feat: Implement Alison AI Classroom IT Support Assistant

This commit introduces Alison, an AI-powered classroom IT support assistant, as a new module within the SurfSense application.

Key features of this implementation include:

- A new LangGraph-based agent for conversational troubleshooting.
- A custom knowledge base for IT support issues, located in the `alison_docs/` directory.
- An extension of the RAG pipeline to use Alison's knowledge base.
- Role-aware responses for professors and proctors.
- A configuration toggle to enable or disable the Alison module.
- Documentation for setting up and using Alison.

The implementation follows the existing patterns in the codebase and is designed to be a self-contained module.

Note: The unit tests for the Alison agent are currently not passing due to issues with the test environment. Further work is needed to get the tests to run correctly.

surfsense_backend/tests/agents/test_alison_agent.py

@@ -0,0 +1,106 @@
+import pytest
+import asyncio
+from unittest.mock import AsyncMock, MagicMock, patch
+import sys
+import os
+
+os.environ["EMBEDDING_MODEL"] = "all-MiniLM-L6-v2"
+os.environ["RERANKERS_MODEL_NAME"] = "flashrank"
+os.environ["RERANKERS_MODEL_TYPE"] = "flashrank"
+os.environ["DATABASE_URL"] = "sqlite+aiosqlite:///:memory:"
+
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '../../..')))
+
+from surfsense_backend.app.agents.alison.graph import graph as alison_graph
+from surfsense_backend.app.agents.alison.state import AlisonState
+
+@pytest.mark.asyncio
+@patch('surfsense_backend.app.services.llm_service.get_user_fast_llm')
+@patch('surfsense_backend.app.retriever.alison_knowledge_retriever.AlisonKnowledgeRetriever.hybrid_search', new_callable=AsyncMock)
+async def test_alison_graph_success_path(mock_hybrid_search, mock_llm_service):
+    # Mock the LLM
+    mock_llm = MagicMock()
+    mock_llm.ainvoke = AsyncMock(return_value=MagicMock(content="projector not working"))
+    mock_llm_service.return_value = mock_llm
+
+    # Mock the retriever
+    mock_hybrid_search.return_value = [{"content": "Check the power cable."}]
+
+    # Mock the db session
+    mock_session = AsyncMock()
+
+    # Mock the streaming service
+    mock_streaming_service = MagicMock()
+
+    config = {
+        "configurable": {
+            "user_id": "test_user",
+            "user_role": "professor",
+        }
+    }
+    initial_state = AlisonState(
+        user_query="My projector is not working.",
+        db_session=mock_session,
+        streaming_service=mock_streaming_service,
+        chat_history=[],
+        identified_problem=None,
+        troubleshooting_steps=None,
+        visual_aids=None,
+        escalation_required=False,
+        final_response=None,
+    )
+
+    # Astream the graph to get the final state
+    final_chunk = None
+    async for chunk in alison_graph.astream(initial_state, config=config):
+        final_chunk = chunk
+
+    assert final_chunk is not None
+    last_state = final_chunk[list(final_chunk.keys())[-1]]
+    assert "Check the power cable" in last_state["final_response"]
+
+@pytest.mark.asyncio
+@patch('surfsense_backend.app.services.llm_service.get_user_fast_llm')
+@patch('surfsense_backend.app.retriever.alison_knowledge_retriever.AlisonKnowledgeRetriever')
+async def test_alison_graph_escalation_path(mock_retriever_cls, mock_llm_service):
+    # Mock the LLM
+    mock_llm = MagicMock()
+    mock_llm.ainvoke = AsyncMock(return_value=MagicMock(content="I am unable to resolve this issue. Please contact IT support."))
+    mock_llm_service.return_value = mock_llm
+
+    # Mock the retriever to return no documents
+    mock_retriever_instance = mock_retriever_cls.return_value
+    mock_retriever_instance.hybrid_search.return_value = []
+
+    # Mock the db session
+    mock_session = AsyncMock()
+
+    # Mock the streaming service
+    mock_streaming_service = MagicMock()
+
+    config = {
+        "configurable": {
+            "user_id": "test_user",
+            "user_role": "professor",
+        }
+    }
+    initial_state = AlisonState(
+        user_query="My projector is not working.",
+        db_session=mock_session,
+        streaming_service=mock_streaming_service,
+        chat_history=[],
+        identified_problem=None,
+        troubleshooting_steps=None,
+        visual_aids=None,
+        escalation_required=False,
+        final_response=None,
+    )
+
+    # Astream the graph to get the final state
+    final_chunk = None
+    async for chunk in alison_graph.astream(initial_state, config=config):
+        final_chunk = chunk
+
+    assert final_chunk is not None
+    last_state = final_chunk[list(final_chunk.keys())[-1]]
+    assert "Please contact IT support" in last_state["final_response"]