diff --git a/RAG/.env.sample b/RAG/.env.sample new file mode 100644 index 0000000..5f6fcc9 --- /dev/null +++ b/RAG/.env.sample @@ -0,0 +1,21 @@ +JWT_AUTH_SECRET_KEY=09d25e094faa6ca2556c818166b7a9563b93f7099f6f0f4caa6cf63b88e8d3e7 +DB_TYPE=postgres +POSTGRES_USER=... +POSTGRES_DATABASE=... +POSTGRES_PASSWORD=... +POSTGRES_HOST=... +POSTGRES_PORT=... +GROQ_INFERENCE_API_KEY=gsk_... +TAVILY_API_KEY=tvly-... +LLM_PROVIDER=azure_openai +AZURE_OPENAI_ENDPOINT=https://.openai.azure.com +AZURE_OPENAI_API_KEY=.... +OPENAI_LLM_MODEL_NAME=... +OPENAI_API_VERSION=... +EMBEDDING_MODEL_PROVIDER=azure_openai +OPENAI_EMBEDDING_MODEL_NAME=... +EMBEDDING_DIMENTION=... + +LANGFUSE_SECRET_KEY=... +LANGFUSE_PUBLIC_KEY=... +LANGFUSE_HOST=... \ No newline at end of file diff --git a/RAG/.gitignore b/RAG/.gitignore new file mode 100644 index 0000000..c29b2ed --- /dev/null +++ b/RAG/.gitignore @@ -0,0 +1,175 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# UV +# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +#uv.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/latest/usage/project/#working-with-version-control +.pdm.toml +.pdm-python +.pdm-build/ + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ + +# PyPI configuration file +.pypirc +.secret/ +*.ipynb + +Index/ \ No newline at end of file diff --git a/RAG/.python-version b/RAG/.python-version new file mode 100644 index 0000000..24ee5b1 --- /dev/null +++ b/RAG/.python-version @@ -0,0 +1 @@ +3.13 diff --git a/RAG/.vscode/extensions.json b/RAG/.vscode/extensions.json new file mode 100644 index 0000000..28f106d --- /dev/null +++ b/RAG/.vscode/extensions.json @@ -0,0 +1,17 @@ +{ + "recommendations": [ + "charliermarsh.ruff", + "codezombiech.gitignore", + "cstrap.python-snippets", + "kevinrose.vsc-python-indent", + "mechatroner.rainbow-csv", + "ms-python.black-formatter", + "ms-python.debugpy", + "ms-python.isort", + "ms-python.python", + "njqdev.vscode-python-typehint", + "oderwat.indent-rainbow", + "usernamehw.errorlens", + "ms-python.mypy-type-checker" + ] +} diff --git a/RAG/.vscode/launch.json b/RAG/.vscode/launch.json new file mode 100644 index 0000000..9c7e0d3 --- /dev/null +++ b/RAG/.vscode/launch.json @@ -0,0 +1,13 @@ +{ + "version": "0.2.0", + "configurations": [ + { + "name": "Python Debugger: FastAPI", + "type": "debugpy", + "request": "launch", + "module": "uvicorn", + "args": ["app.main:app", "--reload"], + "jinja": true + } + ] +} diff --git a/RAG/Dockerfile b/RAG/Dockerfile new file mode 100644 index 0000000..e69de29 diff --git a/RAG/README.md b/RAG/README.md new file mode 100644 index 0000000..4e5531d --- /dev/null +++ b/RAG/README.md @@ -0,0 +1,303 @@ +# RAG_General_Template + +A FastAPI project for creating applications using the Retrieval-Augmented Generation (RAG) approach. + + +## Projecr Startup Information +* Run Project via uv : + - As this Project is uv Dependent it will be very easy to run projects with uv. This required installed uv in your global environment. + - Install UV via PIP :`pip install uv` + - Install uv Directly : `powershell -c "irm https://astral.sh/uv/install.ps1 | more"` + - Run Projects :`uv run uvicorn main:app --reload` + +* Run Project Without uv : + - Create Python Virtual env using venv : `python -m venv env` + - Activate Virtual env : `.\env\Scripts\activate` + - Install Dependencies : `pip install -r requirements.txt` + - Run Projects :`uvicorn main:app --reload` + + +## Additional Setup Information + +* Database : + - Setup Postgresql Database in your local or Server and add Cred into .env file or Environment Variable + - Setup the DB_TYPE variable with database name `postgres` +* Monitoring Tool : + - Use **Langfuse** as monitoring Tools add Langfuse config on env + - Setup langfuse on Docker or use langfuse cloud url : [text](https://cloud.langfuse.com/) +## Folder Structure + +```plaintext +RAG_General_Template/ +├── app/ # Main application logic. +│ ├── main.py # Entry point of the application. +│ ├── __init__.py # Package marker. +│ ├── config/ # Application configurations (settings, logging). +│ │ ├── settings.py # Configuration settings. +│ │ ├── logging_config.py # Logging configuration. +│ ├── core/ # Core functionalities (authentication, constants). +│ │ ├── auth.py # Authentication logic. +│ │ ├── constants.py # Core constants. +│ ├── db/ # Database setup and ORM models. +│ │ ├── models/ # ORM models for database tables. +│ │ │ ├── chat_history.py # Chat history model. +│ │ │ ├── user.py # User model. +│ ├── routes/ # API endpoint route definitions. +│ │ ├── conversation.py # Conversation-related routes. +│ │ ├── users.py # User-related routes. +│ ├── schemas/ # Pydantic schemas for data validation. +│ │ ├── auth.py # Authentication schemas. +│ │ ├── chat.py # Chat-related schemas. +│ │ ├── user.py # User schemas. +│ ├── services/ # Service layer for business logic. +│ │ ├── RAG/ # RAG component services. +│ │ │ ├── document_parser.py # Document parsing logic. +│ │ │ ├── llm_search.py # Language model search logic. +│ │ │ ├── prompts.py # Prompt management. +│ │ │ ├── vectorstore.py # Vector storage management. +│ ├── tests/ # Unit and integration tests. +│ │ ├── test_items.py # Tests for item routes. +│ │ ├── test_users.py # Tests for user routes. +├── scripts/ # Utility scripts. +├── pyproject.toml # PyProject TOML file. +├── .gitignore # Git ignore file. +├── requirements.txt # Project dependencies. +└── README.md # Project README file. +``` +## Project Overview + +This project provides a template for creating applications using the Retrieval-Augmented Generation (RAG) approach. It includes various components for handling AI-driven interactions, data storage, and API endpoints. + +## Detailed Module Description + +### app/main.py +The main entry point of the application. It initializes the FastAPI app and configures routes and middleware. + +### app/config/ +Contains configuration files for settings and logging. + +- **settings.py**: + This file contains configuration settings for the application, such as environment variables and constants. Key features include: + - **Environment Variables**: Utilizes the `dotenv` package to load environment variables, ensuring that critical settings like `JWT_AUTH_SECRET_KEY`, `TAVILY_API_KEY`, and database credentials are securely managed. + - **Database Configuration**: Supports both PostgreSQL and SQLite, dynamically configuring the SQLAlchemy database URL based on the `DB_TYPE` environment variable. + - **Security Settings**: Configures JWT authentication settings, including the secret key and algorithm. + - **API Keys and Hosts**: Manages API keys and host configurations for external services like `LANGFUSE`. +- **logging_config.py**: Configures logging for the application. + +### app/core/ +This module contains core functionalities such as authentication and constants. Key features include: + +- **auth.py**: + - Defines authentication-related API endpoints and helper functions. + - Implements password hashing and verification using `passlib`. + - Provides JWT-based authentication mechanisms, including token creation and user authentication. + - Includes functions to check if an email or username is already taken in the database. +- **constants.py**: + - Contains constant values used across the core module, ensuring consistency and reducing hard-coded values. +- **dependencies.py**: Manages dependency injection. +- **events.py**: Handles application events. + +### app/db/ +This module is responsible for setting up the database and defining the ORM models using SQLAlchemy. It includes the following components: + +- **Base Class**: All ORM models inherit from the `Base` class, which is configured in the settings module. This serves as the declarative base for SQLAlchemy models. + +- **Models**: The `models` directory contains the ORM models that define the database schema. + + - **chat_history.py**: + - Defines the `Conversation` model, which represents chat history. + - Contains fields such as `conversation_id`, `user_id`, and `history`. + - Establishes a relationship with the `User` model, allowing for easy retrieval of user-related conversation history. + + - **user.py**: + - Defines the `User` model, which represents user data. + - Contains fields such as `user_id`, `username`, `email`, and `_password_hash`. + - Establishes a relationship with the `Conversation` model, enabling user-specific conversation tracking. + +These models are crucial for managing user data and chat history within the application, providing a structured way to interact with the database. + +### app/routes/ +This module defines the API endpoint routes for the application, handling various user and conversation-related functionalities. It includes: + +- **conversation.py**: + - Manages conversation-related routes, allowing users to interact with their chat history. + - **Endpoints**: + - `GET /conversations`: Retrieves a list of conversations for the current user. + - `GET /conversations/{id}`: Retrieves a specific conversation by ID. + - `POST /conversations`: Creates a new conversation and processes user queries. + +- **users.py**: + - Handles user-related routes, including user creation and authentication. + - **Endpoints**: + - `POST /users`: Creates a new user account, ensuring unique email and username. + - `POST /login`: Authenticates a user and returns an access token. + - `GET /users/me`: Retrieves the current user's information. + - `POST /upload`: Allows users to upload files, which are processed and stored. + +These routes are essential for managing user interactions and data flow within the application, providing a structured way to handle API requests. + +### app/schemas/ +Pydantic schemas for data validation. + +- **auth.py**: Authentication schemas. +- **chat.py**: Chat-related schemas. +- **user.py**: User data schemas. + +### app/services/ +Service layer for business logic. + +- **RAG/document_parser.py**: Parses documents for RAG processing. +- **RAG/llm_search.py**: Manages language model search operations. +- **RAG/prompts.py**: Handles prompt management for interactions. +- **RAG/vectorstore.py**: Manages vector storage for embeddings. + +#### app/services/RAG/ +This module is the heart of the Retrieval-Augmented Generation (RAG) system, providing essential services for document processing, language model interactions, and vector storage. It includes: + +- **document_parser.py**: + - Provides functionality to parse PDF documents and extract text from each page. + - **Functions**: + - `parse_documents`: Parses PDF content and extracts text, returning a list of Document objects with metadata. + - `context_parser_input`: Converts Document objects into context strings with XML-like tags. + - `context_parser_output`: Extracts content and metadata from context strings. + +- **llm_search.py**: + - Manages interactions with language models to process queries and retrieve relevant document chunks. + - **Functions**: + - `get_relevent_chunks`: Filters retrieved document chunks based on relevance to the language model response. + - `get_llm_response`: Retrieves relevant document chunks and invokes the language model to generate a response. + +- **prompts.py**: + - Contains prompt templates for guiding language model interactions. + - **Features**: + - `default_template_prompt`: A template for generating responses based on provided context and metadata. + +- **vectorstore.py**: + - Handles vector storage operations using FAISS for efficient similarity searches. + - **Functions**: + - `save_on_vector_store`: Saves documents to a FAISS vector store for later retrieval. + - `similarity_search`: Performs similarity searches to find documents related to a query. + - `validate_index_path`: Ensures the validity of the index path used for vector storage. + +This module is crucial for enabling the RAG capabilities of the application, allowing it to efficiently process documents, interact with language models, and store/retrieve data using vector embeddings. + + +## Best Practice Tools + +This section outlines the key tools used in our project for code formatting, linting, and type checking. Each tool is configured to maintain code quality and consistency across the project. + +### Black: Python Code Formatter + +Black is an opinionated code formatter that ensures consistent code style across your project. It's designed to be uncompromising, requiring minimal configuration. + +- **GitHub**: [Black on GitHub](https://github.com/psf/black) +- **Documentation**: [Black Documentation](https://black.readthedocs.io/en/stable/) + +#### Configuration in `pyproject.toml` + +```toml +[tool.black] +line-length = 88 +skip-string-normalization = true +exclude = '''/( + \.git + | \.mypy_cache + | \.venv + | \.venv2 + | \.venv3 + | build + | dist + | alembic +)/''' +``` + +**Explanation**: + +- `line-length = 88`: Sets the maximum line length to 88 characters, which is Black's default. +- `skip-string-normalization = true`: Prevents Black from converting all string quotes to double quotes. +- `exclude`: Specifies directories and files that Black should not format. This includes version control, cache directories, virtual environments, and build artifacts. + +### Ruff: Fast Python Linter + +Ruff is a high-performance Python linter written in Rust. It can replace multiple traditional Python linters and fixers, offering significant speed improvements. + +- **GitHub**: [Ruff on GitHub](https://github.com/charliermarsh/ruff) +- **Documentation**: [Ruff Documentation](https://beta.ruff.rs/docs/) + +#### Configuration in `pyproject.toml` + +```toml +[tool.ruff] +line-length = 88 +select = ["E", "F", "B", "W", "I", "C", "N"] +ignore = ["E501"] +exclude = [ + ".git", + ".mypy_cache", + ".venv", + ".venv2", + ".venv3", + "build", + "dist", + "alembic/**/*", + "*/__init__.py" +] + +[tool.ruff.per-file-ignores] +"__init__.py" = ["F401"] + +[tool.ruff.isort] +known-third-party = ["fastapi", "pydantic", "sqlalchemy"] +``` + +**Explanation**: + +- `line-length = 88`: Matches Black's default line length for consistency. +- `select`: Enables specific rule sets: + - `E`: pycodestyle errors + - `F`: Pyflakes + - `B`: flake8-bugbear + - `W`: pycodestyle warnings + - `I`: isort + - `C`: mccabe complexity + - `N`: pep8-naming +- `ignore = ["E501"]`: Disables the line length check (E501) as it's handled by Black. +- `exclude`: Lists directories and files to be ignored by Ruff. +- `per-file-ignores`: Specifies rules to ignore for specific files. Here, unused imports (F401) are allowed in `__init__.py` files. +- `isort`: Configures import sorting, specifying known third-party libraries. + +### mypy: Static Type Checker + +mypy is an optional static type checker for Python that helps catch type-related errors before runtime. + +- **GitHub**: [mypy on GitHub](https://github.com/python/mypy) +- **Documentation**: [mypy Documentation](https://mypy.readthedocs.io/en/stable/) + +#### Configuration in `pyproject.toml` + +```toml +[tool.mypy] +strict = true +disallow_untyped_defs = false +ignore_missing_imports = true +warn_unused_ignores = true +ignore_errors = false +exclude = '.*/__init__.py' + +[[tool.mypy.overrides]] +module = ["fastapi", "pydantic", "sqlalchemy"] +ignore_missing_imports = true +``` + +**Explanation**: + +- `strict = true`: Enables strict type checking for maximum type safety. +- `disallow_untyped_defs = false`: Allows functions without type annotations. +- `ignore_missing_imports = true`: Ignores errors from missing type stubs for third-party libraries. +- `warn_unused_ignores = true`: Warns about unnecessary ignore comments. +- `ignore_errors = false`: Ensures mypy reports all type errors. +- `exclude = '.*/__init__.py'`: Excludes `__init__.py` files from type checking. +- `overrides`: Specifies settings for specific modules, here ignoring missing imports for FastAPI, Pydantic, and SQLAlchemy. + +These configurations ensure consistent code style, catch potential errors early, and maintain a high standard of code quality across the project. + diff --git a/RAG/app/__init__.py b/RAG/app/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/RAG/app/config/__init__.py b/RAG/app/config/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/RAG/app/config/logging_config.py b/RAG/app/config/logging_config.py new file mode 100644 index 0000000..05c2a68 --- /dev/null +++ b/RAG/app/config/logging_config.py @@ -0,0 +1,79 @@ +""" +This file defines the logging configuration for the application. +""" +import logging + +import colorlog + + +def create_console_handler(): + """ + Create a console handler for logging. + + Returns: + logging.StreamHandler: A console handler for logging. + + This function creates a console handler for logging. It sets the log level to DEBUG and configures a colored formatter + with custom log colors for different log levels. The formatter formats the log message with the log color, timestamp, + logger name, log level, and message. The function then sets the formatter on the console handler and returns it. + """ + console_handler = logging.StreamHandler() + console_handler.setLevel(logging.DEBUG) + + formatter = colorlog.ColoredFormatter( + "%(log_color)s%(asctime)s - %(name)s - %(levelname)s - %(message)s", + datefmt="%Y-%m-%d %H:%M:%S", + log_colors={ + "DEBUG": "cyan", + "INFO": "green", + "WARNING": "yellow", + "ERROR": "red", + "CRITICAL": "red,bg_white", + }, + ) + console_handler.setFormatter(formatter) + return console_handler + + + +def get_logger(name: str): + """ + Returns a logger object with the specified name. + + Parameters: + name (str): The name of the logger. + + Returns: + logging.Logger: A logger object with the specified name. + + This function creates a logger object with the specified name and sets its log level to the value of the + environment variable. It also adds a console handler and a Seq handler (if enabled) to the logger. If file logging is + enabled, it adds a file handler to the logger. The function returns the logger object. + """ + logger = logging.getLogger(name) + + # if not logger.handlers: + logger.setLevel("INFO") + console_handler = create_console_handler() + + logger.addHandler(console_handler) + return logger + + +def log_startup_to_console(): + """ + Logs the startup information to the console. + + This function creates a logger object for the "startup" name and sets its log level to the value of the + environment variable. It then logs the value of using the info level. If seq_enabled() returns True, + it logs "Seq log enabled". If file_enabled() returns True, it logs "File logging enabled". + + Returns: + None + """ + startup_logger = get_logger("startup") + startup_logger.info("Starting up LOGS...") + +log_startup_to_console() + +logger = get_logger(__name__) diff --git a/RAG/app/config/settings.py b/RAG/app/config/settings.py new file mode 100644 index 0000000..1da55fc --- /dev/null +++ b/RAG/app/config/settings.py @@ -0,0 +1,115 @@ +""" +This file contains configuration settings for the application, +such as environment variables and constants. +""" +import os +from pathlib import Path + +from dotenv import main +from pydantic import SecretStr +from sqlalchemy import create_engine +from sqlalchemy.ext.declarative import declarative_base +from sqlalchemy.orm import sessionmaker + +main.load_dotenv() + +def load_env_var_strict(name: str) -> str: + """Loads an environment variable and raises an error if not set.""" + value = os.getenv(name) + if value is None: + raise ValueError(f"Environment variable {name} is not set") + return value + +## Loading Environment Variables +JWT_AUTH_SECRET_KEY = load_env_var_strict('JWT_AUTH_SECRET_KEY') +ALGORITHM = "HS256" +ACCESS_TOKEN_EXPIRE_MINUTES = 50 + +## Configuration Settings +DB_TYPE = os.getenv("DB_TYPE", "sqlite").lower() +BASE_DIR = Path(__file__).resolve().parent.parent + +if DB_TYPE == "postgres": + # PostgreSQL Database Configuration + POSTGRES_USER = load_env_var_strict('POSTGRES_USER') + POSTGRES_DATABASE = load_env_var_strict('POSTGRES_DATABASE') + POSTGRES_PASSWORD = load_env_var_strict('POSTGRES_PASSWORD') + POSTGRES_HOST = load_env_var_strict('POSTGRES_HOST') + POSTGRES_PORT = load_env_var_strict('POSTGRES_PORT') + SQLALCHEMY_DATABASE_URL = f"postgresql://{POSTGRES_USER}:{POSTGRES_PASSWORD}@{POSTGRES_HOST}:{POSTGRES_PORT}/{POSTGRES_DATABASE}" +else: + # SQLite Database Configuration + SQLALCHEMY_DATABASE_URL = f"sqlite:///{BASE_DIR}/db.sqlite3" + +## Loading Environments Variable +TAVILY_API_KEY = load_env_var_strict('TAVILY_API_KEY') + + + +LANGFUSE_SECRET_KEY = load_env_var_strict('LANGFUSE_SECRET_KEY') +LANGFUSE_PUBLIC_KEY = load_env_var_strict('LANGFUSE_PUBLIC_KEY') +LANGFUSE_HOST = os.getenv('LANGFUSE_HOST', 'http://localhost:3000') + +# Langfuse Configuration +LANGFUSE_CONFIG = { + 'secret_key': LANGFUSE_SECRET_KEY, + 'public_key': LANGFUSE_PUBLIC_KEY, + 'host': LANGFUSE_HOST +} +from langfuse.callback import CallbackHandler + +langfuse_handler = CallbackHandler(**LANGFUSE_CONFIG) + + +# ORM Engine Configuration +engine = create_engine(SQLALCHEMY_DATABASE_URL, connect_args={"check_same_thread": False} if DB_TYPE == "sqlite" else {}) +SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine) + +# Base ORM Model +Base = declarative_base() +Base.metadata.create_all(bind=engine) + +# DB Utilities +def get_session(): + ''' Return Database ORM Session Object''' + db = SessionLocal() + try: + yield db + finally: + db.close() + + +AGENT_CONFIG_RUNABLE = {"thread_id": 42} +DEFAULT_INDEX_PATH = load_env_var_strict("DEFAULT_INDEX_PATH") +DEFAULT_INDEX_PATH = BASE_DIR/DEFAULT_INDEX_PATH +RELEVENCY_CHECK_MODEL = "cross-encoder/ms-marco-MiniLM-L-6-v2" +RELEVENCY_SCORE_THRESH=0.7 +### LLM Model Configuration +LLM_PROVIDER=load_env_var_strict('LLM_PROVIDER') +if LLM_PROVIDER=='groq': + GROQ_API_KEY = load_env_var_strict('GROQ_INFERENCE_API_KEY') + GROQ_MODEL_NAME = "mixtral-8x7b-32768" + from langchain_groq import ChatGroq + default_llm_model = ChatGroq(model=GROQ_MODEL_NAME, + temperature=0.3, api_key=SecretStr(GROQ_API_KEY)) + +elif LLM_PROVIDER=='azure_openai': + OPENAI_MODEL_NAME = 'gpt-4o' + AZURE_OPENAI_ENDPOINT = load_env_var_strict('AZURE_OPENAI_ENDPOINT') + from langchain_openai import AzureChatOpenAI + default_llm_model = AzureChatOpenAI(model_name="gpt-4o" ) + +EMBEDDING_MODEL_PROVIDER = load_env_var_strict('EMBEDDING_MODEL_PROVIDER') +# Embedding Model Configuration +if EMBEDDING_MODEL_PROVIDER=="azure_openai": + model_name=load_env_var_strict('OPENAI_EMBEDDING_MODEL_NAME') + from langchain_openai import AzureOpenAIEmbeddings + embed_model = AzureOpenAIEmbeddings(model=model_name) + EMBEDDING_MODEL_VECTOR_LENGTH=int(load_env_var_strict("EMBEDDING_DIMENTION")) +else: + from langchain_huggingface import HuggingFaceEmbeddings + + embed_model = HuggingFaceEmbeddings(model_name="Alibaba-NLP/gte-base-en-v1.5", + model_kwargs = {'trust_remote_code': True}) + EMBEDDING_MODEL_VECTOR_LENGTH = len(embed_model.embed_query("Hello World")) + diff --git a/RAG/app/constants.py b/RAG/app/constants.py new file mode 100644 index 0000000..caf252c --- /dev/null +++ b/RAG/app/constants.py @@ -0,0 +1,21 @@ +from enum import StrEnum + +AUTH_HEADER={"WWW-Authenticate": "Bearer"} + +class TokenType(StrEnum): + BEARER="bearer" + +GENERAL_TYPE_ERROR="data must be a {} model" +ALLOWED_FILE_TYPES = ['pdf','docx'] + +class LoggingMessages: + FUNCTION_START = "Process of function started." + FUNCTION_END = "Process of function ended." + APPLICATION_STARTED = "Application started." + START_CONVERSATION = "Conversation Endpoint has been called " + EMBEDDING_STARTED = "Embedding Started for File %s" + EMBEDDING_ENDED = "Embedding ended for the file %s " + DOCUMENT_PARSER_STTARTED = "Document Parsing is started" + DOCUMENT_PARSER_END = "Document Parsing is end " + LLM_CALL_INNITIATE="Message has been send to LLM Model" + LLM_RESPONSE_RECIEVED="LLM Response has been recieved successfully" \ No newline at end of file diff --git a/RAG/app/core/__init__.py b/RAG/app/core/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/RAG/app/core/auth.py b/RAG/app/core/auth.py new file mode 100644 index 0000000..99c44d7 --- /dev/null +++ b/RAG/app/core/auth.py @@ -0,0 +1,90 @@ +""" +Defines authentication-related API endpoints. +""" +from datetime import datetime, timedelta, timezone +from typing import Annotated + +from fastapi import Depends, HTTPException, status +from fastapi.security import OAuth2PasswordBearer +from jose import JWTError, jwt +from passlib.context import CryptContext +from pydantic import EmailStr +from sqlalchemy.orm import Session + +from app import constants as global_constant +from app.config.settings import ALGORITHM, JWT_AUTH_SECRET_KEY, Base, get_session +from app.core import constants as core_constant +from app.db.models.user import User +from app.routes.constants import RoutingPoints +from app.schemas.auth import TokenEncode + +oauth2_scheme = OAuth2PasswordBearer(tokenUrl=RoutingPoints.LOGIN_USER) +pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto") + + +def is_email_or_username_taken(email: EmailStr, + username:str, model:Base , session:Session ) -> bool | str: + '''check in database the given email is already exist or not + input: + email : Email String + model : model or table where to check + session : SQLAlchemy Database Session Utility + return str: + return 'email' if email exist + return 'username' if username exist + return None for new user + ''' + existing_object = session.query(model).filter_by(email=email).first() + if existing_object: + return core_constant.USER_ID.EMAIL + existing_object = session.query(model).filter_by(username=username).first() + if existing_object: + return core_constant.USER_ID.USERNAME + return False +## Helper Functions +def verify_password(plain_password, hashed_password): + """Password Verification by converting Hash""" + return pwd_context.verify(plain_password, hashed_password) + + +def get_password_hash(password): + """Return Hash of any string """ + return pwd_context.hash(password) + + +def authenticate_user(username: str, password: str, session:Session): + """Authenticated an user""" + if user := session.query(User).filter_by(username=username).first(): + return user if verify_password(password, user._password_hash) else False + else: + return False + + +def create_access_token(data: TokenEncode, expires_delta: timedelta | None = None): + """Create Access Token usning Openssl Secret key """ + if not isinstance(data, TokenEncode): + raise TypeError(global_constant.GENERAL_TYPE_ERROR.format(type(TokenEncode))) + if expires_delta: + expire = datetime.now(timezone.utc) + expires_delta + else: + expire = datetime.now(timezone.utc) + timedelta(minutes=15) + data.exp = expire + return jwt.encode(data.model_dump(), JWT_AUTH_SECRET_KEY, algorithm=ALGORITHM) + +async def get_current_user(token: Annotated[str, Depends(oauth2_scheme)],session:Session=Depends(get_session)): + """Authenticate user and return current user if authentication success""" + credentials_exception = HTTPException( + status_code=status.HTTP_401_UNAUTHORIZED, + detail=core_constant.MSG_INVALID_CREDENTIALS, + headers=global_constant.AUTH_HEADER, + ) + try: + payload = jwt.decode(token, JWT_AUTH_SECRET_KEY, algorithms=[ALGORITHM]) + username: str = payload.get("sub") + if username is None: + raise credentials_exception + except JWTError as e: + raise credentials_exception from e + if user := session.query(User).filter_by(username=username).first(): + return user + raise credentials_exception diff --git a/RAG/app/core/constants.py b/RAG/app/core/constants.py new file mode 100644 index 0000000..7974f56 --- /dev/null +++ b/RAG/app/core/constants.py @@ -0,0 +1,7 @@ +from enum import StrEnum + +MSG_INVALID_CREDENTIALS="Could not validate credentials" +class USER_ID(StrEnum): + USERNAME = 'username' + EMAIL = 'email' + diff --git a/RAG/app/db/__init__.py b/RAG/app/db/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/RAG/app/db/models/__init__.py b/RAG/app/db/models/__init__.py new file mode 100644 index 0000000..74e5ee3 --- /dev/null +++ b/RAG/app/db/models/__init__.py @@ -0,0 +1,2 @@ +from app.db.models.user import User +from app.db.models.chat_history import Conversation diff --git a/RAG/app/db/models/chat_history.py b/RAG/app/db/models/chat_history.py new file mode 100644 index 0000000..70141a2 --- /dev/null +++ b/RAG/app/db/models/chat_history.py @@ -0,0 +1,16 @@ +"""Database ORM models for Chat History.""" + +from sqlalchemy import JSON, Column, ForeignKey, Integer +from sqlalchemy.orm import relationship + +from app.config.settings import Base + +'''This module contains All the SQLAlchemy Database Schemas or Model +''' + +class Conversation(Base): + __tablename__ = "conversation" + conversation_id = Column(Integer, primary_key= True,autoincrement=True) + user_id = Column(Integer, ForeignKey('user.user_id'), nullable=False) + history = Column(JSON, nullable=False) + user = relationship('User', back_populates='conversation') diff --git a/RAG/app/db/models/user.py b/RAG/app/db/models/user.py new file mode 100644 index 0000000..4237dd9 --- /dev/null +++ b/RAG/app/db/models/user.py @@ -0,0 +1,20 @@ +""" +Database ORM models for users. +""" +from sqlalchemy import Column, Integer, String +from sqlalchemy.orm import relationship + +from app.config.settings import Base + +'''This module contains All the SQLAlchemy Database Schemas or Model +''' + + + +class User(Base): + __tablename__ = "user" + user_id = Column(Integer, primary_key= True,autoincrement=True) + username = Column(String(100),unique=True,nullable=False) + email = Column(String(100),unique=True, index= True, nullable= False ) + _password_hash = Column(String(200), nullable=False) + conversation = relationship('Conversation', back_populates='user') diff --git a/RAG/app/main.py b/RAG/app/main.py new file mode 100644 index 0000000..5ae8771 --- /dev/null +++ b/RAG/app/main.py @@ -0,0 +1,33 @@ +""" +Main FastAPI application file. +Define your FastAPI app and include routers here. +""" +from fastapi import FastAPI + +from app.config.settings import Base, engine +from app.routes.conversation import conversation_routes +from app.routes.users import user_route +from app.config.logging_config import logger, get_logger +from app.constants import LoggingMessages +app = FastAPI() + +# Include your routers here +# from app.routes import users, items +app.include_router(user_route) +app.include_router(conversation_routes) +logger.info(LoggingMessages.APPLICATION_STARTED) + + +Base.metadata.create_all(bind=engine) + +@app.get("/") +async def root(): + # logger.info(LoggingMessages.APPLICATION_STARTED) + logger = get_logger(__name__) + logger.info("Hii I am Great") + '''Root Endpoint''' + return {"message": "View /docs for Documentation "} + +if __name__ == "__main__": + import uvicorn + uvicorn.run(app, host="0.0.0.0", port=8000) diff --git a/RAG/app/routes/__init__.py b/RAG/app/routes/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/RAG/app/routes/constants.py b/RAG/app/routes/constants.py new file mode 100644 index 0000000..a263235 --- /dev/null +++ b/RAG/app/routes/constants.py @@ -0,0 +1,27 @@ +class RoutingPoints: + '''Contains Routing Constant''' + CREATE_USER = '/user' + LOGIN_USER = '/login' + GET_USER = '/user' + CREATE_NEW_CONVERSATION='/conversation' + GET_CONVERSATION_LIST='/conversation' + GET_CONVERSATION='/conversation/{conversation_id}' + CHAT_CONVERSATION='/conversation/{conversation_id}' + UPLOAD_DOCUMENT='/upload' + +class RoutingCategory: + '''contains Catagory of Routing Points''' + AUTH = 'User Auth' + VIEW = 'View User' + CONVERSATION= "Chat Conversation" + UPLOAD= ' Document Upload' + +class ErrorMessages: + '''Containd Constant Error Messages ''' + EMAIL_ALREADY_TAKEN = 'email is already taken' + USERNAME_ALREADY_TAKEN = 'username is already taken' + ALREADY_TAKEN = "{} is already Taken" + INCORRECT_CREDENTIALS = "Incorrect username or password" + CONVERSATION_NOT_EXIST= 'Conversation not exist' + EMPTY_FILENAME_ERROR="File name is empty" + INDEX_NOT_FOUND= "Index is not found" diff --git a/RAG/app/routes/conversation.py b/RAG/app/routes/conversation.py new file mode 100644 index 0000000..4cae52e --- /dev/null +++ b/RAG/app/routes/conversation.py @@ -0,0 +1,89 @@ +from typing import Annotated + +from fastapi import APIRouter, Depends, HTTPException +from sqlalchemy.orm import Session + +from app.config.logging_config import logger +from app.config.settings import get_session +from app.constants import LoggingMessages +from app.core.auth import get_current_user +from app.db.models import Conversation +from app.routes.constants import ErrorMessages, RoutingCategory, RoutingPoints +from app.schemas.chat import AIChat, ChatResponse, HumanChat, Query +from app.schemas.user import User as UserSchema +from app.services.RAG.llm_search import get_llm_response + +conversation_routes = APIRouter() + +@conversation_routes.get(RoutingPoints.GET_CONVERSATION_LIST,tags=[RoutingCategory.CONVERSATION ]) +async def get_chat(current_user: Annotated[UserSchema, Depends(get_current_user)], + session:Session=Depends(get_session)): + + try: + conversation_list = session.query(Conversation).filter( + Conversation.user_id==current_user.user_id).all() + return conversation_list + except Exception as e: + raise HTTPException(status_code=500, detail= f'{e}') + + + +@conversation_routes.get(RoutingPoints.GET_CONVERSATION,tags=[RoutingCategory.CONVERSATION ]) +async def get_chat(conversation_id:int, + current_user: Annotated[UserSchema, Depends(get_current_user)], + session:Session=Depends(get_session)): + + try: + if conversation := session.query(Conversation).filter( + Conversation.user_id == current_user.user_id).filter( + Conversation.conversation_id==conversation_id).first(): + return conversation + else: + raise HTTPException(status_code=404, detail = ErrorMessages.CONVERSATION_NOT_EXIST) + except : + raise HTTPException(status_code=404, detail=ErrorMessages.CONVERSATION_NOT_EXIST) + + + +@conversation_routes.post(RoutingPoints.CREATE_NEW_CONVERSATION,tags=[RoutingCategory.CONVERSATION ]) +async def ask_question(query:Query, current_user: Annotated[UserSchema,Depends(get_current_user)], + session:Session=Depends(get_session)): + + chat_history= [] + response = get_llm_response(query.question, current_user.user_id) + + chat_history += [ + HumanChat(content=response['query']), + AIChat(content=response['answer'],resources=response['resource']) + ] + chat_history_json = [chat.model_dump() for chat in chat_history] + conversation = Conversation(user_id=current_user.user_id , history=chat_history_json) + session.add(conversation) + session.commit() + session.refresh(conversation) + return ChatResponse(answer=response['answer'], references= response['resource'], conversation_id=conversation.conversation_id) + + + +@conversation_routes.post(RoutingPoints.CHAT_CONVERSATION,tags=[RoutingCategory.CONVERSATION ]) +async def ask_question(conversation_id : int, query:Query, + current_user: Annotated[UserSchema,Depends(get_current_user)], + session:Session=Depends(get_session)): + logger.info(LoggingMessages.START_CONVERSATION) + conversation = session.query(Conversation).filter( + Conversation.conversation_id==conversation_id and + Conversation.user_id == current_user.user_id).first() + chat_history_json = conversation.history + response = get_llm_response(query.question, current_user.user_id) + chat_history = [ + HumanChat(content=response['query']), + AIChat(content=response['answer'],resources=response['resource']) + ] + chat_history_json += [chat.model_dump() for chat in chat_history] + conversation.history = chat_history_json + session.add(conversation) + session.commit() + session.refresh(conversation) + return ChatResponse(answer=response['answer'], + references=response['resource'], + conversation_id=conversation.conversation_id) diff --git a/RAG/app/routes/users.py b/RAG/app/routes/users.py new file mode 100644 index 0000000..918c1ff --- /dev/null +++ b/RAG/app/routes/users.py @@ -0,0 +1,80 @@ +'''This module Contains all Routing Points functions related to Users ''' + +from datetime import timedelta +from typing import Annotated + +from fastapi import APIRouter, Depends, File, HTTPException, UploadFile, status +from fastapi.security import OAuth2PasswordRequestForm +from sqlalchemy.orm import Session + +from app import constants as global_constant +from app.config.logging_config import logger +from app.config.settings import ACCESS_TOKEN_EXPIRE_MINUTES, get_session +from app.constants import LoggingMessages +from app.core.auth import ( + authenticate_user, + create_access_token, + get_current_user, + get_password_hash, + is_email_or_username_taken, +) +from app.db import models +from app.routes.constants import ErrorMessages, RoutingCategory, RoutingPoints +from app.schemas import user as schemas +from app.schemas.auth import Token, TokenEncode +from app.services.RAG.document_parser import parse_documents +from app.services.RAG.vectorstore import save_on_vector_store + +user_route = APIRouter() + +@user_route.post(RoutingPoints.CREATE_USER, tags=[RoutingCategory.AUTH]) +async def create(user:schemas.UserCreate, session:Session = Depends(get_session)): + '''Create New User''' + if validate_entity := is_email_or_username_taken(user.email,user.username, models.user.User,session): + raise HTTPException(status_code=400, detail=ErrorMessages.ALREADY_TAKEN.format(validate_entity)) + new_user = models.user.User(email = user.email,username= user.username, + _password_hash = get_password_hash(user.password) ) + session.add(new_user) + session.commit() + session.refresh(new_user) + access_token_expires = timedelta(minutes=ACCESS_TOKEN_EXPIRE_MINUTES) + access_token = create_access_token( + data=TokenEncode(sub = user.username), expires_delta=access_token_expires) + return Token(access_token=access_token, token_type=global_constant.TokenType.BEARER) + +@user_route.post(RoutingPoints.LOGIN_USER, tags=[RoutingCategory.AUTH] ) +async def login_for_access_token( + form_data: Annotated[OAuth2PasswordRequestForm, Depends()], + session: Session = Depends(get_session) + ) -> Token: + '''Return Access Token for Login User ''' + user = authenticate_user(form_data.username, form_data.password, session) + if not user: + raise HTTPException( + status_code=status.HTTP_401_UNAUTHORIZED, + detail=ErrorMessages.INCORRECT_CREDENTIALS, + headers=global_constant.AUTH_HEADER, + ) + access_token_expires = timedelta(minutes=ACCESS_TOKEN_EXPIRE_MINUTES) + access_token = create_access_token( + data=TokenEncode(sub = user.username), expires_delta=access_token_expires + ) + return Token(access_token=access_token, token_type=global_constant.TokenType.BEARER) + +@user_route.get(RoutingPoints.GET_USER, response_model=schemas.User,tags=[RoutingCategory.VIEW]) +async def read_users_me(current_user: Annotated[schemas.User,Depends(get_current_user)]): + result = current_user + return result + +@user_route.post(RoutingPoints.UPLOAD_DOCUMENT, tags=[RoutingCategory.UPLOAD]) +async def upload_file( current_user: Annotated[schemas.User,Depends(get_current_user)], + file: UploadFile = File(...)): + if not file.filename : + raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, + detail=ErrorMessages.EMPTY_FILENAME_ERROR) + documents = parse_documents(await file.read(), file.filename, file.content_type, + file_metadata={'user_name':current_user.username}) + logger.info(LoggingMessages.EMBEDDING_STARTED%file.filename) + save_on_vector_store(documents,current_user.user_id) + logger.info(LoggingMessages.EMBEDDING_ENDED%file.filename) + return {'message':'File uploaded and Index successfully'} diff --git a/RAG/app/schemas/__init__.py b/RAG/app/schemas/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/RAG/app/schemas/auth.py b/RAG/app/schemas/auth.py new file mode 100644 index 0000000..f1a77cf --- /dev/null +++ b/RAG/app/schemas/auth.py @@ -0,0 +1,19 @@ +""" +Pydantic schemas for auth-related operations. +""" +from datetime import datetime + +from pydantic import BaseModel + + +class SessionData(BaseModel): + username: str + + +class Token(BaseModel): + access_token: str + token_type: str + +class TokenEncode(BaseModel): + sub: str | None = None + exp:datetime | None = None diff --git a/RAG/app/schemas/chat.py b/RAG/app/schemas/chat.py new file mode 100644 index 0000000..e862f84 --- /dev/null +++ b/RAG/app/schemas/chat.py @@ -0,0 +1,25 @@ +'''Pydantic schemas for chat related operations. ''' + +from typing import List + +from pydantic import BaseModel + + +class Query(BaseModel): + '''Query Schema''' + question:str + +class ChatResponse(BaseModel): + '''Chat Response Schema''' + answer:str + references : List[dict|str] | None + conversation_id:int + +class HumanChat(BaseModel): + role:str = 'USER' + content:str + +class AIChat(BaseModel): + role:str = 'AI' + content:str + resources:List[dict|str] | None diff --git a/RAG/app/schemas/user.py b/RAG/app/schemas/user.py new file mode 100644 index 0000000..d0ea2c4 --- /dev/null +++ b/RAG/app/schemas/user.py @@ -0,0 +1,20 @@ +""" +Pydantic schemas for user-related operations. +""" +from pydantic import BaseModel, EmailStr + + +class User(BaseModel): + '''Schemas to validate User to match with Database Table''' + user_id:int + username: str + email: str + class Config: + '''match ORM model''' + from_attribute = True + +class UserCreate(BaseModel): + '''Schemas to validate User Data on Post Request''' + username: str + email: EmailStr + password:str diff --git a/RAG/app/services/RAG/__init__.py b/RAG/app/services/RAG/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/RAG/app/services/RAG/document_parser.py b/RAG/app/services/RAG/document_parser.py new file mode 100644 index 0000000..3ad4def --- /dev/null +++ b/RAG/app/services/RAG/document_parser.py @@ -0,0 +1,104 @@ +''' +This module provides functionality to parse PDF documents and extract text from each page. +Functions: + parse_documents(file_content: bytes, filename: str | None = 'unknown', filetype: str = 'pdf') -> list: + +''' +import io +import re +from typing import Dict, List +from uuid import uuid4 + +import pymupdf +from langchain_core.documents import Document +from langchain_text_splitters import RecursiveCharacterTextSplitter + +from app.config.logging_config import logger +from app.constants import LoggingMessages + + +def parse_documents(file_content:bytes, filename:str | None = 'unknown', filetype:str='pdf', file_metadata:dict = {}): + """ + Parses the content of a PDF document from bytes and extracts text from each page. + Args: + file_content (bytes): The content of the PDF file in bytes. + filename (str, optional): The name of the file. Defaults to 'unknown'. + filetype (str, optional): The type of the file. Defaults to 'pdf'. + Returns: + list: A list of Document objects, each containing the text of a page and metadata including the filename, page number, and title. + """ + logger.info(LoggingMessages.DOCUMENT_PARSER_STTARTED) + pdf_stream = io.BytesIO(file_content) + def _get_title(text:str): + '''Extract Title from First Page''' + for line in text: + if line.strip(): + return line + with pymupdf.open(filename=filename, stream=pdf_stream, filetype=filetype) as doc: + title = _get_title(doc[0].get_text().split('\n')) + documents = [ + Document( + page_content=page.get_text(), + metadata = { + 'filename':filename, + 'page_number': page.number+1, + 'title':title, + **file_metadata + } ) for page in doc + ] + if documents: + text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder( + chunk_size=256, chunk_overlap=16 + ) + documents = text_splitter.split_documents(documents) + logger.info(LoggingMessages.DOCUMENT_PARSER_END) + return documents + + + +def context_parser_input(documents:List[Document])->str : + + """ + Parses a list of Document objects into a list of context strings formatted in XML-like tags. + Args: + documents (List[Document]): A list of Document objects, each containing metadata and page content. + Returns: + List[str]: A list of strings, each representing a document's content wrapped in a context tag with metadata attributes. + """ + + context_template = ' {page_content} \n' + parsed_contexts = [] + for doc in documents: + metadata_str = f'id="{uuid4()} "'+' '.join([f'{key}="{value}"' for key, value in doc.metadata.items()]) + context_str = context_template.format(metadata=metadata_str, page_content=doc.page_content) + parsed_contexts.append(context_str) + return parsed_contexts + + + +def context_parser_output(contexts:List[str] ) -> Dict[str, str | dict]: + """ + Parses the given context string to extract content and metadata attributes. + Args: + context (str): The context string containing content and metadata attributes. + Returns: + Dict[str, str | dict]: A dictionary with two keys: + - "content": The extracted content as a string. + - "metadata": A dictionary of extracted metadata attributes as key-value pairs. + """ + content_pattern = re.compile(r"(.*?)", re.DOTALL) + if not isinstance(contexts, list): + contexts = [contexts] + context_list = [] + for context in contexts: + content_match = content_pattern.search(context) + attributes_part = content_match.group(1).strip() if content_match else "" + content = content_match.group(2).strip() if content_match else "" + # Extract attributes as key-value pairs + attributes_pattern = re.compile(r"(\w+)=\"(.*?)\"") + attributes = dict(attributes_pattern.findall(attributes_part)) + context_list.append( { + "content": content, + "metadata": attributes}) + + return context_list diff --git a/RAG/app/services/RAG/llm_search.py b/RAG/app/services/RAG/llm_search.py new file mode 100644 index 0000000..a6bfd60 --- /dev/null +++ b/RAG/app/services/RAG/llm_search.py @@ -0,0 +1,70 @@ + +import json +from typing import Any + +from langfuse.callback import CallbackHandler +from sentence_transformers import CrossEncoder + +from app.config.logging_config import logger +from app.config.settings import ( + LANGFUSE_CONFIG, + RELEVENCY_CHECK_MODEL, + RELEVENCY_SCORE_THRESH, + default_llm_model, +) +from app.constants import LoggingMessages +from app.services.RAG.document_parser import context_parser_input, context_parser_output +from app.services.RAG.prompts import default_template_prompt +from app.services.RAG.vectorstore import similarity_search + +langfuse_handler = CallbackHandler(**LANGFUSE_CONFIG) +def get_relevent_chunks(llm_response:Any, retrieved_chunks:Any): + """ + Filters and returns relevant chunks from the retrieved chunks based on their relevance to the LLM response. + Args: + llm_response (Any): The response from the language model. + retrieved_chunks (Any): A collection of chunks retrieved from a source, each containing 'page_content' and 'metadata'. + Returns: + List[Dict[str, Any]]: A list of dictionaries, each containing 'content' and 'metadata' of the relevant chunks. + """ + cross_encoder = CrossEncoder(RELEVENCY_CHECK_MODEL) + # Compare LLM response with retrieved chunks + chunk_texts = [chunk.page_content for chunk in retrieved_chunks] + pairs = [(llm_response, chunk) for chunk in chunk_texts] + # Get relevance scores (0 to 1) + scores = cross_encoder.predict(pairs) + # Filter chunks based on a threshold + used_chunks = [ + { + "content":retrieved_chunks[i].page_content, + "metadata":retrieved_chunks[i].metadata + } for i, score in enumerate(scores) + if score > RELEVENCY_SCORE_THRESH + ] + return used_chunks + +def get_llm_response(query:str, user_id: str): + retrieved_chunks = similarity_search(query=query, user_id=user_id) + llm_chain = default_template_prompt | default_llm_model + logger.info(LoggingMessages.LLM_CALL_INNITIATE) + response = llm_chain.invoke( + { + "query" : query, + "context" : context_parser_input(retrieved_chunks), + }, + config={"callbacks": [langfuse_handler]} + ) + llm_response = response.content + response_json_str = llm_response[7:-3] + response_json = json.loads(response_json_str) + llm_answer = response_json['answer'] + relevent_chunks = response_json ['relevent_chunks'] + # resource = get_relevent_chunks(response,retrieved_chunks) + + logger.info(LoggingMessages.LLM_RESPONSE_RECIEVED) + + return ({ + 'query': query, + "answer": llm_answer, + "resource" : context_parser_output(relevent_chunks) + }) diff --git a/RAG/app/services/RAG/prompts.py b/RAG/app/services/RAG/prompts.py new file mode 100644 index 0000000..2739245 --- /dev/null +++ b/RAG/app/services/RAG/prompts.py @@ -0,0 +1,30 @@ +'''This is the Prompt List''' + +from langchain_core.prompts import PromptTemplate + +default_template_prompt = PromptTemplate.from_template( + """ + You are an AI assistant tasked with answering user questions based on the provided\ + context in form of tags where metadata is also mentioned as properties of Tags. \ + Context are enclosed by tag. + As a response Write your answer in following Json format. + Response Format : + + "answer" : "Write your answer here", + "relevent_chunks" : "List of all chunks. Write all exact chunks as provided in a list that are actually used to generate the answer with there proper format with all the information of that chunk." + + + If the context does not contain relevant information, respond with \ + "I don't know based on the available information." + + + Context: + {context} + + Question: + {query} + + Provide a concise and accurate answer based on the context and chat history above. + """ + +) diff --git a/RAG/app/services/RAG/vectorstore.py b/RAG/app/services/RAG/vectorstore.py new file mode 100644 index 0000000..63f4205 --- /dev/null +++ b/RAG/app/services/RAG/vectorstore.py @@ -0,0 +1,80 @@ +from pathlib import Path +from typing import List + +import faiss +from langchain_community.vectorstores import FAISS +from langchain_core.documents import Document + +from app.config.logging_config import logger +from app.config.settings import ( + DEFAULT_INDEX_PATH, + EMBEDDING_MODEL_VECTOR_LENGTH, + embed_model, +) +from app.constants import LoggingMessages +from app.routes.constants import ErrorMessages + +index = faiss.IndexFlatL2(EMBEDDING_MODEL_VECTOR_LENGTH) + + + +def validate_index_path(index_path: str | Path | None): + """ + Validates the provided index path. + Parameters: + index_path (str | Path | None): The path to the index. It can be a string, a Path object, or None. + Returns: + Path: The resolved Path object if the index_path is valid. + Raises: + Exception: If the index_path is None. + """ + if index_path is None : + raise Exception(ErrorMessages.INDEX_NOT_FOUND) + elif not isinstance(index_path,Path): + index_path = Path(index_path).resolve() + if not index_path.exists(): + raise Exception(ErrorMessages.INDEX_NOT_FOUND) + return index_path + +def save_on_vector_store(documents : List[Document], user_id: str, index_path:str|Path|None=DEFAULT_INDEX_PATH) : + """ + Save documents to a FAISS vector store. + Parameters: + documents (List[Document]): A list of documents to be added to the vector store. + index_path (str | Path | None): The path to the existing FAISS index. If None, a new index will be created. + Returns: + None + """ + user_id = str(user_id) + if index_path and not isinstance(index_path,Path): + index_path= Path(index_path).resolve() + if (index_path/user_id).exists() : + faiss_store = FAISS.load_local(index_path/user_id, embed_model,allow_dangerous_deserialization=True) + faiss_store.add_documents(documents) + else: + faiss_store = FAISS.from_documents(documents, embed_model) + faiss_store.save_local((index_path/user_id).as_posix()) + logger.info(LoggingMessages.FUNCTION_END) + +def similarity_search(query:str, user_id: str, index_path: str|Path|None = DEFAULT_INDEX_PATH)-> List[Document]: + """ + Perform a similarity search on the given query using the specified index path. + Args: + query (str): The query string to search for. + index_path (str | Path | None, optional): The path to the index file. Defaults to DEFAULT_INDEX_PATH. + Returns: + List[Document]: A list of documents that are similar to the query. + Raises: + Exception: If the index_path is None. + """ + user_id = str(user_id) + index_path = validate_index_path(index_path/user_id) + faiss_store = FAISS.load_local(index_path.as_posix(), embed_model,allow_dangerous_deserialization=True) + results = faiss_store.similarity_search(query, k=3) + return results + +def get_retriver( user_id: str, index_path: str|Path|None = DEFAULT_INDEX_PATH): + user_id = str(user_id) + index_path = validate_index_path(index_path/user_id) + result = FAISS.load_local(index_path.as_posix(), embed_model,allow_dangerous_deserialization=True).as_retriever() + return result diff --git a/RAG/app/services/__init__.py b/RAG/app/services/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/RAG/app/tests/__init__.py b/RAG/app/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/RAG/app/tests/conftest.py b/RAG/app/tests/conftest.py new file mode 100644 index 0000000..d69e1b0 --- /dev/null +++ b/RAG/app/tests/conftest.py @@ -0,0 +1,3 @@ +""" +Test configuration and fixtures. +""" diff --git a/RAG/app/tests/test_items.py b/RAG/app/tests/test_items.py new file mode 100644 index 0000000..2666f66 --- /dev/null +++ b/RAG/app/tests/test_items.py @@ -0,0 +1,3 @@ +""" +Unit tests for item-related functionality. +""" diff --git a/RAG/app/tests/test_main.py b/RAG/app/tests/test_main.py new file mode 100644 index 0000000..2a02aec --- /dev/null +++ b/RAG/app/tests/test_main.py @@ -0,0 +1,3 @@ +""" +Unit tests for the main application entry point. +""" diff --git a/RAG/app/tests/test_users.py b/RAG/app/tests/test_users.py new file mode 100644 index 0000000..6c77def --- /dev/null +++ b/RAG/app/tests/test_users.py @@ -0,0 +1,3 @@ +""" +Unit tests for user-related functionality. +""" diff --git a/RAG/pyproject.toml b/RAG/pyproject.toml new file mode 100644 index 0000000..92ce82b --- /dev/null +++ b/RAG/pyproject.toml @@ -0,0 +1,98 @@ +[project] +name = "rag-general-template" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +requires-python = ">=3.11" +dependencies = [ + "alembic>=1.14.1", + "beautifulsoup4>=4.12.3", + "black>=24.10.0", + "colorlog>=6.9.0", + "duckduckgo-search==5.3.1b1", + "faiss-cpu>=1.9.0.post1", + "faker>=35.2.0", + "fastapi>=0.115.7", + "langchain>=0.3.15", + "langchain-community>=0.3.15", + "langchain-groq>=0.2.3", + "langchain-huggingface>=0.1.2", + "langchain-openai>=0.3.3", + "langfuse>=2.57.13", + "langgraph>=0.2.68", + "lxml>=5.3.0", + "mypy>=1.14.1", + "passlib[bcrypt]>=1.7.4", + "psycopg2-binary>=2.9.10", + "pydantic[email]>=2.10.6", + "pyjwt>=2.10.1", + "pymupdf>=1.25.3", + "pypdf>=5.3.0", + "python-dotenv>=1.0.1", + "python-jose[cryptography]>=3.3.0", + "python-multipart>=0.0.20", + "ruff>=0.9.3", + "sentence-transformers>=3.4.1", + "sqlalchemy>=2.0.37", + "tavily-python>=0.5.0", + "tiktoken>=0.8.0", + "uvicorn>=0.34.0", +] + +[tool.black] +line-length = 88 +skip-string-normalization = true +exclude = '''/( + \.git + | \.mypy_cache + | \.venv + | \.venv2 + | \.venv3 + | build + | dist + | alembic +)/''' + +[tool.ruff] +line-length = 88 +exclude = [ + ".git", + ".mypy_cache", + ".venv", + ".venv2", + ".venv3", + "build", + "dist", + "alembic/**/*", + "*/__init__.py" +] + +[tool.ruff.lint] +select = ["E", "F", "B", "W", "I", "C", "N"] +ignore = ["E501"] +per-file-ignores = { "__init__.py" = ["F401"] } + +[tool.ruff.lint.isort] +known-third-party = ["fastapi", "pydantic", "sqlalchemy"] + +[tool.mypy] +strict = true +disallow_untyped_defs = false +ignore_missing_imports = true +warn_unused_ignores = true +ignore_errors = false +exclude = '.*/__init__.py' + +[[tool.mypy.overrides]] +module = ["fastapi", "pydantic", "sqlalchemy"] +ignore_missing_imports = true + +[build-system] +requires = ["setuptools", "wheel"] +build-backend = "setuptools.build_meta" + +[dependency-groups] +dev = [ + "ipykernel>=6.29.5", +] + diff --git a/RAG/requirements.txt b/RAG/requirements.txt new file mode 100644 index 0000000..50cc819 --- /dev/null +++ b/RAG/requirements.txt @@ -0,0 +1,18 @@ +alembic>=1.14.1 +fastapi>=0.115.7 +black>=24.10.0 +langchain>=0.3.15 +langchain-groq>=0.2.3 +langfuse>=2.57.13 +langgraph>=0.2.68 +mypy>=1.14.1 +passlib[bcrypt]>=1.7.4 +psycopg2-binary>=2.9.10 +pydantic[email]>=2.10.6 +pyjwt>=2.10.1 +python-dotenv>=1.0.1 +python-jose[cryptography]>=3.3.0 +python-multipart>=0.0.20 +ruff>=0.9.3 +sqlalchemy>=2.0.37 +uvicorn>=0.34.0 \ No newline at end of file diff --git a/RAG/scripts/run_lint_checks.sh b/RAG/scripts/run_lint_checks.sh new file mode 100644 index 0000000..7aba20f --- /dev/null +++ b/RAG/scripts/run_lint_checks.sh @@ -0,0 +1,46 @@ +#!/usr/bin/env bash + +set -e + +echo "Running code checks..." + +# Determine Python command +if command -v python3 &> /dev/null; then + PYTHON=python3 +elif command -v python &> /dev/null; then + PYTHON=python +else + echo "Error: Python not found. Please install Python 3." + exit 1 +fi + +# Function to run checks +run_check() { + if command -v "" &> /dev/null; then + echo "Running ..." + "" + else + echo "Warning: not found. Skipping." + fi +} + +# Change to the project root directory +cd "./.." + +# Ensure pyproject.toml exists +if [ ! -f pyproject.toml ]; then + echo "Error: pyproject.toml not found in the project root." + exit 1 +fi + +# Run Black +run_check black --config pyproject.toml . + +# Run Ruff +run_check ruff check --config pyproject.toml . + +# Run mypy +run_check mypy --config-file pyproject.toml . + +echo "All checks completed!" + diff --git a/RAG/uv.lock b/RAG/uv.lock new file mode 100644 index 0000000..e660b30 --- /dev/null +++ b/RAG/uv.lock @@ -0,0 +1,2880 @@ +version = 1 +requires-python = ">=3.11" +resolution-markers = [ + "python_full_version >= '3.12.4'", + "python_full_version >= '3.12' and python_full_version < '3.12.4'", + "python_full_version < '3.12'", +] + +[[package]] +name = "aiohappyeyeballs" +version = "2.4.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = 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