feat: add site assistant component for guided tool selection

- Introduced SiteAssistant component to assist users in selecting the right tools based on their queries.
- Integrated assistant into the main App component.
- Implemented message handling and storage for user-assistant interactions.
- Added quick prompts for common user queries related to tools.
- Enhanced ToolLandingPage and DownloadButton components with SharePanel for sharing tool results.
- Updated translations for new assistant features and sharing options.
- Added API methods for chat functionality with the assistant, including streaming responses.
This commit is contained in:
Your Name
2026-03-14 10:07:55 +02:00
parent e06e64f85f
commit 2b3367cdea
21 changed files with 1877 additions and 39 deletions

View File

@@ -8,6 +8,7 @@ from app.extensions import cors, limiter, talisman, init_celery
from app.services.account_service import init_account_db
from app.services.rating_service import init_ratings_db
from app.services.ai_cost_service import init_ai_cost_db
from app.services.site_assistant_service import init_site_assistant_db
def create_app(config_name=None):
@@ -77,6 +78,7 @@ def create_app(config_name=None):
init_account_db()
init_ratings_db()
init_ai_cost_db()
init_site_assistant_db()
# Register blueprints
from app.routes.health import health_bp
@@ -103,6 +105,7 @@ def create_app(config_name=None):
from app.routes.html_to_pdf import html_to_pdf_bp
from app.routes.pdf_ai import pdf_ai_bp
from app.routes.rating import rating_bp
from app.routes.assistant import assistant_bp
app.register_blueprint(health_bp, url_prefix="/api")
app.register_blueprint(auth_bp, url_prefix="/api/auth")
@@ -128,5 +131,6 @@ def create_app(config_name=None):
app.register_blueprint(html_to_pdf_bp, url_prefix="/api/convert")
app.register_blueprint(pdf_ai_bp, url_prefix="/api/pdf-ai")
app.register_blueprint(rating_bp, url_prefix="/api/ratings")
app.register_blueprint(assistant_bp, url_prefix="/api/assistant")
return app

View File

@@ -0,0 +1,84 @@
"""Site assistant routes — global AI helper for the product UI."""
import json
from flask import Blueprint, Response, jsonify, request, stream_with_context
from app.extensions import limiter
from app.services.policy_service import resolve_web_actor
from app.services.site_assistant_service import chat_with_site_assistant, stream_site_assistant_chat
assistant_bp = Blueprint("assistant", __name__)
def _parse_chat_payload():
payload = request.get_json(silent=True) or {}
message = str(payload.get("message", "")).strip()
if not message:
return None, (jsonify({"error": "Message is required."}), 400)
if len(message) > 4000:
return None, (jsonify({"error": "Message is too long."}), 400)
actor = resolve_web_actor()
return {
"message": message,
"session_id": str(payload.get("session_id", "")).strip() or None,
"fingerprint": str(payload.get("fingerprint", "")).strip() or "anonymous",
"tool_slug": str(payload.get("tool_slug", "")).strip(),
"page_url": str(payload.get("page_url", "")).strip(),
"locale": str(payload.get("locale", "en")).strip() or "en",
"user_id": actor.user_id,
"history": payload.get("history") if isinstance(payload.get("history"), list) else None,
}, None
def _sse(event: str, data: dict) -> str:
return f"event: {event}\ndata: {json.dumps(data, ensure_ascii=True)}\n\n"
@assistant_bp.route("/chat", methods=["POST"])
@limiter.limit("20/minute")
def assistant_chat_route():
"""Answer a product-help message and store the conversation for later analysis."""
chat_kwargs, error_response = _parse_chat_payload()
if error_response:
return error_response
try:
result = chat_with_site_assistant(**chat_kwargs)
except ValueError as exc:
return jsonify({"error": str(exc)}), 400
except Exception:
return jsonify({"error": "Assistant is temporarily unavailable."}), 500
return jsonify(result), 200
@assistant_bp.route("/chat/stream", methods=["POST"])
@limiter.limit("20/minute")
def assistant_chat_stream_route():
"""Stream assistant replies incrementally over SSE."""
chat_kwargs, error_response = _parse_chat_payload()
if error_response:
return error_response
try:
events = stream_site_assistant_chat(**chat_kwargs)
except ValueError as exc:
return jsonify({"error": str(exc)}), 400
except Exception:
return jsonify({"error": "Assistant is temporarily unavailable."}), 500
def generate():
for event in events:
yield _sse(event["event"], event["data"])
return Response(
stream_with_context(generate()),
content_type="text/event-stream; charset=utf-8",
headers={
"Cache-Control": "no-cache",
"X-Accel-Buffering": "no",
},
)

View File

@@ -1,17 +1,11 @@
"""AI Chat Service — OpenRouter integration for flowchart improvement."""
import os
import json
import logging
import requests
logger = logging.getLogger(__name__)
from app.services.openrouter_config_service import get_openrouter_settings
# Configuration
OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY", "")
OPENROUTER_MODEL = os.getenv("OPENROUTER_MODEL", "stepfun/step-3.5-flash:free")
OPENROUTER_BASE_URL = os.getenv(
"OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1/chat/completions"
)
logger = logging.getLogger(__name__)
SYSTEM_PROMPT = """You are a flowchart improvement assistant. You help users improve their flowcharts by:
1. Suggesting better step titles and descriptions
@@ -34,7 +28,9 @@ def chat_about_flowchart(message: str, flow_data: dict | None = None) -> dict:
Returns:
{"reply": "...", "updated_flow": {...} | None}
"""
if not OPENROUTER_API_KEY:
settings = get_openrouter_settings()
if not settings.api_key:
return {
"reply": _fallback_response(message, flow_data),
"updated_flow": None,
@@ -60,13 +56,13 @@ def chat_about_flowchart(message: str, flow_data: dict | None = None) -> dict:
try:
response = requests.post(
OPENROUTER_BASE_URL,
settings.base_url,
headers={
"Authorization": f"Bearer {OPENROUTER_API_KEY}",
"Authorization": f"Bearer {settings.api_key}",
"Content-Type": "application/json",
},
json={
"model": OPENROUTER_MODEL,
"model": settings.model,
"messages": messages,
"max_tokens": 500,
"temperature": 0.7,
@@ -92,7 +88,7 @@ def chat_about_flowchart(message: str, flow_data: dict | None = None) -> dict:
usage = data.get("usage", {})
log_ai_usage(
tool="flowchart_chat",
model=OPENROUTER_MODEL,
model=settings.model,
input_tokens=usage.get("prompt_tokens", max(1, len(message) // 4)),
output_tokens=usage.get("completion_tokens", max(1, len(reply) // 4)),
)
@@ -146,10 +142,10 @@ def _fallback_response(message: str, flow_data: dict | None) -> str:
return (
f"Your flowchart '{title}' contains {step_count} steps "
f"({decision_count} decisions). To get AI-powered suggestions, "
f"please configure the OPENROUTER_API_KEY environment variable."
f"please configure OPENROUTER_API_KEY for the application."
)
return (
"AI chat requires the OPENROUTER_API_KEY to be configured. "
"Please set up the environment variable for full AI functionality."
"AI chat requires OPENROUTER_API_KEY to be configured for the application. "
"Set it once in the app configuration for full AI functionality."
)

View File

@@ -0,0 +1,37 @@
"""Shared OpenRouter configuration access for all AI-enabled services."""
from dataclasses import dataclass
import os
from flask import current_app, has_app_context
DEFAULT_OPENROUTER_MODEL = "stepfun/step-3.5-flash:free"
DEFAULT_OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1/chat/completions"
@dataclass(frozen=True)
class OpenRouterSettings:
api_key: str
model: str
base_url: str
def get_openrouter_settings() -> OpenRouterSettings:
"""Return the effective OpenRouter settings for the current execution context."""
if has_app_context():
api_key = str(current_app.config.get("OPENROUTER_API_KEY", "")).strip()
model = str(
current_app.config.get("OPENROUTER_MODEL", DEFAULT_OPENROUTER_MODEL)
).strip() or DEFAULT_OPENROUTER_MODEL
base_url = str(
current_app.config.get("OPENROUTER_BASE_URL", DEFAULT_OPENROUTER_BASE_URL)
).strip() or DEFAULT_OPENROUTER_BASE_URL
return OpenRouterSettings(api_key=api_key, model=model, base_url=base_url)
return OpenRouterSettings(
api_key=os.getenv("OPENROUTER_API_KEY", "").strip(),
model=os.getenv("OPENROUTER_MODEL", DEFAULT_OPENROUTER_MODEL).strip()
or DEFAULT_OPENROUTER_MODEL,
base_url=os.getenv("OPENROUTER_BASE_URL", DEFAULT_OPENROUTER_BASE_URL).strip()
or DEFAULT_OPENROUTER_BASE_URL,
)

View File

@@ -1,18 +1,12 @@
"""PDF AI services — Chat, Summarize, Translate, Table Extract."""
import os
import json
import logging
import requests
logger = logging.getLogger(__name__)
from app.services.openrouter_config_service import get_openrouter_settings
# Configuration
OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY", "")
OPENROUTER_MODEL = os.getenv("OPENROUTER_MODEL", "stepfun/step-3.5-flash:free")
OPENROUTER_BASE_URL = os.getenv(
"OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1/chat/completions"
)
logger = logging.getLogger(__name__)
class PdfAiError(Exception):
@@ -58,9 +52,11 @@ def _call_openrouter(
except Exception:
pass # Don't block if cost service unavailable
if not OPENROUTER_API_KEY:
settings = get_openrouter_settings()
if not settings.api_key:
raise PdfAiError(
"AI service is not configured. Set OPENROUTER_API_KEY environment variable."
"AI service is not configured. Set OPENROUTER_API_KEY in the application configuration."
)
messages = [
@@ -70,13 +66,13 @@ def _call_openrouter(
try:
response = requests.post(
OPENROUTER_BASE_URL,
settings.base_url,
headers={
"Authorization": f"Bearer {OPENROUTER_API_KEY}",
"Authorization": f"Bearer {settings.api_key}",
"Content-Type": "application/json",
},
json={
"model": OPENROUTER_MODEL,
"model": settings.model,
"messages": messages,
"max_tokens": max_tokens,
"temperature": 0.5,
@@ -102,7 +98,7 @@ def _call_openrouter(
usage = data.get("usage", {})
log_ai_usage(
tool=tool_name,
model=OPENROUTER_MODEL,
model=settings.model,
input_tokens=usage.get("prompt_tokens", _estimate_tokens(user_message)),
output_tokens=usage.get("completion_tokens", _estimate_tokens(reply)),
)

View File

@@ -0,0 +1,594 @@
"""Site assistant service — page-aware AI help plus persistent conversation logging."""
import json
import logging
import os
import sqlite3
import uuid
from datetime import datetime, timezone
import requests
from flask import current_app
from app.services.openrouter_config_service import get_openrouter_settings
from app.services.ai_cost_service import AiBudgetExceededError, check_ai_budget, log_ai_usage
logger = logging.getLogger(__name__)
MAX_HISTORY_MESSAGES = 8
MAX_MESSAGE_LENGTH = 4000
TOOL_CATALOG = [
{"slug": "pdf-to-word", "label": "PDF to Word", "summary": "convert PDF files into editable Word documents"},
{"slug": "word-to-pdf", "label": "Word to PDF", "summary": "turn DOC or DOCX files into PDF documents"},
{"slug": "compress-pdf", "label": "Compress PDF", "summary": "reduce PDF file size while preserving readability"},
{"slug": "merge-pdf", "label": "Merge PDF", "summary": "combine multiple PDF files into one document"},
{"slug": "split-pdf", "label": "Split PDF", "summary": "extract ranges or split one PDF into separate pages"},
{"slug": "rotate-pdf", "label": "Rotate PDF", "summary": "rotate PDF pages to the correct orientation"},
{"slug": "pdf-to-images", "label": "PDF to Images", "summary": "convert each PDF page into PNG or JPG images"},
{"slug": "images-to-pdf", "label": "Images to PDF", "summary": "combine multiple images into one PDF"},
{"slug": "watermark-pdf", "label": "Watermark PDF", "summary": "add text watermarks to PDF pages"},
{"slug": "remove-watermark-pdf", "label": "Remove Watermark", "summary": "remove supported text and image-overlay watermarks from PDFs"},
{"slug": "protect-pdf", "label": "Protect PDF", "summary": "add password protection to PDF files"},
{"slug": "unlock-pdf", "label": "Unlock PDF", "summary": "remove PDF password protection when the password is known"},
{"slug": "page-numbers", "label": "Page Numbers", "summary": "add page numbers in different positions"},
{"slug": "pdf-editor", "label": "PDF Editor", "summary": "optimize and clean PDF copies"},
{"slug": "pdf-flowchart", "label": "PDF Flowchart", "summary": "analyze PDF procedures and turn them into flowcharts"},
{"slug": "pdf-to-excel", "label": "PDF to Excel", "summary": "extract structured table data into spreadsheet files"},
{"slug": "html-to-pdf", "label": "HTML to PDF", "summary": "convert HTML documents into PDF"},
{"slug": "reorder-pdf", "label": "Reorder PDF", "summary": "rearrange PDF pages using a full page order"},
{"slug": "extract-pages", "label": "Extract Pages", "summary": "create a PDF from selected pages"},
{"slug": "chat-pdf", "label": "Chat with PDF", "summary": "ask questions about one uploaded PDF"},
{"slug": "summarize-pdf", "label": "Summarize PDF", "summary": "generate a concise summary of one PDF"},
{"slug": "translate-pdf", "label": "Translate PDF", "summary": "translate PDF content into another language"},
{"slug": "extract-tables", "label": "Extract Tables", "summary": "find tables in a PDF and export them"},
{"slug": "image-converter", "label": "Image Converter", "summary": "convert images between common formats"},
{"slug": "image-resize", "label": "Image Resize", "summary": "resize images to exact dimensions"},
{"slug": "compress-image", "label": "Compress Image", "summary": "reduce image file size"},
{"slug": "ocr", "label": "OCR", "summary": "extract text from image or scanned PDF content"},
{"slug": "remove-background", "label": "Remove Background", "summary": "remove image backgrounds automatically"},
{"slug": "qr-code", "label": "QR Code", "summary": "generate QR codes from text or URLs"},
{"slug": "video-to-gif", "label": "Video to GIF", "summary": "convert short videos into GIF animations"},
{"slug": "word-counter", "label": "Word Counter", "summary": "count words, characters, and reading metrics"},
{"slug": "text-cleaner", "label": "Text Cleaner", "summary": "clean up text spacing and formatting"},
]
SYSTEM_PROMPT = """You are the SaaS-PDF site assistant.
You help users choose the right tool, understand how to use the current tool, and explain site capabilities.
Rules:
- Reply in the same language as the user.
- Keep answers practical and concise.
- Prefer recommending existing site tools over generic outside advice.
- If the user is already on a tool page, explain that tool first, then mention alternatives only when useful.
- Never claim to process or access a file unless the current tool explicitly supports file upload.
- When the user asks what tool to use, recommend 1-3 tools max and explain why.
- If the user asks about sharing or privacy, explain that download links may expire and users should avoid sharing sensitive files publicly.
"""
def _connect() -> sqlite3.Connection:
db_path = current_app.config["DATABASE_PATH"]
db_dir = os.path.dirname(db_path)
if db_dir:
os.makedirs(db_dir, exist_ok=True)
connection = sqlite3.connect(db_path)
connection.row_factory = sqlite3.Row
connection.execute("PRAGMA foreign_keys = ON")
return connection
def _utc_now() -> str:
return datetime.now(timezone.utc).isoformat()
def init_site_assistant_db() -> None:
"""Create assistant conversation tables if they do not exist."""
with _connect() as conn:
conn.executescript(
"""
CREATE TABLE IF NOT EXISTS assistant_conversations (
id INTEGER PRIMARY KEY AUTOINCREMENT,
session_id TEXT NOT NULL UNIQUE,
user_id INTEGER,
fingerprint TEXT NOT NULL,
tool_slug TEXT DEFAULT '',
page_url TEXT DEFAULT '',
locale TEXT DEFAULT 'en',
created_at TEXT NOT NULL,
updated_at TEXT NOT NULL
);
CREATE TABLE IF NOT EXISTS assistant_messages (
id INTEGER PRIMARY KEY AUTOINCREMENT,
conversation_id INTEGER NOT NULL,
role TEXT NOT NULL CHECK(role IN ('user', 'assistant', 'system')),
content TEXT NOT NULL,
tool_slug TEXT DEFAULT '',
page_url TEXT DEFAULT '',
locale TEXT DEFAULT 'en',
metadata_json TEXT NOT NULL DEFAULT '{}',
created_at TEXT NOT NULL,
FOREIGN KEY (conversation_id) REFERENCES assistant_conversations(id) ON DELETE CASCADE
);
CREATE INDEX IF NOT EXISTS idx_assistant_conversations_user_id
ON assistant_conversations(user_id);
CREATE INDEX IF NOT EXISTS idx_assistant_messages_conversation_id
ON assistant_messages(conversation_id);
CREATE INDEX IF NOT EXISTS idx_assistant_messages_created_at
ON assistant_messages(created_at);
"""
)
def chat_with_site_assistant(
message: str,
session_id: str | None,
fingerprint: str,
tool_slug: str = "",
page_url: str = "",
locale: str = "en",
user_id: int | None = None,
history: list[dict] | None = None,
) -> dict:
"""Generate an assistant reply and persist both sides of the conversation."""
prepared = _prepare_chat_request(
message=message,
session_id=session_id,
fingerprint=fingerprint,
tool_slug=tool_slug,
page_url=page_url,
locale=locale,
user_id=user_id,
history=history,
)
normalized_message = prepared["message"]
normalized_session_id = prepared["session_id"]
normalized_tool_slug = prepared["tool_slug"]
normalized_page_url = prepared["page_url"]
normalized_locale = prepared["locale"]
normalized_fingerprint = prepared["fingerprint"]
normalized_history = prepared["history"]
conversation_id = prepared["conversation_id"]
try:
check_ai_budget()
reply = _request_ai_reply(
message=normalized_message,
tool_slug=normalized_tool_slug,
page_url=normalized_page_url,
locale=normalized_locale,
history=normalized_history,
)
except AiBudgetExceededError:
reply = _fallback_reply(normalized_message, normalized_tool_slug)
except Exception as exc:
logger.warning("Site assistant fallback triggered: %s", exc)
reply = _fallback_reply(normalized_message, normalized_tool_slug)
_record_message(
conversation_id=conversation_id,
role="user",
content=normalized_message,
tool_slug=normalized_tool_slug,
page_url=normalized_page_url,
locale=normalized_locale,
metadata={"fingerprint": normalized_fingerprint},
)
_record_message(
conversation_id=conversation_id,
role="assistant",
content=reply,
tool_slug=normalized_tool_slug,
page_url=normalized_page_url,
locale=normalized_locale,
metadata={"model": _response_model_name()},
)
return {
"session_id": normalized_session_id,
"reply": reply,
"stored": True,
}
def stream_site_assistant_chat(
message: str,
session_id: str | None,
fingerprint: str,
tool_slug: str = "",
page_url: str = "",
locale: str = "en",
user_id: int | None = None,
history: list[dict] | None = None,
):
"""Yield assistant response events incrementally for SSE clients."""
prepared = _prepare_chat_request(
message=message,
session_id=session_id,
fingerprint=fingerprint,
tool_slug=tool_slug,
page_url=page_url,
locale=locale,
user_id=user_id,
history=history,
)
normalized_message = prepared["message"]
normalized_session_id = prepared["session_id"]
normalized_tool_slug = prepared["tool_slug"]
normalized_page_url = prepared["page_url"]
normalized_locale = prepared["locale"]
normalized_fingerprint = prepared["fingerprint"]
normalized_history = prepared["history"]
conversation_id = prepared["conversation_id"]
def generate_events():
yield {"event": "session", "data": {"session_id": normalized_session_id}}
_record_message(
conversation_id=conversation_id,
role="user",
content=normalized_message,
tool_slug=normalized_tool_slug,
page_url=normalized_page_url,
locale=normalized_locale,
metadata={"fingerprint": normalized_fingerprint},
)
reply = ""
response_model = "fallback"
try:
check_ai_budget()
settings = get_openrouter_settings()
if not settings.api_key:
raise RuntimeError("OPENROUTER_API_KEY is not configured for the application.")
response_model = settings.model
messages = _build_ai_messages(
message=normalized_message,
tool_slug=normalized_tool_slug,
page_url=normalized_page_url,
locale=normalized_locale,
history=normalized_history,
)
for chunk in _stream_ai_reply(messages=messages, settings=settings):
if not chunk:
continue
reply += chunk
yield {"event": "chunk", "data": {"content": chunk}}
if not reply.strip():
raise RuntimeError("Assistant returned an empty reply.")
log_ai_usage(
tool="site_assistant",
model=settings.model,
input_tokens=max(1, len(normalized_message) // 4),
output_tokens=max(1, len(reply) // 4),
)
except AiBudgetExceededError:
reply = _fallback_reply(normalized_message, normalized_tool_slug)
yield {"event": "chunk", "data": {"content": reply}}
except Exception as exc:
logger.warning("Site assistant streaming fallback triggered: %s", exc)
if not reply.strip():
reply = _fallback_reply(normalized_message, normalized_tool_slug)
yield {"event": "chunk", "data": {"content": reply}}
response_model = "fallback"
_record_message(
conversation_id=conversation_id,
role="assistant",
content=reply,
tool_slug=normalized_tool_slug,
page_url=normalized_page_url,
locale=normalized_locale,
metadata={"model": response_model},
)
yield {
"event": "done",
"data": {
"session_id": normalized_session_id,
"reply": reply,
"stored": True,
},
}
return generate_events()
def _ensure_conversation(
session_id: str,
user_id: int | None,
fingerprint: str,
tool_slug: str,
page_url: str,
locale: str,
) -> int:
now = _utc_now()
with _connect() as conn:
row = conn.execute(
"SELECT id FROM assistant_conversations WHERE session_id = ?",
(session_id,),
).fetchone()
if row is not None:
conn.execute(
"""
UPDATE assistant_conversations
SET user_id = ?, fingerprint = ?, tool_slug = ?, page_url = ?, locale = ?, updated_at = ?
WHERE id = ?
""",
(user_id, fingerprint, tool_slug, page_url, locale, now, row["id"]),
)
return int(row["id"])
cursor = conn.execute(
"""
INSERT INTO assistant_conversations (
session_id, user_id, fingerprint, tool_slug, page_url, locale, created_at, updated_at
) VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""",
(session_id, user_id, fingerprint, tool_slug, page_url, locale, now, now),
)
return int(cursor.lastrowid)
def _record_message(
conversation_id: int,
role: str,
content: str,
tool_slug: str,
page_url: str,
locale: str,
metadata: dict | None = None,
) -> None:
with _connect() as conn:
conn.execute(
"""
INSERT INTO assistant_messages (
conversation_id, role, content, tool_slug, page_url, locale, metadata_json, created_at
) VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""",
(
conversation_id,
role,
content,
tool_slug,
page_url,
locale,
json.dumps(metadata or {}, ensure_ascii=True),
_utc_now(),
),
)
def _prepare_chat_request(
message: str,
session_id: str | None,
fingerprint: str,
tool_slug: str,
page_url: str,
locale: str,
user_id: int | None,
history: list[dict] | None,
) -> dict:
normalized_message = (message or "").strip()[:MAX_MESSAGE_LENGTH]
if not normalized_message:
raise ValueError("Message is required.")
normalized_session_id = (session_id or "").strip() or str(uuid.uuid4())
normalized_tool_slug = (tool_slug or "").strip()[:120]
normalized_page_url = (page_url or "").strip()[:500]
normalized_locale = (locale or "en").strip()[:16] or "en"
normalized_fingerprint = (fingerprint or "anonymous").strip()[:120] or "anonymous"
normalized_history = _normalize_history(history)
conversation_id = _ensure_conversation(
session_id=normalized_session_id,
user_id=user_id,
fingerprint=normalized_fingerprint,
tool_slug=normalized_tool_slug,
page_url=normalized_page_url,
locale=normalized_locale,
)
return {
"message": normalized_message,
"session_id": normalized_session_id,
"tool_slug": normalized_tool_slug,
"page_url": normalized_page_url,
"locale": normalized_locale,
"fingerprint": normalized_fingerprint,
"history": normalized_history,
"conversation_id": conversation_id,
}
def _normalize_history(history: list[dict] | None) -> list[dict[str, str]]:
normalized: list[dict[str, str]] = []
for item in history or []:
if not isinstance(item, dict):
continue
role = str(item.get("role", "")).strip().lower()
content = str(item.get("content", "")).strip()[:MAX_MESSAGE_LENGTH]
if role not in {"user", "assistant"} or not content:
continue
normalized.append({"role": role, "content": content})
return normalized[-MAX_HISTORY_MESSAGES:]
def _request_ai_reply(
message: str,
tool_slug: str,
page_url: str,
locale: str,
history: list[dict[str, str]],
) -> str:
settings = get_openrouter_settings()
if not settings.api_key:
raise RuntimeError("OPENROUTER_API_KEY is not configured for the application.")
messages = _build_ai_messages(
message=message,
tool_slug=tool_slug,
page_url=page_url,
locale=locale,
history=history,
)
response = requests.post(
settings.base_url,
headers={
"Authorization": f"Bearer {settings.api_key}",
"Content-Type": "application/json",
},
json={
"model": settings.model,
"messages": messages,
"max_tokens": 400,
"temperature": 0.3,
},
timeout=30,
)
response.raise_for_status()
data = response.json()
reply = (
data.get("choices", [{}])[0]
.get("message", {})
.get("content", "")
.strip()
)
if not reply:
raise RuntimeError("Assistant returned an empty reply.")
usage = data.get("usage", {})
log_ai_usage(
tool="site_assistant",
model=settings.model,
input_tokens=usage.get("prompt_tokens", max(1, len(message) // 4)),
output_tokens=usage.get("completion_tokens", max(1, len(reply) // 4)),
)
return reply
def _build_ai_messages(
message: str,
tool_slug: str,
page_url: str,
locale: str,
history: list[dict[str, str]],
) -> list[dict[str, str]]:
context_lines = [
f"Current locale: {locale or 'en'}",
f"Current tool slug: {tool_slug or 'none'}",
f"Current page URL: {page_url or 'unknown'}",
"Available tools:",
]
context_lines.extend(
f"- {tool['label']} ({tool['slug']}): {tool['summary']}"
for tool in TOOL_CATALOG
)
context = "\n".join(context_lines)
messages: list[dict[str, str]] = [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "system", "content": context},
]
messages.extend(history)
messages.append({"role": "user", "content": message})
return messages
def _stream_ai_reply(messages: list[dict[str, str]], settings):
response = requests.post(
settings.base_url,
headers={
"Authorization": f"Bearer {settings.api_key}",
"Content-Type": "application/json",
"Accept": "text/event-stream",
},
json={
"model": settings.model,
"messages": messages,
"max_tokens": 400,
"temperature": 0.3,
"stream": True,
},
timeout=60,
stream=True,
)
response.raise_for_status()
try:
for raw_line in response.iter_lines(decode_unicode=True):
if not raw_line:
continue
line = raw_line.strip()
if not line.startswith("data:"):
continue
payload = line[5:].strip()
if not payload or payload == "[DONE]":
continue
try:
data = json.loads(payload)
except json.JSONDecodeError:
continue
choices = data.get("choices") or []
if not choices:
continue
delta = choices[0].get("delta") or {}
content = delta.get("content")
if isinstance(content, str) and content:
yield content
finally:
response.close()
def _fallback_reply(message: str, tool_slug: str) -> str:
msg_lower = message.lower()
if any(keyword in msg_lower for keyword in ["merge", "combine", "دمج", "جمع"]):
return "إذا كنت تريد جمع أكثر من ملف PDF في ملف واحد فابدأ بأداة Merge PDF. إذا كنت تريد فقط إعادة ترتيب الصفحات داخل ملف واحد فاستخدم Reorder PDF."
if any(keyword in msg_lower for keyword in ["split", "extract", "قس", "استخراج"]):
return "لإخراج صفحات محددة في ملف جديد استخدم Extract Pages، أما إذا أردت تقسيم الملف إلى صفحات أو نطاقات متعددة فاستخدم Split PDF."
if any(keyword in msg_lower for keyword in ["watermark", "علامة", "filigrane"]):
return "إذا أردت إضافة علامة مائية فاستخدم Watermark PDF. إذا أردت إزالة علامة موجودة فاستخدم Remove Watermark، مع ملاحظة أن العلامات المسطحة أو المدمجة بعمق قد لا تكون قابلة للإزالة دائماً."
if tool_slug:
tool = next((item for item in TOOL_CATALOG if item["slug"] == tool_slug), None)
if tool:
return (
f"أنت الآن على أداة {tool['label']}. هذه الأداة تُستخدم لـ {tool['summary']}. "
"إذا وصفت لي ما تريد فعله بالتحديد فسأرشدك إلى الخطوات أو إلى أداة أنسب داخل الموقع."
)
return (
"أستطيع مساعدتك في اختيار الأداة المناسبة داخل الموقع أو شرح طريقة استخدامها. "
"اذكر لي الهدف الذي تريد الوصول إليه مثل ضغط PDF أو إزالة الخلفية أو ترجمة ملف PDF، وسأقترح الأداة المناسبة مباشرة."
)
def _response_model_name() -> str:
settings = get_openrouter_settings()
return settings.model if settings.api_key else "fallback"

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View File

@@ -72,7 +72,7 @@ class BaseConfig:
AWS_S3_BUCKET = os.getenv("AWS_S3_BUCKET", "saas-pdf-temp-files")
AWS_S3_REGION = os.getenv("AWS_S3_REGION", "eu-west-1")
# CORS
# CORS
CORS_ORIGINS = os.getenv("CORS_ORIGINS", "http://localhost:5173").split(",")
# Rate Limiting
@@ -80,7 +80,7 @@ class BaseConfig:
RATELIMIT_DEFAULT = "100/hour"
# OpenRouter AI
OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY", "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")
OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY", "")
OPENROUTER_MODEL = os.getenv("OPENROUTER_MODEL", "stepfun/step-3.5-flash:free")
OPENROUTER_BASE_URL = os.getenv(
"OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1/chat/completions"

View File

@@ -8,6 +8,7 @@ from app import create_app
from app.services.account_service import init_account_db
from app.services.rating_service import init_ratings_db
from app.services.ai_cost_service import init_ai_cost_db
from app.services.site_assistant_service import init_site_assistant_db
@pytest.fixture
@@ -33,6 +34,7 @@ def app():
init_account_db()
init_ratings_db()
init_ai_cost_db()
init_site_assistant_db()
# Create temp directories
os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)

View File

@@ -0,0 +1,71 @@
"""Tests for the site assistant API route."""
import json
class TestAssistantRoute:
def test_requires_message(self, client):
response = client.post('/api/assistant/chat', json={})
assert response.status_code == 400
assert response.get_json()['error'] == 'Message is required.'
def test_success_returns_reply_and_session(self, client, monkeypatch):
monkeypatch.setattr(
'app.routes.assistant.chat_with_site_assistant',
lambda **kwargs: {
'session_id': kwargs['session_id'] or 'assistant-session-1',
'reply': 'Use Merge PDF for combining files.',
'stored': True,
},
)
response = client.post(
'/api/assistant/chat',
json={
'message': 'How do I combine files?',
'fingerprint': 'visitor-1',
'tool_slug': 'merge-pdf',
},
)
assert response.status_code == 200
body = response.get_json()
assert body['stored'] is True
assert body['reply'] == 'Use Merge PDF for combining files.'
assert body['session_id']
def test_stream_returns_sse_events(self, client, monkeypatch):
monkeypatch.setattr(
'app.routes.assistant.stream_site_assistant_chat',
lambda **kwargs: iter([
{'event': 'session', 'data': {'session_id': 'assistant-session-1'}},
{'event': 'chunk', 'data': {'content': 'Use Merge '}},
{'event': 'chunk', 'data': {'content': 'PDF.'}},
{
'event': 'done',
'data': {
'session_id': 'assistant-session-1',
'reply': 'Use Merge PDF.',
'stored': True,
},
},
]),
)
response = client.post(
'/api/assistant/chat/stream',
json={
'message': 'How do I combine files?',
'fingerprint': 'visitor-1',
'tool_slug': 'merge-pdf',
},
)
assert response.status_code == 200
assert response.headers['Content-Type'].startswith('text/event-stream')
body = response.get_data(as_text=True)
assert 'event: session' in body
assert f"data: {json.dumps({'session_id': 'assistant-session-1'})}" in body
assert 'event: chunk' in body
assert 'Use Merge PDF.' in body

View File

@@ -0,0 +1,119 @@
"""Tests for shared OpenRouter configuration resolution across AI services."""
from app.services.openrouter_config_service import get_openrouter_settings
from app.services.pdf_ai_service import _call_openrouter
from app.services.site_assistant_service import _request_ai_reply
class _FakeResponse:
def __init__(self, payload):
self._payload = payload
def raise_for_status(self):
return None
def json(self):
return self._payload
class TestOpenRouterConfigService:
def test_prefers_flask_config_when_app_context_exists(self, app, monkeypatch):
monkeypatch.setenv('OPENROUTER_API_KEY', 'env-key')
monkeypatch.setenv('OPENROUTER_MODEL', 'env-model')
monkeypatch.setenv('OPENROUTER_BASE_URL', 'https://env.example/api')
with app.app_context():
app.config.update({
'OPENROUTER_API_KEY': 'config-key',
'OPENROUTER_MODEL': 'config-model',
'OPENROUTER_BASE_URL': 'https://config.example/api',
})
settings = get_openrouter_settings()
assert settings.api_key == 'config-key'
assert settings.model == 'config-model'
assert settings.base_url == 'https://config.example/api'
def test_falls_back_to_environment_without_app_context(self, monkeypatch):
monkeypatch.setenv('OPENROUTER_API_KEY', 'env-key')
monkeypatch.setenv('OPENROUTER_MODEL', 'env-model')
monkeypatch.setenv('OPENROUTER_BASE_URL', 'https://env.example/api')
settings = get_openrouter_settings()
assert settings.api_key == 'env-key'
assert settings.model == 'env-model'
assert settings.base_url == 'https://env.example/api'
class TestAiServicesUseSharedConfig:
def test_pdf_ai_uses_flask_config(self, app, monkeypatch):
captured = {}
monkeypatch.setattr('app.services.ai_cost_service.check_ai_budget', lambda: None)
monkeypatch.setattr('app.services.ai_cost_service.log_ai_usage', lambda **kwargs: captured.setdefault('usage', kwargs))
def fake_post(url, headers, json, timeout):
captured['url'] = url
captured['headers'] = headers
captured['json'] = json
captured['timeout'] = timeout
return _FakeResponse({
'choices': [{'message': {'content': 'Configured PDF reply'}}],
'usage': {'prompt_tokens': 11, 'completion_tokens': 7},
})
monkeypatch.setattr('app.services.pdf_ai_service.requests.post', fake_post)
with app.app_context():
app.config.update({
'OPENROUTER_API_KEY': 'config-key',
'OPENROUTER_MODEL': 'config-model',
'OPENROUTER_BASE_URL': 'https://config.example/pdf-ai',
})
reply = _call_openrouter('system prompt', 'user question', max_tokens=321, tool_name='pdf_chat')
assert reply == 'Configured PDF reply'
assert captured['url'] == 'https://config.example/pdf-ai'
assert captured['headers']['Authorization'] == 'Bearer config-key'
assert captured['json']['model'] == 'config-model'
assert captured['json']['max_tokens'] == 321
assert captured['usage']['model'] == 'config-model'
def test_site_assistant_uses_flask_config(self, app, monkeypatch):
captured = {}
monkeypatch.setattr('app.services.site_assistant_service.log_ai_usage', lambda **kwargs: captured.setdefault('usage', kwargs))
def fake_post(url, headers, json, timeout):
captured['url'] = url
captured['headers'] = headers
captured['json'] = json
captured['timeout'] = timeout
return _FakeResponse({
'choices': [{'message': {'content': 'Configured assistant reply'}}],
'usage': {'prompt_tokens': 13, 'completion_tokens': 9},
})
monkeypatch.setattr('app.services.site_assistant_service.requests.post', fake_post)
with app.app_context():
app.config.update({
'OPENROUTER_API_KEY': 'assistant-key',
'OPENROUTER_MODEL': 'assistant-model',
'OPENROUTER_BASE_URL': 'https://config.example/assistant',
})
reply = _request_ai_reply(
message='How do I merge files?',
tool_slug='merge-pdf',
page_url='https://example.com/tools/merge-pdf',
locale='en',
history=[{'role': 'assistant', 'content': 'Previous reply'}],
)
assert reply == 'Configured assistant reply'
assert captured['url'] == 'https://config.example/assistant'
assert captured['headers']['Authorization'] == 'Bearer assistant-key'
assert captured['json']['model'] == 'assistant-model'
assert captured['json']['messages'][-1] == {'role': 'user', 'content': 'How do I merge files?'}
assert captured['usage']['model'] == 'assistant-model'

View File

@@ -0,0 +1,105 @@
"""Tests for site assistant persistence and fallback behavior."""
import json
import sqlite3
from app.services.site_assistant_service import chat_with_site_assistant, stream_site_assistant_chat
class TestSiteAssistantService:
def test_chat_persists_conversation_and_messages(self, app, monkeypatch):
with app.app_context():
monkeypatch.setattr(
'app.services.site_assistant_service._request_ai_reply',
lambda **kwargs: 'Use Merge PDF if you want one combined document.',
)
result = chat_with_site_assistant(
message='How can I combine PDF files?',
session_id='assistant-session-123',
fingerprint='visitor-123',
tool_slug='merge-pdf',
page_url='https://example.com/tools/merge-pdf',
locale='en',
user_id=None,
history=[{'role': 'user', 'content': 'Hello'}],
)
assert result['stored'] is True
assert result['session_id'] == 'assistant-session-123'
assert 'Merge PDF' in result['reply']
connection = sqlite3.connect(app.config['DATABASE_PATH'])
connection.row_factory = sqlite3.Row
conversation = connection.execute(
'SELECT session_id, fingerprint, tool_slug, locale FROM assistant_conversations WHERE session_id = ?',
('assistant-session-123',),
).fetchone()
messages = connection.execute(
'SELECT role, content FROM assistant_messages ORDER BY id ASC'
).fetchall()
assert conversation['fingerprint'] == 'visitor-123'
assert conversation['tool_slug'] == 'merge-pdf'
assert conversation['locale'] == 'en'
assert [row['role'] for row in messages] == ['user', 'assistant']
assert 'How can I combine PDF files?' in messages[0]['content']
assert 'Merge PDF' in messages[1]['content']
def test_stream_chat_persists_streamed_reply(self, app, monkeypatch):
class FakeStreamResponse:
def raise_for_status(self):
return None
def iter_lines(self, decode_unicode=True):
yield 'data: ' + json.dumps({
'choices': [{'delta': {'content': 'Use Merge '}}],
})
yield 'data: ' + json.dumps({
'choices': [{'delta': {'content': 'PDF for this.'}}],
})
yield 'data: [DONE]'
def close(self):
return None
with app.app_context():
monkeypatch.setattr(
'app.services.site_assistant_service.check_ai_budget',
lambda: None,
)
monkeypatch.setattr(
'app.services.site_assistant_service.requests.post',
lambda *args, **kwargs: FakeStreamResponse(),
)
app.config.update({
'OPENROUTER_API_KEY': 'config-key',
'OPENROUTER_MODEL': 'config-model',
})
events = list(stream_site_assistant_chat(
message='How can I combine PDF files?',
session_id='assistant-stream-123',
fingerprint='visitor-123',
tool_slug='merge-pdf',
page_url='https://example.com/tools/merge-pdf',
locale='en',
user_id=None,
history=[{'role': 'assistant', 'content': 'Hello'}],
))
assert events[0]['event'] == 'session'
assert events[1]['event'] == 'chunk'
assert events[2]['event'] == 'chunk'
assert events[-1]['event'] == 'done'
assert events[-1]['data']['reply'] == 'Use Merge PDF for this.'
connection = sqlite3.connect(app.config['DATABASE_PATH'])
connection.row_factory = sqlite3.Row
messages = connection.execute(
'SELECT role, content, metadata_json FROM assistant_messages ORDER BY id ASC'
).fetchall()
assert [row['role'] for row in messages] == ['user', 'assistant']
assert messages[1]['content'] == 'Use Merge PDF for this.'
assert 'config-model' in messages[1]['metadata_json']