursive .md avec limites (200 fichiers, 200K chars)
- Cache SHA-256, redaction secrets, priorité README/index
- SSE streaming, badges sources cliquables, historique localStorage
- Commandes palette: BooksLM ouvrir/nouvelle conversation

Providers AI (4 nouveaux):
- NVIDIA (integrate.api.nvidia.com)
- QwenCloud (dashscope.aliyuncs.com)
- Xiaomi (api.xiaomi.com)
- Mistral (api.mistral.ai)
- Tous OpenAI-compatible, auto-listing modèles

Fix: dropdown config-select suit maintenant le thème (option bg/color)
27 tests BooksLM + 466 tests au total
2026-09-06 19:42:40 -04:00

148 lines
5.3 KiB
Python

"""BooksLM API routes — directory-scoped AI chat for Obsidian vaults."""
import json
import logging
from pathlib import Path
from fastapi import APIRouter, Depends, HTTPException
from fastapi.responses import StreamingResponse
from pydantic import BaseModel, Field
from backend.auth.middleware import check_vault_access, require_auth
from backend.bookslm import build_system_prompt, collect_directory_context
from backend.indexer import get_vault_data
logger = logging.getLogger("obsigate.bookslm_routes")
router = APIRouter(prefix="/api/ai/bookslm", tags=["BooksLM"])
# ── Request models ──
class BooksLMContextRequest(BaseModel):
vault: str = Field(description="Vault name")
directory: str = Field(default="", description="Relative directory path within the vault")
class BooksLMChatRequest(BaseModel):
vault: str = Field(description="Vault name")
directory: str = Field(default="", description="Relative directory path within the vault")
message: str = Field(description="User message")
conversation_history: list[dict[str, str]] = Field(
default_factory=list,
description="Previous conversation turns [{role, content}]",
)
# ── Endpoints ──
@router.post("/context")
async def api_bookslm_context(
req: BooksLMContextRequest,
current_user=Depends(require_auth),
):
"""Collect directory context for BooksLM.
Returns file list, content, and metadata for the specified directory.
"""
if not check_vault_access(req.vault, current_user):
raise HTTPException(status_code=403, detail=f"Accès refusé à la vault '{req.vault}'")
vault_data = get_vault_data(req.vault)
if not vault_data:
raise HTTPException(status_code=404, detail=f"Vault '{req.vault}' not found")
vault_path = Path(vault_data["path"])
context = collect_directory_context(vault_path, req.directory)
return context
@router.post("/chat")
async def api_bookslm_chat(
req: BooksLMChatRequest,
current_user=Depends(require_auth),
):
"""Chat with AI about directory contents (BooksLM).
Builds context from the directory, then sends the user message
with a system prompt containing all file contents to the AI provider.
Returns an SSE stream with the response.
"""
if not check_vault_access(req.vault, current_user):
raise HTTPException(status_code=403, detail=f"Accès refusé à la vault '{req.vault}'")
vault_data = get_vault_data(req.vault)
if not vault_data:
raise HTTPException(status_code=404, detail=f"Vault '{req.vault}' not found")
vault_path = Path(vault_data["path"])
# Collect context
context = collect_directory_context(vault_path, req.directory)
if context["file_count"] == 0:
raise HTTPException(status_code=404, detail="Aucun fichier markdown trouvé dans ce dossier")
# Build system prompt
system_prompt = build_system_prompt(context)
# Call AI provider
from backend.ai import DEFAULT_PROVIDER, PROVIDERS, _call_deepseek_openrouter, _call_gemini
# Build messages with conversation history
messages_text = ""
if req.conversation_history:
for turn in req.conversation_history:
role = turn.get("role", "user")
content = turn.get("content", "")
if role == "user":
messages_text += f"\n\nUtilisateur : {content}"
elif role == "assistant":
messages_text += f"\n\nAssistant : {content}"
# Current message
user_prompt = req.message
if messages_text:
user_prompt = f"Historique de la conversation :{messages_text}\n\nQuestion actuelle : {req.message}"
async def generate_sse():
try:
cfg_name = DEFAULT_PROVIDER
# Check if default provider is available
if cfg_name != "gemini" and cfg_name in PROVIDERS:
if not PROVIDERS[cfg_name].get("api_key"):
# Find first available provider
for pname, pcfg in PROVIDERS.items():
if pcfg.get("api_key") and pname != "gemini":
cfg_name = pname
break
if cfg_name == "gemini" and PROVIDERS.get("gemini", {}).get("api_key"):
response = await _call_gemini(user_prompt, system_prompt, temperature=0.3, max_tokens=4096)
else:
response = await _call_deepseek_openrouter(
user_prompt, system_prompt,
provider=cfg_name if cfg_name in PROVIDERS else None,
temperature=0.3,
max_tokens=4096,
)
# Send the full response as a single SSE event
data = json.dumps({"token": response}, ensure_ascii=False)
yield f"event: message\ndata: {data}\n\n"
yield "event: done\ndata: {}\n\n"
except Exception as e:
logger.error(f"BooksLM chat error: {e}")
error_data = json.dumps({"error": str(e)}, ensure_ascii=False)
yield f"event: error\ndata: {error_data}\n\n"
return StreamingResponse(
generate_sse(),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
},
)