Move stuff around, make installable

README.md

@@ -1,15 +1,32 @@
 # Dump your knowledge, let AI refine it
 
+## Installation
+
+Create a Python environment with Python 3.10+. Install the requirements and the package:
+
+``` sh
+python -m pip install -r requirements.txt
+python -m pip install .
+```
+
+For development, instead do:
+
+``` sh
+python -m pip install -r requirements.txt
+python -m pip install -r requirements-dev.txt
+python -m pip install -e .
+```
+
 ## Starting
 
-Install stuff, then, in one terminal, start the background worker:
+In one terminal, start the background worker:
 
 ```sh
 cd src
 python worker.py
 ```
 
-Start the web server:
+In another terminal, start the web server:
 
 ```sh
 cd src

VERSION

@@ -0,0 +1 @@
+0.0.1

requests.org

@@ -22,7 +22,7 @@ curl -X 'POST' \
 #+end_src
 
 #+RESULTS:
-: Submitted job 04d44970ced1473999dfab77b02202b8
+: Submitted job 6012b198ffe0467d9344a196a2ced121
 
 #+begin_src bash
 curl -X 'POST' \
@@ -36,16 +36,16 @@ curl -X 'POST' \
 #+end_src
 
 #+RESULTS:
-: Submitted job 3cc2104aec0748b1bd5743c321b169ac
+: Submitted job 05058b906f524fb4bfedc4f5a84eff06
 
 #+begin_src bash
 curl -X 'GET' \
-  'http://localhost:8080/check_status/22b158499b744f42918912cd387fd657' \
+  'http://localhost:8080/check_status/6012b198ffe0467d9344a196a2ced121' \
   -H 'accept: application/json'
 #+end_src
 
 #+RESULTS:
-| {"id":"22b158499b744f42918912cd387fd657" | status:"done" | last_updated:"2023-05-05T14:54:11"} |
+| {"id":"6012b198ffe0467d9344a196a2ced121" | status:"done" | last_updated:"2023-05-08T12:27:07"} |
 
 #+begin_src bash
 curl -X 'GET' \
@@ -54,4 +54,4 @@ curl -X 'GET' \
 #+end_src
 
 #+RESULTS:
-| [{"id":"3cc2104aec0748b1bd5743c321b169ac" | author:"ben" | summary:"A new approach to NLP that incorporates reinforcement learning and human feedback. How does it work? Why does it work? In this post | I’ll explain how it works. RLHF is a new approach to NLP that incorporates reinforcement learning and human feedback. It’s a new approach to NLP that incorporates reinforcement learning and human feedback. It’s a new approach to NLP that incorporates reinforcement learning and human feedback. It’s a new approach to NLP that incorporates reinforcement learning and human feedback. It’s a new approach to NLP that incorporates reinforcement learning and human feedback." | tags:["#general" | #rlhf] | date:"2023-05-05T14:56:32"} | {"id":"04d44970ced1473999dfab77b02202b8" | author:"ben" | summary:"GitLab | the most comprehensive | scalable enterprise DevSecOps platform for software innovation | and Google Cloud today announced an extension of their strategic partnership to deliver secure AI offerings to the enterprise. By leveraging Google Cloud's customizable foundation models and open generative AI infrastructure | GitLab will provide customers with AI-assisted features directly within the enterprise DevSecOps platform. The company's AI capabilities are designed to help enterprises improve productivity and reduce costs." | tags:["#general"] | date:"2023-05-05T14:56:31"}] |
+| [{"id":"05058b906f524fb4bfedc4f5a84eff06" | author:"ben" | summary:"A new approach to NLP that incorporates reinforcement learning and human feedback. How does it work? Why does it work? In this post | I’ll explain how it works. RLHF is a new approach to NLP that incorporates reinforcement learning and human feedback. It’s a new approach to NLP that incorporates reinforcement learning and human feedback. It’s a new approach to NLP that incorporates reinforcement learning and human feedback. It’s a new approach to NLP that incorporates reinforcement learning and human feedback. It’s a new approach to NLP that incorporates reinforcement learning and human feedback." | tags:["#general" | #rlhf] | date:"2023-05-08T12:27:31"} | {"id":"6012b198ffe0467d9344a196a2ced121" | author:"ben" | summary:"GitLab | the most comprehensive | scalable enterprise DevSecOps platform for software innovation | and Google Cloud today announced an extension of their strategic partnership to deliver secure AI offerings to the enterprise. By leveraging Google Cloud's customizable foundation models and open generative AI infrastructure | GitLab will provide customers with AI-assisted features directly within the enterprise DevSecOps platform. The company's AI capabilities are designed to help enterprises improve productivity and reduce costs." | tags:["#general"] | date:"2023-05-08T12:27:07"}] |

requirements-dev.txt

@@ -2,3 +2,5 @@ black
 isort
 mypy
 ruff
+pytest
+pytest-cov

setup.py

@@ -0,0 +1,44 @@
+import os
+
+from setuptools import setup, find_packages
+
+
+with open('VERSION', 'r') as f:
+    version = f.read().rstrip()
+
+with open('requirements.txt') as f:
+    install_requires = [l.strip() for l in f]
+
+
+python_requires = '>=3.10'
+
+tests_require = [
+    'black',
+    'mypy',
+    'pytest',
+    'pytest-cov',
+    'ruff',
+]
+
+here = os.path.abspath(os.path.dirname(__file__))
+try:
+    README = open(os.path.join(here, 'README.md')).read()
+except IOError:
+    README = ''
+
+
+setup(
+    name='gistillery',
+    version=version,
+    description="TODO",
+    long_description=README,
+    license='new BSD 3-Clause',
+    packages=find_packages('src'),
+    package_dir={'': 'src'},
+    include_package_data=True,
+    python_requires=python_requires,
+    install_requires=install_requires,
+    extras_require={
+        'tests': tests_require,
+    },
+)

src/{ml.py → gistillery/ml.py}

@@ -5,7 +5,7 @@ import re
 
 import httpx
 
-from base import JobInput
+from gistillery.base import JobInput
 
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.DEBUG)

src/{webservice.py → gistillery/webservice.py}

@@ -3,8 +3,8 @@ import uuid
 
 from fastapi import FastAPI
 
-from base import EntriesResult, JobStatus, JobStatusResult, RequestInput
-from db import TABLES, get_db_cursor
+from gistillery.base import EntriesResult, JobStatus, JobStatusResult, RequestInput
+from gistillery.db import TABLES, get_db_cursor
 
 
 logger = logging.getLogger(__name__)

src/{worker.py → gistillery/worker.py}

@@ -1,9 +1,9 @@
 import time
 from dataclasses import dataclass
 
-from base import JobInput
-from db import get_db_cursor
-from ml import (
+from gistillery.base import JobInput
+from gistillery.db import get_db_cursor
+from gistillery.ml import (
     DefaultUrlProcessor,
     HfTransformersSummarizer,
     HfTransformersTagger,