[refactoring] code cleanage

.gitignore

@@ -1 +1,163 @@
-.streamlit/secrets.toml
+# Byte-compiled / optimized / DLL files
+.streamlit/
+__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/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/

app.py

@@ -1,45 +1,22 @@
 import streamlit as st
-from langchain_openai import ChatOpenAI
-from langchain_core.prompts import ChatPromptTemplate
-from langchain.schema import StrOutputParser
-
-chat_llm = ChatOpenAI(
-    openai_api_key=st.secrets["OPENAI_API_KEY"],
-    model=st.secrets["OPENAI_MODEL"],
-)
+from model import chat_chain
 
 caption_examples_file_path = "./data/caption_examples.txt"
-
-prompt = ChatPromptTemplate.from_messages(
-    [
-        (
-            "system",
-            "You are a instagram post writer and you writing captions for posts for company that make hiking and bicycle backpacks. Responde with 2 sentence max, use context as example",
-        ),
-        ( "system", "{example}" ),
-        ( "human", "{question}" ),
-    ]
-)
-
-chat_chain = prompt | chat_llm | StrOutputParser()
-
 with open(caption_examples_file_path, "r") as file:
     caption_examples = file.read()
 
-
 if "visibility" not in st.session_state:
     st.session_state.visibility = "visible"
     st.session_state.disabled = False
     st.session_state.placeholder = "Example: Generate post about backpack Black Mamba with volume of 22 liters"
 
-
 st.set_page_config(
-    page_title="Backpack title generator",
-    page_icon="👋",
+    page_title="Backpack Title Generator",
+    page_icon="🎒"
 )
-st.write("# Welcome to InstaGPT! 👋")
-st.markdown("""Writes caption for a desired backpacks in style of Osprey""")
 
+st.write("# Welcome to InstaGPT! 👋")
+st.markdown("Write captions for backpacks in the style of Osprey")
 
 text_input = st.text_input(
     "Enter some text 👇",
@@ -48,18 +25,19 @@ text_input = st.text_input(
     placeholder=st.session_state.placeholder,
 )
 
-predefined_strings = ["Generate post about backpack Black Mamba with volume of 22 liters", "Write a post about giveaway of 3 backpacks from new collection", "Create new post about backpack Adventure for 250 dollars"]
+st.write("Examples:")
+st.write("Generate post about backpack Black Mamba with volume of 22 liters")
+st.write("Write a post about giveaway of 3 backpacks from new collection")
+st.write("Create new post about backpack Adventure for 250 dollars")
 
-st.write("Examples: \n\n Generate post about backpack Black Mamba with volume of 22 liters \n\n Write a post about giveaway of 3 backpacks from new collection \n\n Create new post about backpack Adventure for 250 dollars")
+generate_response = st.button("Generate")
 
-generate_respose = st.button("Generate")
 if text_input:
-    st.write("You entered: ", text_input)
+    st.write("You entered:", text_input)
 
-
-if generate_respose:
+if generate_response:
     if text_input == "":
-        st.write("Enter something")
+        st.write("Please enter some text.")
     else:
         response = chat_chain.invoke(
             {
@@ -67,6 +45,4 @@ if generate_respose:
                 "question": text_input,
             }
         )
-
-        st.write("Generated: ", response)
-
+        st.write("Generated:", response)

model.py

@@ -0,0 +1,24 @@
+import streamlit as st
+from langchain_openai import ChatOpenAI
+from langchain_core.prompts import ChatPromptTemplate
+from langchain.schema import StrOutputParser
+
+chat_llm = ChatOpenAI(
+    openai_api_key=st.secrets["OPENAI_API_KEY"],
+    model=st.secrets["OPENAI_MODEL"],
+)
+
+
+prompt = ChatPromptTemplate.from_messages(
+    [
+        (
+            "system",
+            "You are a instagram post writer and you writing captions for posts for company that make hiking and bicycle backpacks. "
+            "Responde with 2 sentence max, use context as example. ",
+        ),
+        ( "system", "{example}" ),
+        ( "human", "{question}" ),
+    ]
+)
+
+chat_chain = prompt | chat_llm | StrOutputParser()