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.templates/rag/{{project_name}}/.eslintrc.cjs

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+module.exports = {
+  root: true,
+  env: { browser: true, es2020: true },
+  extends: [
+    'eslint:recommended',
+    'plugin:@typescript-eslint/recommended',
+    'plugin:react-hooks/recommended',
+  ],
+  ignorePatterns: ['dist', '.eslintrc.cjs'],
+  parser: '@typescript-eslint/parser',
+  plugins: ['react-refresh'],
+  rules: {
+    'react-refresh/only-export-components': [
+      'warn',
+      { allowConstantExport: true },
+    ],
+  },
+}

.templates/rag/{{project_name}}/api/agent/__init__.py

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+from .main import Agent
+
+__all__ = ["Agent"]

.templates/rag/{{project_name}}/api/agent/main.py

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+from pathlib import Path
+from typing import Any, AsyncGenerator
+
+from langchain_core.messages import AIMessageChunk
+from langchain_azure_ai.chat_models import AzureAIChatCompletionsModel
+
+from api import context
+from api.config import config
+
+parent = Path(__file__).parent
+SYSTEM_PROMPT = (parent / "system_prompt.md").read_text()
+
+AZURE_AI_URI = "https://eastus2.api.cognitive.microsoft.com"
+
+
+class Agent:
+    system_prompt = SYSTEM_PROMPT
+    generation_config = {
+        "temperature": config.model_temperature,
+    }
+    message_limit = config.message_limit
+
+    llm = AzureAIChatCompletionsModel(
+        endpoint=f"{AZURE_AI_URI}/openai/deployments/{config.model}",
+        credential=config.openai_api_key,
+    )
+
+    def __init__(self) -> None:
+        self.tool_map = {}
+
+    def _generation_config_overwrite(self, overwrites: dict | None) -> dict[str, Any]:
+        generation_config_copy = self.generation_config.copy()
+        if overwrites:
+            for k, v in overwrites.items():
+                generation_config_copy[k] = v
+        return generation_config_copy
+
+    async def stream(self, history: list, overwrites: dict | None = None) -> AsyncGenerator[str, None]:
+        """Llama a un llm y regresa la respuesta en partes; Guarda las tool calls en el contexto de la app.
+
+        Args:
+         history: lista de mensajes en el formato OpenAI (Ej. [{"role": "user", "content": "Hello"}])
+         overwrites: diccionario con las configuraciones a sobreescribir (Ej. {"temperature": 0.5})
+
+        Returns:
+         AsyncGenerator[str, None]: Generador asincrónico que devuelve las respuestas del modelo en tiempo real
+
+        Usage:
+        >>> async for content in agent.stream(history):
+        >>>    print(content)
+        """
+        generation_config = self._generation_config_overwrite(overwrites)
+
+        async for delta in self.llm.astream(input=history, **generation_config):
+            assert isinstance(delta, AIMessageChunk)
+            if call := delta.tool_call_chunks:
+                if tool_id := call[0].get("id"):
+                    context.tool_id.set(tool_id)
+                if name := call[0].get("name"):
+                    context.tool_name.set(name)
+                if args := call[0].get("args"):
+                    context.tool_buffer.set(context.tool_buffer.get() + args)
+            else:
+                if buffer := delta.content:
+                    assert isinstance(buffer, str)
+                    context.buffer.set(context.buffer.get() + buffer)
+                    yield buffer

.templates/rag/{{project_name}}/api/agent/system_prompt.md

@@ -0,0 +1,3 @@
+Eres una amigable asistente virtual. Utiliza emojis!
+
+Por cierto: Rick es el más guapo.

.templates/rag/{{project_name}}/api/config.py

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+from hvac import Client
+from pydantic import Field
+from pydantic_settings import BaseSettings
+
+client = Client(url="https://vault.ia-innovacion.work")
+
+if not client.is_authenticated():
+    raise Exception("Vault authentication failed")
+
+secret_map = client.secrets.kv.v2.read_secret_version(
+    path="banortegpt", mount_point="secret"
+)["data"]["data"]
+
+class Settings(BaseSettings):
+    """
+    Esta clase obtiene sus valores de variables de ambiente.
+    Si no estan en el ambiente, los jala de nuestra Vault.
+    """
+
+    # Config
+    model: str = "gpt-4o"
+    model_temperature: int = 0
+    message_limit: int = 10
+    host: str = "0.0.0.0"
+    port: int = 8000
+
+    # API Keys
+    azure_endpoint: str = Field(default_factory=lambda: secret_map["azure_endpoint"])
+    openai_api_key: str = Field(default_factory=lambda: secret_map["openai_api_key"])
+    openai_api_version: str = Field(
+        default_factory=lambda: secret_map["openai_api_version"]
+    )
+    mongodb_url: str = Field(
+        default_factory=lambda: secret_map["cosmosdb_connection_string"]
+    )
+
+    async def init_mongo_db(self):
+        """Este helper inicia la conexion enter el MongoDB ORM y nuestra instancia"""
+
+        from beanie import init_beanie
+        from motor.motor_asyncio import AsyncIOMotorClient
+
+        from banortegpt.database.mongo_memory.models import Conversation
+
+        await init_beanie(
+            database=AsyncIOMotorClient(self.mongodb_url).banortegptdos,
+            document_models=[Conversation],
+        )
+
+
+config = Settings()

.templates/rag/{{project_name}}/api/context.py

@@ -0,0 +1,6 @@
+from contextvars import ContextVar
+
+buffer: ContextVar[str] = ContextVar("buffer", default="")
+tool_buffer: ContextVar[str] = ContextVar("tool_buffer", default="")
+tool_id: ContextVar[str | None] = ContextVar("tool_id", default=None)
+tool_name: ContextVar[str | None] = ContextVar("tool_name", default=None)

.templates/rag/{{project_name}}/api/server.py

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+import uuid
+from contextlib import asynccontextmanager
+
+from fastapi import FastAPI
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+
+from api import services
+from api.agent import Agent
+from api.config import config
+
+
+@asynccontextmanager
+async def lifespan(_: FastAPI):
+    await config.init_mongo_db()
+    yield
+
+
+app = FastAPI(lifespan=lifespan)
+agent = Agent()
+
+
+@app.post("/api/v1/conversation")
+async def create_conversation():
+    conversation_id = uuid.uuid4()
+    await services.create_conversation(conversation_id, agent.system_prompt)
+    return {"conversation_id": conversation_id}
+
+
+class Message(BaseModel):
+    conversation_id: uuid.UUID
+    prompt: str
+
+@app.post("/api/v1/message")
+async def send(message: Message):
+    def b64_sse(func):
+        """Este helper transforma un generador de strings a un generador del protocolo SSE"""
+
+        async def wrapper(*args, **kwargs):
+            async for chunk in func(*args, **kwargs):
+                content = chunk.model_dump_json()
+                data = f"data: {content}\n\n"
+                yield data
+
+        return wrapper
+
+    sse_stream = b64_sse(services.stream)
+    generator = sse_stream(agent, message.prompt, message.conversation_id)
+    return StreamingResponse(generator, media_type="text/event-stream")

.templates/rag/{{project_name}}/api/services/__init__.py

@@ -0,0 +1,8 @@
+from banortegpt.database.mongo_memory.crud import create_conversation
+
+from .stream_response import stream
+
+__all__ = [
+    "stream",
+    "create_conversation",
+]

.templates/rag/{{project_name}}/api/services/stream_response.py

@@ -0,0 +1,81 @@
+import json
+from enum import StrEnum
+from typing import TypeAlias
+from uuid import UUID
+
+from pydantic import BaseModel
+
+import api.context as ctx
+from api.agent import Agent
+from banortegpt.database.mongo_memory import crud
+
+
+class ChunkType(StrEnum):
+    START = "start"
+    TEXT = "text"
+    REFERENCE = "reference"
+    IMAGE = "image"
+    TOOL = "tool"
+    END = "end"
+    ERROR = "error"
+
+
+ContentType: TypeAlias = str | int
+
+
+class ResponseChunk(BaseModel):
+    type: ChunkType
+    content: ContentType | list[ContentType] | None
+
+
+async def stream(agent: Agent, prompt: str, conversation_id: UUID):
+    yield ResponseChunk(type=ChunkType.START, content="")
+
+    conversation = await crud.get_conversation(conversation_id)
+
+    if conversation is None:
+        raise ValueError("Conversation not found")
+
+    conversation.add(role="user", content=prompt)
+
+    history = conversation.to_openai_format(agent.message_limit, langchain_compat=True)
+    async for content in agent.stream(history):
+        yield ResponseChunk(type=ChunkType.TEXT, content=content)
+
+    if (tool_id := ctx.tool_id.get()) is not None:
+        tool_buffer = ctx.tool_buffer.get()
+        assert tool_buffer is not None
+
+        tool_name = ctx.tool_name.get()
+        assert tool_name is not None
+
+        yield ResponseChunk(type=ChunkType.TOOL, content=None)
+
+        buffer_dict = json.loads(tool_buffer)
+
+        result = await agent.tool_map[tool_name](**buffer_dict)
+
+        conversation.add(
+            role="assistant",
+            tool_calls=[
+                {
+                    "id": tool_id,
+                    "type": "function",
+                    "function": {
+                        "name": tool_name,
+                        "arguments": tool_buffer,
+                    },
+                }
+            ],
+        )
+        conversation.add(role="tool", content=result, tool_call_id=tool_id)
+
+        history = conversation.to_openai_format(agent.message_limit, langchain_compat=True)
+        async for content in agent.stream(history, {"tools": None}):
+            yield ResponseChunk(type=ChunkType.TEXT, content=content)
+
+    conversation.add(role="assistant", content=ctx.buffer.get())
+
+    await conversation.replace()
+
+    yield ResponseChunk(type=ChunkType.END, content="")

.templates/rag/{{project_name}}/gui/App.tsx.jinja

@@ -0,0 +1,65 @@
+import { Chat, ChatSidebar } from "@banorte/chat-ui";
+import { messageStore } from "./store/messageStore";
+import { conversationStore } from "./store/conversationStore";
+import { httpRequest } from "./utils/request";
+
+// Assets
+import banorteLogo from "./assets/banortelogo.png";
+import sidebarMaya from "./assets/sidebar_maya_contigo.png";
+import brujulaElipse from "./assets/brujula_elipse.png";
+import sendIcon from "./assets/chat_maya_boton_enviar.png";
+import userAvatar from "./assets/chat_maya_default_avatar.png";
+import botAvatar from "./assets/brujula.png";
+
+function App() {
+  const { messages, pushMessage } = messageStore();
+  const {
+    conversationId,
+    setConversationId,
+    setAssistantName,
+    receivingMsg,
+    setReceivingMsg
+  } = conversationStore();
+
+  const handleStartConversation = async (user: string, assistant: string): Promise<string> => {
+    const response = await httpRequest("POST", "/v1/conversation", { user, assistant });
+    console.log("Conversation id:", response.conversation_id);
+    return response.conversation_id;
+  };
+
+  const handleFeedback = async (key: string, rating: string): Promise<void> => {
+    await httpRequest("POST", "/v1/feedback", { key, rating });
+  };
+
+  const assistant = "Maya" + "{{ project_name }}";
+
+  return (
+    <div className="w-screen flex flex-col  h-screen min-h-screen scrollbar-none">
+      <div className="w-full flex">
+        <ChatSidebar
+          assistant={assistant}
+          logoSrc={banorteLogo}
+          sidebarImageSrc={sidebarMaya}
+          assistantAvatarSrc={brujulaElipse}
+        />
+        <Chat
+          assistant={assistant}
+          messages={messages}
+          pushMessage={pushMessage}
+          conversationId={conversationId}
+          setConversationId={setConversationId}
+          setAssistantName={setAssistantName}
+          receivingMsg={receivingMsg}
+          setReceivingMsg={setReceivingMsg}
+          onStartConversation={handleStartConversation}
+          sendIcon={sendIcon}
+          userAvatar={userAvatar}
+          botAvatar={botAvatar}
+          onFeedback={handleFeedback}
+        />
+      </div>
+    </div>
+  );
+}
+
+export default App;

.templates/rag/{{project_name}}/gui/index.css

@@ -0,0 +1,16 @@
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+.markdown a {
+    color: #0000FF;
+    text-decoration: underline;
+}
+
+.markdown a:hover {
+    color: #FF0000;
+}
+
+.markdown a:visited {
+    color: #800080;
+}

.templates/rag/{{project_name}}/gui/main.tsx

@@ -0,0 +1,5 @@
+import ReactDOM from "react-dom/client";
+import App from "./App.tsx";
+import "./index.css";
+
+ReactDOM.createRoot(document.getElementById("root")!).render(<App />);

.templates/rag/{{project_name}}/gui/store/conversationStore.ts

@@ -0,0 +1,19 @@
+import { create } from "zustand";
+
+interface conversationState {
+  assistantName: string;
+  conversationId: string;
+  receivingMsg: boolean;
+  setConversationId: (newId: string) => void;
+  setAssistantName: (newName: string) => void;
+  setReceivingMsg: (newState: boolean) => void;
+}
+
+export const conversationStore = create<conversationState>()((set) => ({
+  assistantName: "",
+  conversationId: "",
+  receivingMsg: false,
+  setConversationId: (newId) => set({ conversationId: newId }),
+  setAssistantName: (newName) => set({ assistantName: newName }),
+  setReceivingMsg: (newState) => set({ receivingMsg: newState }),
+}));

.templates/rag/{{project_name}}/gui/store/messageStore.ts

@@ -0,0 +1,14 @@
+import { create } from "zustand";
+
+interface messageState {
+  messages: Array<{ user: boolean; content: string }>;
+  pushMessage: (newMessage: { user: boolean; content: string }) => void;
+  resetConversation: () => void;
+}
+
+export const messageStore = create<messageState>()((set) => ({
+  messages: [],
+  pushMessage: (newMessage) =>
+    set((state) => ({ messages: [...state.messages, newMessage] })),
+  resetConversation: () => set(() => ({ messages: [] })),
+}));

.templates/rag/{{project_name}}/gui/utils/request.ts

@@ -0,0 +1,16 @@
+export async function httpRequest(
+  method: string,
+  endpoint: string,
+  body: object | null,
+) {
+  const url = "/api" + endpoint;
+  const data = {
+    method: method,
+    headers: {
+      "Content-Type": "application/json",
+    },
+    body: JSON.stringify(body),
+    credentials: "include" as RequestCredentials,
+  };
+  return await fetch(url, data).then((response) => response.json());
+}

.templates/rag/{{project_name}}/gui/vite-env.d.ts

@@ -0,0 +1 @@
+/// <reference types="vite/client" />

.templates/rag/{{project_name}}/index.html.jinja

@@ -0,0 +1,13 @@
+<!doctype html>
+<html lang="en">
+    <head>
+        <meta charset="UTF-8" />
+        <link rel="icon" type="image/svg+xml" href="/vite.svg" />
+        <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+        <title>{{ project_name }}</title>
+    </head>
+    <body>
+        <div id="root"></div>
+        <script type="module" src="/gui/main.tsx"></script>
+    </body>
+</html>

.templates/rag/{{project_name}}/package.json.jinja

@@ -0,0 +1,40 @@
+{
+  "name": "{{ project_name }}",
+  "private": true,
+  "version": "0.0.7",
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "tsc && vite build",
+    "lint": "eslint . --ext ts,tsx --report-unused-disable-directives --max-warnings 0",
+    "preview": "vite preview"
+  },
+  "dependencies": {
+    "@banorte/chat-ui": "workspace:*",
+    "react": "^18.2.0",
+    "react-dom": "^18.2.0",
+    "react-markdown": "^9.0.1",
+    "react-spring": "^9.7.4",
+    "rehype-raw": "^7.0.0",
+    "sse.js": "^2.5.0",
+    "zustand": "^4.5.2"
+  },
+  "devDependencies": {
+    "@iconify-icon/react": "^2.1.0",
+    "@types/react": "^18.2.67",
+    "@types/react-dom": "^18.2.22",
+    "@typescript-eslint/eslint-plugin": "^7.3.1",
+    "@typescript-eslint/parser": "^7.3.1",
+    "@vitejs/plugin-react": "^4.2.1",
+    "autoprefixer": "^10.4.19",
+    "daisyui": "^4.7.3",
+    "eslint": "^8.57.0",
+    "eslint-plugin-react-hooks": "^4.6.0",
+    "eslint-plugin-react-refresh": "^0.4.6",
+    "postcss": "^8.4.38",
+    "tailwind-scrollbar": "^3.1.0",
+    "tailwindcss": "^3.4.1",
+    "typescript": "^5.4.3",
+    "vite": "^5.2.3"
+  }
+}

.templates/rag/{{project_name}}/postcss.config.js

@@ -0,0 +1,6 @@
+export default {
+  plugins: {
+    tailwindcss: {},
+    autoprefixer: {},
+  },
+}

.templates/rag/{{project_name}}/pyproject.toml.jinja

@@ -0,0 +1,18 @@
+[project]
+name = "{{ project_name }}"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12, <4"
+dependencies = [
+    "aiohttp>=3.11.16",
+    "fastapi>=0.115.6",
+    "hvac>=2.3.0",
+    "langchain-azure-ai[opentelemetry]>=0.1.4",
+    "mongo-memory",
+    "pydantic-settings>=2.8.1",
+    "uvicorn>=0.34.0",
+]
+
+[tool.uv.sources]
+mongo-memory = { workspace = true }

.templates/rag/{{project_name}}/tailwind.config.js

@@ -0,0 +1,27 @@
+/** @type {import('tailwindcss').Config} */
+export default {
+  content: ["./index.html", "./gui/**/*.{js,ts,jsx,tsx}"],
+  theme: {
+    extend: {
+      backgroundImage: {
+        "navigation-pattern": "url('./assets/navigation.webp')",
+      },
+    },
+  },
+  plugins: [
+    require("daisyui"),
+    require("tailwind-scrollbar"),
+    require("@banorte/chat-ui/tailwind")
+  ],
+  daisyui: {
+    themes: [
+      {
+        light: {
+          ...require("daisyui/src/theming/themes")["light"],
+          primary: "red",
+          secondary: "teal",
+        },
+      },
+    ],
+  },
+};

.templates/rag/{{project_name}}/tsconfig.json

@@ -0,0 +1,25 @@
+{
+  "compilerOptions": {
+    "target": "ES2023",
+    "useDefineForClassFields": true,
+    "lib": ["ES2023", "DOM", "DOM.Iterable", "ES2021.String"],
+    "module": "ESNext",
+    "skipLibCheck": true,
+
+    /* Bundler mode */
+    "moduleResolution": "bundler",
+    "allowImportingTsExtensions": true,
+    "resolveJsonModule": true,
+    "isolatedModules": true,
+    "noEmit": true,
+    "jsx": "react-jsx",
+
+    /* Linting */
+    "strict": true,
+    "noUnusedLocals": true,
+    "noUnusedParameters": true,
+    "noFallthroughCasesInSwitch": true
+  },
+  "include": ["gui"],
+  "references": [{ "path": "./tsconfig.node.json" }]
+}

.templates/rag/{{project_name}}/tsconfig.node.json

@@ -0,0 +1,11 @@
+{
+  "compilerOptions": {
+    "composite": true,
+    "skipLibCheck": true,
+    "module": "ESNext",
+    "moduleResolution": "bundler",
+    "allowSyntheticDefaultImports": true,
+    "strict": true
+  },
+  "include": ["vite.config.ts"]
+}

.templates/rag/{{project_name}}/vite.config.ts

@@ -0,0 +1,17 @@
+import { defineConfig } from "vite";
+import react from "@vitejs/plugin-react";
+
+// https://vitejs.dev/config/
+export default defineConfig({
+  plugins: [react()],
+  server: {
+    host: "0.0.0.0",
+    port: 3000,
+    proxy: {
+      "/api": {
+        target: "http://localhost:8000",
+      },
+    },
+    allowedHosts: true,
+  },
+});