Merge branch 'release/FirstProjRelease'
This commit is contained in:
Samuele Locatelli
+52
@@ -0,0 +1,52 @@
|
||||
# Python
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*.pyo
|
||||
*.pyd
|
||||
*.egg
|
||||
*.egg-info/
|
||||
dist/
|
||||
build/
|
||||
*.env
|
||||
.env
|
||||
|
||||
# Virtual environments
|
||||
venv/
|
||||
env/
|
||||
.venv/
|
||||
.env/
|
||||
|
||||
# Jupyter Notebook checkpoints
|
||||
.ipynb_checkpoints/
|
||||
|
||||
# Logs
|
||||
*.log
|
||||
|
||||
# Node.js
|
||||
node_modules/
|
||||
npm-debug.log*
|
||||
yarn-debug.log*
|
||||
yarn-error.log*
|
||||
.pnpm-debug.log*
|
||||
|
||||
# Build files
|
||||
dist/
|
||||
build/
|
||||
*.lock
|
||||
|
||||
# Environment variables
|
||||
.env
|
||||
.env.local
|
||||
.env.*.local
|
||||
|
||||
# IDEs and editors
|
||||
.vscode/
|
||||
.idea/
|
||||
*.swp
|
||||
*.swo
|
||||
*.swn
|
||||
*.bak
|
||||
|
||||
# OS-specific files
|
||||
.DS_Store
|
||||
Thumbs.db
|
||||
@@ -1,93 +1,69 @@
|
||||
# chat-proxy
|
||||
|
||||
Progetto di web chat verso motore LLM (proxy) per task chat e supporto coding privato/riservato.
|
||||
|
||||
## Obiettivi generali
|
||||
|
||||
## Getting started
|
||||
L'obiettivo iniziale è avere un agente AI basato su soluzioni opensource
|
||||
* da eseguire localmente su HW presente in ufficio
|
||||
* dove poter effettuare chiaamte anche con codice sorgente proprietario senza temere di inviare info riservate esternamente
|
||||
* per poter avere un agente sempre disponibile con le risorse allocate
|
||||
* da poter successivamente addestrare con risorse interne tra cui
|
||||
* wiki
|
||||
* sorgenti di codice aziendale
|
||||
|
||||
To make it easy for you to get started with GitLab, here's a list of recommended next steps.
|
||||
## Setup soluzione
|
||||
|
||||
Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
|
||||
La soluzione è basata sul seguente stack
|
||||
|
||||
## Add your files
|
||||
* LM Studio per esecuzione modello LLM locale (al momento su workstation Sam + scheda video AMD e poi NVidia)
|
||||
* Abilitazione LM Studio x chiamate locali su porta 1234
|
||||
* virtual machine linux con soluzione backend/frontend di proxy/caching verso il modello AI di LM Studio
|
||||
|
||||
- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
|
||||
- [ ] [Add files using the command line](https://docs.gitlab.com/topics/git/add_files/#add-files-to-a-git-repository) or push an existing Git repository with the following command:
|
||||
## Startup
|
||||
|
||||
```
|
||||
cd existing_repo
|
||||
git remote add origin https://gitlab.steamware.net/egalware-web/llm/chat-proxy.git
|
||||
git branch -M main
|
||||
git push -uf origin main
|
||||
Al momento per l0'esecuzione della soluzione, sulla virtual machine di proxy, vanno avviati backend (python) e frontend (node) manualmente.
|
||||
|
||||
Avvio soluzione:
|
||||
|
||||
backend
|
||||
```bash
|
||||
uvicorn main:app --host 0.0.0.0 --port 8000 --reload
|
||||
```
|
||||
|
||||
## Integrate with your tools
|
||||
frontend
|
||||
```bash
|
||||
npm run dev
|
||||
```
|
||||
|
||||
- [ ] [Set up project integrations](https://gitlab.steamware.net/egalware-web/llm/chat-proxy/-/settings/integrations)
|
||||
|
||||
## Collaborate with your team
|
||||
|
||||
- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
|
||||
- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
|
||||
- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
|
||||
- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
|
||||
- [ ] [Set auto-merge](https://docs.gitlab.com/user/project/merge_requests/auto_merge/)
|
||||
|
||||
## Test and Deploy
|
||||
|
||||
Use the built-in continuous integration in GitLab.
|
||||
|
||||
- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/)
|
||||
- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing (SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
|
||||
- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
|
||||
- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
|
||||
- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
|
||||
|
||||
***
|
||||
|
||||
# Editing this README
|
||||
|
||||
When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thanks to [makeareadme.com](https://www.makeareadme.com/) for this template.
|
||||
|
||||
## Suggestions for a good README
|
||||
|
||||
Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
|
||||
|
||||
## Name
|
||||
Choose a self-explaining name for your project.
|
||||
|
||||
## Description
|
||||
Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
|
||||
|
||||
## Badges
|
||||
On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
|
||||
|
||||
## Visuals
|
||||
Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
|
||||
|
||||
## Installation
|
||||
Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
|
||||
ToDo's: trasformare in servizi da abilitare all'avvio macchina
|
||||
|
||||
## Usage
|
||||
Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
|
||||
|
||||
## Support
|
||||
Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
|
||||
Per utilizzare la soluzione basta andare (in ufficio o via vpn) all'indirizzo
|
||||
|
||||
https://chat.egalware.com
|
||||
|
||||
e da li fare domande all'AI.
|
||||
|
||||
## Roadmap
|
||||
If you have ideas for releases in the future, it is a good idea to list them in the README.
|
||||
|
||||
## Contributing
|
||||
State if you are open to contributions and what your requirements are for accepting them.
|
||||
Mancano molti punti di ottimizzazione:
|
||||
- [ ] gestione utenti locali (oauth? openID? user/pwd? username? IP?)
|
||||
- [ ] gestione sessioni indipendenti (setup REDIS da verificare) per gli utenti con history
|
||||
- [ ] miglioramento grafica
|
||||
- [ ] output performances
|
||||
- [ ] test modelli LLM più consistenti con scheda video + capace
|
||||
- [ ] completamento logiche RAG
|
||||
- [ ] fine tuning (o qualunque altra tecnica di post-addestramento) per aggiungere sorgenti private tra cui
|
||||
- [ ] wiki aziendali
|
||||
- [ ] documentazione
|
||||
- [ ] codice sorgente (eventualmente da repo GIT con + versioni)
|
||||
|
||||
For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
|
||||
## Versioni
|
||||
|
||||
You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
|
||||
| Versione | Note | Data |
|
||||
|---------------|-----------------------------------------|------------|
|
||||
| 0.1.2508.2019 | Versione test solo locale con LM Studio | 2025.08.20 |
|
||||
| 0.1.2508.2119 | Versione con esecuzione locale completa | 2025.08.21 |
|
||||
|
||||
## Authors and acknowledgment
|
||||
Show your appreciation to those who have contributed to the project.
|
||||
|
||||
## License
|
||||
For open source projects, say how it is licensed.
|
||||
|
||||
## Project status
|
||||
If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
|
||||
|
||||
BIN
Binary file not shown.
@@ -0,0 +1,52 @@
|
||||
from fastapi import FastAPI, Request
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
import requests
|
||||
import redis
|
||||
import json
|
||||
|
||||
r = redis.Redis(host='localhost', port=6379, db=0)
|
||||
|
||||
def save_chat(user_id, message):
|
||||
r.rpush(f"chat:{user_id}", json.dumps(message))
|
||||
|
||||
def get_chat(user_id):
|
||||
messages = r.lrange(f"chat:{user_id}", 0, -1)
|
||||
return [json.loads(m.decode('utf-8')) for m in messages]
|
||||
|
||||
app = FastAPI()
|
||||
|
||||
# Allow frontend access
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
# Store sessions in memory (simple version)
|
||||
sessions = {}
|
||||
|
||||
@app.post("/chat")
|
||||
async def chat(request: Request):
|
||||
data = await request.json()
|
||||
user_id = data.get("user_id", "default")
|
||||
message = data["message"]
|
||||
|
||||
# Retrieve session history
|
||||
save_chat(user_id, {"role": "user", "content": message})
|
||||
history = get_chat(user_id)
|
||||
|
||||
# Send to LM Studio
|
||||
response = requests.post("http://10.74.83.100:1234/v1/chat/completions", json={
|
||||
"model": "qwen/qwen3-4b-2507", # Replace with actual model name
|
||||
"messages": history
|
||||
})
|
||||
|
||||
result = response.json()
|
||||
reply = result["choices"][0]["message"]["content"]
|
||||
|
||||
# save in REDIS chat history
|
||||
save_chat(user_id, {"role": "assistant", "content": reply})
|
||||
|
||||
return {"response": reply}
|
||||
|
||||
@@ -0,0 +1,4 @@
|
||||
fastapi
|
||||
uvicorn
|
||||
requests
|
||||
|
||||
@@ -0,0 +1,15 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Egalware's LM Studio Chat App</title>
|
||||
<link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.2/dist/css/bootstrap.min.css" rel="stylesheet" />
|
||||
|
||||
</head>
|
||||
<body>
|
||||
<div id="root"></div>
|
||||
<script type="module" src="/src/main.jsx"></script>
|
||||
</body>
|
||||
</html>
|
||||
|
||||
Generated
+1645
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,18 @@
|
||||
{
|
||||
"name": "lm-chat-frontend",
|
||||
"version": "1.0.0",
|
||||
"dependencies": {
|
||||
"react": "^18.3.1",
|
||||
"react-dom": "^18.3.1",
|
||||
"react-markdown": "^10.1.0",
|
||||
"vite": "^4.0.0"
|
||||
},
|
||||
"scripts": {
|
||||
"dev": "vite --host"
|
||||
},
|
||||
"devDependencies": {
|
||||
"autoprefixer": "^10.4.21",
|
||||
"postcss": "^8.5.6",
|
||||
"tailwindcss": "^4.1.12"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,69 @@
|
||||
/* src/App.css */
|
||||
body {
|
||||
font-family: sans-serif;
|
||||
}
|
||||
|
||||
body, html {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
height: 100%;
|
||||
font-family: sans-serif;
|
||||
}
|
||||
|
||||
.chat-container {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
height: 100vh;
|
||||
background-color: #f3f4f6;
|
||||
}
|
||||
|
||||
.chat-box {
|
||||
flex: 1;
|
||||
overflow-y: auto;
|
||||
padding: 1rem;
|
||||
}
|
||||
|
||||
.message {
|
||||
margin: 0.5rem 0;
|
||||
padding: 0.75rem;
|
||||
border-radius: 8px;
|
||||
max-width: 80%;
|
||||
}
|
||||
|
||||
.message.user {
|
||||
background-color: #dbeafe;
|
||||
align-self: flex-end;
|
||||
text-align: right;
|
||||
}
|
||||
|
||||
.message.assistant {
|
||||
background-color: #e5e7eb;
|
||||
align-self: flex-start;
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
.input-bar {
|
||||
display: flex;
|
||||
padding: 1rem;
|
||||
background-color: white;
|
||||
border-top: 1px solid #ccc;
|
||||
}
|
||||
|
||||
.chat-input {
|
||||
flex: 1;
|
||||
padding: 0.75rem;
|
||||
border: 1px solid #ccc;
|
||||
border-radius: 8px;
|
||||
font-size: 1rem;
|
||||
}
|
||||
|
||||
.send-button {
|
||||
margin-left: 0.5rem;
|
||||
padding: 0.75rem 1rem;
|
||||
background-color: #3b82f6;
|
||||
color: white;
|
||||
border: none;
|
||||
border-radius: 8px;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
@@ -0,0 +1,81 @@
|
||||
import React, { useState, useRef, useEffect } from 'react';
|
||||
import ReactMarkdown from 'react-markdown';
|
||||
import './App.css';
|
||||
|
||||
function App() {
|
||||
const [messages, setMessages] = useState([]);
|
||||
const [input, setInput] = useState("");
|
||||
const messagesEndRef = useRef(null);
|
||||
const [loading, setLoading] = useState(false);
|
||||
|
||||
const sendMessage = async () => {
|
||||
if (!input.trim()) return;
|
||||
|
||||
const userMessage = { role: "user", content: input };
|
||||
setMessages(prev => [...prev, userMessage]);
|
||||
setInput("");
|
||||
setLoading(true); // 🚀 show loader
|
||||
|
||||
try {
|
||||
const res = await fetch("/chat", {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify({ user_id: "user1", message: input })
|
||||
});
|
||||
|
||||
const data = await res.json();
|
||||
const botMessage = { role: "assistant", content: data.response };
|
||||
setMessages(prev => [...prev, botMessage]);
|
||||
} finally {
|
||||
setLoading(false); // ✅ hide loader
|
||||
}
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
|
||||
}, [messages]);
|
||||
|
||||
return (
|
||||
<div className="chat-container">
|
||||
<header className="navbar navbar-dark bg-primary sticky-top">
|
||||
<div className="container-fluid">
|
||||
<span className="navbar-brand mb-0 h1">Egalware's LM Studio Chat</span>
|
||||
</div>
|
||||
</header>
|
||||
<div className="chat-box">
|
||||
{loading && (
|
||||
<div className="d-flex justify-content-start p-2">
|
||||
<div className="spinner-border text-secondary" role="status" style={{width: "1.5rem", height: "1.5rem"}}>
|
||||
<span className="visually-hidden">Thinking...</span>
|
||||
</div>
|
||||
<span className="ms-2 text-muted">The model is processing...</span>
|
||||
</div>
|
||||
)}
|
||||
{messages.map((msg, i) => (
|
||||
<div key={i} className={`d-flex mb-2 ${msg.role === "user" ? "justify-content-end" : "justify-content-start"}`}>
|
||||
<div className={`p-2 rounded shadow-sm ${msg.role === "user" ? "bg-primary text-white" : "bg-light text-dark border" }`} style={{ maxWidth: "75%" }}>
|
||||
<ReactMarkdown>{msg.content}</ReactMarkdown>
|
||||
</div>
|
||||
</div>
|
||||
))}
|
||||
|
||||
<div ref={messagesEndRef} />
|
||||
</div>
|
||||
<div className="input-bar d-flex justify-content-center p-3 bg-light border-top">
|
||||
<div className="w-100 w-md-75 w-lg-50 d-flex">
|
||||
<input className="form-control me-2"
|
||||
value={input}
|
||||
onChange={e => setInput(e.target.value)}
|
||||
onKeyDown={e => e.key === "Enter" && sendMessage()}
|
||||
placeholder="Type your message..."
|
||||
autoFocus
|
||||
/>
|
||||
<button className="btn btn-primary" onClick={sendMessage}>Send</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
export default App;
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// src/main.jsx
|
||||
import React from 'react'
|
||||
import ReactDOM from 'react-dom/client'
|
||||
import App from './App.jsx'
|
||||
import './App.css'
|
||||
|
||||
ReactDOM.createRoot(document.getElementById('root')).render(
|
||||
<React.StrictMode>
|
||||
<App />
|
||||
</React.StrictMode>
|
||||
)
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// vite.config.js
|
||||
module.exports = {
|
||||
server: {
|
||||
host: '0.0.0.0',
|
||||
port: 5173,
|
||||
hmr: {
|
||||
protocol: 'wss',
|
||||
host: 'chat.egalware.com'
|
||||
},
|
||||
allowedHosts: ['chat.egalware.com']
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
[Unit]
|
||||
Description=LM Studio proxy Python Backend Service
|
||||
After=network.target
|
||||
|
||||
[Service]
|
||||
User=samuele
|
||||
WorkingDirectory=/home/samuele/lm-chat-app/backend
|
||||
ExecStart=/usr/bin/env uvicorn main:app --host 0.0.0.0 --port 8000 --reload
|
||||
Restart=always
|
||||
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
|
||||
@@ -0,0 +1,16 @@
|
||||
[Unit]
|
||||
Description=LM Studio proxy Node Frontend Service
|
||||
After=network.target
|
||||
|
||||
[Service]
|
||||
User=samuele
|
||||
WorkingDirectory=/home/samuele/lm-chat-app/frontend
|
||||
ExecStart=/home/samuele/lm-chat-app/start-frontend.sh
|
||||
Restart=always
|
||||
RestartSec=1
|
||||
StandardOutput=journal
|
||||
StandardError=journal
|
||||
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
|
||||
@@ -0,0 +1,16 @@
|
||||
[Unit]
|
||||
Description=Streamlit LM Studio Chatbot proxy Service
|
||||
After=network.target
|
||||
|
||||
[Service]
|
||||
User=samuele
|
||||
WorkingDirectory=/home/samuele/lm-chat-app/streamlit
|
||||
ExecStart=/home/samuele/lm-chat-app/start-streamlit.sh
|
||||
Restart=always
|
||||
RestartSec=1
|
||||
StandardOutput=journal
|
||||
StandardError=journal
|
||||
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
|
||||
Executable
+7
@@ -0,0 +1,7 @@
|
||||
#!/bin/bash
|
||||
export NVM_DIR="$HOME/.nvm"
|
||||
source "$NVM_DIR/nvm.sh"
|
||||
nvm use 20
|
||||
cd /home/samuele/lm-chat-app/frontend
|
||||
npm run dev
|
||||
|
||||
Executable
+4
@@ -0,0 +1,4 @@
|
||||
#!/bin/bash
|
||||
cd /home/samuele/lm-chat-app/streamlit
|
||||
streamlit run app.py
|
||||
|
||||
@@ -0,0 +1,8 @@
|
||||
## Streamlit chatbot client
|
||||
|
||||
Client Chatbot con update realtime che sfrutta le API di openAI per connettersi a LM Studio locale
|
||||
|
||||
esempio tratto inizialmente da qui:
|
||||
|
||||
https://github.com/ingridstevens/AI-projects/tree/main/streamlit-streaming-langchain
|
||||
|
||||
@@ -0,0 +1,66 @@
|
||||
####
|
||||
#### Streamlit Streaming using LM Studio as OpenAI Standin
|
||||
#### run with `streamlit run app.py`
|
||||
|
||||
# !pip install pypdf langchain langchain_openai
|
||||
|
||||
import streamlit as st
|
||||
from langchain_core.messages import AIMessage, HumanMessage
|
||||
from langchain_openai import ChatOpenAI
|
||||
from langchain_core.output_parsers import StrOutputParser
|
||||
from langchain_core.prompts import ChatPromptTemplate
|
||||
|
||||
# app config
|
||||
st.set_page_config(page_title="Egalware Chatbot", page_icon="🤖")
|
||||
st.title("Egalware's Streaming Chatbot")
|
||||
|
||||
def get_response(user_query, chat_history):
|
||||
|
||||
template = """
|
||||
You are a helpful assistant. Answer the following questions considering the history of the conversation:
|
||||
|
||||
Chat history: {chat_history}
|
||||
|
||||
User question: {user_question}
|
||||
"""
|
||||
|
||||
prompt = ChatPromptTemplate.from_template(template)
|
||||
|
||||
# Using LM Studio Local Inference Server
|
||||
llm = ChatOpenAI(base_url="http://10.74.83.100:1234/v1",api_key="lm-studio", model="qwen/qwen3-4b-2507")
|
||||
|
||||
chain = prompt | llm | StrOutputParser()
|
||||
|
||||
return chain.stream({
|
||||
"chat_history": chat_history,
|
||||
"user_question": user_query,
|
||||
})
|
||||
|
||||
# session state
|
||||
if "chat_history" not in st.session_state:
|
||||
st.session_state.chat_history = [
|
||||
AIMessage(content="Hello, I am a bot. How can I help you?"),
|
||||
]
|
||||
|
||||
|
||||
# conversation
|
||||
for message in st.session_state.chat_history:
|
||||
if isinstance(message, AIMessage):
|
||||
with st.chat_message("AI"):
|
||||
st.write(message.content)
|
||||
elif isinstance(message, HumanMessage):
|
||||
with st.chat_message("Human"):
|
||||
st.write(message.content)
|
||||
|
||||
# user input
|
||||
user_query = st.chat_input("Type your message here...")
|
||||
if user_query is not None and user_query != "":
|
||||
st.session_state.chat_history.append(HumanMessage(content=user_query))
|
||||
|
||||
with st.chat_message("Human"):
|
||||
st.markdown(user_query)
|
||||
|
||||
with st.chat_message("AI"):
|
||||
response = st.write_stream(get_response(user_query, st.session_state.chat_history))
|
||||
|
||||
st.session_state.chat_history.append(AIMessage(content=response))
|
||||
Reference in New Issue
Block a user