[refactor]: restructure backend for improved modularity and separation of concerns

backend/app/agents/__init__.py

@@ -1,6 +1,6 @@
 from .devrel.agent import DevRelAgent
-from .shared.base_agent import BaseAgent, AgentState
-from .shared.classification_router import ClassificationRouter
+from .base_agent import BaseAgent, AgentState
+from .classification_router import ClassificationRouter
 
 __all__ = [
     "DevRelAgent",

backend/app/agents/devrel/__init__.py

@@ -0,0 +1 @@
+

backend/app/agents/devrel/agent.py

@@ -4,18 +4,18 @@
 from langgraph.graph import StateGraph, END
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langgraph.checkpoint.memory import InMemorySaver
-from ..shared.base_agent import BaseAgent, AgentState
-from ..shared.classification_router import MessageCategory
+from ..base_agent import BaseAgent, AgentState
+from ..classification_router import MessageCategory
 from .tools.search_tool import TavilySearchTool
 from .tools.faq_tool import FAQTool
 from app.core.config import settings
-from .nodes.gather_context_node import gather_context_node
-from .nodes.handle_faq_node import handle_faq_node
-from .nodes.handle_web_search_node import handle_web_search_node
-from .nodes.handle_technical_support_node import handle_technical_support_node
-from .nodes.handle_onboarding_node import handle_onboarding_node
-from .nodes.generate_response_node import generate_response_node
-from .nodes.summarization_node import check_summarization_needed, summarize_conversation_node, store_summary_to_database
+from .nodes.gather_context import gather_context_node
+from .nodes.handlers.faq import handle_faq_node
+from .nodes.handlers.web_search import handle_web_search_node
+from .nodes.handlers.technical_support import handle_technical_support_node
+from .nodes.handlers.onboarding import handle_onboarding_node
+from .generate_response_node import generate_response_node
+from .nodes.summarization import check_summarization_needed, summarize_conversation_node, store_summary_to_database
 
 logger = logging.getLogger(__name__)
 

backend/app/agents/devrel/nodes/generate_response_node.py → backend/app/agents/devrel/generate_response_node.py

@@ -1,28 +1,12 @@
 import logging
 from typing import Dict, Any
-from app.agents.shared.state import AgentState
+from app.agents.state import AgentState
 from langchain_core.messages import HumanMessage
-from ..prompts.base_prompt import GENERAL_LLM_RESPONSE_PROMPT
+from .prompts.base_prompt import GENERAL_LLM_RESPONSE_PROMPT
+from .nodes.handlers.web_search import create_search_response
 
 logger = logging.getLogger(__name__)
 
-async def _create_search_response(task_result: Dict[str, Any]) -> str:
-    """Create a response string from search results."""
-    query = task_result.get("query")
-    results = task_result.get("results", [])
-    if not results:
-        return f"I couldn't find any information for '{query}'. You might want to try rephrasing your search."
-
-    response_parts = [f"Here's what I found for '{query}':"]
-    for i, result in enumerate(results[:3]):
-        title = result.get('title', 'N/A')
-        snippet = result.get('snippet', 'N/A')
-        url = result.get('url', '#')
-        result_line = f"{i+1}. {title}: {snippet}"
-        response_parts.append(result_line)
-        response_parts.append(f"   (Source: {url})")
-    response_parts.append("You can ask me to search again with a different query if these aren't helpful.")
-    return "\n".join(response_parts)
 
 async def _create_llm_response(state: AgentState, task_result: Dict[str, Any], llm) -> str:
     """Generate a response using the LLM based on the current state and task result."""
@@ -89,7 +73,7 @@ async def generate_response_node(state: AgentState, llm) -> dict:
     if task_result.get("type") == "faq":
         final_response = task_result.get("response", "I don't have a specific answer for that question.")
     elif task_result.get("type") == "web_search":
-        final_response = await _create_search_response(task_result)
+        final_response = create_search_response(task_result)
     else:
         final_response = await _create_llm_response(state, task_result, llm)
 

backend/app/agents/devrel/nodes/gather_context_node.py → backend/app/agents/devrel/nodes/gather_context.py

@@ -1,7 +1,6 @@
 import logging
 from datetime import datetime
-from app.agents.shared.state import AgentState
-from app.agents.shared.classification_router import MessageCategory
+from app.agents.state import AgentState
 
 logger = logging.getLogger(__name__)
 

backend/app/agents/devrel/nodes/handle_faq_node.py → backend/app/agents/devrel/nodes/handlers/faq.py

@@ -1,5 +1,5 @@
 import logging
-from app.agents.shared.state import AgentState
+from app.agents.state import AgentState
 
 logger = logging.getLogger(__name__)
 

backend/app/agents/devrel/nodes/handle_onboarding_node.py → backend/app/agents/devrel/nodes/handlers/onboarding.py

@@ -1,5 +1,5 @@
 import logging
-from app.agents.shared.state import AgentState
+from app.agents.state import AgentState
 
 logger = logging.getLogger(__name__)
 

backend/app/agents/devrel/nodes/handle_technical_support_node.py → backend/app/agents/devrel/nodes/handlers/technical_support.py

@@ -1,5 +1,5 @@
 import logging
-from app.agents.shared.state import AgentState
+from app.agents.state import AgentState
 
 logger = logging.getLogger(__name__)
 

backend/app/agents/devrel/nodes/handle_web_search_node.py → backend/app/agents/devrel/nodes/handlers/web_search.py

@@ -1,12 +1,16 @@
 import logging
-from app.agents.shared.state import AgentState
+from typing import Dict, Any
+from app.agents.state import AgentState
 from langchain_core.messages import HumanMessage
-from ..prompts.search_prompt import EXTRACT_SEARCH_QUERY_PROMPT
+from app.agents.devrel.prompts.search_prompt import EXTRACT_SEARCH_QUERY_PROMPT
+
 
 logger = logging.getLogger(__name__)
 
 async def _extract_search_query(message: str, llm) -> str:
-    """Extract a concise search query from the user's message."""
+    """
+    Extract a concise search query from the user's message by invoking the LLM.
+    """
     logger.info(f"Extracting search query from: {message[:100]}")
     try:
         prompt = EXTRACT_SEARCH_QUERY_PROMPT.format(message=message)
@@ -19,7 +23,9 @@ async def _extract_search_query(message: str, llm) -> str:
     return search_query
 
 async def handle_web_search_node(state: AgentState, search_tool, llm) -> dict:
-    """Handle web search requests"""
+    """
+    Handle web search requests
+    """
     logger.info(f"Handling web search for session {state.session_id}")
 
     latest_message = ""
@@ -41,3 +47,25 @@ async def handle_web_search_node(state: AgentState, search_tool, llm) -> dict:
         "tools_used": ["tavily_search"],
         "current_task": "web_search_handled"
     }
+
+def create_search_response(task_result: Dict[str, Any]) -> str:
+    """
+    Create a user-friendly response string from search results.
+    """
+    query = task_result.get("query")
+    results = task_result.get("results", [])
+
+    if not results:
+        return f"I couldn't find any information for '{query}'. You might want to try rephrasing your search."
+
+    response_parts = [f"Here's what I found for '{query}':"]
+    for i, result in enumerate(results[:5]):
+        title = result.get('title', 'N/A')
+        snippet = result.get('snippet', 'N/A')
+        url = result.get('url', '#')
+        result_line = f"{i+1}. {title}: {snippet}"
+        response_parts.append(result_line)
+        response_parts.append(f"   (Source: {url})")
+
+    response_parts.append("You can ask me to search again with a different query if these aren't helpful.")
+    return "\n".join(response_parts)

backend/app/agents/devrel/nodes/summarization_node.py → backend/app/agents/devrel/nodes/summarization.py

@@ -1,7 +1,7 @@
 import logging
 from datetime import datetime, timedelta
 from typing import Dict, Any
-from app.agents.shared.state import AgentState
+from app.agents.state import AgentState
 from langchain_core.messages import HumanMessage
 from app.agents.devrel.prompts.summarization_prompt import CONVERSATION_SUMMARY_PROMPT
 
@@ -12,7 +12,9 @@
 THREAD_TIMEOUT_HOURS = 1
 
 async def check_summarization_needed(state: AgentState) -> Dict[str, Any]:
-    """Check if summarization is needed and update interaction count"""
+    """
+    Check if summarization is needed and update interaction count
+    """
 
     current_count = getattr(state, 'interaction_count', 0)
     new_count = current_count + 1
@@ -46,14 +48,15 @@ async def check_summarization_needed(state: AgentState) -> Dict[str, Any]:
     return updates
 
 async def summarize_conversation_node(state: AgentState, llm) -> Dict[str, Any]:
-    """Summarize the conversation and update the state"""
+    """
+    Summarize the conversation and update the state
+    """
     logger.info(f"Summarizing conversation for session {state.session_id}")
 
     try:
         current_count = state.interaction_count
         logger.info(f"Summarizing at interaction count: {current_count}")
 
-        # Get the recent messages
         all_messages = state.messages
 
         if not all_messages:
@@ -66,7 +69,6 @@ async def summarize_conversation_node(state: AgentState, llm) -> Dict[str, Any]:
             for msg in all_messages
         ])
 
-        # Create prompt
         existing_summary = state.conversation_summary
         if not existing_summary or existing_summary == "This is the beginning of our conversation.":
             existing_summary = "No previous summary - this is the start of our conversation tracking."
@@ -85,11 +87,9 @@ async def summarize_conversation_node(state: AgentState, llm) -> Dict[str, Any]:
         logger.info(f"Generating summary with {len(all_messages)} messages, "
                     f"conversation text length: {len(conversation_text)}")
 
-        # Generate summary
         response = await llm.ainvoke([HumanMessage(content=prompt)])
         new_summary = response.content.strip()
 
-        # Extract key topics from summary
         new_topics = await _extract_key_topics(new_summary, llm)
 
         logger.info(f"Conversation summarized successfully for session {state.session_id}")
@@ -121,7 +121,6 @@ async def _extract_key_topics(summary: str, llm) -> list[str]:
         response = await llm.ainvoke([HumanMessage(content=topic_prompt)])
         topics_text = response.content.strip()
 
-        # Parse topics from response
         topics = [topic.strip() for topic in topics_text.split(',') if topic.strip()]
         return topics[:5]  # Limiting to 5 topics
 

backend/app/api/__init__.py

@@ -0,0 +1,11 @@
+"""
+API package for the Devr.AI backend.
+
+This package contains all API-related components:
+- router: Main API router with all endpoints
+- v1: Version 1 API endpoints
+"""
+
+from .router import api_router
+
+__all__ = ["api_router"]

backend/app/api/router.py

@@ -0,0 +1,19 @@
+from fastapi import APIRouter
+from .v1.auth import router as auth_router
+from .v1.health import router as health_router
+
+api_router = APIRouter()
+
+api_router.include_router(
+    auth_router,
+    prefix="/v1/auth",
+    tags=["Authentication"]
+)
+
+api_router.include_router(
+    health_router,
+    prefix="/v1",
+    tags=["Health"]
+)
+
+__all__ = ["api_router"]

backend/app/api/v1/__init__.py

@@ -0,0 +1 @@
+

backend/app/api/v1/auth.py

@@ -1,8 +1,8 @@
 from fastapi import APIRouter, Request, HTTPException, Query
 from fastapi.responses import HTMLResponse
-from app.db.supabase.supabase_client import get_supabase_client
-from app.db.supabase.users_service import find_user_by_session_and_verify, get_verification_session_info
-from app.db.weaviate.user_profiling import profile_user_from_github
+from app.database.supabase.client import get_supabase_client
+from app.services.auth.verification import find_user_by_session_and_verify, get_verification_session_info
+from app.services.user.profiling import profile_user_from_github
 from typing import Optional
 import logging
 import asyncio

backend/app/api/v1/health.py

@@ -0,0 +1,86 @@
+import logging
+from fastapi import APIRouter, HTTPException, Depends
+from app.database.weaviate.client import get_weaviate_client
+from app.core.dependencies import get_app_instance
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from main import DevRAIApplication
+
+router = APIRouter()
+logger = logging.getLogger(__name__)
+
+
+@router.get("/health")
+async def health_check(app_instance: "DevRAIApplication" = Depends(get_app_instance)):
+    """
+    General health check endpoint to verify services are running.
+
+    Returns:
+        dict: Status of the application and its services
+    """
+    try:
+        async with get_weaviate_client() as client:
+            weaviate_ready = await client.is_ready()
+
+        return {
+            "status": "healthy",
+            "services": {
+                "weaviate": "ready" if weaviate_ready else "not_ready",
+                "discord_bot": "running" if app_instance.discord_bot and not app_instance.discord_bot.is_closed() else "stopped"
+            }
+        }
+    except Exception as e:
+        logger.error(f"Health check failed: {e}")
+        raise HTTPException(
+            status_code=503,
+            detail={
+                "status": "unhealthy",
+                "error": str(e)
+            }
+        ) from e
+
+
+@router.get("/health/weaviate")
+async def weaviate_health():
+    """Check specifically Weaviate service health."""
+    try:
+        async with get_weaviate_client() as client:
+            is_ready = await client.is_ready()
+
+        return {
+            "service": "weaviate",
+            "status": "ready" if is_ready else "not_ready"
+        }
+    except Exception as e:
+        logger.error(f"Weaviate health check failed: {e}")
+        raise HTTPException(
+            status_code=503,
+            detail={
+                "service": "weaviate",
+                "status": "unhealthy",
+                "error": str(e)
+            }
+        ) from e
+
+
+@router.get("/health/discord")
+async def discord_health(app_instance: "DevRAIApplication" = Depends(get_app_instance)):
+    """Check specifically Discord bot health."""
+    try:
+        bot_status = "running" if app_instance.discord_bot and not app_instance.discord_bot.is_closed() else "stopped"
+
+        return {
+            "service": "discord_bot",
+            "status": bot_status
+        }
+    except Exception as e:
+        logger.error(f"Discord bot health check failed: {e}")
+        raise HTTPException(
+            status_code=503,
+            detail={
+                "service": "discord_bot",
+                "status": "unhealthy",
+                "error": str(e)
+            }
+        ) from e

backend/app/core/config/__init__.py

@@ -0,0 +1,3 @@
+from .settings import settings
+
+__all__ = ["settings"]

backend/app/core/dependencies.py

@@ -0,0 +1,12 @@
+from fastapi import Request
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from main import DevRAIApplication
+
+async def get_app_instance(request: Request) -> "DevRAIApplication":
+    """
+    Dependency to get the application instance from FastAPI's state.
+    This avoids circular imports by using dependency injection.
+    """
+    return request.app.state.app_instance

backend/app/core/orchestration/agent_coordinator.py

@@ -5,9 +5,9 @@
 from app.agents.devrel.agent import DevRelAgent
 # TODO: Implement GitHub agent
 # from app.agents.github.agent import GitHubAgent
-from app.agents.shared.state import AgentState
+from app.agents.state import AgentState
 from app.core.orchestration.queue_manager import AsyncQueueManager
-from app.agents.devrel.nodes.summarization_node import store_summary_to_database
+from app.agents.devrel.nodes.summarization import store_summary_to_database
 from langsmith import traceable
 
 logger = logging.getLogger(__name__)