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feat(refacto): changed a bit of things to make better dx (#984)
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4
.github/workflows/aws-preview.yml
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4
.github/workflows/aws-preview.yml
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@ -4,7 +4,7 @@ on:
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push:
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branches: [ "main" ]
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paths:
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- 'backend/core/**'
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- 'backend/**'
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env:
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AWS_REGION: eu-west-3
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@ -56,7 +56,7 @@ jobs:
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ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
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IMAGE_TAG: ${{ github.sha }}
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with:
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context: ./backend/core/
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context: ./backend/
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push: true
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tags: ${{ env.ECR_REGISTRY }}/${{ env.ECR_REPOSITORY }}:${{ env.IMAGE_TAG }}, ${{ env.ECR_REGISTRY }}/${{ env.ECR_REPOSITORY }}:latest, ghcr.io/stangirard/quivr:latest
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cache-from: type=gha
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2
.github/workflows/aws.yml
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2
.github/workflows/aws.yml
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@ -55,7 +55,7 @@ jobs:
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ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
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IMAGE_TAG: ${{ github.sha }}
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with:
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context: ./backend/core/
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context: ./backend/
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push: true
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tags: ${{ env.ECR_REGISTRY }}/${{ env.ECR_REPOSITORY }}:${{ env.IMAGE_TAG }}, ${{ env.ECR_REGISTRY }}/${{ env.ECR_REPOSITORY }}:${{ github.ref_name}}, ghcr.io/stangirard/quivr:${{ github.ref_name}}
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cache-from: type=gha
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6
.github/workflows/backend-tests.yml
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6
.github/workflows/backend-tests.yml
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@ -4,11 +4,11 @@ on:
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push:
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branches: [main]
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paths:
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- 'backend/core/**'
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- 'backend/**'
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pull_request:
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branches: [main]
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paths:
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- 'backend/core/**'
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- 'backend/**'
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workflow_dispatch:
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inputs:
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logLevel:
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@ -34,7 +34,7 @@ jobs:
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runs-on: ubuntu-latest
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defaults:
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run:
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working-directory: ./backend/core
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working-directory: ./backend
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environment: preview
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strategy:
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matrix:
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@ -95,11 +95,11 @@ Additionally, you'll need a [Supabase](https://supabase.com/) account for:
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- **Step 2 - Bis**: Copy the `.XXXXX_env` files
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```bash
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cp .backend_env.example backend/core/.env
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cp .backend_env.example backend/.env
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cp .frontend_env.example frontend/.env
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```
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- **Step 3**: Update the `backend/core/.env` and `frontend/.env` file
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- **Step 3**: Update the `backend/.env` and `frontend/.env` file
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> _Your `supabase_service_key` can be found in your Supabase dashboard under Project Settings -> API. Use the `anon` `public` key found in the `Project API keys` section._
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@ -107,9 +107,9 @@ Additionally, you'll need a [Supabase](https://supabase.com/) account for:
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> _The `NEXT_PUBLIC_BACKEND_URL` is set to localhost:5050 for the docker. Update it if you are running the backend on a different machine._
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> _To activate vertexAI with PaLM from GCP follow the instructions [here](https://python.langchain.com/en/latest/modules/models/llms/integrations/google_vertex_ai_palm.html) and update `backend/core/.env`- It is an advanced feature, please be expert in GCP before trying to use it_
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> _To activate vertexAI with PaLM from GCP follow the instructions [here](https://python.langchain.com/en/latest/modules/models/llms/integrations/google_vertex_ai_palm.html) and update `backend/.env`- It is an advanced feature, please be expert in GCP before trying to use it_
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- [ ] Change variables in `backend/core/.env`
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- [ ] Change variables in `backend/.env`
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- [ ] Change variables in `frontend/.env`
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- **Step 4**: Use the `migration.sh` script to run the migration scripts
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BIN
backend/pandoc-3.1.6.1-1-arm64.deb
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BIN
backend/pandoc-3.1.6.1-1-arm64.deb
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@ -1,20 +0,0 @@
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# Use the same base image as the 'backend-core' container
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FROM python:3.11-bullseye
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# Install necessary packages
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RUN apt-get update && apt-get install -y liblzma-dev cmake git
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# Set the working directory
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WORKDIR /app
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# Copy the requirements file
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COPY ./requirements.txt /app/requirements.txt
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# Install Python dependencies
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RUN pip install --no-cache-dir -r /app/requirements.txt --timeout 100
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# Copy your application's code to the Docker container
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COPY . /app
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# Start the Uvicorn server on port 5051
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "5051"]
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@ -1,17 +0,0 @@
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import logging
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def get_logger(logger_name, log_level=logging.INFO):
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logger = logging.getLogger(logger_name)
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logger.setLevel(log_level)
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logger.propagate = False # Prevent log propagation to avoid double logging
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formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(name)s: %(message)s")
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console_handler = logging.StreamHandler()
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console_handler.setFormatter(formatter)
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if not logger.handlers:
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logger.addHandler(console_handler)
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return logger
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@ -1,30 +0,0 @@
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import os
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import sentry_sdk
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from fastapi import FastAPI, HTTPException
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from fastapi.responses import JSONResponse
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from logger import get_logger
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from routes.completions_routes import completions_router
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logger = get_logger(__name__)
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if os.getenv("SENTRY_DSN"):
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sentry_sdk.init(
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dsn=os.getenv("SENTRY_DSN"),
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# Set traces_sample_rate to 1.0 to capture 100%
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# of transactions for performance monitoring.
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# We recommend adjusting this value in production,
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traces_sample_rate=1.0,
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)
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app = FastAPI()
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app.include_router(completions_router)
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@app.exception_handler(HTTPException)
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async def http_exception_handler(_, exc):
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return JSONResponse(
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status_code=exc.status_code,
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content={"detail": exc.detail},
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)
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@ -1,18 +0,0 @@
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from typing import List
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from pydantic import BaseModel, Field
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class Message(BaseModel):
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role: str = Field(
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...,
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description="The role of the messages author. One of system, user, assistant, or function.",
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)
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content: str = Field(
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...,
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description="The contents of the message. content is required for all messages, and may be null for assistant messages with function calls.",
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)
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class Messages(BaseModel):
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messages: List[Message]
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@ -1,11 +0,0 @@
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langchain==0.0.228
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tiktoken==0.4.0
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fastapi==0.95.2
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uvicorn==0.22.0
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transformers==4.30.1
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asyncpg==0.27.0
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flake8==6.0.0
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flake8-black==0.3.6
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sentence_transformers>=2.0.0
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sentry-sdk==1.26.0
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pyright==1.1.316
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@ -1,18 +0,0 @@
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from fastapi import APIRouter
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from logger import get_logger
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from models.messages import Messages
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logger = get_logger(__name__)
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completions_router = APIRouter()
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@completions_router.post("/chat/completions", tags=["Chat Completions"])
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async def post_chat_completions(
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model: str, # make union of all models
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messages: Messages,
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) -> str:
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logger.info(
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f"Received chat completions request for {model} with messages {messages}"
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)
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return f"Hello from {model}!"
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from fastapi import APIRouter
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from logger import getLogger
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logger = getLogger(__name__)
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embeddings_router = APIRouter()
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@embeddings_router.post("/embeddings", tags=["Embeddings"])
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async def post_embeddings(
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model: str,
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input: str | list[str],
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) -> str:
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logger.info(f"Received embeddings request for {model} with input {input}")
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return f"Hello from embeddings {model}!"
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