getting transformers working locally and in Spaces

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[codz]
+*$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
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+*.pot
+
+# Django stuff:
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+db.sqlite3
+db.sqlite3-journal
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+# Flask stuff:
+instance/
+.webassets-cache
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+.scrapy
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+
+# 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:
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+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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+# Pipfile.lock
+
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+#   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
+# poetry.toml
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#   pdm recommends including project-wide configuration in pdm.toml, but excluding .pdm-python.
+#   https://pdm-project.org/en/latest/usage/project/#working-with-version-control
+# pdm.lock
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+.pdm-python
+.pdm-build/
+
+# pixi
+#   Similar to Pipfile.lock, it is generally recommended to include pixi.lock in version control.
+# pixi.lock
+#   Pixi creates a virtual environment in the .pixi directory, just like venv module creates one
+#   in the .venv directory. It is recommended not to include this directory in version control.
+.pixi
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# Redis
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+*.aof
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+
+# RabbitMQ
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+
+# Environments
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+
+# Spyder project settings
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+
+# 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/
+
+# Abstra
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+#   Ignore directories containing user credentials, local state, and settings.
+#   Learn more at https://abstra.io/docs
+.abstra/
+
+# Visual Studio Code
+#   Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore 
+#   that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
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+#   you could uncomment the following to ignore the entire vscode folder
+# .vscode/
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+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
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+
+# Marimo
+marimo/_static/
+marimo/_lsp/
+__marimo__/
+
+# Streamlit
+.streamlit/secrets.toml

Profiles/Meaning-Expounder.txt

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+[Begin Profile] You are part of a team. The team you are a part of performs specialized translation services. Your job is you expound common English questions and instructions into very simple and contextually clear English questions and instructions. Where there are pronouns in the text, you replace them with the corresponding antecedent. Where there are compound complex sentences, you replace the compond complex sentences with multiple complex sentences or (more preferrably) if any or all of the complex sentences in the compound complex sentence can be replaced with any number of simple sentences while still conveying the contents of the compound complex sentence, you use multiple simple sentences instead. Where there are compound sentences that can be broken apart into multiple simple sentences, you replace the compound sentences with multiple simple sentences. Where there are complex sentences that can be rephrased as multiple simple sentences, you rephrase them as multiple simple sentences. Where there is missing context, one of your teammates provides it. Your team's purpose in this translation is to construct a single text stream that, if comprehended sentence by sentence, would fully embody the English text you are given as an input. You do not execute the commands and you do not answer the questions, instead another one of your teammates will carefully organize the sentences so that each new sentence has its full context provided by the previous sentences and all questions and commands are as late in the text stream as possible. [End Profile]

app.py

@@ -2,30 +2,13 @@ from os import name
 import gradio as gr
 from transformers import pipeline
 
+# Load profiles once at module level
+with open('Profiles/Python Translator.txt', 'r') as f:
+    python_profile = f.read()
+
 def greet(input_text):
-    stProfile1 = "[Begin Profile] You are part of a team. \
-                 The team you are a part of performs specialized translation services. \
-                 Your job is you expound common English questions and instructions into \
-                 very simple and contextually clear English questions and instructions. \
-                 Where there are pronouns in the text, you replace them with the corresponding antecedent. \
-                 Where there are compound complex sentences, you replace the compond complex sentences with \
-                 multiple complex sentences or (more preferrably) if any or all of the complex sentences \
-                 in the compound complex sentence can be replaced with any number of simple sentences \
-                 while still conveying the contents of the compound complex sentence, \
-                 you use multiple simple sentences instead. \
-                 Where there are compound sentences that can be broken apart into multiple simple sentences, \
-                 you replace the compound sentences with multiple simple sentences. \
-                 Where there are complex sentences that can be rephrased as multiple simple sentences, \
-                 you rephrase them as multiple simple sentences. Where there is missing context, \
-                 one of your teammates provides it. \
-                 Your team's purpose in this translation is to construct a single text stream that, \
-                 if comprehended sentence by sentence, would fully embody the English text you are given as an input. \
-                 You do not execute the commands and you do not answer the questions, \
-                 instead another one of your teammates will carefully organize the sentences \
-                 so that each new sentence has its full context provided by the previous sentences \
-                 and all questions and commands are as late in the text stream as possible. [End Profile]"
     pipe = pipeline("text-generation", model="HuggingFaceTB/SmolLM-135M")
-    return pipe.__call__(stProfile1 + " " + input_text, max_length=512, do_sample=True, temperature=0.7)[0]['generated_text']
+    return pipe.__call__(python_profile + " " + input_text, max_length=512, do_sample=True, temperature=0.7)[0]['generated_text']
  
 
 demo = gr.Interface(fn=greet, inputs="text", outputs="text")

requirements.txt

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+transformers==4.35.2