From f6b4d699369477923eac820780a3a9bd464c4a5f Mon Sep 17 00:00:00 2001 From: ErikO <49541561+EJOOSTEROP@users.noreply.github.com> Date: Thu, 17 Aug 2023 21:16:19 +0000 Subject: [PATCH] Initial commit. --- .devcontainer/devcontainer.json | 50 + .devcontainer/dockerfile | 5 + .env.example | 4 + .flake8 | 29 + .gitignore | 175 ++ .vscode/settings.json | 19 + README.md | 364 +++ docs/pdf/CIBC_AIF_2022_ENG.pdf | Bin 0 -> 238520 bytes docs/pdf/test.txt | 1 + experiments.md | 78 + license.txt | 20 + media/llms.png | Bin 0 -> 152713 bytes noxfile.py | 48 + poetry.lock | 3064 +++++++++++++++++++++++++ poetry.toml | 2 + pyproject.toml | 105 + quke/__init__.py | 29 + quke/conf/__init__.py | 0 quke/conf/config.yaml | 15 + quke/conf/embedding/cohere.yaml | 28 + quke/conf/embedding/hf_r.yaml | 28 + quke/conf/embedding/huggingface.yaml | 28 + quke/conf/embedding/openai.yaml | 28 + quke/conf/experiment/llama2.yaml | 5 + quke/conf/experiment/openai.yaml | 5 + quke/conf/experiment/openaihf.yaml | 5 + quke/conf/llm/cohere.yaml | 7 + quke/conf/llm/falcon7b.yaml | 11 + quke/conf/llm/gpt3-5.yaml | 8 + quke/conf/llm/llama2.yaml | 15 + quke/conf/question/eps.yaml | 3 + quke/conf/question/growth.yaml | 3 + quke/conf/question/tabulation.yaml | 3 + quke/embed.py | 200 ++ quke/llm_chat.py | 134 ++ quke/quke.py | 193 ++ quke/trial questions.txt | 4 + tests/__init__.py | 0 tests/conf/__init__.py | 0 tests/conf/config.yaml | 11 + tests/conf/embedding/cohere.yaml | 28 + tests/conf/embedding/hf_r.yaml | 28 + tests/conf/embedding/huggingface.yaml | 28 + tests/conf/embedding/openai.yaml | 28 + tests/conf/experiment/llama2.yaml | 5 + tests/conf/experiment/openai.yaml | 5 + tests/conf/experiment/openaihf.yaml | 5 + tests/conf/llm/cohere.yaml | 7 + tests/conf/llm/falcon7b.yaml | 11 + tests/conf/llm/gpt3-5.yaml | 8 + tests/conf/llm/llama2.yaml | 15 + tests/conf/question/eps.yaml | 3 + tests/conf/question/tabulation.yaml | 3 + tests/data/src_doc/test.txt | 1 + tests/test_001.py | 100 + 55 files changed, 5002 insertions(+) create mode 100755 .devcontainer/devcontainer.json create mode 100755 .devcontainer/dockerfile create mode 100644 .env.example create mode 100644 .flake8 create mode 100644 .gitignore create mode 100644 .vscode/settings.json create mode 100644 README.md create mode 100755 docs/pdf/CIBC_AIF_2022_ENG.pdf create mode 100644 docs/pdf/test.txt create mode 100644 experiments.md create mode 100755 license.txt create mode 100755 media/llms.png create mode 100644 noxfile.py create mode 100644 poetry.lock create mode 100644 poetry.toml create mode 100644 pyproject.toml create mode 100644 quke/__init__.py create mode 100644 quke/conf/__init__.py create mode 100644 quke/conf/config.yaml create mode 100644 quke/conf/embedding/cohere.yaml create mode 100644 quke/conf/embedding/hf_r.yaml create mode 100644 quke/conf/embedding/huggingface.yaml create mode 100644 quke/conf/embedding/openai.yaml create mode 100644 quke/conf/experiment/llama2.yaml create mode 100644 quke/conf/experiment/openai.yaml create mode 100644 quke/conf/experiment/openaihf.yaml create mode 100644 quke/conf/llm/cohere.yaml create mode 100644 quke/conf/llm/falcon7b.yaml create mode 100644 quke/conf/llm/gpt3-5.yaml create mode 100644 quke/conf/llm/llama2.yaml create mode 100644 quke/conf/question/eps.yaml create mode 100644 quke/conf/question/growth.yaml create mode 100644 quke/conf/question/tabulation.yaml create mode 100644 quke/embed.py create mode 100644 quke/llm_chat.py create mode 100644 quke/quke.py create mode 100644 quke/trial questions.txt create mode 100644 tests/__init__.py create mode 100644 tests/conf/__init__.py create mode 100644 tests/conf/config.yaml create mode 100644 tests/conf/embedding/cohere.yaml create mode 100644 tests/conf/embedding/hf_r.yaml create mode 100644 tests/conf/embedding/huggingface.yaml create mode 100644 tests/conf/embedding/openai.yaml create mode 100644 tests/conf/experiment/llama2.yaml create mode 100644 tests/conf/experiment/openai.yaml create mode 100644 tests/conf/experiment/openaihf.yaml create mode 100644 tests/conf/llm/cohere.yaml create mode 100644 tests/conf/llm/falcon7b.yaml create mode 100644 tests/conf/llm/gpt3-5.yaml create mode 100644 tests/conf/llm/llama2.yaml create mode 100644 tests/conf/question/eps.yaml create mode 100644 tests/conf/question/tabulation.yaml create mode 100644 tests/data/src_doc/test.txt create mode 100644 tests/test_001.py diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json new file mode 100755 index 0000000..efdc83a --- /dev/null +++ b/.devcontainer/devcontainer.json @@ -0,0 +1,50 @@ +// For format details, see https://aka.ms/devcontainer.json. For config options, see the +// README at: https://github.com/devcontainers/templates/tree/main/src/python +{ + "name": "LangChain - Python 3", + + "build": { + "dockerfile": "./dockerfile", + "context": "." + }, + + // Features to add to the dev container. More info: https://containers.dev/features. + "features": { + "ghcr.io/devcontainers/features/common-utils:2": { + "installZsh": true, + "installOhMyZsh": true, + "installOhMyZshConfig": true, + "upgradePackages": true, + "username": "devcontainer" + }, + "ghcr.io/devcontainers-contrib/features/poetry:2": { + "version": "latest" + }, + "ghcr.io/devcontainers-contrib/features/nox:2": { + "version": "latest" + } + }, + + // Use 'forwardPorts' to make a list of ports inside the container available locally. + // "forwardPorts": [], + + // Use 'postCreateCommand' to run commands after the container is created. + // "postCreateCommand": "pip3 install --user -r requirements.txt", + "postCreateCommand": "poetry install" , + + // Configure tool-specific properties. + "customizations": { + "vscode": { + "extensions": [ + "ms-python.python", + "ms-python.vscode-pylance", + "Gruntfuggly.todo-tree" + ] + } + }, + + // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root. + // "remoteUser": "root" + "remoteUser": "vscode" + +} diff --git a/.devcontainer/dockerfile b/.devcontainer/dockerfile new file mode 100755 index 0000000..c3af78e --- /dev/null +++ b/.devcontainer/dockerfile @@ -0,0 +1,5 @@ +FROM mcr.microsoft.com/devcontainers/python:1-3.11-bullseye + +# [Optional] Uncomment this section to install additional OS packages. +# RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \ +# && apt-get -y install --no-install-recommends \ No newline at end of file diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..fea42b9 --- /dev/null +++ b/.env.example @@ -0,0 +1,4 @@ +OPENAI_API_KEY = "YOUR-KEY" +HUGGINGFACEHUB_API_TOKEN = "YOUR-KEY" +COHERE_API_KEY = "YOUR-KEY" +REPLICATE_API_TOKEN = "YOUR-KEY" \ No newline at end of file diff --git a/.flake8 b/.flake8 new file mode 100644 index 0000000..459c60b --- /dev/null +++ b/.flake8 @@ -0,0 +1,29 @@ +[flake8] +# https://stackoverflow.com/questions/50177173/how-do-i-get-flake8-to-reliably-ignore-rules-in-vs-code + +select = ANN,B,B9,BLK,D,DAR,E,F,I,S,W +# add ,C for copyright notices, S for bandit, B for bugbear, BLK for Black +# select = E,F,W,I,C +ignore=E203,E501,W503 + +exclude = + .git + ,.nox + ,build + ,dist + + +max-line-length = 119 +max-complexity = 10 + +application-import-names = quke,tests + +import-order-style = google +docstring-convention = google + +per-file-ignores = tests/*:S101, quke/conf/*:D104 + +# add ',C' to 'select=' in order to show the copyright warnings. +copyright-check = True +copyright-min-file-size = 50 +copyright-regexp=Copyright \(c\) XXXX. All Rights Reserved \ No newline at end of file diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..283dbe3 --- /dev/null +++ b/.gitignore @@ -0,0 +1,175 @@ +# quke specific +old-for-reference/ +idata/ +outputs/ +multirun/ +docs/youtube/ +docs/src_docs/ +docs/pdf - Copy/ +.chroma/ + +# 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 + +# 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/#use-with-ide +.pdm.toml + +# 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/ +DEL__init__.py +DEL_setup.py +readme - SAMPLE.md +quke/temp.yaml +quke/wip.py diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..cc2e7ff --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,19 @@ +{ + "todo-tree.tree.showBadges": true, + "todo-tree.tree.disableCompactFolders": true, + "python.testing.pytestArgs": [ + "tests" + ], + "python.testing.unittestEnabled": false, + "python.testing.pytestEnabled": true, + + + "[python]": { + "editor.defaultFormatter": "ms-python.black-formatter", + "editor.formatOnSave": true, + "editor.codeActionsOnSave": { + "source.organizeImports": true + }, + }, + "isort.args":["--profile", "black"], +} \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..1f58850 --- /dev/null +++ b/README.md @@ -0,0 +1,364 @@ + + + + + + + + + + + +[![Contributors][contributors-shield]][contributors-url] +[![Forks][forks-shield]][forks-url] +[![Stargazers][stars-shield]][stars-url] +[![Issues][issues-shield]][issues-url] +[![MIT License][license-shield]][license-url] +[![LinkedIn][linkedin-shield]][linkedin-url] + + + + + +
+
+ + Logo + + +

quke

+ +

+ Compare the answering capabilities of different LLMs - for example LlaMa, ChatGPT, Cohere, Falcon - against user provided document(s) and questions. +
+ Explore the docs » +
+
+ + Report Bug + · + Request Feature +

+
+ + + +
+ Table of Contents +
    +
  1. + About The Project + +
    2. +
  2. + Getting Started + +
    3. +
  3. + Usage + +
    4. + +
  4. License
    5. +
  5. Contact
    6. + +
+
+ + + +## About The Project +Compare the answering capabilities of different LLMs - for example LlaMa, ChatGPT, Cohere, Falcon - against user provided document(s) and questions. + +Specify the different models, embedding tools and vector databases in configuration files. + +Maintain reproducable experiments reflecting combinations of these configurations. + +

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+ +## Getting Started +### Prerequisites +#### Poetry +The instructions assume a Python environment with [Poetry][poetry-url] installed. Development of the tool is done in Python 3.11. While Poetry is not actually needed for the tool to function, the examples assume Poetry is installed. + +#### API keys +The tool uses 3rd party hosted inference APIs. API keys need to be specified as environment variables. + +The services used: +- [HuggingFace][huggingface-url] +- [OpenAI][openai-url] +- [Cohere][cohere-url] +- [Replicate][replicate-url] + +The API keys can be specied in a [.env file][.env-url]. Use the provided .env.example file as an example (enter your own API keys and rename it to '.env'). + +At present, all services used in the example configuration have free tiers available. + +

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+ +### Installation +Navigate to the directory that contains the pyproject.toml file, then execute the +```sh +poetry install +``` +command. + +

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+ + +## Usage +For the examples the project comes with a public financial document for a Canadian Bank (CIBC) as source pdf file. + +### Base +In order to run the first example, ensure to specify your HuggingFace API key. + +Use the command +```sh +poetry run quke +``` +to ask the default questions, using the default embedding and the default LLM. + +The answers provided by the LLM - in addition to various other logging messages - are saved in the ./output/ or ./multirun directories in separate date and time subdirectories, including in a file called `chat_session.md`. + +The defaults are specified in the config.yaml file (in the ./quke/conf/ directory). + +

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+ +### Specify models and embeddings +*Ensure to specify your Cohere API key before running.* + +As per the configuration files, the default LLM is Falcon and the default embedding uses HuggingFace embedding. + +To specify a different LLM - Cohere in this example - run the following: +```sh +poetry run quke embedding=huggingface llm=cohere question=eps +``` + + +

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+ +### Experiments +*Ensure to specify your OpenAI API key before running.* + +The LLMs, embeddings, questions and other configurations can be captured in experiment config files. The command +```sh +poetry run quke +experiment=openai +``` +uses an experiment file openai.yaml (see folder ./config/experiments) which specifies the LLM, embedding and questions to be used. It is equivalent to running: +```sh +poetry run quke embedding=openai llm=gpt3-5 question=eps +``` +Multiple experiments can be run at once as follows: + +*Ensure to specify your Replicate API key before running.* +```sh +poetry run quke --multirun +experiment=openai,llama2 +``` + + +

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+ +### Configuration +LLMs, embeddings, questions, experiments and other items are specified in a set of configuration files. These are saved in the ./config directory. + +The [Hydra][hydra-url] package is used for configuration management. Their website explains more about the configuration system in general. + +Four different models are specified (ChatGPT, LlaMa2, Falcon, and Cohere); using 4 different APIs (OpenAI, HuggingFace, Cohere and Replicate). + +Additional LLMs (or embeddings, questions) can be set up by adding new configuration files. + +

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+ +### Search your own documents +The documents to be searched are stored in the ./docs/pdf directory. At present only pdf documents are considered. +Note to set `vectorstore_write_mode` to `append` or `overwrite` in the embedding configuration file (or delete the folder with the existing vector database, in the ./idata folder). + +

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+ +### Limitations +The free tiers for the third party services generally come with fairly strict limitations. They differ between services; and may differ over time. + + To try out the tool with your own documents it is best to start with a single small source document, no more than two questions and only one combination of LLM/embedding. + +Error messages due to limitations of the APIs are not always clearly indicated as such. + +

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+ +### Privacy +The tool uses third party APIs (OpenAI, HuggingFace, Cohere, Replicate). These process your source documents and your questions, to the extent that you provide these. They track your usage of their APIs. They may do other things; I do not know. + +The tool uses the [LangChain][langchain-url] Python package to interact with the third party services. I do not know if the package 'leaks' any of the data in any way. + +In general I do not know to what extent any of the data is encrypted during transmission. + +The tool shares no information with me. + +

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+ + + +### Built With + +* [![Cohere][cohere.com]][cohere-url] +* [![HuggingFace][huggingface.com]][huggingface-url] +* [![OpenAI][openai.com]][openai-url] +* [![Replicate][replicate.com]][replicate-url] +

+* [![Hydra][hydra.com]][hydra-url] +* [![LangChain][langchain.com]][langchain-url] + +

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+ + + + + + + + + + + + +## License + +Distributed under the MIT License. See `LICENSE.txt` for more information. + +

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+ + + + +## Contact + + + +Project Link: [https://github.com/ejoosterop/quke](https://github.com/ejoosterop/quke) + +

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+ + + + + + + + + +[contributors-shield]: https://img.shields.io/github/contributors/ejoosterop/quke.svg?style=for-the-badge +[contributors-url]: https://github.com/ejoosterop/quke/graphs/contributors +[forks-shield]: https://img.shields.io/github/forks/ejoosterop/quke.svg?style=for-the-badge +[forks-url]: https://github.com/ejoosterop/quke/network/members +[stars-shield]: https://img.shields.io/github/stars/ejoosterop/quke.svg?style=for-the-badge +[stars-url]: https://github.com/ejoosterop/quke/stargazers +[issues-shield]: https://img.shields.io/github/issues/ejoosterop/quke.svg?style=for-the-badge +[issues-url]: https://github.com/ejoosterop/quke/issues +[license-shield]: https://img.shields.io/github/license/ejoosterop/quke.svg?style=for-the-badge +[license-url]: https://github.com/ejoosterop/quke/blob/master/LICENSE.txt +[linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge&logo=linkedin&colorB=555 +[linkedin-url]: https://linkedin.com/in/erik-oosterop-9505a21 +[product-screenshot]: images/screenshot.png + + +[cohere-url]: https://cohere.com/ +[huggingface-url]: https://huggingface.co/ +[hydra-url]: https://hydra.cc/ +[langchain-url]: https://python.langchain.com/ +[openai-url]: https://openai.com/ +[poetry-url]: https://python-poetry.org/ +[replicate-url]: https://replicate.com/ +[.env-url]: https://pypi.org/project/python-dotenv/ + +[openai.com]: https://img.shields.io/badge/openai-412991?style=for-the-badge&logo=openai&logoColor=white + +[huggingface.com]: https://img.shields.io/badge/huggingface-yellow?style=for-the-badge&logo=huggingface&logoColor=white +[cohere.com]: https://img.shields.io/badge/Cohere-013220?style=for-the-badge&logo=cohere&logoColor=white +[replicate.com]: https://img.shields.io/badge/replicate-black?style=for-the-badge&logo=replicate&logoColor=white + +[hydra.com]: https://img.shields.io/badge/hydra-white?style=for-the-badge&logo=python&logoColor=black +[langchain.com]: 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It was founded in 2019. \ No newline at end of file diff --git a/experiments.md b/experiments.md new file mode 100644 index 0000000..1df445e --- /dev/null +++ b/experiments.md @@ -0,0 +1,78 @@ +# Base case, Falcon +embedding: hugginface +llm: falcon7b +question: eps + +Q: What is EPS according to the AIF? +Earnings per share (EPS) is a measure of a company's profitability. It is calculated by dividing the company's earnings by the number of outstanding shares of its common stock. The company's earnings can be found in its income statement. + +Q: What is CIBC? +CIBC was formed in 1875 by the merger of The Canadian Bank of Commerce and Imperial Bank of Canada. It is a leading Canadian financial institution with a presence in North America. It offers a wide range of financial services, including personal and business banking, wealth management, and investment services. + +# Cohere +embedding: hugginface +llm: cohere +question: eps + +Q: What is EPS according to the AIF? +EPS stands for earnings per share. It is a financial ratio that measures the profitability of a company. It is calculated by dividing the company's net income by the number of outstanding shares. + +In the AIF, EPS is referred to as reported diluted EPS and adjusted diluted EPS. Reported diluted EPS is the company's net income divided by the number of outstanding shares, including the impact of dilutive securities. Adjusted diluted EPS is the company's net income divided by the number of outstanding shares, excluding the impact of dilutive securities and certain items of note. + +The 3-year CAGR for reported and adjusted diluted EPS is 6.1% and 5.8%, respectively, and the 5-year CAGR is 3.5% and 4.9%, respectively. These rates represent the compound annual growth rate of the company's EPS over the past 3 and 5 years. + +Q: What is CIBC? +Yes, I would like to know more about CIBC. + +CIBC is a diversified financial institution governed by the Bank Act (Canada), which constitutes its charter. CIBC was formed through the amalgamation of The Canadian Bank of Commerce and Imperial Bank of Canada in 1961. The Canadian Bank of Commerce was originally incorporated as Bank of Canada by special act of the legislature of the Province of Canada in 1858. Subsequently, the name was changed to The Canadian Bank of Commerce and it opened for business under that name in 1867. Imperial Bank of Canada was incorporated in 1875 by special act of the Parliament of Canada and commenced operations in that year. The address of the registered and head office of CIBC is 81 Bay Street, CIBC SQUARE, Toronto, Ontario, Canada, M5J 0E7. + +Would you like to know more about the history of CIBC? + +# Cohere +embedding: openai +llm: cohere +question: eps + +Q: What is EPS according to the AIF? +EPS stands for earnings per share. It is a financial ratio that measures the profitability of a company. It is calculated by dividing the company's net income by the number of outstanding shares. + +In the AIF, EPS is used to evaluate the company's financial performance and to set targets for future growth. The company's 2022 target for EPS growth is 5%-10%, with a long-term target of 7% to 10%. + +It is important to note that EPS is just one of many financial ratios that can be used to evaluate a company's financial performance, and it should be considered in conjunction with other ratios and metrics to get a more comprehensive understanding of the company's financial health. + +Q: What is CIBC? +CIBC is a diversified financial institution governed by the Bank Act (Canada), which constitutes its charter. CIBC was formed through the amalgamation of The Canadian Bank of Commerce and Imperial Bank of Canada in 1961. The Canadian Bank of Commerce was originally incorporated as Bank of Canada by special act of the legislature of the Province of Canada in 1858. Subsequently, the name was changed to The Canadian Bank of Commerce and it opened for business under that name in 1867. Imperial Bank of Canada was incorporated in 1875 by special act of the Parliament of Canada and commenced operations in that year. The address of the registered and head office of CIBC is 81 Bay Street, CIBC SQUARE, Toronto, Ontario, Canada, M5J 0E7. + +# OpenAI +embedding: openai +llm: gpt3-5 +question: eps + +Q: What is EPS according to the AIF? +EPS stands for Earnings Per Share. According to the AIF, CIBC has set targets for adjusted average annual diluted earnings per share (EPS) and aims to deliver a compound annual growth rate (CAGR) of 7% to 10% through the cycle. The AIF also provides information on CIBC's reported and adjusted diluted EPS for the past three and five years. + +Q: What is CIBC? +CIBC (Canadian Imperial Bank of Commerce) is a diversified financial institution governed by the Bank Act (Canada), which constitutes its charter. It was formed through the amalgamation of The Canadian Bank of Commerce and Imperial Bank of Canada in 1961. CIBC is a leading North American financial institution that serves its clients through four main strategic business units: Canadian Personal and Business Banking, Canadian Commercial Banking and Wealth Management, U.S. Commercial Banking and Wealth Management, and Capital Markets. Information about CIBC's business lines and functional groups is provided in the 2022 Annual Report on pages 22 to 32. + +# OpenAI using HF embeddings +embedding: huggingface +llm: gpt3-5 +question: eps + +Q: What is EPS according to the AIF? +EPS stands for Earnings Per Share. It is a financial metric that represents the portion of a company's profit that is allocated to each outstanding share of common stock. The AIF provides both reported and adjusted diluted EPS figures for CIBC for the years 2018-2022. + +Q: What is CIBC? +CIBC (Canadian Imperial Bank of Commerce) is a leading North American financial institution. It was formed through the amalgamation of The Canadian Bank of Commerce and Imperial Bank of Canada in 1961. CIBC serves its clients through four main strategic business units: Canadian Personal and Business Banking, Canadian Commercial Banking and Wealth Management, U.S. Commercial Banking and Wealth Management, and Capital Markets. CIBC is governed by the Bank Act (Canada), which constitutes its charter. It is the fifth largest Canadian chartered bank in terms of market capitalization as of October 31, 2022. + + +# Llama2 +embedding: openai +llm: llama2 +question: eps + +Q: What is EPS according to the AIF? +EPS stands for "diluted earnings per share" and is a financial measure used to evaluate a company's profitability. According to the CIBC 2022 Annual Information Form (AIF), reported diluted EPS was $6.68 in 2022, compared to $6.96 in 2021, down 4%. Adjusted diluted EPS was $7.05 in 2022, compared to $7.23 in 2021, down 2%. The 3-year and 5-year CAGR for reported and adjusted diluted EPS were 6.1% and 5.8%, respectively. + +Q: What is CIBC? +CIBC stands for Canadian Imperial Bank of Commerce. It is a leading North American financial institution that provides a range of financial products and services to its clients through its four main strategic business units: Canadian Personal and Business Banking, Canadian Commercial Banking and Wealth Management, U.S. Commercial Banking and Wealth Management, and Capital Markets. CIBC is headquartered in Toronto, Ontario, Canada, and is governed by the Bank Act (Canada), which constitutes its charter. \ No newline at end of file diff --git a/license.txt b/license.txt new file mode 100755 index 0000000..640f145 --- /dev/null +++ b/license.txt @@ -0,0 +1,20 @@ +Copyright (c) 2012-2023 Erik Oosterop and others + +Permission is hereby granted, free of charge, to any person obtaining +a copy of this software and associated documentation files (the +"Software"), to deal in the Software without restriction, including +without limitation the rights to use, copy, modify, merge, publish, +distribute, sublicense, and/or sell copies of the Software, and to +permit persons to whom the Software is furnished to do so, subject to +the following conditions: + +The above copyright notice and this permission notice shall be +included in all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +NONINFRINGEMENT. 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VS Code is using Poetry Python interpreter, +# which does not know nox. Hence, use the terminal to run nox. +# TODO: apply some of this: https://github.com/cjolowicz/hypermodern-python/blob/master/noxfile.py#L14 +# especially look at roughly line 51, flake/lint +import nox + + +# TODO: Is this an option: https://nox-poetry.readthedocs.io/en/stable/ +@nox.session +def flake(session): + session.install( + "flake8", + "flake8-docstrings", + "flake8-copyright", + "flake8-annotations", + "flake8-bandit", + "flake8-black", + "flake8-bugbear", + "flake8-import-order", + "darglint", + ) + session.run("flake8", "./quke/") + + +@nox.session +def black(session): + session.install("black") + session.run("black", "./quke/") + + +@nox.session +def ruff(session): + session.install("ruff") + session.run("ruff", "check", "./quke/", "./tests/", "pyproject.toml") + + +@nox.session +def test(session): + # Not certain this is a good approach. 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100644 index 0000000..c6125a4 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,105 @@ +[tool.poetry] +name = "quke" +version = "0.1.3" +description = "Compare the answering capabilities of different LLMs - for example LlaMa, ChatGPT, Cohere, Falcon - against user provided document(s) and questions." +authors = ["Erik Oosterop"] +maintainers = ["Erik Oosterop"] +license = "MIT" +readme = "README.md" +homepage = "" +repository = "https://github.com/EJOOSTEROP/quke" +documentation = "" +keywords = ["ML", "LLM", "compare", "chat", "semantic search"] + + +[tool.poetry.scripts] +quke = "quke.quke:quke" + +[tool.poetry.dependencies] +python = "^3.11" +langchain = "^0.0.229" +hydra-core = "^1.3.2" +python-dotenv = "^1.0.0" +pymupdf = "^1.22.5" +yt-dlp = "^2023.7.6" +pydub = "^0.25.1" +ffmpeg = "^1.4" +pypdf = "^3.12.1" +bs4 = "^0.0.1" +tiktoken = "^0.4.0" +chromadb = "^0.3.29" +lark = "^1.1.7" +huggingface-hub = "^0.16.4" +openai = "^0.27.8" +cohere = "^4.17.0" +replicate = "^0.9.0" +mdutils = "^1.6.0" +rich = "^13.5.2" + + +[tool.poetry.dev-dependencies] +pytest = "^7.4.0" +requests-mock = "^1.11.0" + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" + +[tool.pytest.ini_options] +markers = [ + "expensive: uses API key and likely paid or at least limited resources (deselect with '-m \"not expensive\"')", + "serial", +] + +[tool.ruff] +include = ["*.py", "*.pyi", "**/pyproject.toml"] +fix = false +line-length = 119 +select = [ # https://beta.ruff.rs/docs/rules/ + "A", # prevent using keywords that clobber python builtins + "ANN", # type annotation + "B", # bugbear: security warnings + "C", + "C90", + "D", # pydocstyle + "DAR", # darglint, but does not seem to be implemented at the moment + "DTZ", # date timezone + "E", # pycodestyle + "F", # pyflakes + "I", # isort + "ISC", # implicit string concatenation + "PT", # pytest style + "PTH", # use pathlib + "Q", + "S", # Bandit + "SIM", # simplify + "UP", # alert you when better syntax is available in your python version + "RUF", # the ruff developer's own rules +] + +ignore = [ + "E203", # comments allowed + "E501", +] + +# fixing is off by default +fixable = [ + "F401", # Remove unused imports. + "NPY001", # Fix numpy types, which are removed in 1.24. + "RUF100", # Remove unused noqa comments. +] + +[tool.ruff.per-file-ignores] +"tests/**/*.py" = [ + # at least this three should be fine in tests: + "S101", # asserts allowed in tests... + "ARG", # Unused function args -> fixtures nevertheless are functionally relevant... + "FBT", # Don't care about booleans as positional arguments in tests, e.g. via @pytest.mark.parametrize() + # The below are debateable + "PLR2004", # Magic value used in comparison, ... + "S311", # Standard pseudo-random generators are not suitable for cryptographic purposes + "D", # no pydocstyle +] + +[tool.ruff.pydocstyle] +convention = "google" \ No newline at end of file diff --git a/quke/__init__.py b/quke/__init__.py new file mode 100644 index 0000000..f71c3af --- /dev/null +++ b/quke/__init__.py @@ -0,0 +1,29 @@ +"""Compare Large Language Models' capabilities. + +Compare the answering capabilities of different LLMs - for example LlaMa, ChatGPT, +Cohere, Falcon - against user provided document(s) and questions. + +LLMs, embeddings and other settings can be specified in configuration files. +""" +from collections import namedtuple +from enum import Enum + + +class DatabaseAction(Enum): + """Enum for vectorstore write action. + + Value to be specified in config file. + + Action is performed at folder level. For example, if set to OVERWRITE the + existing folder will be completely deleted before creating a new vector store. + """ + + NO_OVERWRITE = 0 + APPEND = 1 + OVERWRITE = 2 + + +ClassImportDefinition = namedtuple( + "ClassImportDefinition", ["module_name", "class_name"] +) +ClassRateLimit = namedtuple("ClassRateLimit", ["count_limit", "delay"]) diff --git a/quke/conf/__init__.py b/quke/conf/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/quke/conf/config.yaml b/quke/conf/config.yaml new file mode 100644 index 0000000..05047ab --- /dev/null +++ b/quke/conf/config.yaml @@ -0,0 +1,15 @@ +internal_data_folder: idata +source_document_folder: "./docs/pdf/" +experiment_summary_file: 'chat_session.md' + +embed_only: False + +defaults: + - _self_ + - llm: falcon7b + - embedding: huggingface + - question: eps + +hydra: + job: + chdir: False \ No newline at end of file diff --git a/quke/conf/embedding/cohere.yaml b/quke/conf/embedding/cohere.yaml new file mode 100644 index 0000000..9540e22 --- /dev/null +++ b/quke/conf/embedding/cohere.yaml @@ -0,0 +1,28 @@ +vectordb: + module_name: langchain.vectorstores + class_name: Chroma + vectorstore_location: vector_store/chromadb_cohere + + # Possible values for vectorstore_write_mode: overwrite, no_overwrite, append + # This works at the vectorstore_location level. + # -If the folder exists and 'no_overwrite' is specified: document will not be embedded + # -If the folder exists and 'overwrite' is specified, all contents of the vectordb folder will be deleted and a new vectordb will be created. + # -If set to 'append' the new embeddings will be appended to any existing vectordb. If a source document is specified twice it will be embedded twice. + vectorstore_write_mode: no_overwrite + +embedding: + module_name: langchain.embeddings + class_name: CohereEmbeddings + kwargs: #optional +# repo_id: sentence-transformers/all-mpnet-base-v2 + rate_limit_chunks: 300 # max about 200 when I trialed (free account). Must depend on many considerations. + rate_limit_delay: 60 # in seconds + +splitter: + module_name: langchain.text_splitter + class_name: CharacterTextSplitter + args: + chunk_size: 1000 + chunk_overlap: 150 + separator: "\n" + length_function: len # this cannot be configured. Can only be len (or not present) \ No newline at end of file diff --git a/quke/conf/embedding/hf_r.yaml b/quke/conf/embedding/hf_r.yaml new file mode 100644 index 0000000..165e567 --- /dev/null +++ b/quke/conf/embedding/hf_r.yaml @@ -0,0 +1,28 @@ +vectordb: + module_name: langchain.vectorstores + class_name: Chroma + vectorstore_location: vector_store/chromadb_hf_recursive + + # Possible values for vectorstore_write_mode: overwrite, no_overwrite, append + # This works at the vectorstore_location level. + # -If the folder exists and 'no_overwrite' is specified: document will not be embedded + # -If the folder exists and 'overwrite' is specified, all contents of the vectordb folder will be deleted and a new vectordb will be created. + # -If set to 'append' the new embeddings will be appended to any existing vectordb. If a source document is specified twice it will be embedded twice. + vectorstore_write_mode: overwrite + +embedding: + module_name: langchain.embeddings + class_name: HuggingFaceHubEmbeddings + kwargs: #optional + repo_id: sentence-transformers/all-mpnet-base-v2 + rate_limit_chunks: 201 # max about 200 when I trialed (free account). Must depend on many considerations. + rate_limit_delay: 306 # in seconds + +splitter: + module_name: langchain.text_splitter + class_name: RecursiveCharacterTextSplitter + args: + chunk_size: 800 + chunk_overlap: 200 +# separator: "\n" + length_function: len # this cannot be configured. Can only be len (or not present) diff --git a/quke/conf/embedding/huggingface.yaml b/quke/conf/embedding/huggingface.yaml new file mode 100644 index 0000000..c9054e7 --- /dev/null +++ b/quke/conf/embedding/huggingface.yaml @@ -0,0 +1,28 @@ +vectordb: + module_name: langchain.vectorstores + class_name: Chroma + vectorstore_location: vector_store/chromadb_hf_del + + # Possible values for vectorstore_write_mode: overwrite, no_overwrite, append + # This works at the vectorstore_location level. + # -If the folder exists and 'no_overwrite' is specified: document will not be embedded + # -If the folder exists and 'overwrite' is specified, all contents of the vectordb folder will be deleted and a new vectordb will be created. + # -If set to 'append' the new embeddings will be appended to any existing vectordb. If a source document is specified twice it will be embedded twice. + vectorstore_write_mode: overwrite + +embedding: + module_name: langchain.embeddings + class_name: HuggingFaceHubEmbeddings + kwargs: #optional + repo_id: sentence-transformers/all-mpnet-base-v2 + rate_limit_chunks: 201 # max about 200 when I trialed (free account). Must depend on many considerations. + rate_limit_delay: 306 # in seconds + +splitter: + module_name: langchain.text_splitter + class_name: CharacterTextSplitter + args: + chunk_size: 1000 + chunk_overlap: 150 + separator: "\n" + length_function: len # this cannot be configured. Can only be len (or not present) diff --git a/quke/conf/embedding/openai.yaml b/quke/conf/embedding/openai.yaml new file mode 100644 index 0000000..301a606 --- /dev/null +++ b/quke/conf/embedding/openai.yaml @@ -0,0 +1,28 @@ +vectordb: + module_name: langchain.vectorstores + class_name: Chroma + vectorstore_location: vector_store/chromadb_openai + + # Possible values for vectorstore_write_mode: overwrite, no_overwrite, append + # This works at the vectorstore_location level. + # -If the folder exists and 'no_overwrite' is specified: document will not be embedded + # -If the folder exists and 'overwrite' is specified, all contents of the vectordb folder will be deleted and a new vectordb will be created. + # -If set to 'append' the new embeddings will be appended to any existing vectordb. If a source document is specified twice it will be embedded twice. + vectorstore_write_mode: overwrite + +embedding: + module_name: langchain.embeddings + class_name: OpenAIEmbeddings + kwargs: #optional +# repo_id: sentence-transformers/all-mpnet-base-v2 + rate_limit_chunks: 200 # max about 200 when I trialed (free account). Must depend on many considerations. + rate_limit_delay: 60 # in seconds + +splitter: + module_name: langchain.text_splitter + class_name: CharacterTextSplitter + args: + chunk_size: 1000 + chunk_overlap: 150 + separator: "\n" + length_function: len # this cannot be configured. Can only be len (or not present) diff --git a/quke/conf/experiment/llama2.yaml b/quke/conf/experiment/llama2.yaml new file mode 100644 index 0000000..d10c346 --- /dev/null +++ b/quke/conf/experiment/llama2.yaml @@ -0,0 +1,5 @@ +# @package _global_ +defaults: + - override /llm: llama2 + - override /embedding: openai + - override /question: eps \ No newline at end of file diff --git a/quke/conf/experiment/openai.yaml b/quke/conf/experiment/openai.yaml new file mode 100644 index 0000000..96502da --- /dev/null +++ b/quke/conf/experiment/openai.yaml @@ -0,0 +1,5 @@ +# @package _global_ +defaults: + - override /llm: gpt3-5 + - override /embedding: openai + - override /question: eps \ No newline at end of file diff --git a/quke/conf/experiment/openaihf.yaml b/quke/conf/experiment/openaihf.yaml new file mode 100644 index 0000000..b0999df --- /dev/null +++ b/quke/conf/experiment/openaihf.yaml @@ -0,0 +1,5 @@ +# @package _global_ +defaults: + - override /llm: gpt3-5 + - override /embedding: huggingface + - override /question: eps \ No newline at end of file diff --git a/quke/conf/llm/cohere.yaml b/quke/conf/llm/cohere.yaml new file mode 100644 index 0000000..7aad6ca --- /dev/null +++ b/quke/conf/llm/cohere.yaml @@ -0,0 +1,7 @@ +module_name_llm: langchain.llms +class_name_llm: Cohere +name: command-nightly + +llm_args: + model: ${llm.name} + temperature: 0 \ No newline at end of file diff --git a/quke/conf/llm/falcon7b.yaml b/quke/conf/llm/falcon7b.yaml new file mode 100644 index 0000000..8dcd1c2 --- /dev/null +++ b/quke/conf/llm/falcon7b.yaml @@ -0,0 +1,11 @@ +module_name_llm: langchain.llms +class_name_llm: HuggingFaceHub +name: tiiuae/falcon-7b-instruct + +llm_args: + repo_id: ${llm.name} + model_kwargs: + max_length: 2000 + temperature: 0.5 + max_new_tokens: 200 + num_return_sequences: 3 diff --git a/quke/conf/llm/gpt3-5.yaml b/quke/conf/llm/gpt3-5.yaml new file mode 100644 index 0000000..44e7271 --- /dev/null +++ b/quke/conf/llm/gpt3-5.yaml @@ -0,0 +1,8 @@ +#type: OpenAI #import OpenAI maybe needed to set the API key, though langchain may just take it from env? +module_name_llm: langchain.chat_models +class_name_llm: ChatOpenAI +name: gpt-3.5-turbo-0301 + +llm_args: + model_name: ${llm.name} + temperature: 0 \ No newline at end of file diff --git a/quke/conf/llm/llama2.yaml b/quke/conf/llm/llama2.yaml new file mode 100644 index 0000000..916f2bb --- /dev/null +++ b/quke/conf/llm/llama2.yaml @@ -0,0 +1,15 @@ +module_name_llm: langchain.llms +class_name_llm: Replicate +name: a16z-infra/llama-2-7b-chat:5ec5fdadd80ace49f5a2b2178cceeb9f2f77c493b85b1131002c26e6b2b13184 +#name: a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5 + +llm_args: + model: ${llm.name} + input: + temperature: 0.75 + max_length: 500 + max_new_tokens: 500 + min_new_tokens: -1 + top_p: 1 + +# NOTE: At present responses for the 13B version are too short to be useful. Not sure what is causing this. \ No newline at end of file diff --git a/quke/conf/question/eps.yaml b/quke/conf/question/eps.yaml new file mode 100644 index 0000000..fa64d14 --- /dev/null +++ b/quke/conf/question/eps.yaml @@ -0,0 +1,3 @@ +questions: +- What is EPS according to the AIF? +- What is CIBC? \ No newline at end of file diff --git a/quke/conf/question/growth.yaml b/quke/conf/question/growth.yaml new file mode 100644 index 0000000..241b969 --- /dev/null +++ b/quke/conf/question/growth.yaml @@ -0,0 +1,3 @@ +questions: +- What is CIBC's EPS growth target in 2022? +- What is it going forward? \ No newline at end of file diff --git a/quke/conf/question/tabulation.yaml b/quke/conf/question/tabulation.yaml new file mode 100644 index 0000000..8e637ae --- /dev/null +++ b/quke/conf/question/tabulation.yaml @@ -0,0 +1,3 @@ +questions: +- Please tabularize the EPS for each year. +- From the table, which year has the highest EPS? \ No newline at end of file diff --git a/quke/embed.py b/quke/embed.py new file mode 100644 index 0000000..15b619e --- /dev/null +++ b/quke/embed.py @@ -0,0 +1,200 @@ +"""Reads documents from a provided directory, performs embedding and captures the embeddings in a vector store.""" +import importlib +import logging # functionality managed by Hydra +import os +import shutil +import time +from collections import defaultdict +from dataclasses import dataclass, field +from glob import glob + +# [ ] TODO: PyMU is faster, PyPDF more accurate: https://github.com/py-pdf/benchmarks +from langchain.document_loaders import CSVLoader, PyMuPDFLoader, TextLoader + +from . import ClassImportDefinition, ClassRateLimit, DatabaseAction + + +@dataclass +class DocumentLoaderDef: + """Definition for LangChain document loaders.""" + + ext: str = "pdf" + loader: object = PyMuPDFLoader + kwargs: defaultdict[dict] = field(default_factory=dict) # empty dict + + +DOC_LOADERS = [ + DocumentLoaderDef(ext="pdf", loader=PyMuPDFLoader), + DocumentLoaderDef(ext="txt", loader=TextLoader, kwargs={"encoding": "utf8"}), + DocumentLoaderDef(ext="csv", loader=CSVLoader), +] +"""Defines the kind of source documents to be searched (specifically to be embedded into the vector store).""" + + +def get_loaders(src_doc_folder: str, loader: DocumentLoaderDef) -> list: + """Returns loaders for each relevant file in the provided folder. + + LangChain loaders are used to load various types of documents in preparation + of embedding and persisting in vector stores. + + Args: + src_doc_folder: The folder of the source files. + loader: Definition of the loader. Loaders exist for example for + pdf, text and csv files. + """ + ext = loader.ext + + # to make ext case insensitive + ext = "".join([f"[{ch}{ch.swapcase()}]" for ch in ext]) + src_file_names = glob( + os.path.join(src_doc_folder, "**", f"*.{ext}"), recursive=True + ) # also looks in subfolders + + # TODO: Problem with embedding more than 2 files at once, or some number of pages/chunks (using HF)? + # Error message does not really help. Appending in steps does work. + loaders = [loader.loader(pdf_name, **loader.kwargs) for pdf_name in src_file_names] + + return loaders + + +def get_pages_from_document(src_doc_folder: str) -> list: + """Reads documents from the directory/folder provided and returns a list of pages and metadata.""" + pages = [] + for docloader in DOC_LOADERS: + for loader in get_loaders(src_doc_folder, docloader): + pages.extend(loader.load()) + + try: + logging.info( + f"Document loaded: {len(pages)} pages, last one {pages[-1].metadata}" + ) + except Exception: + logging.warning( + f"No source documents loaded. No valid files found in {src_doc_folder}. " + "Must be .pdf, .txt or .csv." + ) + + return pages + + +def get_chunks_from_pages(pages: list, splitter_params) -> list: + """Splits pages into smaller chunks used for embedding.""" + # for splitter args containing 'func', the yaml value is converted into a Python function. + # TODO: Security risk? Hence a safe_list of functions is provided; severly limiting flexibility. + # TODO: The other limiting factor: any parameter containing 'func' is eval()-ed into a function reference; + # also no other parameter is. + safe_function_list = ["len"] + for key in splitter_params["splitter_args"]: + if ("func".lower() in key.lower()) and splitter_params["splitter_args"][ + key + ] in safe_function_list: + splitter_params["splitter_args"][key] = eval( + splitter_params["splitter_args"][key] + ) + + module = importlib.import_module(splitter_params["splitter_import"].module_name) + class_ = getattr(module, splitter_params["splitter_import"].class_name) + splitter = class_ + + text_splitter = splitter(**splitter_params["splitter_args"]) + + chunks = text_splitter.split_documents(pages) + + logging.info(f"Documents split. {len(chunks)} chunks from {len(pages)} pages.") + return chunks + + +def embed( + src_doc_folder: str, + vectordb_location: str, + embedding_import: ClassImportDefinition, + embedding_kwargs: dict, + vectordb_import: ClassImportDefinition, + rate_limit: ClassRateLimit, + splitter_params: dict, + write_mode: DatabaseAction = DatabaseAction.NO_OVERWRITE, +) -> int: + """Reads documents from a provided directory, performs embedding and captures the embeddings in a vector store.""" + logging.info(f"Starting to embed into VectorDB: {vectordb_location}") + + # if folder does not exist, or write_mode is APPEND no need to do anything here. + if os.path.exists(vectordb_location) and not os.path.isfile( # noqa: SIM102 + vectordb_location + ): + if os.listdir( + vectordb_location + ): # path exists and is not empty - assumed to contain vectordb + if write_mode == DatabaseAction.NO_OVERWRITE: # skip embedding + logging.info( + f"No new embeddings created. Embedding database already exists at " + f"{vectordb_location!r}. Remove database folder, or change embedding config " + "vectorstore_write_mode to OVERWRITE or APPEND." + ) + return + if ( + write_mode == DatabaseAction.OVERWRITE + ): # remove exising database before embedding + # TODO: Is this too harsh to delete the full folder? At least create a backup? + logging.warning( + f"The folder containing the embedding database ({vectordb_location}) and all its contents " + "about to be overwritten." + ) + shutil.rmtree(vectordb_location) + + # get bite sized chunks from source documents + chunks = get_chunks_from_pages( + get_pages_from_document(src_doc_folder), splitter_params + ) + + logging.warning( + "CAUTION: This function uses external compute services (like OpenAI or HuggingFace). " + "This is likely to cost money." + ) + + # Use chunker to embed in chunks with a wait time in between. As a basic way to deal with some rate limiting. + def chunker(seq, size): + return (seq[pos : pos + size] for pos in range(0, len(seq), size)) + + c = 0 + for fewer_chunks in chunker(chunks, rate_limit.count_limit): + if c > 0: + delay = rate_limit.delay + logging.info(f"Sleeping for {delay} seconds due to rate limiter.") + time.sleep(delay) + + c += embed_these_chunks( + fewer_chunks, + vectordb_location, + embedding_import, + embedding_kwargs, + vectordb_import, + ) + + return c + + +def embed_these_chunks( + chunks, + vectordb_location: str, + embedding_import: ClassImportDefinition, + embedding_kwargs: dict, + vectordb_import: ClassImportDefinition, +) -> int: + """Embed the provided chunks and capture into a vector store.""" + module = importlib.import_module(embedding_import.module_name) + class_ = getattr(module, embedding_import.class_name) + embedding = class_(**embedding_kwargs) + + module = importlib.import_module(vectordb_import.module_name) + class_ = getattr(module, vectordb_import.class_name) + vectordb_type = class_() + + vectordb = vectordb_type.from_documents( + documents=chunks, embedding=embedding, persist_directory=vectordb_location + ) + + vectordb.persist() + + logging.info(f"{len(chunks)} chunks persisted into database at {vectordb_location}") + + return len(chunks) diff --git a/quke/llm_chat.py b/quke/llm_chat.py new file mode 100644 index 0000000..db797af --- /dev/null +++ b/quke/llm_chat.py @@ -0,0 +1,134 @@ +"""Sets up all elements required for a chat session.""" +import importlib +import logging # functionality managed by Hydra +import os +from collections import defaultdict +from datetime import datetime + +from langchain.chains import ConversationalRetrievalChain +from langchain.memory import ConversationBufferMemory +from mdutils.fileutils import MarkDownFile +from mdutils.mdutils import MdUtils + +from . import ClassImportDefinition + + +def chat( + vectordb_location: str, + embedding_import: ClassImportDefinition, + vectordb_import: ClassImportDefinition, + llm_import: ClassImportDefinition, + llm_parameters, + prompt_parameters, + output_file, +) -> object: + """Initiates a chat with an LLM. + + Sets up all components required for the chat including the LLM, + embedding model, vector store, chat memory, retriever and actual + questions. + """ + module = importlib.import_module(embedding_import.module_name) + class_ = getattr(module, embedding_import.class_name) + embedding = class_() + + logging.warning( + "CAUTION: This function uses external compute services " + "(like OpenAI or HuggingFace). This is likely to cost money." + ) + module = importlib.import_module(vectordb_import.module_name) + class_ = getattr(module, vectordb_import.class_name) + vectordb = class_(embedding_function=embedding, persist_directory=vectordb_location) + + module = importlib.import_module(llm_import.module_name) + class_ = getattr(module, llm_import.class_name) + llm = class_(**llm_parameters) + + memory = ConversationBufferMemory( + memory_key="chat_history", + return_messages=True, + output_key="answer", + ) + + qa = ConversationalRetrievalChain.from_llm( + llm, + retriever=vectordb.as_retriever(), + memory=memory, + return_source_documents=True, + ) + + # NOTE: trial API keys may have very restrictive rules. It is plausible that you run into + # constraints after the 2nd question. + for question in prompt_parameters: + result = qa({"question": question}) + + # print(qa({"question": question})) + + # erik = source_documents + # print(f"==============={erik}") + + chat_output(question, result) + chat_output_to_file(result, output_file) + + logging.info("=======================") + + return qa + + +def chat_output(question: str, result: dict) -> None: + """Logs a chat question and anwer.""" + logging.info("=======================") + logging.info(f"Q: {question}") + logging.info(f"A: {result['answer']}") + + src_docs = [doc.metadata for doc in result["source_documents"]] + src_docs = dict_crosstab(src_docs, "source", "page") + for key, value in src_docs.items(): + logging.info(f"Source document: {key}, Pages used: {value}") + + +# TODO: Either I do not understand mdutils or it is an unfriendly package when trying to append. +def chat_output_to_file(result: dict, output_file) -> None: + """Populates a record of the chat with the LLM into a markdown file.""" + first_write = not os.path.isfile(output_file["path"]) + + mdFile = MdUtils(file_name="tmp.md") + + if first_write: + mdFile.new_header(1, "LLM Chat Session with quke") + mdFile.write( + datetime.now().astimezone().strftime("%a %d-%b-%Y %H:%M %Z"), align="center" + ) + mdFile.new_paragraph("") + mdFile.new_header(2, "Experiment settings", header_id="settings") + mdFile.insert_code(output_file["conf_yaml"], language="yaml") + mdFile.new_header(2, "Chat", header_id="chat") + else: + existing_text = MarkDownFile().read_file(file_name=output_file["path"]) + mdFile.new_paragraph(existing_text) + + mdFile.new_paragraph(f"Q: {result['question']}") + mdFile.new_paragraph(f"A: {result['answer']}") + + src_docs = [doc.metadata for doc in result["source_documents"]] + src_docs = dict_crosstab(src_docs, "source", "page") + for key, value in src_docs.items(): + mdFile.new_paragraph(f"Source document: {key}, Pages used: {value}") + + new = MarkDownFile(name=output_file["path"]) + + new.append_end((mdFile.get_md_text()).strip()) + + +def dict_crosstab(source, key, listed, missing="NA"): + """Limited and simple version of a crosstab query on a dict.""" + dict_subs = [] + for d in source: + dict_subs.append({key: d[key], listed: d.get(listed, missing)}.values()) + + d = defaultdict(list) + for k, v in dict_subs: + d[k].append(v) + d[k] = list(set(d[k])) + + return dict(d) # TODO: consider sorted(d.items()) diff --git a/quke/quke.py b/quke/quke.py new file mode 100644 index 0000000..0792ff6 --- /dev/null +++ b/quke/quke.py @@ -0,0 +1,193 @@ +"""Main module to initiate quke, to compare chat results. + +LLMs, embedding model, vector store and other components can be congfigured. +""" +import logging # functionality managed by Hydra +import os + +import hydra +from dotenv import find_dotenv, load_dotenv +from hydra.utils import to_absolute_path +from omegaconf import DictConfig, OmegaConf +from rich.console import Console + +from . import ClassImportDefinition, ClassRateLimit, DatabaseAction, embed, llm_chat + +_ = load_dotenv(find_dotenv()) + + +class ConfigParser: + """Turns config into a more programming friendly and consistent format. + + For core classes and functions groups configuration by + class/function arguments for convenience. + + Provides an abstraction layer on top of the structure of the + Hydra configuration files. + """ + + def __init__(self, cfg: DictConfig) -> None: + """Creates configuration abstraction.""" + self.cfg = cfg + + # TODO: Read from cfg + self.src_doc_folder = cfg.source_document_folder + + # TODO: Is this sufficiently robust? What if the user wants a folder not related to wcd/pwd? + # Consider using os.path.isabs(path) or os.path.abspath(path). Or just pass the string and + # 'Python will handle it'? + self.vectordb_location = os.path.join( + os.getcwd(), + cfg.internal_data_folder, + cfg.embedding.vectordb.vectorstore_location, + ) + self.embedding_import = ClassImportDefinition( + cfg.embedding.embedding.module_name, cfg.embedding.embedding.class_name + ) + self.vectordb_import = ClassImportDefinition( + cfg.embedding.vectordb.module_name, cfg.embedding.vectordb.class_name + ) + self.llm_import = ClassImportDefinition( + cfg.llm.module_name_llm, cfg.llm.class_name_llm + ) + self.embedding_rate_limit = ClassRateLimit( + cfg.embedding.embedding.rate_limit_chunks, + cfg.embedding.embedding.rate_limit_delay, + ) + self.embedding_kwargs = self.get_embedding_kwargs(cfg) + + self.splitter_import = ClassImportDefinition( + cfg.embedding.splitter.module_name, cfg.embedding.splitter.class_name + ) + self.splitter_args = self.get_args_dict(cfg.embedding.splitter.args) + + try: + self.write_mode = DatabaseAction[ + (cfg.embedding.vectordb.vectorstore_write_mode).upper() + ] + except Exception: + logging.warn( + f"Invalid value configured for cfg.embedding.vectorstore_write_mode: " + f"{cfg.embedding.vectordb.vectorstore_write_mode}. Using no_overwrite instead." + ) + self.write_mode = DatabaseAction.NO_OVERWRITE + + self.questions = cfg.question.questions + + try: + if not cfg.embed_only: + self.embed_only = False + else: + self.embed_only = True + except Exception: + self.embed_only = False + + # TODO: need something better for output folder + # https://hydra.cc/docs/tutorials/basic/running_your_app/working_directory/ + try: # try statement done for testing suite + self.output_file = os.path.join( + hydra.core.hydra_config.HydraConfig.get()["runtime"]["output_dir"], + cfg.experiment_summary_file, + ) + except Exception: + self.output_file = cfg.experiment_summary_file + + def get_embed_params(self): + """Based on the config files returns the set of parameters need to start embedding.""" + embed_parameters = { + "src_doc_folder": self.src_doc_folder, + "vectordb_location": self.vectordb_location, + "embedding_import": self.embedding_import, + "embedding_kwargs": self.embedding_kwargs, + "vectordb_import": self.vectordb_import, + "rate_limit": self.embedding_rate_limit, + "splitter_params": self.get_splitter_params(), + "write_mode": self.write_mode, + } + return embed_parameters + + def get_chat_params(self): + """Based on the config files returns the set of parameters need to start a chat.""" + chat_parameters = { + "vectordb_location": self.vectordb_location, + "embedding_import": self.embedding_import, + "vectordb_import": self.vectordb_import, + "llm_import": self.llm_import, + "llm_parameters": self.get_llm_parameters(), + "prompt_parameters": self.questions, + "output_file": self.get_chat_session_file_parameters(self.cfg), + } + return chat_parameters + + def get_splitter_params(self) -> dict: + """Based on the config files returns the set of parameters needed to split source documents.""" + return { + "splitter_import": self.splitter_import, + "splitter_args": self.splitter_args, + } + + def get_args_dict(self, cfg_sub): + """Takes a subset of the Hydra configs and returns the same as a dict.""" + return OmegaConf.to_container(cfg_sub, resolve=True) + + def get_llm_parameters(self): + """Based on the config files returns the set of parameters needed to setup an LLM.""" + return OmegaConf.to_container(self.cfg.llm.llm_args, resolve=True) + + def get_chat_session_file_parameters(self, cfg: DictConfig) -> dict: + """Returns the full configuration in a single yaml and file location for output.""" + chat_sesion_file_parameters = { + "path": self.output_file, + "conf_yaml": OmegaConf.to_yaml(cfg), + } + return chat_sesion_file_parameters + + def get_embedding_kwargs(self, cfg: DictConfig) -> dict: + """Based on the config files returns the set of parameters needed for embedding.""" + try: + embedding_kwargs = ( + cfg.embedding.embedding.kwargs if cfg.embedding.embedding.kwargs else {} + ) + """ + if cfg.embedding.embedding.kwargs: + embedding_kwargs = cfg.embedding.embedding.kwargs + else: + embedding_kwargs = {} + """ + except Exception: + embedding_kwargs = {} + return embedding_kwargs + + +@hydra.main(version_base=None, config_path="conf", config_name="config") +def quke(cfg: DictConfig) -> None: + """The main function to initiate a chat. + + Including the embedding of the provided source documents. + """ + console = Console() + config_parser = ConfigParser(cfg) + + embed_parameters = config_parser.get_embed_params() + + with console.status("Embedding...", spinner="aesthetic"): + # python -m rich.spinner to see options + embed.embed(**embed_parameters) + logging.info("\n" + OmegaConf.to_yaml(cfg)) + + if not config_parser.embed_only: + with console.status("Chatting...", spinner="aesthetic"): + chat_parameters = config_parser.get_chat_params() + llm_chat.chat(**chat_parameters) + + logging.info( + f"Source documents loaded from: {to_absolute_path(config_parser.src_doc_folder)}" + ) + logging.info( + f"Vector store created in: {to_absolute_path(config_parser.vectordb_location)}" + ) + logging.info(f"Results captured in: {to_absolute_path(config_parser.output_file)}") + + +if __name__ == "__main__": + quke() diff --git a/quke/trial questions.txt b/quke/trial questions.txt new file mode 100644 index 0000000..5a8441f --- /dev/null +++ b/quke/trial questions.txt @@ -0,0 +1,4 @@ +poetry run quke embedding=huggingface llm=llama2 ++question.questions=['Using only the document provided can you tell what is Lufthansa? End your answer with my pleasure.'] +==> Cohere, OpenAI say the document does not mention Lufthansa. +==> Falcon7b comes back with an answer, describing Lufthansa correctly but clearly not using the AIF. Not sure if this is Falcon or HuggingFace who is the problem. +==> Llama2 (using Replicate) does not return an answer at the moment. Somehow Lanchain is also not timing out... \ No newline at end of file diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/conf/__init__.py b/tests/conf/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/conf/config.yaml b/tests/conf/config.yaml new file mode 100644 index 0000000..5f692f0 --- /dev/null +++ b/tests/conf/config.yaml @@ -0,0 +1,11 @@ +internal_data_folder: "./tests/data/idata" +source_document_folder: "./tests/data/src_doc/" +experiment_summary_file: 'chat_session.md' + +embed_only: False + +defaults: + - _self_ + - llm: falcon7b + - embedding: huggingface + - question: eps \ No newline at end of file diff --git a/tests/conf/embedding/cohere.yaml b/tests/conf/embedding/cohere.yaml new file mode 100644 index 0000000..9540e22 --- /dev/null +++ b/tests/conf/embedding/cohere.yaml @@ -0,0 +1,28 @@ +vectordb: + module_name: langchain.vectorstores + class_name: Chroma + vectorstore_location: vector_store/chromadb_cohere + + # Possible values for vectorstore_write_mode: overwrite, no_overwrite, append + # This works at the vectorstore_location level. + # -If the folder exists and 'no_overwrite' is specified: document will not be embedded + # -If the folder exists and 'overwrite' is specified, all contents of the vectordb folder will be deleted and a new vectordb will be created. + # -If set to 'append' the new embeddings will be appended to any existing vectordb. If a source document is specified twice it will be embedded twice. + vectorstore_write_mode: no_overwrite + +embedding: + module_name: langchain.embeddings + class_name: CohereEmbeddings + kwargs: #optional +# repo_id: sentence-transformers/all-mpnet-base-v2 + rate_limit_chunks: 300 # max about 200 when I trialed (free account). Must depend on many considerations. + rate_limit_delay: 60 # in seconds + +splitter: + module_name: langchain.text_splitter + class_name: CharacterTextSplitter + args: + chunk_size: 1000 + chunk_overlap: 150 + separator: "\n" + length_function: len # this cannot be configured. Can only be len (or not present) \ No newline at end of file diff --git a/tests/conf/embedding/hf_r.yaml b/tests/conf/embedding/hf_r.yaml new file mode 100644 index 0000000..165e567 --- /dev/null +++ b/tests/conf/embedding/hf_r.yaml @@ -0,0 +1,28 @@ +vectordb: + module_name: langchain.vectorstores + class_name: Chroma + vectorstore_location: vector_store/chromadb_hf_recursive + + # Possible values for vectorstore_write_mode: overwrite, no_overwrite, append + # This works at the vectorstore_location level. + # -If the folder exists and 'no_overwrite' is specified: document will not be embedded + # -If the folder exists and 'overwrite' is specified, all contents of the vectordb folder will be deleted and a new vectordb will be created. + # -If set to 'append' the new embeddings will be appended to any existing vectordb. If a source document is specified twice it will be embedded twice. + vectorstore_write_mode: overwrite + +embedding: + module_name: langchain.embeddings + class_name: HuggingFaceHubEmbeddings + kwargs: #optional + repo_id: sentence-transformers/all-mpnet-base-v2 + rate_limit_chunks: 201 # max about 200 when I trialed (free account). Must depend on many considerations. + rate_limit_delay: 306 # in seconds + +splitter: + module_name: langchain.text_splitter + class_name: RecursiveCharacterTextSplitter + args: + chunk_size: 800 + chunk_overlap: 200 +# separator: "\n" + length_function: len # this cannot be configured. Can only be len (or not present) diff --git a/tests/conf/embedding/huggingface.yaml b/tests/conf/embedding/huggingface.yaml new file mode 100644 index 0000000..c9054e7 --- /dev/null +++ b/tests/conf/embedding/huggingface.yaml @@ -0,0 +1,28 @@ +vectordb: + module_name: langchain.vectorstores + class_name: Chroma + vectorstore_location: vector_store/chromadb_hf_del + + # Possible values for vectorstore_write_mode: overwrite, no_overwrite, append + # This works at the vectorstore_location level. + # -If the folder exists and 'no_overwrite' is specified: document will not be embedded + # -If the folder exists and 'overwrite' is specified, all contents of the vectordb folder will be deleted and a new vectordb will be created. + # -If set to 'append' the new embeddings will be appended to any existing vectordb. If a source document is specified twice it will be embedded twice. + vectorstore_write_mode: overwrite + +embedding: + module_name: langchain.embeddings + class_name: HuggingFaceHubEmbeddings + kwargs: #optional + repo_id: sentence-transformers/all-mpnet-base-v2 + rate_limit_chunks: 201 # max about 200 when I trialed (free account). Must depend on many considerations. + rate_limit_delay: 306 # in seconds + +splitter: + module_name: langchain.text_splitter + class_name: CharacterTextSplitter + args: + chunk_size: 1000 + chunk_overlap: 150 + separator: "\n" + length_function: len # this cannot be configured. Can only be len (or not present) diff --git a/tests/conf/embedding/openai.yaml b/tests/conf/embedding/openai.yaml new file mode 100644 index 0000000..301a606 --- /dev/null +++ b/tests/conf/embedding/openai.yaml @@ -0,0 +1,28 @@ +vectordb: + module_name: langchain.vectorstores + class_name: Chroma + vectorstore_location: vector_store/chromadb_openai + + # Possible values for vectorstore_write_mode: overwrite, no_overwrite, append + # This works at the vectorstore_location level. + # -If the folder exists and 'no_overwrite' is specified: document will not be embedded + # -If the folder exists and 'overwrite' is specified, all contents of the vectordb folder will be deleted and a new vectordb will be created. + # -If set to 'append' the new embeddings will be appended to any existing vectordb. If a source document is specified twice it will be embedded twice. + vectorstore_write_mode: overwrite + +embedding: + module_name: langchain.embeddings + class_name: OpenAIEmbeddings + kwargs: #optional +# repo_id: sentence-transformers/all-mpnet-base-v2 + rate_limit_chunks: 200 # max about 200 when I trialed (free account). Must depend on many considerations. + rate_limit_delay: 60 # in seconds + +splitter: + module_name: langchain.text_splitter + class_name: CharacterTextSplitter + args: + chunk_size: 1000 + chunk_overlap: 150 + separator: "\n" + length_function: len # this cannot be configured. Can only be len (or not present) diff --git a/tests/conf/experiment/llama2.yaml b/tests/conf/experiment/llama2.yaml new file mode 100644 index 0000000..d10c346 --- /dev/null +++ b/tests/conf/experiment/llama2.yaml @@ -0,0 +1,5 @@ +# @package _global_ +defaults: + - override /llm: llama2 + - override /embedding: openai + - override /question: eps \ No newline at end of file diff --git a/tests/conf/experiment/openai.yaml b/tests/conf/experiment/openai.yaml new file mode 100644 index 0000000..96502da --- /dev/null +++ b/tests/conf/experiment/openai.yaml @@ -0,0 +1,5 @@ +# @package _global_ +defaults: + - override /llm: gpt3-5 + - override /embedding: openai + - override /question: eps \ No newline at end of file diff --git a/tests/conf/experiment/openaihf.yaml b/tests/conf/experiment/openaihf.yaml new file mode 100644 index 0000000..b0999df --- /dev/null +++ b/tests/conf/experiment/openaihf.yaml @@ -0,0 +1,5 @@ +# @package _global_ +defaults: + - override /llm: gpt3-5 + - override /embedding: huggingface + - override /question: eps \ No newline at end of file diff --git a/tests/conf/llm/cohere.yaml b/tests/conf/llm/cohere.yaml new file mode 100644 index 0000000..7aad6ca --- /dev/null +++ b/tests/conf/llm/cohere.yaml @@ -0,0 +1,7 @@ +module_name_llm: langchain.llms +class_name_llm: Cohere +name: command-nightly + +llm_args: + model: ${llm.name} + temperature: 0 \ No newline at end of file diff --git a/tests/conf/llm/falcon7b.yaml b/tests/conf/llm/falcon7b.yaml new file mode 100644 index 0000000..8dcd1c2 --- /dev/null +++ b/tests/conf/llm/falcon7b.yaml @@ -0,0 +1,11 @@ +module_name_llm: langchain.llms +class_name_llm: HuggingFaceHub +name: tiiuae/falcon-7b-instruct + +llm_args: + repo_id: ${llm.name} + model_kwargs: + max_length: 2000 + temperature: 0.5 + max_new_tokens: 200 + num_return_sequences: 3 diff --git a/tests/conf/llm/gpt3-5.yaml b/tests/conf/llm/gpt3-5.yaml new file mode 100644 index 0000000..44e7271 --- /dev/null +++ b/tests/conf/llm/gpt3-5.yaml @@ -0,0 +1,8 @@ +#type: OpenAI #import OpenAI maybe needed to set the API key, though langchain may just take it from env? +module_name_llm: langchain.chat_models +class_name_llm: ChatOpenAI +name: gpt-3.5-turbo-0301 + +llm_args: + model_name: ${llm.name} + temperature: 0 \ No newline at end of file diff --git a/tests/conf/llm/llama2.yaml b/tests/conf/llm/llama2.yaml new file mode 100644 index 0000000..916f2bb --- /dev/null +++ b/tests/conf/llm/llama2.yaml @@ -0,0 +1,15 @@ +module_name_llm: langchain.llms +class_name_llm: Replicate +name: a16z-infra/llama-2-7b-chat:5ec5fdadd80ace49f5a2b2178cceeb9f2f77c493b85b1131002c26e6b2b13184 +#name: a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5 + +llm_args: + model: ${llm.name} + input: + temperature: 0.75 + max_length: 500 + max_new_tokens: 500 + min_new_tokens: -1 + top_p: 1 + +# NOTE: At present responses for the 13B version are too short to be useful. Not sure what is causing this. \ No newline at end of file diff --git a/tests/conf/question/eps.yaml b/tests/conf/question/eps.yaml new file mode 100644 index 0000000..fa64d14 --- /dev/null +++ b/tests/conf/question/eps.yaml @@ -0,0 +1,3 @@ +questions: +- What is EPS according to the AIF? +- What is CIBC? \ No newline at end of file diff --git a/tests/conf/question/tabulation.yaml b/tests/conf/question/tabulation.yaml new file mode 100644 index 0000000..8e637ae --- /dev/null +++ b/tests/conf/question/tabulation.yaml @@ -0,0 +1,3 @@ +questions: +- Please tabularize the EPS for each year. +- From the table, which year has the highest EPS? \ No newline at end of file diff --git a/tests/data/src_doc/test.txt b/tests/data/src_doc/test.txt new file mode 100644 index 0000000..d3a8df1 --- /dev/null +++ b/tests/data/src_doc/test.txt @@ -0,0 +1 @@ +Francis de Groot is a non-existent actor that has not played in any Hollywood production. \ No newline at end of file diff --git a/tests/test_001.py b/tests/test_001.py new file mode 100644 index 0000000..c131ddc --- /dev/null +++ b/tests/test_001.py @@ -0,0 +1,100 @@ +import os + +import pytest +from hydra import compose, initialize + +from quke.embed import embed, get_chunks_from_pages, get_pages_from_document +from quke.llm_chat import chat +from quke.quke import ConfigParser + +OUTPUT_FILE = "chat_session.md" +INTERNAL_DATA_FOLDER = "./tests/data/idata/" +SRC_DATA_FOLDER = "./tests/data/src_doc/" +TEXT_FILE = "test.txt" + + +@pytest.fixture(scope="session") +def GetConfigEmbedOnly(): + with initialize(version_base=None, config_path="./conf"): + cfg = compose( + config_name="config", + overrides=[ + "embed_only=True", + f"experiment_summary_file={OUTPUT_FILE}", + f"internal_data_folder={INTERNAL_DATA_FOLDER}", + "embedding.vectordb.vectorstore_write_mode=overwrite", + ], + ) + return cfg + + +@pytest.fixture(scope="session") +def GetConfigLLMOnly(tmp_path_factory): + folder = tmp_path_factory.mktemp("output") + output_file = os.path.join(folder, OUTPUT_FILE) + with initialize(version_base=None, config_path="./conf"): + cfg = compose( + config_name="config", + overrides=[ + "embed_only=False", + f"experiment_summary_file={output_file}", + f"internal_data_folder={INTERNAL_DATA_FOLDER}", + "embedding.vectordb.vectorstore_write_mode=no_overwrite", + ], + ) + return cfg + + +@pytest.fixture(scope="session") +def GetPages() -> list: + return get_pages_from_document(SRC_DATA_FOLDER) + + +@pytest.fixture(scope="session") +def GetChunks(GetPages: list, GetConfigEmbedOnly) -> list: + return get_chunks_from_pages( + GetPages, ConfigParser(GetConfigEmbedOnly).get_splitter_params() + ) + + +def test_documentloader(GetPages: list): + assert len(GetPages) > 0 + + text_file_found = False + for item in GetPages: + if TEXT_FILE in item.metadata["source"]: + text_file_found = True + assert text_file_found + + +def test_getchunks(GetChunks): + assert len(GetChunks) == 1 # with current basic test just equals 1 + + +def test_config(): + with initialize(version_base=None, config_path="./conf"): + cfg = compose(config_name="config", overrides=["embed_only=True"]) + assert cfg.source_document_folder == "./tests/data/src_doc/" + assert cfg.embed_only is True + assert ( + len(os.listdir(cfg.source_document_folder)) == 1 + ) # only 1 file for the moment + + +@pytest.mark.expensive() +# Do the following to exlude this +# poetry run pytest -m 'not expensive' +def test_embed(GetConfigEmbedOnly): + chunks_embedded = embed(**ConfigParser(GetConfigEmbedOnly).get_embed_params()) + assert chunks_embedded == 1 + + +@pytest.mark.expensive() +# @pytest.mark.skipif(not os.path.exists(os.path.dirname(OUTPUT_FILE)), +# reason=f"Output folder {os.path.dirname(OUTPUT_FILE)} should exist before running test.") +def test_chat(GetConfigLLMOnly): + from langchain.chains import ConversationalRetrievalChain + + chat_result = chat(**ConfigParser(GetConfigLLMOnly).get_chat_params()) + assert isinstance(chat_result, ConversationalRetrievalChain) + assert os.path.isfile(ConfigParser(GetConfigLLMOnly).output_file)