diff --git a/.gitignore b/.gitignore index 4e1f0a1a..d2ee666e 100644 --- a/.gitignore +++ b/.gitignore @@ -1,7 +1,7 @@ .env *.ipynb __pycache__/ -backend/data/* +backend/data/ backend/src/*.json *.pyc *.egg-info/ diff --git a/Makefile b/Makefile index 3f917282..62a75b06 100644 --- a/Makefile +++ b/Makefile @@ -23,11 +23,15 @@ check: .PHONY: docker-up docker-up: - @docker compose up --build --wait + @docker compose -f docker-compose.yml up --build --wait .PHONY: docker-down docker-down: - @docker compose down --remove-orphans + @docker compose -f docker-compose.yml down --remove-orphans + +.PHONY: docker-dev +docker-dev: + @docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build --wait # --- Development Commands --- .PHONY: seed-credentials diff --git a/README.md b/README.md index f5a57050..799536c3 100644 --- a/README.md +++ b/README.md @@ -27,6 +27,31 @@ This setup involves the setting of both the frontend and backend components. We ### Backend Setup +#### Database Schema + +The database automatically creates the following tables: +- `conversations` - Stores conversation metadata (id, user_id, title, timestamps) +- `messages` - Stores individual messages within conversations + +#### Setting Up PostgreSQL Database Variables + +The backend uses PostgreSQL for conversation persistence. Configure these database variables in your `.env` file: + +- `POSTGRES_USER` - Database username (default: `orassistant`) +- `POSTGRES_PASSWORD` - Database password (default: `password`) +- `POSTGRES_DB` - Database name (default: `orassistant_db`) +- `POSTGRES_HOST` - Database host (default: `postgres` for Docker, `localhost` for local) +- `POSTGRES_PORT` - Database port (default: `5432`) + +**For local development without Docker:** +1. Install PostgreSQL on your system +2. Create a database: `createdb orassistant_db` +3. Set `POSTGRES_HOST=localhost` in your `.env` file + +**For Docker deployment:** +- The database is automatically configured via docker-compose +- Data persists in a Docker volume named `postgres_data` + #### Option 1 - Docker Ensure you have `docker` and `docker-compose` installed in your system. diff --git a/backend/.env.example b/backend/.env.example index d5729375..d8212e2a 100644 --- a/backend/.env.example +++ b/backend/.env.example @@ -22,7 +22,7 @@ GOOGLE_GEMINI=2.0_flash LLM_TEMP=1 -EMBEDDINGS_TYPE=GOOGLE_VERTEXAI +EMBEDDINGS_TYPE=GOOGLE_GENAI GOOGLE_EMBEDDINGS=text-embedding-004 HF_EMBEDDINGS=thenlper/gte-large HF_RERANKER=BAAI/bge-reranker-base @@ -70,3 +70,10 @@ HEALTHCHECK_INTERVAL=30s HEALTHCHECK_TIMEOUT=10s HEALTHCHECK_RETRIES=5 HEALTHCHECK_START_PERIOD=1200s + +# PostgreSQL Database Configuration +POSTGRES_USER=orassistant +POSTGRES_PASSWORD=password +POSTGRES_DB=orassistant_db +POSTGRES_HOST=postgres +POSTGRES_PORT=5432 diff --git a/backend/Dockerfile b/backend/Dockerfile index 8d035d19..b8cbb94f 100644 --- a/backend/Dockerfile +++ b/backend/Dockerfile @@ -2,7 +2,18 @@ FROM ghcr.io/astral-sh/uv:python3.13-bookworm-slim WORKDIR /ORAssistant-backend -RUN apt-get update && apt-get install -y pandoc git wget curl git-lfs && git lfs install +RUN apt-get update && apt-get install -y \ + build-essential \ + curl \ + gcc \ + git \ + git-lfs \ + libpq-dev \ + pandoc \ + postgresql-client \ + wget && \ + git lfs install && \ + rm -rf /var/lib/apt/lists/* RUN pip install uv diff --git a/backend/Dockerfile_slim b/backend/Dockerfile_slim index 338ec110..7b7c8cb9 100644 --- a/backend/Dockerfile_slim +++ b/backend/Dockerfile_slim @@ -3,10 +3,18 @@ FROM ghcr.io/astral-sh/uv:python3.13-bookworm-slim WORKDIR /ORAssistant-backend RUN apt-get update && apt-get install -y \ - pandoc git wget curl \ - git-lfs + build-essential \ + curl \ + gcc \ + git \ + git-lfs \ + libpq-dev \ + pandoc \ + postgresql-client \ + wget && \ + git lfs install && \ + rm -rf /var/lib/apt/lists/* -RUN git lfs install RUN pip install uv COPY ./pyproject.toml /ORAssistant-backend/pyproject.toml diff --git a/backend/chatbot.py b/backend/chatbot.py index e3b007b4..c86450a5 100644 --- a/backend/chatbot.py +++ b/backend/chatbot.py @@ -1,6 +1,6 @@ import os import logging -from src.api.routers import graphs +from src.api.routers import conversations def get_history_str(chat_history: list[dict[str, str]]) -> str: @@ -13,7 +13,7 @@ def get_history_str(chat_history: list[dict[str, str]]) -> str: chat_history: list[dict[str, str]] = [] if __name__ == "__main__": - rg = graphs.rg + rg = conversations.rg os.system("clear") while True: diff --git a/backend/main.py b/backend/main.py index 64142ebe..5c61a5cf 100644 --- a/backend/main.py +++ b/backend/main.py @@ -2,10 +2,13 @@ import uvicorn from dotenv import load_dotenv -from src.api.main import app - load_dotenv() +if os.getenv("USE_CUDA", "false").lower() != "true": + os.environ["CUDA_VISIBLE_DEVICES"] = "" + +from src.api.main import app # noqa: E402 + def main() -> None: uvicorn.run( diff --git a/backend/pyproject.toml b/backend/pyproject.toml index 4b5d32f2..1a762332 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -5,9 +5,12 @@ description = "Add your description here" readme = "README.md" requires-python = ">=3.13" dependencies = [ + "asyncpg>=0.30.0", "faiss-cpu==1.12.0", "fastapi==0.116.1", "fastmcp>=2.12.2", + "google-cloud-storage>=2.19.0", + "httpx>=0.28.1", "huggingface-hub[cli]==0.34.4", "langchain==0.3.27", "langchain-community==0.3.27", @@ -19,10 +22,14 @@ dependencies = [ "langgraph==0.6.6", "markdown==3.8.2", "myst-parser==4.0.1", + "nest-asyncio>=1.6.0", "nltk==3.9.1", "openai==1.100.2", - "pypdf==6.1.3", + "psycopg2-binary>=2.9.11", + "pydantic>=2.11.7", + "pypdf==6.0.0", "rank-bm25==0.2.2", + "rich>=13.7.0", "sentence-transformers>=5.1.0", "sphinx==8.1.3", "sphinx-autobuild==2024.10.3", @@ -30,6 +37,7 @@ dependencies = [ "sphinx-copybutton==0.5.2", "sphinx-external-toc==1.0.1", "sphinxcontrib-mermaid==1.0.0", + "sqlalchemy>=2.0.43", "unstructured==0.18.13", ] @@ -58,6 +66,10 @@ markers = [ ] asyncio_mode = "auto" +[[tool.mypy.overrides]] +module = "nest_asyncio" +ignore_missing_imports = true + [tool.mypy] exclude = [ "^tests/", diff --git a/backend/src/agents/retriever_graph.py b/backend/src/agents/retriever_graph.py index cfd8d809..2161c1b2 100644 --- a/backend/src/agents/retriever_graph.py +++ b/backend/src/agents/retriever_graph.py @@ -106,12 +106,21 @@ def classify(self, state: AgentState) -> dict[str, list[str]]: return {"agent_type": [response.content]} # type: ignore def fork_route(self, state: AgentState) -> str: - # TODO: if more than one agent add handler - if not self.enable_mcp: - tmp = "rag_agent" - else: - tmp = "mcp_agent" - return tmp + """Route to the appropriate agent based on classification""" + agent_type = state.get("agent_type", []) + + if not agent_type: + # Default to RAG agent if no classification + return "rag_agent" + + # Return the classified agent type + classified = agent_type[0] + + # If MCP is disabled but classifier chose MCP, fall back to RAG + if classified == "mcp_agent" and not self.enable_mcp: + return "rag_agent" + + return classified def initialize(self) -> None: self.workflow = StateGraph(AgentState) diff --git a/backend/src/agents/retriever_rag.py b/backend/src/agents/retriever_rag.py index 4fc86815..aad7d337 100644 --- a/backend/src/agents/retriever_rag.py +++ b/backend/src/agents/retriever_rag.py @@ -194,8 +194,11 @@ def rag_route(self, state: AgentState) -> str: def rag_generate(self, state: AgentState) -> dict[str, list[AnyMessage]]: query = state["messages"][-1].content context = state["context"][-1].content + chat_history = state.get("chat_history", "") - ans = self.llm_chain.invoke({"context": context, "question": query}) + ans = self.llm_chain.invoke( + {"context": context, "question": query, "chat_history": chat_history} + ) if ans is not None: return {"messages": [ans]} diff --git a/backend/src/api/main.py b/backend/src/api/main.py index e06b2d95..8045a314 100644 --- a/backend/src/api/main.py +++ b/backend/src/api/main.py @@ -1,16 +1,31 @@ from fastapi import FastAPI -from .routers import graphs, healthcheck, helpers, ui +from .routers import healthcheck, helpers, ui, conversations from fastapi.middleware.cors import CORSMiddleware +from contextlib import asynccontextmanager +from src.database.config import init_database +import logging +from typing import AsyncGenerator -app = FastAPI() +logger = logging.getLogger(__name__) + + +@asynccontextmanager +async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]: + """Initialize database on startup.""" + logger.info("Initializing database connection...") + init_database() + yield + logger.info("Shutting down...") + + +app = FastAPI(lifespan=lifespan) -# Add CORS middleware app.add_middleware( CORSMiddleware, allow_origins=[ "http://localhost:3000", "http://127.0.0.1:3000", - "http://localhost:8001", # mock endpoint + "http://localhost:8001", "http://127.0.0.1:8001", ], allow_credentials=True, @@ -18,6 +33,6 @@ allow_headers=["*"], ) app.include_router(healthcheck.router) -app.include_router(graphs.router) app.include_router(helpers.router) app.include_router(ui.router) +app.include_router(conversations.router) diff --git a/backend/src/api/models/response_model.py b/backend/src/api/models/response_model.py index 6d6005c5..6d8c3818 100644 --- a/backend/src/api/models/response_model.py +++ b/backend/src/api/models/response_model.py @@ -1,11 +1,14 @@ -from pydantic import BaseModel +from typing import Optional +from pydantic import BaseModel, ConfigDict +from datetime import datetime +from uuid import UUID class UserInput(BaseModel): query: str - chat_history: list[dict[str, str]] = [] list_sources: bool = False list_context: bool = False + conversation_uuid: Optional[UUID] = None class ContextSource(BaseModel): @@ -28,8 +31,32 @@ class ChatResponse(BaseModel): tools: list[str] = [] -class ChatToolResponse(BaseModel): - response: str - sources: list[str] = [] - context: list[str] = [] - tools: list[str] = [] +class MessageResponse(BaseModel): + uuid: UUID + conversation_uuid: UUID + role: str + content: str + context_sources: Optional[dict] = None + tools: Optional[list] = None + created_at: datetime + + model_config = ConfigDict(from_attributes=True) + + +class ConversationResponse(BaseModel): + uuid: UUID + title: Optional[str] = None + created_at: datetime + updated_at: datetime + messages: list[MessageResponse] = [] + + model_config = ConfigDict(from_attributes=True) + + +class ConversationListResponse(BaseModel): + uuid: UUID + title: Optional[str] = None + created_at: datetime + updated_at: datetime + + model_config = ConfigDict(from_attributes=True) diff --git a/backend/src/api/routers/chains.py b/backend/src/api/routers/chains.py deleted file mode 100644 index 32d20808..00000000 --- a/backend/src/api/routers/chains.py +++ /dev/null @@ -1,222 +0,0 @@ -import os -from typing import Any -from fastapi import APIRouter -from dotenv import load_dotenv -from typing import Union - -from langchain_google_vertexai import ChatVertexAI -from langchain_google_genai import ChatGoogleGenerativeAI -from langchain_ollama import ChatOllama - -from ...chains.hybrid_retriever_chain import HybridRetrieverChain -from ...chains.similarity_retriever_chain import SimilarityRetrieverChain -from ...prompts.prompt_templates import summarise_prompt_template -from ..models.response_model import ChatResponse, UserInput, ContextSource - -load_dotenv() - -required_env_vars = [ - "USE_CUDA", - "LLM_TEMP", - "HF_EMBEDDINGS", - "HF_RERANKER", - "GOOGLE_GEMINI", -] - -if any(os.getenv(var) is None for var in required_env_vars): - raise ValueError("One or more environment variables are not set.") - -use_cuda: bool = False -llm_temp: float = 0.0 - -if str(os.getenv("USE_CUDA")).lower() in ("true"): - use_cuda = True - -llm_temp_str = os.getenv("LLM_TEMP") -if llm_temp_str is not None: - llm_temp = float(llm_temp_str) - -embeddings_type: str = str(os.getenv("EMBEDDINGS_TYPE")) - -if embeddings_type == "HF": - embeddings_model_name = str(os.getenv("HF_EMBEDDINGS")) -elif embeddings_type == "GOOGLE_GENAI" or embeddings_type == "GOOGLE_VERTEXAI": - embeddings_model_name = str(os.getenv("GOOGLE_EMBEDDINGS")) - -embeddings_config = {"type": embeddings_type, "name": embeddings_model_name} - -hf_reranker: str = str(os.getenv("HF_RERANKER")) - -llm: Union[ChatGoogleGenerativeAI, ChatVertexAI, ChatOllama] - -if os.getenv("LLM_MODEL") == "ollama": - model_name = str(os.getenv("OLLAMA_MODEL")) - llm = ChatOllama(model=model_name, temperature=llm_temp) - -elif os.getenv("LLM_MODEL") == "gemini": - gemini_model = os.getenv("GOOGLE_GEMINI") - if gemini_model in {"1_pro", "1.5_flash", "1.5_pro"}: - raise ValueError( - f"The selected Gemini model '{gemini_model}' (version 1.0–1.5) is disabled. " - "Please upgrade to version 2.0 or higher (e.g., 2.0_flash, 2.5_pro)." - ) - elif gemini_model == "2.0_flash": - llm = ChatVertexAI(model_name="gemini-2.0-flash", temperature=llm_temp) - elif gemini_model == "2.5_flash": - llm = ChatVertexAI(model_name="gemini-2.5-flash", temperature=llm_temp) - elif gemini_model == "2.5_pro": - llm = ChatVertexAI(model_name="gemini-2.5-pro", temperature=llm_temp) - else: - raise ValueError("GOOGLE_GEMINI environment variable not set to a valid value.") - -else: - raise ValueError("LLM_MODEL environment variable not set to a valid value.") - -router = APIRouter(prefix="/chains", tags=["chains"]) - -hybrid_retriever_chain = HybridRetrieverChain( - llm_model=llm, - prompt_template_str=summarise_prompt_template, - embeddings_config=embeddings_config, - contextual_rerank=True, - reranking_model_name=hf_reranker, - use_cuda=use_cuda, - markdown_docs_path=["./data/markdown"], - other_docs_path=["./data/pdf"], - html_docs_path=["./data/html"], -) -hybrid_retriever_chain.create_hybrid_retriever() -hybrid_retriever = hybrid_retriever_chain.retriever -hybrid_llm_chain = hybrid_retriever_chain.get_llm_chain() - -sim_retriever_chain = SimilarityRetrieverChain( - llm_model=llm, - prompt_template_str=summarise_prompt_template, - embeddings_config=embeddings_config, - use_cuda=use_cuda, - markdown_docs_path=["./data/markdown"], - other_docs_path=["./data/pdf"], - html_docs_path=["./data/html"], -) -sim_retriever_chain.create_similarity_retriever() -sim_llm_chain = sim_retriever_chain.get_llm_chain() - - -@router.get("/listAll") -async def list_all_chains() -> list[str]: - return [ - "/graphs/agent-retriever", - "/chains/hybrid", - "/chains/sim", - "/chains/ensemble", - ] - - -@router.post("/hybrid", response_model=ChatResponse) -async def get_hybrid_response(user_input: UserInput) -> ChatResponse: - user_question = user_input.query - result = hybrid_llm_chain.invoke(user_question) - - context_sources = [] - for i in result["context"]: - if "url" in i.metadata: - context_sources.append( - ContextSource(context=i.page_content, source=i.metadata["url"]) - ) - elif "source" in i.metadata: - context_sources.append( - ContextSource(context=i.page_content, source=i.metadata["source"]) - ) - - if user_input.list_sources and user_input.list_context: - response = {"response": result["answer"], "context_sources": context_sources} - elif user_input.list_sources: - response = { - "response": result["answer"], - "context_sources": [ - ContextSource(context="", source=cs.source) for cs in context_sources - ], - } - elif user_input.list_context: - response = { - "response": result["answer"], - "context_sources": [ - ContextSource(context=cs.context, source="") for cs in context_sources - ], - } - else: - response = {"response": result["answer"], "context_sources": []} - - return ChatResponse(**response) - - -@router.post("/hybrid/get_chunks") -async def get_hybrid_chunks(user_input: UserInput) -> dict[str, Any]: - if hybrid_retriever is not None: - doc_chunks = hybrid_retriever.invoke(input="placement") - response = { - "response": [ - {"page_content": doc.page_content, "src": doc.metadata.get("source")} - for doc in doc_chunks - ] - } - else: - raise ValueError("Hybrid retriever not initialized") - - return response - - -@router.post("/sim") -async def get_sim_response(user_input: UserInput) -> ChatResponse: - user_question = user_input.query - result = sim_llm_chain.invoke(user_question) - - context_sources = [] - for i in result["context"]: - if "url" in i.metadata: - context_sources.append( - ContextSource(context=i.page_content, source=i.metadata["url"]) - ) - elif "source" in i.metadata: - context_sources.append( - ContextSource(context=i.page_content, source=i.metadata["source"]) - ) - - if user_input.list_sources and user_input.list_context: - response = {"response": result["answer"], "context_sources": context_sources} - elif user_input.list_sources: - response = { - "response": result["answer"], - "context_sources": [ - ContextSource(context="", source=cs.source) for cs in context_sources - ], - } - elif user_input.list_context: - response = { - "response": result["answer"], - "context_sources": [ - ContextSource(context=cs.context, source="") for cs in context_sources - ], - } - else: - response = {"response": result["answer"], "context_sources": []} - - return ChatResponse(**response) - - -@router.post("/sim/get_chunks") -async def get_sim_chunks(user_input: UserInput) -> dict[str, Any]: - user_question = user_input.query - - if sim_retriever_chain.retriever is not None: - doc_chunks = sim_retriever_chain.retriever.invoke(input=user_question) - response = { - "response": [ - {"page_content": doc.page_content, "src": doc.metadata.get("source")} - for doc in doc_chunks - ] - } - else: - raise ValueError("Similarity retriever not initialized") - - return response diff --git a/backend/src/api/routers/graphs.py b/backend/src/api/routers/conversations.py similarity index 62% rename from backend/src/api/routers/graphs.py rename to backend/src/api/routers/conversations.py index 166d5c6b..48fa4869 100644 --- a/backend/src/api/routers/graphs.py +++ b/backend/src/api/routers/conversations.py @@ -3,20 +3,29 @@ from dotenv import load_dotenv from typing import Any -from fastapi import APIRouter +from uuid import UUID +from fastapi import APIRouter, Depends, HTTPException from langchain_google_vertexai import ChatVertexAI from langchain_google_genai import ChatGoogleGenerativeAI from langchain_ollama import ChatOllama from langchain_core.messages import AIMessageChunk from starlette.responses import StreamingResponse +from sqlalchemy.orm import Session from ...agents.retriever_graph import RetrieverGraph -from ..models.response_model import ChatResponse, ContextSource, UserInput +from ...database import get_db +from ...database import crud +from ..models.response_model import ( + ChatResponse, + ContextSource, + UserInput, + ConversationResponse, + ConversationListResponse, +) load_dotenv() logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO").upper()) - required_env_vars = [ "USE_CUDA", "LLM_TEMP", @@ -82,7 +91,7 @@ "Please upgrade to version 2.0 or higher (e.g., 2.0_flash, 2.5_pro)." ) elif gemini_model == "2.0_flash": - llm = ChatVertexAI(model_name="gemini-2.0-flash", temperature=llm_temp) + llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=llm_temp) elif gemini_model == "2.5_flash": llm = ChatVertexAI(model_name="gemini-2.5-flash", temperature=llm_temp) elif gemini_model == "2.5_pro": @@ -93,19 +102,17 @@ else: raise ValueError("LLM_MODEL environment variable not set to a valid value.") -router = APIRouter(prefix="/graphs", tags=["graphs"]) +router = APIRouter(prefix="/conversations", tags=["conversations"]) def extract_rag_context_sources(output: list) -> list[ContextSource]: - """Extract context sources from RAG agent output.""" context_sources = [] - for element in output[1:-1]: # Skip first (classify) and last (generate) nodes + for element in output[1:-1]: if isinstance(element, dict): for key, value in element.items(): if key.startswith("retrieve_") and isinstance(value, dict): urls = value.get("urls", []) context = value.get("context", "") - # Create context sources from urls and context for url in urls: context_sources.append( ContextSource(context=context, source=url) @@ -114,7 +121,6 @@ def extract_rag_context_sources(output: list) -> list[ContextSource]: def extract_mcp_context_sources(output: list) -> tuple[list[ContextSource], list[str]]: - """Extract context sources and tools from MCP/arch agent output.""" context_sources = [] tools = [] @@ -131,12 +137,10 @@ def extract_mcp_context_sources(output: list) -> tuple[list[ContextSource], list def validate_output_structure(output: Any) -> bool: - """Validate that output has the expected structure.""" return isinstance(output, list) and len(output) > 2 and isinstance(output[-1], dict) def log_invalid_output(output: Any) -> None: - """Log details about invalid output structure.""" logging.error( f"Invalid output structure: type={type(output)}, len={len(output) if isinstance(output, list) else 'N/A'}" ) @@ -147,16 +151,12 @@ def log_invalid_output(output: Any) -> None: def get_agent_type(output: list) -> tuple[bool, str]: - """Determine agent type from output structure. - Returns: (is_rag_agent, generate_key) - """ is_rag_agent = "rag_generate" in output[-1] generate_key = "rag_generate" if is_rag_agent else "generate" return is_rag_agent, generate_key def extract_llm_response(output: list, generate_key: str) -> str | None: - """Extract LLM response from output if available.""" if generate_key not in output[-1]: logging.error(f"Missing {generate_key} key") return None @@ -176,28 +176,20 @@ def extract_llm_response(output: list, generate_key: str) -> str | None: def parse_agent_output(output: list) -> tuple[str, list[ContextSource], list[str]]: - """ - Parse agent output and extract response, context sources, and tools. - """ - # Default return values default_response = "LLM response extraction failed" context_sources: list[ContextSource] = [] tools: list[str] = [] - # Validate output structure if not validate_output_structure(output): log_invalid_output(output) return default_response, context_sources, tools - # Determine agent type is_rag_agent, generate_key = get_agent_type(output) - # Extract LLM response llm_response = extract_llm_response(output, generate_key) if llm_response is None: return default_response, context_sources, tools - # Extract context sources based on agent type if is_rag_agent: context_sources = extract_rag_context_sources(output) else: @@ -219,22 +211,44 @@ def parse_agent_output(output: list) -> tuple[str, list[ContextSource], list[str rg.initialize() -def get_history_str(chat_history: list[dict[str, str]]) -> str: +def get_history_str(db: Session, conversation_uuid: UUID) -> str: + history = crud.get_conversation_history(db, conversation_uuid) history_str = "" - for i in chat_history: - history_str += f"User : {i['User']}\nAI : {i['AI']}\n\n" + for i in history: + user_msg = i.get("User", "") + ai_msg = i.get("AI", "") + if user_msg and ai_msg: + history_str += f"User : {user_msg}\nAI : {ai_msg}\n\n" return history_str @router.post("/agent-retriever", response_model=ChatResponse) -async def get_agent_response(user_input: UserInput) -> ChatResponse: +async def get_agent_response( + user_input: UserInput, db: Session = Depends(get_db) +) -> ChatResponse: + """Processes a user query using the retriever agent, maintains conversation context, and returns the generated response along with relevant context sources and tools used.""" user_question = user_input.query + conversation_uuid = user_input.conversation_uuid + + conversation = crud.get_or_create_conversation( + db, + conversation_uuid=conversation_uuid, + title=user_question[:100] if user_question else None, + ) + + crud.create_message( + db=db, + conversation_uuid=conversation.uuid, + role="user", + content=user_question, + ) + inputs = { "messages": [ ("user", user_question), ], - "chat_history": get_history_str(user_input.chat_history), + "chat_history": get_history_str(db, conversation.uuid), } if rg.graph is not None: @@ -242,9 +256,22 @@ async def get_agent_response(user_input: UserInput) -> ChatResponse: else: raise ValueError("RetrieverGraph not initialized.") - # Use the extracted function to parse agent output llm_response, context_sources, tools = parse_agent_output(output) + context_sources_dict: dict[str, Any] = { + "sources": [ + {"source": cs.source, "context": cs.context} for cs in context_sources + ] + } + crud.create_message( + db=db, + conversation_uuid=conversation.uuid, + role="assistant", + content=llm_response, + context_sources=context_sources_dict, + tools=tools, + ) + response: dict[str, Any] if user_input.list_sources and user_input.list_context: response = { @@ -278,18 +305,34 @@ async def get_agent_response(user_input: UserInput) -> ChatResponse: return ChatResponse(**response) -async def get_response_stream(user_input: UserInput): # type: ignore[no-untyped-def] +async def get_response_stream(user_input: UserInput, db: Session) -> Any: user_question = user_input.query + conversation_uuid = user_input.conversation_uuid + + conversation = crud.get_or_create_conversation( + db, + conversation_uuid=conversation_uuid, + title=user_question[:100] if user_question else None, + ) + + crud.create_message( + db=db, + conversation_uuid=conversation.uuid, + role="user", + content=user_question, + ) + inputs = { "messages": [ ("user", user_question), ], - "chat_history": get_history_str(user_input.chat_history), + "chat_history": get_history_str(db, conversation.uuid), } urls: list[str] = [] current_llm_call_count = 1 + chunks: list[str] = [] if rg.graph is not None: async for event in rg.graph.astream_events(inputs, version="v2"): @@ -299,24 +342,81 @@ async def get_response_stream(user_input: UserInput): # type: ignore[no-untyped current_llm_call_count += 1 if chunk == "on_retriever_start" or chunk == "on_retriever_end": - for document in event.get("data", {}).get("output", {}): + event_data: Any = event.get("data", {}) + output_docs: list[Any] = event_data.get("output", []) + for document in output_docs: urls.append(document.metadata["url"]) - if chunk == "on_chat_model_stream" and current_llm_call_count == 2: - message_content = event.get("data", {}).get("chunk", {}) + if chunk == "on_chat_model_stream" and current_llm_call_count >= 2: + event_data_chunk: Any = event.get("data", {}) + message_content: Any = event_data_chunk.get("chunk", {}) if isinstance(message_content, AIMessageChunk): msg = message_content.content else: msg = None - yield str(msg) + "\n\n" + if msg: + chunks.append(str(msg)) + yield str(msg) + "\n\n" urls = list(set(urls)) yield f"Sources: {', '.join(urls)}\n\n" + full_response = "".join(chunks) + context_sources_dict: dict[str, Any] = { + "sources": [{"source": url, "context": ""} for url in urls] + } + crud.create_message( + db=db, + conversation_uuid=conversation.uuid, + role="assistant", + content=full_response, + context_sources=context_sources_dict, + tools=[], + ) + @router.post("/agent-retriever/stream", response_class=StreamingResponse) -async def get_agent_response_streaming(user_input: UserInput): # type: ignore[no-untyped-def] +async def get_agent_response_streaming( + user_input: UserInput, db: Session = Depends(get_db) +) -> StreamingResponse: + """Provides real-time streaming of the agent's response as it's being generated.""" return StreamingResponse( - get_response_stream(user_input), media_type="text/event-stream" + get_response_stream(user_input, db), media_type="text/event-stream" ) + + +@router.post("", response_model=ConversationResponse, status_code=201) +async def create_conversation(db: Session = Depends(get_db)) -> ConversationResponse: + """Creates a new conversation with an auto-generated UUID identifier.""" + new_conversation = crud.create_conversation(db, conversation_uuid=None, title=None) + return ConversationResponse.model_validate(new_conversation) + + +@router.get("", response_model=list[ConversationListResponse]) +async def list_conversations( + skip: int = 0, limit: int = 100, db: Session = Depends(get_db) +) -> list[ConversationListResponse]: + """Retrieves a paginated list of all conversations without their messages.""" + conversations = crud.get_all_conversations(db, skip=skip, limit=limit) + return [ConversationListResponse.model_validate(conv) for conv in conversations] + + +@router.get("/{id}", response_model=ConversationResponse) +async def get_conversation( + id: UUID, db: Session = Depends(get_db) +) -> ConversationResponse: + """Retrieves a complete conversation including all associated messages.""" + conversation = crud.get_conversation(db, id) + if not conversation: + raise HTTPException(status_code=404, detail="Conversation not found") + return ConversationResponse.model_validate(conversation) + + +@router.delete("/{id}", status_code=204) +async def delete_conversation(id: UUID, db: Session = Depends(get_db)) -> None: + """Permanently removes a conversation and all associated messages from the database.""" + conversation = crud.get_conversation(db, id) + if not conversation: + raise HTTPException(status_code=404, detail="Conversation not found") + crud.delete_conversation(db, id) diff --git a/backend/src/api/routers/healthcheck.py b/backend/src/api/routers/healthcheck.py index 8cc099f0..e3b21c00 100644 --- a/backend/src/api/routers/healthcheck.py +++ b/backend/src/api/routers/healthcheck.py @@ -10,4 +10,5 @@ class HealthCheckResponse(BaseModel): @router.get("/healthcheck", response_model=HealthCheckResponse) async def healthcheck() -> HealthCheckResponse: + """An endpoint to verify that the API is up and running.""" return HealthCheckResponse(status="ok") diff --git a/backend/src/database/__init__.py b/backend/src/database/__init__.py new file mode 100644 index 00000000..2e4deedc --- /dev/null +++ b/backend/src/database/__init__.py @@ -0,0 +1,11 @@ +from .config import get_db, init_database, is_database_available +from .models import Base, Conversation, Message + +__all__ = [ + "get_db", + "init_database", + "is_database_available", + "Base", + "Conversation", + "Message", +] diff --git a/backend/src/database/config.py b/backend/src/database/config.py new file mode 100644 index 00000000..417b314a --- /dev/null +++ b/backend/src/database/config.py @@ -0,0 +1,102 @@ +"""Database configuration and session management.""" + +import os +import logging +from typing import Generator, Optional +from sqlalchemy import create_engine, inspect, text, Engine +from sqlalchemy.orm import sessionmaker, Session +from sqlalchemy.exc import OperationalError +from .models import Base + +logger = logging.getLogger(__name__) + +engine: Optional[Engine] = None +SessionLocal: Optional[sessionmaker[Session]] = None +_db_initialized: bool = False + + +def get_database_url() -> str: + db_user = os.getenv("POSTGRES_USER") + db_password = os.getenv("POSTGRES_PASSWORD") + db_host = os.getenv("POSTGRES_HOST") + db_port = os.getenv("POSTGRES_PORT") + db_name = os.getenv("POSTGRES_DB") + + return f"postgresql://{db_user}:{db_password}@{db_host}:{db_port}/{db_name}" + + +def is_database_available() -> bool: + global engine + + if engine is None: + return False + + try: + with engine.connect() as conn: + conn.execute(text("SELECT 1")) + return True + except OperationalError as e: + logger.debug(f"Database not available: {e}") + return False + + +def init_database() -> bool: + global engine, SessionLocal, _db_initialized + + if _db_initialized and engine is not None and is_database_available(): + return True + + try: + if engine is None: + engine = create_engine( + get_database_url(), + pool_size=10, + max_overflow=20, + pool_pre_ping=True, + echo=False, + connect_args={"connect_timeout": 5}, + ) + + if SessionLocal is None: + SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine) + + if not is_database_available(): + logger.warning("Database is not available. Will retry on next access.") + return False + + inspector = inspect(engine) + existing_tables = inspector.get_table_names() + + if not existing_tables or "conversations" not in existing_tables: + logger.info("Initializing database tables...") + Base.metadata.create_all(bind=engine) + logger.info("Database tables created successfully") + else: + logger.debug("Database tables already exist") + + _db_initialized = True + return True + + except OperationalError as e: + logger.warning(f"Database connection failed: {e}") + logger.warning("Chatbot will run without database persistence.") + return False + except Exception as e: + logger.error(f"Failed to initialize database: {e}") + return False + + +def get_db() -> Generator[Session, None, None]: + if not _db_initialized: + init_database() + + if SessionLocal is None: + raise RuntimeError( + "Database session factory not initialized. Is PostgreSQL running?" + ) + + db = SessionLocal() + try: + yield db + finally: + db.close() diff --git a/backend/src/database/crud.py b/backend/src/database/crud.py new file mode 100644 index 00000000..7ef66d97 --- /dev/null +++ b/backend/src/database/crud.py @@ -0,0 +1,135 @@ +from typing import Optional +from sqlalchemy.orm import Session +from sqlalchemy import desc +from .models import Conversation, Message +from uuid import UUID + + +def create_conversation( + db: Session, conversation_uuid: Optional[UUID] = None, title: Optional[str] = None +) -> Conversation: + conversation = ( + Conversation(uuid=conversation_uuid, title=title) + if conversation_uuid + else Conversation(title=title) + ) + db.add(conversation) + db.commit() + db.refresh(conversation) + return conversation + + +def get_conversation(db: Session, conversation_uuid: UUID) -> Optional[Conversation]: + return db.query(Conversation).filter(Conversation.uuid == conversation_uuid).first() + + +def get_or_create_conversation( + db: Session, conversation_uuid: Optional[UUID] = None, title: Optional[str] = None +) -> Conversation: + if conversation_uuid: + conversation = get_conversation(db, conversation_uuid) + if conversation: + return conversation + return create_conversation(db, conversation_uuid, title) + + +def get_all_conversations( + db: Session, skip: int = 0, limit: int = 100 +) -> list[Conversation]: + return ( + db.query(Conversation) + .order_by(desc(Conversation.updated_at)) + .offset(skip) + .limit(limit) + .all() + ) + + +def update_conversation_title( + db: Session, conversation_uuid: UUID, title: str +) -> Optional[Conversation]: + conversation = get_conversation(db, conversation_uuid) + if conversation: + conversation.title = title + db.commit() + db.refresh(conversation) + return conversation + + +def delete_conversation(db: Session, conversation_uuid: UUID) -> bool: + conversation = get_conversation(db, conversation_uuid) + if conversation: + db.delete(conversation) + db.commit() + return True + return False + + +def create_message( + db: Session, + conversation_uuid: UUID, + role: str, + content: str, + context_sources: Optional[dict] = None, + tools: Optional[list] = None, +) -> Message: + message = Message( + conversation_uuid=conversation_uuid, + role=role, + content=content, + context_sources=context_sources, + tools=tools, + ) + db.add(message) + db.commit() + db.refresh(message) + return message + + +def get_message(db: Session, message_id: UUID) -> Optional[Message]: + return db.query(Message).filter(Message.uuid == message_id).first() + + +def get_conversation_messages( + db: Session, conversation_uuid: UUID, skip: int = 0, limit: int = 100 +) -> list[Message]: + return ( + db.query(Message) + .filter(Message.conversation_uuid == conversation_uuid) + .order_by(Message.created_at) + .offset(skip) + .limit(limit) + .all() + ) + + +def delete_message(db: Session, message_id: UUID) -> bool: + message = get_message(db, message_id) + if message: + db.delete(message) + db.commit() + return True + return False + + +def get_conversation_history( + db: Session, conversation_uuid: UUID +) -> list[dict[str, str]]: + messages = get_conversation_messages(db, conversation_uuid) + history = [] + current_pair: dict[str, str] = {} + + for message in messages: + if message.role == "user": + if current_pair: + history.append(current_pair) + current_pair = {"User": message.content} + elif message.role == "assistant" and current_pair: + current_pair["AI"] = message.content + history.append(current_pair) + current_pair = {} + + if current_pair: + history.append(current_pair) + + return history diff --git a/backend/src/database/models.py b/backend/src/database/models.py new file mode 100644 index 00000000..daa4333a --- /dev/null +++ b/backend/src/database/models.py @@ -0,0 +1,54 @@ +from datetime import datetime, timezone +from typing import Optional +from sqlalchemy import DateTime, ForeignKey, String, Text, JSON, Uuid +from sqlalchemy.orm import DeclarativeBase, relationship, Mapped, mapped_column +from uuid import uuid4, UUID + + +class Base(DeclarativeBase): + pass + + +class Conversation(Base): + __tablename__ = "conversations" + + uuid: Mapped[UUID] = mapped_column(Uuid, primary_key=True, default=uuid4) + title: Mapped[Optional[str]] = mapped_column(String(500), nullable=True) + created_at: Mapped[datetime] = mapped_column( + DateTime(timezone=True), default=lambda: datetime.now(timezone.utc) + ) + updated_at: Mapped[datetime] = mapped_column( + DateTime(timezone=True), + default=lambda: datetime.now(timezone.utc), + onupdate=lambda: datetime.now(timezone.utc), + ) + + messages: Mapped[list["Message"]] = relationship( + "Message", back_populates="conversation", cascade="all, delete-orphan" + ) + + def __repr__(self) -> str: + return f"" + + +class Message(Base): + __tablename__ = "messages" + + uuid: Mapped[UUID] = mapped_column(Uuid, primary_key=True, default=uuid4) + conversation_uuid: Mapped[UUID] = mapped_column( + Uuid, ForeignKey("conversations.uuid", ondelete="CASCADE"), index=True + ) + role: Mapped[str] = mapped_column(String(50)) + content: Mapped[str] = mapped_column(Text) + context_sources: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True) + tools: Mapped[Optional[list]] = mapped_column(JSON, nullable=True) + created_at: Mapped[datetime] = mapped_column( + DateTime(timezone=True), default=lambda: datetime.now(timezone.utc) + ) + + conversation: Mapped["Conversation"] = relationship( + "Conversation", back_populates="messages" + ) + + def __repr__(self) -> str: + return f"" diff --git a/backend/src/openroad_mcp/client/client.py b/backend/src/openroad_mcp/client/client.py index c07d34b9..7bda3040 100644 --- a/backend/src/openroad_mcp/client/client.py +++ b/backend/src/openroad_mcp/client/client.py @@ -1,10 +1,12 @@ +import os import asyncio +import nest_asyncio import logging from typing import Any from datetime import timedelta from langchain_mcp_adapters.client import MultiServerMCPClient # type: ignore -MCP_SERVER_URL = "http://localhost:3001/mcp/" +MCP_SERVER_URL = os.getenv("MCP_SERVER_URL", "http://localhost:3001/mcp/") _tools_cache: Any = None @@ -38,7 +40,14 @@ async def get_tools_async() -> Any: def get_tools() -> Any: """Get MCP tools synchronously""" try: - return asyncio.run(get_tools_async()) + # Try to get existing event loop + try: + _loop = asyncio.get_running_loop() + nest_asyncio.apply() + return asyncio.run(get_tools_async()) + except RuntimeError: + # No running loop, use asyncio.run() + return asyncio.run(get_tools_async()) except Exception as e: logging.warning(f"Failed to connect to MCP server: {e}") return [] diff --git a/backend/src/prompts/prompt_templates.py b/backend/src/prompts/prompt_templates.py index 6ba4c21b..0cd436e4 100644 --- a/backend/src/prompts/prompt_templates.py +++ b/backend/src/prompts/prompt_templates.py @@ -18,6 +18,10 @@ For casual greetings respond politely with a simple, relevant answer. Introduce yourself when asked. +------------------------------------------------------------------------------------ +Chat History: +{chat_history} + ------------------------------------------------------------------------------------ Use the following context: diff --git a/backend/tests/test_api_conversations_streaming.py b/backend/tests/test_api_conversations_streaming.py new file mode 100644 index 00000000..a3a921de --- /dev/null +++ b/backend/tests/test_api_conversations_streaming.py @@ -0,0 +1,504 @@ +"""Unit tests for streaming conversation endpoint.""" + +import pytest +from unittest.mock import Mock, patch, MagicMock +from uuid import uuid4 +from sqlalchemy import create_engine +from sqlalchemy.orm import sessionmaker, Session +from langchain_core.messages import AIMessageChunk + +from src.database.models import Base +from src.database import crud +from src.api.models.response_model import UserInput + +# Patch RetrieverGraph globally before any other imports +mock_rg_instance = MagicMock() +mock_graph_global = MagicMock() +mock_rg_instance.graph = mock_graph_global + +with patch("src.agents.retriever_graph.RetrieverGraph", return_value=mock_rg_instance): + # Import after patching + from src.api.routers import conversations # noqa: F401 + + +@pytest.fixture +def db_session(): + """Create an in-memory SQLite database for testing.""" + engine = create_engine("sqlite:///:memory:") + Base.metadata.create_all(engine) + SessionLocal = sessionmaker(bind=engine) + session = SessionLocal() + yield session + session.close() + + +@pytest.fixture +def mock_retriever_graph(): + """Mock RetrieverGraph for streaming tests.""" + # Reset the mock for each test + mock_graph_global.reset_mock() + yield mock_graph_global + + +@pytest.fixture +def sample_user_input(): + """Sample user input for testing.""" + return UserInput( + query="What is OpenROAD?", + list_sources=False, + list_context=False, + conversation_uuid=uuid4(), + ) + + +class TestStreamingEndpoint: + """Test suite for the streaming endpoint.""" + + @pytest.mark.asyncio + async def test_get_response_stream_basic( + self, db_session: Session, mock_retriever_graph, sample_user_input: UserInput + ): + """Test basic streaming response generation.""" + from src.api.routers.conversations import get_response_stream + + # Mock stream events + async def mock_astream_events(*args, **kwargs): + # Simulate retriever events + yield { + "event": "on_retriever_end", + "data": { + "output": [ + Mock(metadata={"url": "https://example.com/doc1"}), + Mock(metadata={"url": "https://example.com/doc2"}), + ] + }, + } + # Simulate first LLM call end + yield {"event": "on_chat_model_end", "data": {}} + # Simulate second LLM call streaming + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="OpenROAD ")}, + } + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="is a ")}, + } + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="tool.")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + # Collect streamed chunks + chunks = [] + async for chunk in get_response_stream(sample_user_input, db_session): + chunks.append(chunk) + + # Verify chunks + assert len(chunks) > 0 + assert any("OpenROAD " in chunk for chunk in chunks) + assert any("is a " in chunk for chunk in chunks) + assert any("tool." in chunk for chunk in chunks) + assert any("Sources:" in chunk for chunk in chunks) + assert any("example.com/doc1" in chunk for chunk in chunks) + + # Verify conversation and messages were created + all_conversations = crud.get_all_conversations(db_session) + assert len(all_conversations) == 1 + conversation = all_conversations[0] + assert conversation.uuid == sample_user_input.conversation_uuid + + messages = conversation.messages + assert len(messages) == 2 + assert messages[0].role == "user" + assert messages[0].content == "What is OpenROAD?" + assert messages[1].role == "assistant" + assert "OpenROAD is a tool." in messages[1].content + + @pytest.mark.asyncio + async def test_get_response_stream_creates_conversation( + self, db_session: Session, mock_retriever_graph + ): + """Test that streaming creates a new conversation if UUID is None.""" + from src.api.routers.conversations import get_response_stream + + user_input = UserInput( + query="Test question", list_sources=False, conversation_uuid=None + ) + + async def mock_astream_events(*args, **kwargs): + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Test response")}, + } + yield {"event": "on_chat_model_end", "data": {}} + yield {"event": "on_chat_model_end", "data": {}} + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(user_input, db_session): + chunks.append(chunk) + + # Verify conversation was created + all_conversations = crud.get_all_conversations(db_session) + assert len(all_conversations) == 1 + + @pytest.mark.asyncio + async def test_get_response_stream_with_chat_history( + self, db_session: Session, mock_retriever_graph + ): + """Test streaming with existing chat history.""" + from src.api.routers.conversations import get_response_stream + + # Create existing conversation with messages + conv_uuid = uuid4() + _conv = crud.create_conversation( + db_session, conversation_uuid=conv_uuid, title="Test" + ) + crud.create_message( + db_session, + conversation_uuid=conv_uuid, + role="user", + content="Previous question", + ) + crud.create_message( + db_session, + conversation_uuid=conv_uuid, + role="assistant", + content="Previous answer", + ) + + user_input = UserInput(query="Follow-up question", conversation_uuid=conv_uuid) + + captured_inputs = [] + + async def mock_astream_events(inputs, *args, **kwargs): + captured_inputs.append(inputs) + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Follow-up answer")}, + } + yield {"event": "on_chat_model_end", "data": {}} + yield {"event": "on_chat_model_end", "data": {}} + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(user_input, db_session): + chunks.append(chunk) + + # Verify chat history was included in inputs + assert len(captured_inputs) == 1 + assert "chat_history" in captured_inputs[0] + chat_history = captured_inputs[0]["chat_history"] + assert "Previous question" in chat_history + assert "Previous answer" in chat_history + + @pytest.mark.asyncio + async def test_get_response_stream_multiple_retrievals( + self, db_session: Session, mock_retriever_graph, sample_user_input: UserInput + ): + """Test streaming with multiple retrieval events.""" + from src.api.routers.conversations import get_response_stream + + async def mock_astream_events(*args, **kwargs): + # First retrieval + yield { + "event": "on_retriever_start", + "data": { + "output": [Mock(metadata={"url": "https://example.com/doc1"})] + }, + } + # Second retrieval + yield { + "event": "on_retriever_end", + "data": { + "output": [ + Mock(metadata={"url": "https://example.com/doc2"}), + Mock(metadata={"url": "https://example.com/doc3"}), + ] + }, + } + yield {"event": "on_chat_model_end", "data": {}} + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Response")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(sample_user_input, db_session): + chunks.append(chunk) + + # Verify all unique URLs are in sources + sources_chunk = [c for c in chunks if "Sources:" in c][0] + assert "doc1" in sources_chunk + assert "doc2" in sources_chunk + assert "doc3" in sources_chunk + + @pytest.mark.asyncio + async def test_get_response_stream_filters_duplicate_urls( + self, db_session: Session, mock_retriever_graph, sample_user_input: UserInput + ): + """Test that duplicate URLs are filtered out.""" + from src.api.routers.conversations import get_response_stream + + async def mock_astream_events(*args, **kwargs): + yield { + "event": "on_retriever_end", + "data": { + "output": [ + Mock(metadata={"url": "https://example.com/doc1"}), + Mock(metadata={"url": "https://example.com/doc1"}), + Mock(metadata={"url": "https://example.com/doc2"}), + ] + }, + } + yield {"event": "on_chat_model_end", "data": {}} + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Test")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(sample_user_input, db_session): + chunks.append(chunk) + + sources_chunk = [c for c in chunks if "Sources:" in c][0] + # Count occurrences of doc1 + doc1_count = sources_chunk.count("doc1") + assert doc1_count == 1 + + @pytest.mark.asyncio + async def test_get_response_stream_skips_first_llm_call( + self, db_session: Session, mock_retriever_graph, sample_user_input: UserInput + ): + """Test that streaming only outputs from second LLM call onwards.""" + from src.api.routers.conversations import get_response_stream + + async def mock_astream_events(*args, **kwargs): + # First LLM call - should be skipped + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="SHOULD_NOT_APPEAR")}, + } + yield {"event": "on_chat_model_end", "data": {}} + # Second LLM call - should be included + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="SHOULD_APPEAR")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(sample_user_input, db_session): + chunks.append(chunk) + + content_chunks = [c for c in chunks if "Sources:" not in c] + assert not any("SHOULD_NOT_APPEAR" in c for c in content_chunks) + assert any("SHOULD_APPEAR" in c for c in content_chunks) + + @pytest.mark.asyncio + async def test_get_response_stream_handles_non_ai_message_chunks( + self, db_session: Session, mock_retriever_graph, sample_user_input: UserInput + ): + """Test handling of non-AIMessageChunk content.""" + from src.api.routers.conversations import get_response_stream + + async def mock_astream_events(*args, **kwargs): + yield {"event": "on_chat_model_end", "data": {}} + # Send non-AIMessageChunk + yield { + "event": "on_chat_model_stream", + "data": {"chunk": "plain_string"}, # Not an AIMessageChunk + } + # Send valid AIMessageChunk + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Valid content")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(sample_user_input, db_session): + chunks.append(chunk) + + # Should only include valid AIMessageChunk + content_chunks = [c for c in chunks if "Sources:" not in c] + assert any("Valid content" in c for c in content_chunks) + + @pytest.mark.asyncio + async def test_get_response_stream_saves_context_sources( + self, db_session: Session, mock_retriever_graph, sample_user_input: UserInput + ): + """Test that context sources are saved to database.""" + from src.api.routers.conversations import get_response_stream + + async def mock_astream_events(*args, **kwargs): + yield { + "event": "on_retriever_end", + "data": { + "output": [ + Mock(metadata={"url": "https://example.com/doc1"}), + Mock(metadata={"url": "https://example.com/doc2"}), + ] + }, + } + yield {"event": "on_chat_model_end", "data": {}} + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Response")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(sample_user_input, db_session): + chunks.append(chunk) + + # Verify context sources in database + all_conversations = crud.get_all_conversations(db_session) + conversation = all_conversations[0] + assistant_message = [m for m in conversation.messages if m.role == "assistant"][ + 0 + ] + + assert assistant_message.context_sources is not None + assert "sources" in assistant_message.context_sources + sources = assistant_message.context_sources["sources"] + assert len(sources) == 2 + assert any(s["source"] == "https://example.com/doc1" for s in sources) + assert any(s["source"] == "https://example.com/doc2" for s in sources) + + @pytest.mark.asyncio + async def test_get_response_stream_title_truncation( + self, db_session: Session, mock_retriever_graph + ): + """Test that conversation title is truncated to 100 characters.""" + from src.api.routers.conversations import get_response_stream + + long_query = "A" * 150 # 150 characters + user_input = UserInput(query=long_query, conversation_uuid=None) + + async def mock_astream_events(*args, **kwargs): + yield {"event": "on_chat_model_end", "data": {}} + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Response")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(user_input, db_session): + chunks.append(chunk) + + all_conversations = crud.get_all_conversations(db_session) + conversation = all_conversations[0] + assert len(conversation.title) == 100 + + @pytest.mark.asyncio + async def test_get_agent_response_streaming_endpoint( + self, db_session: Session, mock_retriever_graph + ): + """Test the FastAPI streaming endpoint wrapper.""" + from src.api.routers.conversations import get_agent_response_streaming + from starlette.responses import StreamingResponse + + user_input = UserInput(query="Test", conversation_uuid=uuid4()) + + async def mock_astream_events(*args, **kwargs): + yield {"event": "on_chat_model_end", "data": {}} + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Test response")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + response = await get_agent_response_streaming(user_input, db_session) + + assert isinstance(response, StreamingResponse) + assert response.media_type == "text/event-stream" + + @pytest.mark.asyncio + async def test_get_response_stream_graph_not_initialized( + self, db_session: Session, sample_user_input: UserInput + ): + """Test behavior when graph is not initialized.""" + from src.api.routers.conversations import get_response_stream + + with patch("src.api.routers.conversations.rg") as mock_rg: + mock_rg.graph = None + + chunks = [] + async for chunk in get_response_stream(sample_user_input, db_session): + chunks.append(chunk) + + # When graph is None, streaming continues but produces no content chunks + # Should still have sources line + assert any("Sources:" in c for c in chunks) + + @pytest.mark.asyncio + async def test_get_response_stream_empty_content( + self, db_session: Session, mock_retriever_graph, sample_user_input: UserInput + ): + """Test handling of empty message content.""" + from src.api.routers.conversations import get_response_stream + + async def mock_astream_events(*args, **kwargs): + yield {"event": "on_chat_model_end", "data": {}} + # Empty content + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="")}, + } + # Valid content + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Valid")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(sample_user_input, db_session): + chunks.append(chunk) + + # Should only stream non-empty content + content_chunks = [c for c in chunks if "Sources:" not in c and c.strip()] + assert all("Valid" in c for c in content_chunks if c.strip()) + + @pytest.mark.asyncio + async def test_get_response_stream_no_sources( + self, db_session: Session, mock_retriever_graph, sample_user_input: UserInput + ): + """Test streaming when no retrieval sources are found.""" + from src.api.routers.conversations import get_response_stream + + async def mock_astream_events(*args, **kwargs): + # No retriever events + yield {"event": "on_chat_model_end", "data": {}} + yield { + "event": "on_chat_model_stream", + "data": {"chunk": AIMessageChunk(content="Response without sources")}, + } + + mock_retriever_graph.astream_events = mock_astream_events + + chunks = [] + async for chunk in get_response_stream(sample_user_input, db_session): + chunks.append(chunk) + + # Should still have a Sources line (empty) + assert any("Sources:" in c for c in chunks) + sources_chunk = [c for c in chunks if "Sources:" in c][0] + assert sources_chunk.strip() == "Sources:" diff --git a/backend/tests/test_database_config.py b/backend/tests/test_database_config.py new file mode 100644 index 00000000..a993c4ed --- /dev/null +++ b/backend/tests/test_database_config.py @@ -0,0 +1,374 @@ +"""Unit tests for database configuration and session management.""" + +import pytest +import os +from unittest.mock import patch, Mock +from sqlalchemy.exc import OperationalError +from src.database import config +from src.database.config import ( + get_database_url, + is_database_available, + init_database, + get_db, +) + + +class TestGetDatabaseUrl: + """Test suite for database URL construction.""" + + def test_get_database_url_all_vars_set(self): + """Test database URL construction with all environment variables set.""" + with patch.dict( + os.environ, + { + "POSTGRES_USER": "testuser", + "POSTGRES_PASSWORD": "testpass", + "POSTGRES_HOST": "localhost", + "POSTGRES_PORT": "5432", + "POSTGRES_DB": "testdb", + }, + ): + url = get_database_url() + + assert url == "postgresql://testuser:testpass@localhost:5432/testdb" + + def test_get_database_url_different_host(self): + """Test database URL with different host.""" + with patch.dict( + os.environ, + { + "POSTGRES_USER": "user", + "POSTGRES_PASSWORD": "pass", + "POSTGRES_HOST": "db.example.com", + "POSTGRES_PORT": "5433", + "POSTGRES_DB": "mydb", + }, + ): + url = get_database_url() + + assert url == "postgresql://user:pass@db.example.com:5433/mydb" + + +class TestIsDatabaseAvailable: + """Test suite for database availability check.""" + + def test_is_database_available_engine_none(self): + """Test is_database_available returns False when engine is None.""" + with patch.object(config, "engine", None): + result = is_database_available() + + assert result is False + + def test_is_database_available_connection_success(self): + """Test is_database_available returns True when connection succeeds.""" + mock_engine = Mock() + mock_conn = Mock() + mock_engine.connect.return_value.__enter__ = Mock(return_value=mock_conn) + mock_engine.connect.return_value.__exit__ = Mock(return_value=False) + + with patch.object(config, "engine", mock_engine): + result = is_database_available() + + assert result is True + mock_conn.execute.assert_called_once() + + def test_is_database_available_connection_fails(self): + """Test is_database_available returns False on OperationalError.""" + mock_engine = Mock() + mock_engine.connect.side_effect = OperationalError("", "", "") + + with patch.object(config, "engine", mock_engine): + result = is_database_available() + + assert result is False + + +class TestInitDatabase: + """Test suite for database initialization.""" + + def setUp(self): + """Reset global state before each test.""" + config.engine = None + config.SessionLocal = None + config._db_initialized = False + + def test_init_database_already_initialized(self): + """Test init_database returns True when already initialized and available.""" + self.setUp() + mock_engine = Mock() + + with patch.object(config, "engine", mock_engine), patch.object( + config, "SessionLocal", Mock() + ), patch.object(config, "_db_initialized", True), patch( + "src.database.config.is_database_available", return_value=True + ): + result = init_database() + + assert result is True + + def test_init_database_creates_engine(self): + """Test init_database creates engine when None.""" + self.setUp() + + with patch.dict( + os.environ, + { + "POSTGRES_USER": "user", + "POSTGRES_PASSWORD": "pass", + "POSTGRES_HOST": "localhost", + "POSTGRES_PORT": "5432", + "POSTGRES_DB": "testdb", + }, + ), patch("src.database.config.create_engine") as mock_create_engine, patch( + "src.database.config.is_database_available", return_value=True + ), patch("src.database.config.inspect") as mock_inspect: + mock_engine = Mock() + mock_create_engine.return_value = mock_engine + mock_inspector = Mock() + mock_inspector.get_table_names.return_value = ["conversations", "messages"] + mock_inspect.return_value = mock_inspector + + result = init_database() + + assert result is True + mock_create_engine.assert_called_once() + # Verify pool configuration + call_kwargs = mock_create_engine.call_args[1] + assert call_kwargs["pool_size"] == 10 + assert call_kwargs["max_overflow"] == 20 + assert call_kwargs["pool_pre_ping"] is True + assert call_kwargs["echo"] is False + assert call_kwargs["connect_args"]["connect_timeout"] == 5 + + def test_init_database_creates_tables_when_not_exist(self): + """Test init_database creates tables when they don't exist.""" + self.setUp() + + with patch.dict( + os.environ, + { + "POSTGRES_USER": "user", + "POSTGRES_PASSWORD": "pass", + "POSTGRES_HOST": "localhost", + "POSTGRES_PORT": "5432", + "POSTGRES_DB": "testdb", + }, + ), patch("src.database.config.create_engine") as mock_create_engine, patch( + "src.database.config.is_database_available", return_value=True + ), patch("src.database.config.inspect") as mock_inspect, patch( + "src.database.config.Base" + ) as mock_base: + mock_engine = Mock() + mock_create_engine.return_value = mock_engine + mock_inspector = Mock() + mock_inspector.get_table_names.return_value = [] + mock_inspect.return_value = mock_inspector + + result = init_database() + + assert result is True + mock_base.metadata.create_all.assert_called_once_with(bind=mock_engine) + + def test_init_database_skips_table_creation_when_exist(self): + """Test init_database skips table creation when they already exist.""" + self.setUp() + + with patch.dict( + os.environ, + { + "POSTGRES_USER": "user", + "POSTGRES_PASSWORD": "pass", + "POSTGRES_HOST": "localhost", + "POSTGRES_PORT": "5432", + "POSTGRES_DB": "testdb", + }, + ), patch("src.database.config.create_engine") as mock_create_engine, patch( + "src.database.config.is_database_available", return_value=True + ), patch("src.database.config.inspect") as mock_inspect, patch( + "src.database.config.Base" + ) as mock_base: + mock_engine = Mock() + mock_create_engine.return_value = mock_engine + mock_inspector = Mock() + mock_inspector.get_table_names.return_value = ["conversations", "messages"] + mock_inspect.return_value = mock_inspector + + result = init_database() + + assert result is True + mock_base.metadata.create_all.assert_not_called() + + def test_init_database_returns_false_when_unavailable(self): + """Test init_database returns False when database is unavailable.""" + self.setUp() + + with patch.dict( + os.environ, + { + "POSTGRES_USER": "user", + "POSTGRES_PASSWORD": "pass", + "POSTGRES_HOST": "localhost", + "POSTGRES_PORT": "5432", + "POSTGRES_DB": "testdb", + }, + ), patch("src.database.config.create_engine") as mock_create_engine, patch( + "src.database.config.is_database_available", return_value=False + ): + mock_engine = Mock() + mock_create_engine.return_value = mock_engine + + result = init_database() + + assert result is False + assert config._db_initialized is False + + def test_init_database_handles_operational_error(self): + """Test init_database handles OperationalError gracefully.""" + self.setUp() + + with patch.dict( + os.environ, + { + "POSTGRES_USER": "user", + "POSTGRES_PASSWORD": "pass", + "POSTGRES_HOST": "localhost", + "POSTGRES_PORT": "5432", + "POSTGRES_DB": "testdb", + }, + ), patch( + "src.database.config.create_engine", + side_effect=OperationalError("", "", ""), + ): + result = init_database() + + assert result is False + assert config._db_initialized is False + + def test_init_database_handles_generic_exception(self): + """Test init_database handles generic exceptions gracefully.""" + self.setUp() + + with patch.dict( + os.environ, + { + "POSTGRES_USER": "user", + "POSTGRES_PASSWORD": "pass", + "POSTGRES_HOST": "localhost", + "POSTGRES_PORT": "5432", + "POSTGRES_DB": "testdb", + }, + ), patch( + "src.database.config.create_engine", + side_effect=Exception("Unexpected error"), + ): + result = init_database() + + assert result is False + assert config._db_initialized is False + + +class TestGetDb: + """Test suite for database session generator.""" + + def setUp(self): + """Reset global state before each test.""" + config.engine = None + config.SessionLocal = None + config._db_initialized = False + + def test_get_db_initializes_if_not_initialized(self): + """Test get_db calls init_database if not initialized.""" + self.setUp() + + with patch( + "src.database.config.init_database", return_value=True + ) as mock_init, patch.object( + config, "SessionLocal", Mock() + ) as mock_session_local: + mock_session = Mock() + mock_session_local.return_value = mock_session + + # Use generator + gen = get_db() + session = next(gen) + + mock_init.assert_called_once() + assert session == mock_session + + # Clean up generator + try: + next(gen) + except StopIteration: + pass + + def test_get_db_raises_when_session_local_none(self): + """Test get_db raises RuntimeError when SessionLocal is None.""" + self.setUp() + + with patch( + "src.database.config.init_database", return_value=False + ), patch.object(config, "SessionLocal", None), patch.object( + config, "_db_initialized", False + ): + with pytest.raises( + RuntimeError, match="Database session factory not initialized" + ): + gen = get_db() + next(gen) + + def test_get_db_closes_session(self): + """Test get_db properly closes session in finally block.""" + self.setUp() + + mock_session = Mock() + mock_session_local = Mock(return_value=mock_session) + + with patch( + "src.database.config.init_database", return_value=True + ), patch.object(config, "SessionLocal", mock_session_local), patch.object( + config, "_db_initialized", True + ): + # Use generator + gen = get_db() + session = next(gen) + + assert session == mock_session + + # Trigger finally block by completing iteration + try: + next(gen) + except StopIteration: + pass + + # Verify session was closed + mock_session.close.assert_called_once() + + def test_get_db_closes_session_on_exception(self): + """Test get_db closes session even when exception occurs.""" + self.setUp() + + mock_session = Mock() + mock_session_local = Mock(return_value=mock_session) + + with patch( + "src.database.config.init_database", return_value=True + ), patch.object(config, "SessionLocal", mock_session_local), patch.object( + config, "_db_initialized", True + ): + gen = get_db() + _session = next(gen) + + # Simulate exception in code using the session + try: + raise ValueError("Test exception") + except ValueError: + pass + + # Complete generator + try: + next(gen) + except StopIteration: + pass + + # Session should still be closed + mock_session.close.assert_called_once() diff --git a/backend/tests/test_database_crud.py b/backend/tests/test_database_crud.py new file mode 100644 index 00000000..5f59f789 --- /dev/null +++ b/backend/tests/test_database_crud.py @@ -0,0 +1,402 @@ +"""Unit tests for database CRUD operations.""" + +import pytest +from uuid import uuid4, UUID +from sqlalchemy import create_engine +from sqlalchemy.orm import sessionmaker, Session +from src.database.models import Base +from src.database import crud + + +@pytest.fixture +def db_session(): + """Create an in-memory SQLite database for testing.""" + engine = create_engine("sqlite:///:memory:") + Base.metadata.create_all(engine) + SessionLocal = sessionmaker(bind=engine) + session = SessionLocal() + yield session + session.close() + + +class TestConversationCRUD: + """Test suite for Conversation CRUD operations.""" + + def test_create_conversation_with_uuid(self, db_session: Session): + """Test creating conversation with specific UUID.""" + test_uuid = uuid4() + conv = crud.create_conversation( + db_session, conversation_uuid=test_uuid, title="Test Conversation" + ) + + assert conv.uuid == test_uuid + assert conv.title == "Test Conversation" + assert conv.created_at is not None + assert conv.updated_at is not None + + def test_create_conversation_generates_uuid(self, db_session: Session): + """Test auto-generation of UUID for new conversation.""" + conv = crud.create_conversation(db_session, title="Auto UUID") + + assert conv.uuid is not None + assert isinstance(conv.uuid, UUID) + assert conv.title == "Auto UUID" + + def test_create_conversation_without_title(self, db_session: Session): + """Test creating conversation without title.""" + conv = crud.create_conversation(db_session) + + assert conv.uuid is not None + assert conv.title is None + + def test_get_conversation_exists(self, db_session: Session): + """Test retrieving existing conversation.""" + conv = crud.create_conversation(db_session, title="Test") + + retrieved = crud.get_conversation(db_session, conv.uuid) + + assert retrieved is not None + assert retrieved.uuid == conv.uuid + assert retrieved.title == "Test" + + def test_get_conversation_not_exists(self, db_session: Session): + """Test retrieving non-existent conversation returns None.""" + fake_uuid = uuid4() + + result = crud.get_conversation(db_session, fake_uuid) + + assert result is None + + def test_get_or_create_existing_conversation(self, db_session: Session): + """Test get_or_create returns existing conversation.""" + conv = crud.create_conversation(db_session, title="Original") + + result = crud.get_or_create_conversation( + db_session, conversation_uuid=conv.uuid, title="Modified" + ) + + assert result.uuid == conv.uuid + assert result.title == "Original" # Should not update existing + + def test_get_or_create_new_conversation(self, db_session: Session): + """Test get_or_create creates new conversation if not exists.""" + test_uuid = uuid4() + + result = crud.get_or_create_conversation( + db_session, conversation_uuid=test_uuid, title="New" + ) + + assert result.uuid == test_uuid + assert result.title == "New" + + def test_get_or_create_without_uuid(self, db_session: Session): + """Test get_or_create without UUID creates new conversation.""" + result = crud.get_or_create_conversation(db_session, title="Auto") + + assert result.uuid is not None + assert result.title == "Auto" + + def test_get_all_conversations_empty(self, db_session: Session): + """Test get_all_conversations returns empty list when no conversations.""" + conversations = crud.get_all_conversations(db_session) + + assert conversations == [] + + def test_get_all_conversations_ordered(self, db_session: Session): + """Test get_all_conversations returns conversations ordered by updated_at desc.""" + conv1 = crud.create_conversation(db_session, title="First") + conv2 = crud.create_conversation(db_session, title="Second") + conv3 = crud.create_conversation(db_session, title="Third") + + conversations = crud.get_all_conversations(db_session) + + assert len(conversations) == 3 + # Most recently updated should be first + assert conversations[0].uuid == conv3.uuid + assert conversations[1].uuid == conv2.uuid + assert conversations[2].uuid == conv1.uuid + + def test_get_all_conversations_pagination(self, db_session: Session): + """Test get_all_conversations pagination with skip and limit.""" + for i in range(10): + crud.create_conversation(db_session, title=f"Conv {i}") + + # Get first 5 + page1 = crud.get_all_conversations(db_session, skip=0, limit=5) + assert len(page1) == 5 + + # Get next 5 + page2 = crud.get_all_conversations(db_session, skip=5, limit=5) + assert len(page2) == 5 + + # Ensure different conversations + assert page1[0].uuid != page2[0].uuid + + def test_update_conversation_title(self, db_session: Session): + """Test updating conversation title.""" + conv = crud.create_conversation(db_session, title="Original") + + updated = crud.update_conversation_title(db_session, conv.uuid, "Updated Title") + + assert updated is not None + assert updated.title == "Updated Title" + assert updated.uuid == conv.uuid + + def test_update_conversation_title_not_exists(self, db_session: Session): + """Test updating non-existent conversation returns None.""" + fake_uuid = uuid4() + + result = crud.update_conversation_title(db_session, fake_uuid, "New Title") + + assert result is None + + def test_delete_conversation_exists(self, db_session: Session): + """Test deleting existing conversation.""" + conv = crud.create_conversation(db_session, title="To Delete") + + result = crud.delete_conversation(db_session, conv.uuid) + + assert result is True + assert crud.get_conversation(db_session, conv.uuid) is None + + def test_delete_conversation_not_exists(self, db_session: Session): + """Test deleting non-existent conversation returns False.""" + fake_uuid = uuid4() + + result = crud.delete_conversation(db_session, fake_uuid) + + assert result is False + + def test_delete_conversation_cascades_messages(self, db_session: Session): + """Test cascade deletion of messages when conversation is deleted.""" + conv = crud.create_conversation(db_session, title="Test") + msg1 = crud.create_message(db_session, conv.uuid, "user", "Hello") + msg2 = crud.create_message(db_session, conv.uuid, "assistant", "Hi") + + crud.delete_conversation(db_session, conv.uuid) + + # Verify messages are deleted + messages = crud.get_conversation_messages(db_session, conv.uuid) + assert len(messages) == 0 + assert crud.get_message(db_session, msg1.uuid) is None + assert crud.get_message(db_session, msg2.uuid) is None + + +class TestMessageCRUD: + """Test suite for Message CRUD operations.""" + + def test_create_message_basic(self, db_session: Session): + """Test creating basic message.""" + conv = crud.create_conversation(db_session, title="Test") + + msg = crud.create_message(db_session, conv.uuid, "user", "Test message") + + assert msg.uuid is not None + assert msg.conversation_uuid == conv.uuid + assert msg.role == "user" + assert msg.content == "Test message" + assert msg.context_sources is None + assert msg.tools is None + assert msg.created_at is not None + + def test_create_message_with_context_sources(self, db_session: Session): + """Test creating message with context sources.""" + conv = crud.create_conversation(db_session, title="Test") + context = { + "sources": [{"source": "https://example.com", "context": "Example context"}] + } + + msg = crud.create_message( + db_session, + conv.uuid, + "assistant", + "Response", + context_sources=context, + ) + + assert msg.context_sources == context + + def test_create_message_with_tools(self, db_session: Session): + """Test creating message with tools.""" + conv = crud.create_conversation(db_session, title="Test") + tools = ["retrieve_general", "retrieve_install"] + + msg = crud.create_message( + db_session, + conv.uuid, + "assistant", + "Response", + tools=tools, + ) + + assert msg.tools == tools + + def test_get_message_exists(self, db_session: Session): + """Test retrieving existing message.""" + conv = crud.create_conversation(db_session, title="Test") + msg = crud.create_message(db_session, conv.uuid, "user", "Hello") + + retrieved = crud.get_message(db_session, msg.uuid) + + assert retrieved is not None + assert retrieved.uuid == msg.uuid + assert retrieved.content == "Hello" + + def test_get_message_not_exists(self, db_session: Session): + """Test retrieving non-existent message returns None.""" + fake_uuid = uuid4() + + result = crud.get_message(db_session, fake_uuid) + + assert result is None + + def test_get_conversation_messages_ordered(self, db_session: Session): + """Test get_conversation_messages returns messages ordered by created_at.""" + conv = crud.create_conversation(db_session, title="Test") + msg1 = crud.create_message(db_session, conv.uuid, "user", "First") + msg2 = crud.create_message(db_session, conv.uuid, "assistant", "Second") + msg3 = crud.create_message(db_session, conv.uuid, "user", "Third") + + messages = crud.get_conversation_messages(db_session, conv.uuid) + + assert len(messages) == 3 + assert messages[0].uuid == msg1.uuid + assert messages[1].uuid == msg2.uuid + assert messages[2].uuid == msg3.uuid + + def test_get_conversation_messages_pagination(self, db_session: Session): + """Test get_conversation_messages pagination.""" + conv = crud.create_conversation(db_session, title="Test") + for i in range(10): + crud.create_message(db_session, conv.uuid, "user", f"Message {i}") + + # Get first 5 + page1 = crud.get_conversation_messages(db_session, conv.uuid, skip=0, limit=5) + assert len(page1) == 5 + + # Get next 5 + page2 = crud.get_conversation_messages(db_session, conv.uuid, skip=5, limit=5) + assert len(page2) == 5 + + def test_get_conversation_messages_empty(self, db_session: Session): + """Test get_conversation_messages returns empty list for conversation with no messages.""" + conv = crud.create_conversation(db_session, title="Test") + + messages = crud.get_conversation_messages(db_session, conv.uuid) + + assert messages == [] + + def test_delete_message_exists(self, db_session: Session): + """Test deleting existing message.""" + conv = crud.create_conversation(db_session, title="Test") + msg = crud.create_message(db_session, conv.uuid, "user", "To delete") + + result = crud.delete_message(db_session, msg.uuid) + + assert result is True + assert crud.get_message(db_session, msg.uuid) is None + + def test_delete_message_not_exists(self, db_session: Session): + """Test deleting non-existent message returns False.""" + fake_uuid = uuid4() + + result = crud.delete_message(db_session, fake_uuid) + + assert result is False + + +class TestConversationHistory: + """Test suite for conversation history formatting.""" + + def test_get_conversation_history_empty(self, db_session: Session): + """Test get_conversation_history with no messages.""" + conv = crud.create_conversation(db_session, title="Test") + + history = crud.get_conversation_history(db_session, conv.uuid) + + assert history == [] + + def test_get_conversation_history_complete_pairs(self, db_session: Session): + """Test get_conversation_history with complete user-AI pairs.""" + conv = crud.create_conversation(db_session, title="Test") + crud.create_message(db_session, conv.uuid, "user", "Hello") + crud.create_message(db_session, conv.uuid, "assistant", "Hi there") + crud.create_message(db_session, conv.uuid, "user", "How are you?") + crud.create_message(db_session, conv.uuid, "assistant", "I'm good") + + history = crud.get_conversation_history(db_session, conv.uuid) + + assert len(history) == 2 + assert history[0] == {"User": "Hello", "AI": "Hi there"} + assert history[1] == {"User": "How are you?", "AI": "I'm good"} + + def test_get_conversation_history_incomplete_pair_trailing_user( + self, db_session: Session + ): + """Test get_conversation_history handles trailing user message without AI response.""" + conv = crud.create_conversation(db_session, title="Test") + crud.create_message(db_session, conv.uuid, "user", "Hello") + crud.create_message(db_session, conv.uuid, "assistant", "Hi") + crud.create_message(db_session, conv.uuid, "user", "Question without answer") + + history = crud.get_conversation_history(db_session, conv.uuid) + + assert len(history) == 2 + assert history[0] == {"User": "Hello", "AI": "Hi"} + assert history[1] == {"User": "Question without answer"} + + def test_get_conversation_history_multiple_consecutive_users( + self, db_session: Session + ): + """Test get_conversation_history handles multiple consecutive user messages.""" + conv = crud.create_conversation(db_session, title="Test") + crud.create_message(db_session, conv.uuid, "user", "First") + crud.create_message(db_session, conv.uuid, "user", "Second") + crud.create_message(db_session, conv.uuid, "assistant", "Response") + + history = crud.get_conversation_history(db_session, conv.uuid) + + # First user message should be saved as incomplete pair, + # then second user message pairs with AI response + assert len(history) == 2 + assert history[0] == {"User": "First"} + assert history[1] == {"User": "Second", "AI": "Response"} + + def test_get_conversation_history_assistant_without_user(self, db_session: Session): + """Test get_conversation_history handles assistant message without preceding user message.""" + conv = crud.create_conversation(db_session, title="Test") + crud.create_message(db_session, conv.uuid, "assistant", "Unpaired AI message") + crud.create_message(db_session, conv.uuid, "user", "Hello") + crud.create_message(db_session, conv.uuid, "assistant", "Hi") + + history = crud.get_conversation_history(db_session, conv.uuid) + + # First AI message should be ignored (no current_pair) + assert len(history) == 1 + assert history[0] == {"User": "Hello", "AI": "Hi"} + + def test_get_conversation_history_only_user_messages(self, db_session: Session): + """Test get_conversation_history with only user messages.""" + conv = crud.create_conversation(db_session, title="Test") + crud.create_message(db_session, conv.uuid, "user", "Message 1") + crud.create_message(db_session, conv.uuid, "user", "Message 2") + + history = crud.get_conversation_history(db_session, conv.uuid) + + # Each user message creates incomplete pair + assert len(history) == 2 + assert history[0] == {"User": "Message 1"} + assert history[1] == {"User": "Message 2"} + + def test_get_conversation_history_only_assistant_messages( + self, db_session: Session + ): + """Test get_conversation_history with only assistant messages.""" + conv = crud.create_conversation(db_session, title="Test") + crud.create_message(db_session, conv.uuid, "assistant", "Message 1") + crud.create_message(db_session, conv.uuid, "assistant", "Message 2") + + history = crud.get_conversation_history(db_session, conv.uuid) + + # Assistant messages without user messages should be ignored + assert len(history) == 0 diff --git a/backend/tests/test_orfs_rag.py b/backend/tests/test_orfs_rag.py index 49cdd77b..028eff76 100644 --- a/backend/tests/test_orfs_rag.py +++ b/backend/tests/test_orfs_rag.py @@ -3,7 +3,9 @@ import sys # Mock HybridRetrieverChain before importing orfs_rag to prevent model downloads during import -with patch("src.chains.hybrid_retriever_chain.HybridRetrieverChain") as mock_chain_class: +with patch( + "src.chains.hybrid_retriever_chain.HybridRetrieverChain" +) as mock_chain_class: mock_instance = MagicMock() mock_instance.create_hybrid_retriever = MagicMock() mock_instance.retriever = MagicMock() @@ -11,6 +13,7 @@ # Now it's safe to import these modules from src.openroad_mcp.server.orfs.orfs_tools import ORFS + # Import orfs_rag with mocked 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pgadmin_data:/var/lib/pgadmin + +volumes: + pgadmin_data: + driver: local diff --git a/docker-compose.yml b/docker-compose.yml index 2f6e7dc1..cb34eb7a 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -1,10 +1,39 @@ services: + postgres: + image: postgres:16-alpine + container_name: "postgres" + environment: + POSTGRES_USER: ${POSTGRES_USER:-orassistant} + POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-password} + POSTGRES_DB: ${POSTGRES_DB:-orassistant_db} + ports: + - "${POSTGRES_PORT:-5432}:5432" + volumes: + - postgres_data:/var/lib/postgresql/data + networks: + - orassistant-network + healthcheck: + test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-orassistant} -d ${POSTGRES_DB:-orassistant_db}"] + interval: 10s + timeout: 5s + retries: 5 + backend: build: context: ./backend container_name: "backend" + environment: + POSTGRES_HOST: postgres + POSTGRES_PORT: 5432 + POSTGRES_USER: ${POSTGRES_USER:-orassistant} + POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-password} + POSTGRES_DB: ${POSTGRES_DB:-orassistant_db} + MCP_SERVER_URL: ${MCP_SERVER_URL:-http://host.docker.internal:3001/mcp/} ports: - "8000:8000" + depends_on: + postgres: + condition: service_healthy networks: - orassistant-network healthcheck: @@ -29,3 +58,7 @@ services: networks: orassistant-network: driver: bridge + +volumes: + postgres_data: + driver: local