add analysis component

backend/app/routers/agent.py

@@ -1,4 +1,5 @@
 import json
+import logging
 from dataclasses import dataclass
 from typing import Annotated, Any
 
@@ -10,7 +11,7 @@ from pydantic_ai.ui.vercel_ai import VercelAIAdapter
 from starlette.requests import Request
 from starlette.responses import Response
 
-from app.agents import form_auditor, web_search
+from app.agents import analyst, form_auditor, web_search
 from app.core.config import settings
 from app.services.extracted_data_service import get_extracted_data_service
 
@@ -24,27 +25,43 @@ model = OpenAIChatModel(model_name="gpt-4o", provider=provider)
 
 @dataclass
 class Deps:
-    extracted_data: dict[str, Any]
+    extracted_data: list[dict[str, Any]]
 
 
 agent = Agent(model=model, deps_type=Deps)
 
 router = APIRouter(prefix="/api/v1/agent", tags=["Agent"])
 
+logger = logging.getLogger(__name__)
+
 
 @agent.tool
 async def build_audit_report(ctx: RunContext[Deps]):
     """Calls the audit subagent to get a full audit report of the organization"""
-    data = ctx.deps.extracted_data
-
-    with open("data/audit_report.json", "w") as f:
-        json.dump(data, f)
+    data = ctx.deps.extracted_data[0]
 
     result = await form_auditor.build_audit_report(data)
 
     return result.model_dump()
 
 
+@agent.tool
+async def build_analysis_report(ctx: RunContext[Deps]):
+    """Calls the analyst subagent to get a full report of the organization's performance across years"""
+    data = ctx.deps.extracted_data
+    if not data:
+        raise ValueError("No extracted data available for analysis.")
+
+    if len(data) == 1:
+        logger.info(
+            "build_analysis_report called with single-year data; report will still be generated but trends may be limited."
+        )
+
+    result = await analyst.build_performance_report(data)
+
+    return result.model_dump()
+
+
 @agent.tool_plain
 async def search_web_information(query: str, max_results: int = 5):
     """Search the web for up-to-date information using Tavily. Use this when you need current information, news, research, or facts not in your knowledge base."""
@@ -61,6 +78,8 @@ async def chat(request: Request, tema: Annotated[str, Header()]) -> Response:
 
     extracted_data = [doc.get_extracted_data() for doc in data]
 
-    deps = Deps(extracted_data=extracted_data[0])
+    logger.info(f"Extracted data amount: {len(extracted_data)}")
+
+    deps = Deps(extracted_data=extracted_data)
 
     return await VercelAIAdapter.dispatch_request(request, agent=agent, deps=deps)