Add scan route and handling

backend/Dockerfile

@@ -9,6 +9,7 @@ ENV \
 RUN : \
   && apt-get update \
   && apt-get install -y --no-install-recommends \
+  build-essential \
   curl \
   ca-certificates \
   && apt-get clean \

backend/app/api/router.py

@@ -1,7 +1,8 @@
-from app.api.routes import health, login, users
+from app.api.routes import health, login, scan, users
 from app.core.utils import APIRouter
 
 api_router = APIRouter()
 api_router.include_router(health.router)
 api_router.include_router(login.router)
+api_router.include_router(scan.router)
 api_router.include_router(users.router)

backend/app/api/routes/scan.py

@@ -0,0 +1,29 @@
+from fastapi import HTTPException
+from loguru import logger
+from starlette.status import HTTP_500_INTERNAL_SERVER_ERROR
+
+from app.api.deps import CurrentUser
+from app.core.config import settings
+from app.core.utils import APIRouter
+from app.models.scan import AnalysisReport, Topic
+from app.scan.graph import CustomGraph
+
+router = APIRouter(tags=["SCAN"], prefix=f"{settings.API_V1_PREFIX}/scan")
+
+
+@router.post("/")
+async def ask_question(*, topic: Topic, _: CurrentUser) -> AnalysisReport:
+    """Ask SCAN for help with a questions."""
+
+    graph = CustomGraph(topic.topic)
+    try:
+        logger.debug("Preparing analysis")
+        analysis = await graph.execute()
+    except Exception as e:
+        logger.error(f"An error occurred while answering question: {e}")
+        raise HTTPException(
+            status_code=HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="An error occurred when getting an answer",
+        ) from e
+
+    return analysis

backend/app/models/scan.py

@@ -0,0 +1,13 @@
+from camel_converter.pydantic_base import CamelBase
+
+
+class AnalysisReport(CamelBase):
+    dlpfc_analysis: str | None = None
+    vmpfc_analysis: str | None = None
+    ofc_analysis: str | None = None
+    acc_analysis: str | None = None
+    mpfc_analysis: str | None = None
+
+
+class Topic(CamelBase):
+    topic: str

backend/app/scan/graph.py

@@ -0,0 +1,86 @@
+from collections.abc import Hashable
+from typing import cast
+
+from langgraph.graph import END, StateGraph
+
+from app.models.scan import AnalysisReport
+from app.scan.pfc_agents import AgentState, PFCAgents
+
+
+class CustomGraph:
+    def __init__(self, topic: str) -> None:
+        self.topic = topic
+        self.agents = PFCAgents(topic=self.topic)
+        self.workflow = StateGraph(AgentState)
+
+    def build_graph(self) -> None:
+        for role, agent_function in self.agents.agents.items():
+            self.workflow.add_node(role, agent_function)
+
+        def router(state: AgentState) -> str | None:
+            next_agent = state["next"]
+            if next_agent == END:
+                return None
+
+            if next_agent is not None:
+                return next_agent
+            return END
+
+        dlpfc_edges: dict[str, str] = {
+            "VMPFC": "VMPFC",
+            "OFC": "OFC",
+            "ACC": "ACC",
+            "MPFC": "MPFC",
+            END: END,
+        }
+
+        self.workflow.add_conditional_edges("DLPFC", router, cast(dict[Hashable, str], dlpfc_edges))
+
+        for role in ("VMPFC", "OFC", "ACC", "MPFC"):
+            self.workflow.add_conditional_edges(
+                role,
+                router,
+            )
+
+        self.workflow.set_entry_point("DLPFC")
+        self.graph = self.workflow.compile()
+
+    async def execute(self) -> AnalysisReport:
+        self.build_graph()
+
+        initial_state = AgentState(
+            input=self.topic,
+            history=[],
+            next="DLPFC",
+            current_role="DLPFC",
+        )
+
+        final_state = await self.graph.ainvoke(initial_state)
+        return self.prepare_output(cast(AgentState, final_state))
+
+    def prepare_output(self, state: AgentState) -> AnalysisReport:
+        dlpfc_analysis = None
+        vmpfc_analysis = None
+        ofc_analysis = None
+        acc_analysis = None
+        mpfc_analysis = None
+
+        for role, analysis in state["history"]:
+            if role == "DLPFC":
+                dlpfc_analysis = analysis if analysis else None
+            elif role == "VMPFC":
+                vmpfc_analysis = analysis if analysis else None
+            elif role == "OFC":
+                ofc_analysis = analysis if analysis else None
+            elif role == "ACC":
+                acc_analysis = analysis if analysis else None
+            elif role == "MPFC":
+                mpfc_analysis = analysis if analysis else None
+
+        return AnalysisReport(
+            dlpfc_analysis=dlpfc_analysis,
+            vmpfc_analysis=vmpfc_analysis,
+            ofc_analysis=ofc_analysis,
+            acc_analysis=acc_analysis,
+            mpfc_analysis=mpfc_analysis,
+        )

backend/app/scan/openai.py

@@ -0,0 +1,34 @@
+from collections.abc import Iterable
+
+from openai import AsyncOpenAI
+from openai.types.chat import ChatCompletionMessageParam
+
+from app.core.config import settings
+
+
+class OpenAIWrapper:
+    """Wrapper for OpenAI API interactions."""
+
+    def __init__(self, model_name: str):
+        self.model_name = model_name
+        self.client = AsyncOpenAI(api_key=settings.OPENAI_API_KEY)
+
+    async def create_chat_completion(
+        self,
+        messages: Iterable[ChatCompletionMessageParam],
+        max_tokens: int = settings.MAX_TOKENS,
+        temperature: float = settings.TEMPERATURE,
+    ) -> str | None:
+        """Create a chat completion with error handling."""
+
+        response = await self.client.chat.completions.create(
+            model=self.model_name,
+            messages=messages,
+            max_tokens=max_tokens,
+            temperature=temperature,
+        )
+
+        if not response.choices[0].message.content:
+            return None
+
+        return response.choices[0].message.content.strip()