From 915446fdc07f3df84aa9e7e40971a61870d3de00 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Fri, 3 Oct 2025 03:51:24 +0000 Subject: [PATCH 01/10] Initial plan From d172bff3b6f0e9b5b5f29d379a623936b60577c6 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Fri, 3 Oct 2025 03:57:31 +0000 Subject: [PATCH 02/10] Add chatbot page with modular structure Co-authored-by: lambdakris <15176003+lambdakris@users.noreply.github.com> --- frontend/main.py | 3 +- frontend/pages/chat.py | 104 +++++++++++++++++++++++++++++++++++++++++ 2 files changed, 106 insertions(+), 1 deletion(-) create mode 100644 frontend/pages/chat.py diff --git a/frontend/main.py b/frontend/main.py index c9010d6..3fc4b2b 100644 --- a/frontend/main.py +++ b/frontend/main.py @@ -9,8 +9,9 @@ def main(): home_page = st.Page("pages/home.py", title="Home", icon="🏠") about_page = st.Page("pages/about.py", title="About", icon="ℹī¸") todos_page = st.Page("pages/todos.py", title="Todos", icon="📋") + chat_page = st.Page("pages/chat.py", title="Chat", icon="đŸ’Ŧ") - pg = st.navigation([home_page, about_page, todos_page], position="top") + pg = st.navigation([home_page, about_page, todos_page, chat_page], position="top") pg.run() if __name__ == "__main__": diff --git a/frontend/pages/chat.py b/frontend/pages/chat.py new file mode 100644 index 0000000..d91a8e9 --- /dev/null +++ b/frontend/pages/chat.py @@ -0,0 +1,104 @@ +import streamlit as st +import random +import time + +# Initialize chat history in session state +def initialize_chat_history(): + """Initialize chat history if it doesn't exist""" + if "messages" not in st.session_state: + st.session_state.messages = [] + +def display_chat_messages(): + """Display all chat messages from history""" + for message in st.session_state.messages: + with st.chat_message(message["role"]): + st.markdown(message["content"]) + +def get_assistant_response(user_message): + """ + Stub function to simulate LLM response. + In a real implementation, this would call an actual LLM API. + """ + # Simulate processing delay + time.sleep(0.5) + + # Stubbed responses based on simple keyword matching + user_lower = user_message.lower() + + if "hello" in user_lower or "hi" in user_lower: + responses = [ + "Hello! How can I help you today?", + "Hi there! What can I do for you?", + "Hey! Nice to meet you. What's on your mind?" + ] + elif "how are you" in user_lower: + responses = [ + "I'm doing great, thank you for asking! How about you?", + "I'm functioning well! How can I assist you today?" + ] + elif "thank" in user_lower: + responses = [ + "You're welcome! Is there anything else I can help with?", + "Happy to help! Let me know if you need anything else." + ] + elif "bye" in user_lower or "goodbye" in user_lower: + responses = [ + "Goodbye! Have a great day!", + "See you later! Feel free to come back anytime." + ] + elif "help" in user_lower: + responses = [ + "I'm here to help! You can ask me questions about the Proto Stack application, or just chat with me.", + "I can help with various topics. What would you like to know?" + ] + else: + responses = [ + f"That's an interesting point about '{user_message}'. Tell me more!", + f"I understand you mentioned '{user_message}'. Can you elaborate?", + "That's a great question! In a full implementation, I'd provide a detailed response.", + "Interesting! I'd love to help with that. This is a demo chatbot, so my responses are limited.", + ] + + return random.choice(responses) + +def handle_user_input(): + """Handle new user input from chat input widget""" + if prompt := st.chat_input("What would you like to talk about?"): + # Add user message to chat history + st.session_state.messages.append({"role": "user", "content": prompt}) + + # Display user message + with st.chat_message("user"): + st.markdown(prompt) + + # Generate and display assistant response + with st.chat_message("assistant"): + with st.spinner("Thinking..."): + response = get_assistant_response(prompt) + st.markdown(response) + + # Add assistant response to chat history + st.session_state.messages.append({"role": "assistant", "content": response}) + +def show(): + """Display the Chat page""" + st.title("đŸ’Ŧ Chatbot") + st.markdown("Have a conversation with our AI assistant!") + + # Add a button to clear chat history + if st.button("🗑ī¸ Clear Chat History"): + st.session_state.messages = [] + st.rerun() + + st.divider() + + # Initialize chat history + initialize_chat_history() + + # Display existing messages + display_chat_messages() + + # Handle new user input + handle_user_input() + +show() From 4f7f154102e5c567d508d2b0078d6be868d46e17 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Fri, 3 Oct 2025 05:06:56 +0000 Subject: [PATCH 03/10] Move chatbot logic to backend API endpoint Co-authored-by: lambdakris <15176003+lambdakris@users.noreply.github.com> --- backend/main.py | 54 ++++++++++++++++++++++++++++++++++++ frontend/pages/chat.py | 62 ++++++++++++------------------------------ 2 files changed, 71 insertions(+), 45 deletions(-) diff --git a/backend/main.py b/backend/main.py index 2865a37..e57585a 100644 --- a/backend/main.py +++ b/backend/main.py @@ -6,6 +6,7 @@ from pydantic import BaseModel from typing import List import os +import random from dotenv import load_dotenv load_dotenv() @@ -45,6 +46,13 @@ class Todo(BaseModel): class Config: orm_mode = True +# Chat Models +class ChatMessage(BaseModel): + message: str + +class ChatResponse(BaseModel): + response: str + # Note: Tables are now managed by Liquibase migrations # Base.metadata.create_all(bind=engine) - Removed in favor of Liquibase @@ -110,6 +118,52 @@ def delete_todo(todo_id: int, db: Session = Depends(get_db)): db.commit() return {"message": "Todo deleted successfully"} +@app.post("/chat", response_model=ChatResponse) +def chat(message: ChatMessage): + """ + Chat endpoint that provides AI assistant responses. + This is a stubbed implementation using keyword matching. + In a real implementation, this would call an actual LLM API. + """ + user_message = message.message + user_lower = user_message.lower() + + if "hello" in user_lower or "hi" in user_lower: + responses = [ + "Hello! How can I help you today?", + "Hi there! What can I do for you?", + "Hey! Nice to meet you. What's on your mind?" + ] + elif "how are you" in user_lower: + responses = [ + "I'm doing great, thank you for asking! How about you?", + "I'm functioning well! How can I assist you today?" + ] + elif "thank" in user_lower: + responses = [ + "You're welcome! Is there anything else I can help with?", + "Happy to help! Let me know if you need anything else." + ] + elif "bye" in user_lower or "goodbye" in user_lower: + responses = [ + "Goodbye! Have a great day!", + "See you later! Feel free to come back anytime." + ] + elif "help" in user_lower: + responses = [ + "I'm here to help! You can ask me questions about the Proto Stack application, or just chat with me.", + "I can help with various topics. What would you like to know?" + ] + else: + responses = [ + f"That's an interesting point about '{user_message}'. Tell me more!", + f"I understand you mentioned '{user_message}'. Can you elaborate?", + "That's a great question! In a full implementation, I'd provide a detailed response.", + "Interesting! I'd love to help with that. This is a demo chatbot, so my responses are limited.", + ] + + return ChatResponse(response=random.choice(responses)) + if __name__ == "__main__": import uvicorn uvicorn.run(app, host="0.0.0.0", port=8000, debug=True) \ No newline at end of file diff --git a/frontend/pages/chat.py b/frontend/pages/chat.py index d91a8e9..0660a13 100644 --- a/frontend/pages/chat.py +++ b/frontend/pages/chat.py @@ -1,6 +1,9 @@ import streamlit as st -import random -import time +import requests +import os + +# Backend API configuration +API_BASE_URL = os.getenv("API_BASE_URL", "http://backend:8000") # Initialize chat history in session state def initialize_chat_history(): @@ -16,50 +19,19 @@ def display_chat_messages(): def get_assistant_response(user_message): """ - Stub function to simulate LLM response. - In a real implementation, this would call an actual LLM API. + Call the backend API to get AI assistant response. """ - # Simulate processing delay - time.sleep(0.5) - - # Stubbed responses based on simple keyword matching - user_lower = user_message.lower() - - if "hello" in user_lower or "hi" in user_lower: - responses = [ - "Hello! How can I help you today?", - "Hi there! What can I do for you?", - "Hey! Nice to meet you. What's on your mind?" - ] - elif "how are you" in user_lower: - responses = [ - "I'm doing great, thank you for asking! How about you?", - "I'm functioning well! How can I assist you today?" - ] - elif "thank" in user_lower: - responses = [ - "You're welcome! Is there anything else I can help with?", - "Happy to help! Let me know if you need anything else." - ] - elif "bye" in user_lower or "goodbye" in user_lower: - responses = [ - "Goodbye! Have a great day!", - "See you later! Feel free to come back anytime." - ] - elif "help" in user_lower: - responses = [ - "I'm here to help! You can ask me questions about the Proto Stack application, or just chat with me.", - "I can help with various topics. What would you like to know?" - ] - else: - responses = [ - f"That's an interesting point about '{user_message}'. Tell me more!", - f"I understand you mentioned '{user_message}'. Can you elaborate?", - "That's a great question! In a full implementation, I'd provide a detailed response.", - "Interesting! I'd love to help with that. This is a demo chatbot, so my responses are limited.", - ] - - return random.choice(responses) + try: + payload = {"message": user_message} + response = requests.post(f"{API_BASE_URL}/chat", json=payload) + if response.status_code == 200: + return response.json()["response"] + else: + st.error(f"Failed to get response: {response.status_code}") + return "I apologize, but I'm having trouble responding right now. Please try again." + except requests.exceptions.RequestException as e: + st.error(f"Connection error: {e}") + return "I apologize, but I'm having trouble connecting to the backend. Please try again." def handle_user_input(): """Handle new user input from chat input widget""" From 38f0ca12b2f18dc3f986e1b74d20e1e4f240c30e Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Fri, 3 Oct 2025 05:46:00 +0000 Subject: [PATCH 04/10] Refactor chat to dedicated router with LangGraph and OpenAI Co-authored-by: lambdakris <15176003+lambdakris@users.noreply.github.com> --- .env | 4 +++ backend/main.py | 58 +++------------------------------ backend/pyproject.toml | 2 ++ backend/routers/__init__.py | 1 + backend/routers/chat.py | 64 +++++++++++++++++++++++++++++++++++++ 5 files changed, 75 insertions(+), 54 deletions(-) create mode 100644 backend/routers/__init__.py create mode 100644 backend/routers/chat.py diff --git a/.env b/.env index 88001ba..20f1316 100644 --- a/.env +++ b/.env @@ -1,5 +1,9 @@ # Backend Environment Variables DATABASE_URL=postgresql://postgres:password@postgres:5432/todoapp +# OpenAI API Key for chatbot (required) +# Get your API key from https://platform.openai.com/api-keys +OPENAI_API_KEY=your_openai_api_key_here + # Frontend Environment Variables API_BASE_URL=http://backend:8000 \ No newline at end of file diff --git a/backend/main.py b/backend/main.py index e57585a..45c71ce 100644 --- a/backend/main.py +++ b/backend/main.py @@ -6,8 +6,8 @@ from pydantic import BaseModel from typing import List import os -import random from dotenv import load_dotenv +from routers import chat load_dotenv() @@ -46,13 +46,6 @@ class Todo(BaseModel): class Config: orm_mode = True -# Chat Models -class ChatMessage(BaseModel): - message: str - -class ChatResponse(BaseModel): - response: str - # Note: Tables are now managed by Liquibase migrations # Base.metadata.create_all(bind=engine) - Removed in favor of Liquibase @@ -68,6 +61,9 @@ class ChatResponse(BaseModel): allow_headers=["*"], ) +# Include routers +app.include_router(chat.router) + # Dependency to get DB session def get_db(): db = SessionLocal() @@ -118,52 +114,6 @@ def delete_todo(todo_id: int, db: Session = Depends(get_db)): db.commit() return {"message": "Todo deleted successfully"} -@app.post("/chat", response_model=ChatResponse) -def chat(message: ChatMessage): - """ - Chat endpoint that provides AI assistant responses. - This is a stubbed implementation using keyword matching. - In a real implementation, this would call an actual LLM API. - """ - user_message = message.message - user_lower = user_message.lower() - - if "hello" in user_lower or "hi" in user_lower: - responses = [ - "Hello! How can I help you today?", - "Hi there! What can I do for you?", - "Hey! Nice to meet you. What's on your mind?" - ] - elif "how are you" in user_lower: - responses = [ - "I'm doing great, thank you for asking! How about you?", - "I'm functioning well! How can I assist you today?" - ] - elif "thank" in user_lower: - responses = [ - "You're welcome! Is there anything else I can help with?", - "Happy to help! Let me know if you need anything else." - ] - elif "bye" in user_lower or "goodbye" in user_lower: - responses = [ - "Goodbye! Have a great day!", - "See you later! Feel free to come back anytime." - ] - elif "help" in user_lower: - responses = [ - "I'm here to help! You can ask me questions about the Proto Stack application, or just chat with me.", - "I can help with various topics. What would you like to know?" - ] - else: - responses = [ - f"That's an interesting point about '{user_message}'. Tell me more!", - f"I understand you mentioned '{user_message}'. Can you elaborate?", - "That's a great question! In a full implementation, I'd provide a detailed response.", - "Interesting! I'd love to help with that. This is a demo chatbot, so my responses are limited.", - ] - - return ChatResponse(response=random.choice(responses)) - if __name__ == "__main__": import uvicorn uvicorn.run(app, host="0.0.0.0", port=8000, debug=True) \ No newline at end of file diff --git a/backend/pyproject.toml b/backend/pyproject.toml index e9a7edb..458e009 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -14,4 +14,6 @@ dependencies = [ "debugpy", "sqlalchemy>=2.0.43", "pydantic>=2.11.9", + "langgraph", + "langchain-openai", ] diff --git a/backend/routers/__init__.py b/backend/routers/__init__.py new file mode 100644 index 0000000..22da696 --- /dev/null +++ b/backend/routers/__init__.py @@ -0,0 +1 @@ +# Routers module diff --git a/backend/routers/chat.py b/backend/routers/chat.py new file mode 100644 index 0000000..8ada2aa --- /dev/null +++ b/backend/routers/chat.py @@ -0,0 +1,64 @@ +from fastapi import APIRouter +from pydantic import BaseModel +from typing import Annotated +from typing_extensions import TypedDict +from langgraph.graph import StateGraph, START, END +from langgraph.graph.message import add_messages +from langchain_openai import ChatOpenAI +import os + +# Router setup +router = APIRouter( + prefix="/chat", + tags=["chat"] +) + +# Pydantic Models +class ChatMessage(BaseModel): + message: str + +class ChatResponse(BaseModel): + response: str + +# LangGraph State +class State(TypedDict): + messages: Annotated[list, add_messages] + +# Initialize the LLM +llm = ChatOpenAI( + model="gpt-4o-mini", + api_key=os.getenv("OPENAI_API_KEY"), + temperature=0.7 +) + +# Define the chatbot node +def chatbot(state: State): + """ + Simple chatbot node that calls the LLM with the conversation history. + """ + return {"messages": [llm.invoke(state["messages"])]} + +# Build the LangGraph +graph_builder = StateGraph(State) +graph_builder.add_node("chatbot", chatbot) +graph_builder.add_edge(START, "chatbot") +graph_builder.add_edge("chatbot", END) +graph = graph_builder.compile() + +@router.post("", response_model=ChatResponse) +async def chat(message: ChatMessage): + """ + Chat endpoint that provides AI assistant responses using LangGraph and OpenAI. + + This implements a simple conversational AI that maintains context within a single request. + For multi-turn conversations with persistent state, additional session management would be needed. + """ + # Invoke the graph with the user's message + result = graph.invoke({ + "messages": [("user", message.message)] + }) + + # Extract the assistant's response + assistant_message = result["messages"][-1].content + + return ChatResponse(response=assistant_message) From 265f64559512260cd1e4354f2f93299e4b24051b Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Fri, 3 Oct 2025 05:46:58 +0000 Subject: [PATCH 05/10] Add router documentation with architecture details Co-authored-by: lambdakris <15176003+lambdakris@users.noreply.github.com> --- backend/routers/README.md | 72 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 72 insertions(+) create mode 100644 backend/routers/README.md diff --git a/backend/routers/README.md b/backend/routers/README.md new file mode 100644 index 0000000..f6d4f9f --- /dev/null +++ b/backend/routers/README.md @@ -0,0 +1,72 @@ +# Backend Routers + +This directory contains FastAPI routers that organize the API endpoints by feature. + +## Chat Router (`chat.py`) + +The chat router implements a LangGraph-based conversational AI using OpenAI's GPT models. + +### Architecture + +``` +User Message → FastAPI Router → LangGraph StateGraph → OpenAI LLM → Response +``` + +### LangGraph Flow + +``` +START + ↓ +[chatbot node] + ↓ (invokes OpenAI) + ↓ +END +``` + +### Key Components + +- **State**: Manages conversation messages using LangGraph's message history +- **LLM**: ChatOpenAI with gpt-4o-mini model (configurable) +- **Graph**: Simple linear flow that can be extended with additional nodes + +### Configuration + +Set the `OPENAI_API_KEY` environment variable in the `.env` file: + +```bash +OPENAI_API_KEY=your_openai_api_key_here +``` + +Get your API key from: https://platform.openai.com/api-keys + +### Extending the Chatbot + +The LangGraph architecture makes it easy to add: + +1. **Conversation Memory**: Add a checkpointer to maintain state across requests +2. **RAG (Retrieval Augmented Generation)**: Add a retrieval node before the chatbot +3. **Tool Calling**: Add tool nodes for external API calls +4. **Multi-Agent**: Add specialized agent nodes for different tasks +5. **Guardrails**: Add validation nodes for content filtering + +### Example Extension + +```python +# Add a retrieval node for RAG +def retrieve_context(state: State): + query = state["messages"][-1].content + docs = vector_store.similarity_search(query) + return {"context": docs} + +graph_builder.add_node("retrieve", retrieve_context) +graph_builder.add_edge(START, "retrieve") +graph_builder.add_edge("retrieve", "chatbot") +``` + +## Future Routers + +Additional routers can be added for: +- User management (`users.py`) +- Authentication (`auth.py`) +- Analytics (`analytics.py`) +- Admin operations (`admin.py`) From c0945e5d17831c589213ce0b29fb83ddc92fbb08 Mon Sep 17 00:00:00 2001 From: lambdakris Date: Fri, 3 Oct 2025 00:01:33 -0600 Subject: [PATCH 06/10] Update .gitignore to include environment variable files --- .gitignore | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.gitignore b/.gitignore index f10c966..fc04277 100644 --- a/.gitignore +++ b/.gitignore @@ -19,8 +19,8 @@ venv.bak/ *.sqlite3 # Environment variables -.env.local -.env.production +.env +.env.* # Docker .dockerignore From 32460657ca18b213eb7053ebd72e3bd81c4262b3 Mon Sep 17 00:00:00 2001 From: lambdakris Date: Fri, 3 Oct 2025 00:02:26 -0600 Subject: [PATCH 07/10] Sync lock file --- uv.lock | 638 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 638 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-0600 Subject: [PATCH 08/10] Fix LLM model version and load env vars for backend in Docker Compose --- backend/routers/chat.py | 5 +++-- docker-compose.yml | 2 ++ 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/backend/routers/chat.py b/backend/routers/chat.py index 8ada2aa..60af08c 100644 --- a/backend/routers/chat.py +++ b/backend/routers/chat.py @@ -26,8 +26,9 @@ class State(TypedDict): # Initialize the LLM llm = ChatOpenAI( - model="gpt-4o-mini", - api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4.1-mini", + base_url=os.environ["OPENAI_BASE_URL"], + api_key=os.environ["OPENAI_API_KEY"], temperature=0.7 ) diff --git a/docker-compose.yml b/docker-compose.yml index 63a5ce4..f03d72a 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -39,6 +39,8 @@ services: dockerfile: ./backend/Dockerfile environment: DATABASE_URL: postgresql://postgres:password@postgres:5432/todoapp + env_file: + - ./.env ports: - "8000:8000" # Serving port - "5678:5678" # Debugging port From 0a5b83567617e1353d998f6e3976e9c40ffb39ae Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Fri, 3 Oct 2025 06:18:25 +0000 Subject: [PATCH 09/10] Add streaming support for chat responses Co-authored-by: lambdakris <15176003+lambdakris@users.noreply.github.com> --- backend/routers/README.md | 26 ++++++++++++++++++---- backend/routers/chat.py | 47 ++++++++++++++++++++++++++++----------- frontend/pages/chat.py | 33 ++++++++++++++++++--------- 3 files changed, 79 insertions(+), 27 deletions(-) diff --git a/backend/routers/README.md b/backend/routers/README.md index f6d4f9f..24db0d4 100644 --- a/backend/routers/README.md +++ b/backend/routers/README.md @@ -4,12 +4,12 @@ This directory contains FastAPI routers that organize the API endpoints by featu ## Chat Router (`chat.py`) -The chat router implements a LangGraph-based conversational AI using OpenAI's GPT models. +The chat router implements a LangGraph-based conversational AI using OpenAI's GPT models with **streaming support**. ### Architecture ``` -User Message → FastAPI Router → LangGraph StateGraph → OpenAI LLM → Response +User Message → FastAPI Router → LangGraph StateGraph → OpenAI LLM (streaming) → SSE Response ``` ### LangGraph Flow @@ -18,16 +18,26 @@ User Message → FastAPI Router → LangGraph StateGraph → OpenAI LLM → Resp START ↓ [chatbot node] - ↓ (invokes OpenAI) + ↓ (streams from OpenAI) ↓ END ``` +### Streaming Implementation + +The chat endpoint uses: +- **LangGraph's `.astream()` method** with `stream_mode="messages"` for token-by-token streaming +- **FastAPI's `StreamingResponse`** to send Server-Sent Events (SSE) +- **OpenAI's streaming mode** enabled in the ChatOpenAI client + +This provides real-time token-by-token response streaming for a better user experience. + ### Key Components - **State**: Manages conversation messages using LangGraph's message history -- **LLM**: ChatOpenAI with gpt-4o-mini model (configurable) +- **LLM**: ChatOpenAI with gpt-4.1-mini model (streaming enabled) - **Graph**: Simple linear flow that can be extended with additional nodes +- **Streaming**: Server-Sent Events (SSE) format for real-time responses ### Configuration @@ -63,6 +73,14 @@ graph_builder.add_edge(START, "retrieve") graph_builder.add_edge("retrieve", "chatbot") ``` +### Streaming Details + +The endpoint uses LangGraph's message streaming mode: +- Streams individual tokens as they're generated +- Uses Server-Sent Events (SSE) format +- Each event contains a JSON payload with the content chunk +- Frontend can display tokens in real-time using `st.write_stream()` + ## Future Routers Additional routers can be added for: diff --git a/backend/routers/chat.py b/backend/routers/chat.py index 60af08c..48beb5e 100644 --- a/backend/routers/chat.py +++ b/backend/routers/chat.py @@ -1,4 +1,5 @@ from fastapi import APIRouter +from fastapi.responses import StreamingResponse from pydantic import BaseModel from typing import Annotated from typing_extensions import TypedDict @@ -6,6 +7,7 @@ from langgraph.graph.message import add_messages from langchain_openai import ChatOpenAI import os +import json # Router setup router = APIRouter( @@ -24,12 +26,13 @@ class ChatResponse(BaseModel): class State(TypedDict): messages: Annotated[list, add_messages] -# Initialize the LLM +# Initialize the LLM with streaming enabled llm = ChatOpenAI( model="gpt-4.1-mini", base_url=os.environ["OPENAI_BASE_URL"], api_key=os.environ["OPENAI_API_KEY"], - temperature=0.7 + temperature=0.7, + streaming=True ) # Define the chatbot node @@ -46,20 +49,38 @@ def chatbot(state: State): graph_builder.add_edge("chatbot", END) graph = graph_builder.compile() -@router.post("", response_model=ChatResponse) +@router.post("") async def chat(message: ChatMessage): """ - Chat endpoint that provides AI assistant responses using LangGraph and OpenAI. + Chat endpoint that provides streaming AI assistant responses using LangGraph and OpenAI. - This implements a simple conversational AI that maintains context within a single request. + This implements a simple conversational AI that streams responses token-by-token. For multi-turn conversations with persistent state, additional session management would be needed. """ - # Invoke the graph with the user's message - result = graph.invoke({ - "messages": [("user", message.message)] - }) + async def generate_stream(): + """ + Generator function that streams the response from LangGraph. + Uses the 'messages' stream mode to get message updates. + """ + # Stream the graph with the user's message + async for event in graph.astream({ + "messages": [("user", message.message)] + }, stream_mode="messages"): + # event is a tuple of (message, metadata) + # We only want the message content chunks + msg, metadata = event + + # Only stream content from AIMessage (not HumanMessage) + if hasattr(msg, 'content') and msg.content: + # Stream each chunk as a JSON line + chunk_data = {"content": msg.content} + yield f"data: {json.dumps(chunk_data)}\n\n" - # Extract the assistant's response - assistant_message = result["messages"][-1].content - - return ChatResponse(response=assistant_message) + return StreamingResponse( + generate_stream(), + media_type="text/event-stream", + headers={ + "Cache-Control": "no-cache", + "Connection": "keep-alive", + } + ) diff --git a/frontend/pages/chat.py b/frontend/pages/chat.py index 0660a13..c363dba 100644 --- a/frontend/pages/chat.py +++ b/frontend/pages/chat.py @@ -17,21 +17,35 @@ def display_chat_messages(): with st.chat_message(message["role"]): st.markdown(message["content"]) -def get_assistant_response(user_message): +def get_assistant_response_stream(user_message): """ - Call the backend API to get AI assistant response. + Call the backend API to get streaming AI assistant response. + Returns a generator that yields response chunks. """ try: payload = {"message": user_message} - response = requests.post(f"{API_BASE_URL}/chat", json=payload) + response = requests.post( + f"{API_BASE_URL}/chat", + json=payload, + stream=True, + headers={"Accept": "text/event-stream"} + ) + if response.status_code == 200: - return response.json()["response"] + # Stream the response + for line in response.iter_lines(): + if line: + line = line.decode('utf-8') + if line.startswith('data: '): + import json + data = json.loads(line[6:]) # Remove 'data: ' prefix + yield data['content'] else: st.error(f"Failed to get response: {response.status_code}") - return "I apologize, but I'm having trouble responding right now. Please try again." + yield "I apologize, but I'm having trouble responding right now. Please try again." except requests.exceptions.RequestException as e: st.error(f"Connection error: {e}") - return "I apologize, but I'm having trouble connecting to the backend. Please try again." + yield "I apologize, but I'm having trouble connecting to the backend. Please try again." def handle_user_input(): """Handle new user input from chat input widget""" @@ -43,11 +57,10 @@ def handle_user_input(): with st.chat_message("user"): st.markdown(prompt) - # Generate and display assistant response + # Generate and display assistant response with streaming with st.chat_message("assistant"): - with st.spinner("Thinking..."): - response = get_assistant_response(prompt) - st.markdown(response) + # Use st.write_stream to display streaming response + response = st.write_stream(get_assistant_response_stream(prompt)) # Add assistant response to chat history st.session_state.messages.append({"role": "assistant", "content": response}) From d56e0b752c12e2da7541b1095cd147e49806e31c Mon Sep 17 00:00:00 2001 From: lambdakris Date: Fri, 17 Oct 2025 07:54:07 -0600 Subject: [PATCH 10/10] Port from liquibase to flyway as flyway has better stability, docs, and overall dx --- compose.yml | 83 +++++++++++++++++++ database/Dockerfile | 10 +++ database/Dockerfile.liquibase | 13 --- .../flyway/sql/V001__create_todos_table.sql | 11 +++ database/init.sql | 6 -- .../changelogs/db.changelog-master.yaml | 3 - .../v1.0.0/001-create-todos-table.yaml | 45 ---------- database/liquibase/liquibase.properties | 6 -- docker-compose.yml | 70 ---------------- scripts/migrate.sh | 36 ++++---- 10 files changed, 121 insertions(+), 162 deletions(-) create mode 100644 compose.yml create mode 100644 database/Dockerfile delete mode 100644 database/Dockerfile.liquibase create mode 100644 database/flyway/sql/V001__create_todos_table.sql delete mode 100644 database/init.sql delete mode 100644 database/liquibase/changelogs/db.changelog-master.yaml delete mode 100644 database/liquibase/changelogs/v1.0.0/001-create-todos-table.yaml delete mode 100644 database/liquibase/liquibase.properties delete mode 100644 docker-compose.yml diff --git a/compose.yml b/compose.yml new file mode 100644 index 0000000..1758a03 --- /dev/null +++ b/compose.yml @@ -0,0 +1,83 @@ +volumes: + proto_db_volume: + +services: + postgres: + image: postgres:17 + environment: + POSTGRES_DB: proto_db + POSTGRES_USER: proto_db_user + POSTGRES_PASSWORD: proto_db_password + volumes: + - proto_db_volume:/var/lib/postgresql/data + ports: + - "5432:5432" + healthcheck: + test: ["CMD", "pg_isready"] + interval: 30m + timeout: 30s + retries: 3 + start_period: 15s + start_interval: 1s + + flyway: + depends_on: + postgres: + condition: service_healthy + build: + context: . + dockerfile: database/Dockerfile + environment: + FLYWAY_URL: jdbc:postgresql://postgres:5432/proto_db + FLYWAY_USER: proto_db_user + FLYWAY_PASSWORD: proto_db_password + + backend: + depends_on: + flyway: + condition: service_completed_successfully + build: + context: . + dockerfile: backend/Dockerfile + environment: + DATABASE_URL: postgresql://proto_db_user:proto_db_password@postgres:5432/proto_db + OPENAI_API_BASE: ${OPENAI_API_BASE} + OPENAI_API_KEY: ${OPENAI_API_KEY} + HF_TOKEN: ${HF_TOKEN} + TAVILY_API_KEY: ${TAVILY_API_KEY} + ports: + - "8000:8000" # Serving port + - "5678:5678" # Debugging port + develop: + watch: + - path: backend + target: /apps/backend + action: sync + command: uv run -m debugpy --listen 0.0.0.0:5678 -m fastapi dev main.py --host 0.0.0.0 --port 8000 + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:8000"] + interval: 30m + timeout: 30s + retries: 3 + start_period: 15s + start_interval: 1s + + frontend: + depends_on: + backend: + condition: service_healthy + build: + context: . + dockerfile: frontend/Dockerfile + environment: + API_BASE_URL: http://backend:8000 + ports: + - "8501:8501" # Serving port + - "5679:5679" # Debugging port + develop: + watch: + - path: frontend + target: /apps/frontend + action: sync + command: uv run -m debugpy --listen 0.0.0.0:5679 -m streamlit run main.py --server.address 0.0.0.0 --server.port 8501 + diff --git a/database/Dockerfile b/database/Dockerfile new file mode 100644 index 0000000..0433ddd --- /dev/null +++ b/database/Dockerfile @@ -0,0 +1,10 @@ +FROM flyway/flyway:latest + +# Set working directory +WORKDIR /flyway + +# Copy migration scripts +COPY ./database/flyway/sql ./sql + +# Default command to run migrations +CMD [ "migrate" ] \ No newline at end of file diff --git a/database/Dockerfile.liquibase b/database/Dockerfile.liquibase deleted file mode 100644 index 34c2b07..0000000 --- a/database/Dockerfile.liquibase +++ /dev/null @@ -1,13 +0,0 @@ -FROM liquibase/liquibase:4.25 - -# Use the PostgreSQL driver that's already included with the Liquibase image -# The official Liquibase image includes the PostgreSQL driver - -# Set working directory -WORKDIR /liquibase - -# Copy configuration and changelog files -COPY --chown=liquibase:liquibase liquibase/ . - -# Set default command -CMD ["update"] \ No newline at end of file diff --git a/database/flyway/sql/V001__create_todos_table.sql b/database/flyway/sql/V001__create_todos_table.sql new file mode 100644 index 0000000..48ae664 --- /dev/null +++ b/database/flyway/sql/V001__create_todos_table.sql @@ -0,0 +1,11 @@ +-- Create todos table +CREATE TABLE IF NOT EXISTS todos ( + id SERIAL PRIMARY KEY, + title VARCHAR(255) NOT NULL, + description TEXT DEFAULT '', + completed BOOLEAN NOT NULL DEFAULT FALSE +); + +-- Indexes +CREATE INDEX IF NOT EXISTS idx_todos_id ON todos(id); +CREATE INDEX IF NOT EXISTS idx_todos_title ON todos(title); diff --git a/database/init.sql b/database/init.sql deleted file mode 100644 index 202131e..0000000 --- a/database/init.sql +++ /dev/null @@ -1,6 +0,0 @@ --- Database initialization script --- The todoapp database will be created by the POSTGRES_DB environment variable --- This script is here for additional setup if needed in the future - --- Create any additional tables or configurations here --- For now, the FastAPI application will handle table creation via SQLAlchemy \ No newline at end of file diff --git a/database/liquibase/changelogs/db.changelog-master.yaml b/database/liquibase/changelogs/db.changelog-master.yaml deleted file mode 100644 index 0533aa2..0000000 --- a/database/liquibase/changelogs/db.changelog-master.yaml +++ /dev/null @@ -1,3 +0,0 @@ -databaseChangeLog: - - include: - file: v1.0.0/001-create-todos-table.yaml \ No newline at end of file diff --git a/database/liquibase/changelogs/v1.0.0/001-create-todos-table.yaml b/database/liquibase/changelogs/v1.0.0/001-create-todos-table.yaml deleted file mode 100644 index 1da8cc1..0000000 --- a/database/liquibase/changelogs/v1.0.0/001-create-todos-table.yaml +++ /dev/null @@ -1,45 +0,0 @@ -databaseChangeLog: - - changeSet: - id: 001-create-todos-table - author: system - comment: Create the todos table for the todo application - changes: - - createTable: - tableName: todos - columns: - - column: - name: id - type: SERIAL - constraints: - primaryKey: true - nullable: false - - column: - name: title - type: VARCHAR(255) - constraints: - nullable: false - - column: - name: description - type: TEXT - defaultValue: "" - - column: - name: completed - type: BOOLEAN - defaultValueBoolean: false - constraints: - nullable: false - - createIndex: - indexName: idx_todos_id - tableName: todos - columns: - - column: - name: id - - createIndex: - indexName: idx_todos_title - tableName: todos - columns: - - column: - name: title - rollback: - - dropTable: - tableName: todos \ No newline at end of file diff --git a/database/liquibase/liquibase.properties b/database/liquibase/liquibase.properties deleted file mode 100644 index ff07aa5..0000000 --- a/database/liquibase/liquibase.properties +++ /dev/null @@ -1,6 +0,0 @@ -changeLogFile=changelogs/db.changelog-master.yaml -url=jdbc:postgresql://postgres:5432/todoapp -username=postgres -password=password -driver=org.postgresql.Driver -logLevel=INFO \ No newline at end of file diff --git a/docker-compose.yml b/docker-compose.yml deleted file mode 100644 index f03d72a..0000000 --- a/docker-compose.yml +++ /dev/null @@ -1,70 +0,0 @@ -services: - postgres: - image: postgres:17 - environment: - POSTGRES_DB: todoapp - POSTGRES_USER: postgres - POSTGRES_PASSWORD: password - volumes: - - postgres_data:/var/lib/postgresql/data - - ./database/init.sql:/docker-entrypoint-initdb.d/init.sql - ports: - - "5432:5432" - healthcheck: - test: ["CMD", "pg_isready", "-U", "postgres"] - interval: 30s - timeout: 10s - retries: 3 - - liquibase: - depends_on: - postgres: - condition: service_healthy - image: liquibase/liquibase:4.25 - environment: - LIQUIBASE_COMMAND_URL: jdbc:postgresql://postgres:5432/todoapp - LIQUIBASE_COMMAND_USERNAME: postgres - LIQUIBASE_COMMAND_PASSWORD: password - LIQUIBASE_COMMAND_CHANGELOG_FILE: db.changelog-master.yaml - volumes: - - ./database/liquibase/changelogs:/liquibase/changelog - command: ["update"] - - backend: - depends_on: - liquibase: - condition: service_completed_successfully - build: - context: ./ - dockerfile: ./backend/Dockerfile - environment: - DATABASE_URL: postgresql://postgres:password@postgres:5432/todoapp - env_file: - - ./.env - ports: - - "8000:8000" # Serving port - - "5678:5678" # Debugging port - command: uv run -m debugpy --listen 0.0.0.0:5678 -m fastapi dev main.py --host 0.0.0.0 --port 8000 - healthcheck: - test: ["CMD", "curl", "-f", "http://localhost:8000"] - interval: 30s - timeout: 10s - retries: 3 - start_period: 20s - - frontend: - depends_on: - backend: - condition: service_healthy - build: - context: ./ - dockerfile: ./frontend/Dockerfile - environment: - API_BASE_URL: http://backend:8000 - ports: - - "8501:8501" # Serving port - - "5679:5679" # Debugging port - command: uv run -m debugpy --listen 0.0.0.0:5679 -m streamlit run main.py --server.address 0.0.0.0 --server.port 8501 - -volumes: - postgres_data: \ No newline at end of file diff --git a/scripts/migrate.sh b/scripts/migrate.sh index c9fcd34..b4b8106 100755 --- a/scripts/migrate.sh +++ b/scripts/migrate.sh @@ -1,12 +1,15 @@ #!/bin/bash -# Database migration script using Liquibase + +# Database migration script using Flyway # Usage: ./scripts/migrate.sh [command] -# Commands: update, status, rollback-count , validate +# Commands: migrate, info, validate, undo (not supported in Community), clean + + +COMMAND=${1:-migrate} -COMMAND=${1:-update} +echo "Running Flyway migration: $COMMAND" -echo "Running Liquibase migration: $COMMAND" # Ensure PostgreSQL is running docker compose up -d postgres @@ -17,31 +20,26 @@ while ! docker compose exec postgres pg_isready -U postgres >/dev/null 2>&1; do sleep 1 done -echo "PostgreSQL is ready. Running Liquibase $COMMAND..." +echo "PostgreSQL is ready. Running Flyway $COMMAND..." case $COMMAND in - "update") - docker compose run --rm liquibase update + "migrate") + docker compose run --rm flyway -url=jdbc:postgresql://postgres:5432/postgres -user=postgres -password=postgres migrate ;; - "status") - docker compose run --rm liquibase status + "info") + docker compose run --rm flyway -url=jdbc:postgresql://postgres:5432/postgres -user=postgres -password=postgres info ;; "validate") - docker compose run --rm liquibase validate + docker compose run --rm flyway -url=jdbc:postgresql://postgres:5432/postgres -user=postgres -password=postgres validate ;; - "rollback-count") - if [ -z "$2" ]; then - echo "Error: rollback-count requires a count parameter" - echo "Usage: ./scripts/migrate.sh rollback-count " - exit 1 - fi - docker compose run --rm liquibase rollback-count "$2" + "clean") + docker compose run --rm flyway -url=jdbc:postgresql://postgres:5432/postgres -user=postgres -password=postgres clean ;; *) echo "Unknown command: $COMMAND" - echo "Available commands: update, status, validate, rollback-count " + echo "Available commands: migrate, info, validate, clean" exit 1 ;; esac -echo "Liquibase $COMMAND completed." \ No newline at end of file +echo "Flyway $COMMAND completed." \ No newline at end of file