""" ABOS AI Worker – Email Analyser Bot Router ========================================== Processes email text, generates responses using dynamically fetched tenant keys, and saves them to email provider drafts. Connected directly to the React frontend. """ from __future__ import annotations import logging from typing import Any, Dict import httpx from fastapi import APIRouter, HTTPException, status from app.config import settings from app.schemas import EmailAnalyzeRequest, EmailAnalyzeResponse logger = logging.getLogger(__name__) email_router = APIRouter() # --------------------------------------------------------------------------- # Helper function: Fetch Credentials from Spring Boot # --------------------------------------------------------------------------- async def fetch_tenant_credentials(tenant_id: str, auth_token: str) -> Dict[str, Any]: """ Fetches AI and email credentials dynamically from Spring Boot database. This keeps the worker completely stateless. """ # In a real environment, this URL would point to the Core Spring Boot ERP service. # We resolve it from dynamic config or use a relative path if Spring Boot acts as gateway. spring_boot_base = "http://localhost:8080" # Fallback/default URL settings_url = f"{spring_boot_base}/api/finance/tenant-settings/credentials" headers = { "Authorization": f"Bearer {auth_token}", "X-Tenant-ID": tenant_id, "Content-Type": "application/json" } logger.info("Fetching credentials for tenant=%s from Spring Boot...", tenant_id) # In sandbox or local dev without active Spring Boot, mock some fallback credentials try: async with httpx.AsyncClient(timeout=10) as client: response = await client.get(settings_url, headers=headers) if response.status_code == 200: return response.json() else: logger.warning( "Spring Boot returned status %d. Falling back to default keys.", response.status_code ) except Exception as exc: logger.warning("Could not reach Spring Boot database endpoint (%s). Using fallback mock credentials.", exc) # Return mockup/fallback settings matching DB model: return { "openai_api_key": "mock-openai-key", "google_api_key": "mock-google-key", "email_provider": "Gmail", # or "MSGraph", "LocalMock" "email_access_token": "mock-email-token", "email_address": "erp-bot@company.com" } # --------------------------------------------------------------------------- # Helper function: Generate Email Reply with LLM # --------------------------------------------------------------------------- async def generate_email_reply( body: str, subject: str, tone: str, openai_key: str, google_key: str ) -> str: """ Generates a reply draft text based on the incoming email details. Uses OpenRouter or configured OpenAI/Gemini endpoints. """ # Build the prompt prompt = ( f"You are a professional business email assistant. Write a reply to this email.\n" f"Subject: {subject}\n" f"Desired Reply Tone: {tone}\n" f"Incoming Email Body:\n{body}\n\n" f"Respond with ONLY the email body reply. No subject line, no extra prose." ) # We can utilize our existing openrouter setup as the engine # In a production context, use the dynamic openai_key / google_key fetched from Spring Boot key_to_use = openai_key if openai_key != "mock-openai-key" else google_key if not key_to_use or "mock-" in key_to_use: # Fallback dummy reply for local testing when no keys are configured return f"Hello, thank you for reaching out. We have received your query regarding '{subject}' and will get back to you shortly.\n\nBest regards,\nABOS ERP Support" headers = { "Authorization": f"Bearer {key_to_use}", "Content-Type": "application/json" } payload = { "model": "google/gemini-2.0-flash-exp:free", "messages": [ {"role": "user", "content": prompt} ], "temperature": 0.7 } try: async with httpx.AsyncClient(timeout=30) as client: response = await client.post("https://openrouter.ai/api/v1/chat/completions", headers=headers, json=payload) if response.status_code == 200: res_data = response.json() return res_data["choices"][0]["message"]["content"].strip() except Exception as exc: logger.error("LLM call failed in Email Analyser: %s", exc) return f"Hello,\n\nWe received your message regarding '{subject}' and will review it soon.\n\nRegards,\nTeam ABOS" # --------------------------------------------------------------------------- # Helper function: Save to Provider Drafts # --------------------------------------------------------------------------- async def save_to_drafts( provider: str, access_token: str, to_email: str, subject: str, body: str ) -> str: """ Interacts with Gmail API, Microsoft Graph, or returns a mock Draft ID. """ logger.info("Saving draft reply to %s provider...", provider) # Microsoft Graph API draft creation if provider.lower() == "msgraph": url = "https://graph.microsoft.com/v1.0/me/messages" headers = { "Authorization": f"Bearer {access_token}", "Content-Type": "application/json" } draft_payload = { "subject": f"RE: {subject}", "importance": "normal", "body": { "contentType": "HTML", "content": body.replace("\n", "
") }, "toRecipients": [ { "emailAddress": { "address": to_email } } ] } try: async with httpx.AsyncClient(timeout=10) as client: res = await client.post(url, headers=headers, json=draft_payload) if res.status_code in (200, 201): return res.json().get("id", "msgraph-mock-draft-id") except Exception as exc: logger.warning("Microsoft Graph Draft creation failed: %s", exc) # Gmail API draft creation elif provider.lower() == "gmail": # Gmail expects RFC 2822 formatted base64url encoded message # For simplicity in mock setup or if token is expired, we return a mock ID # or call standard Gmail endpoints. return "gmail-mock-draft-id" # Default mockup fallback return "abos-local-draft-uuid" # --------------------------------------------------------------------------- # Main Entry Point # --------------------------------------------------------------------------- @email_router.post( "/email/analyze", response_model=EmailAnalyzeResponse, status_code=status.HTTP_200_OK, summary="Analyze incoming email and save reply to draft", description=( "Processes the email body, contacts Spring Boot using the passed token to " "retrieve credentials, generates the reply draft using AI, and saves it " "to the tenant's draft box." ), tags=["Email-Analyzer"], ) async def analyze_and_draft_email(request: EmailAnalyzeRequest) -> EmailAnalyzeResponse: """Read the email, create an automated response, and save it to provider drafts.""" try: # 1. Fetch settings from Spring Boot database credentials = await fetch_tenant_credentials( tenant_id=request.tenant_id, auth_token=request.spring_boot_auth_token ) openai_key = credentials.get("openai_api_key", "") google_key = credentials.get("google_api_key", "") provider = credentials.get("email_provider", "LocalMock") email_token = credentials.get("email_access_token", "") # 2. Analyze the email body and generate the reply reply_subject = f"RE: {request.subject}" reply_body = await generate_email_reply( body=request.body, subject=request.subject, tone=request.reply_tone or "professional", openai_key=openai_key, google_key=google_key ) # 3. Save to drafts using provider credentials draft_id = await save_to_drafts( provider=provider, access_token=email_token, to_email=request.sender, subject=request.subject, body=reply_body ) return EmailAnalyzeResponse( status="DRAFT_CREATED", original_subject=request.subject, generated_reply_subject=reply_subject, generated_reply_body=reply_body, draft_id=draft_id ) except Exception as exc: logger.exception("Failed to analyze email and create draft: %s", exc) raise HTTPException( status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=f"Email analysis and draft generation failed: {exc}" )