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Browse files- .gitignore +161 -0
- app.py +47 -4
- requirements.txt +4 -0
.gitignore
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@@ -0,0 +1,161 @@
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.DS_Store
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# Byte-compiled / optimized / DLL files
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+
__pycache__/
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+
*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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+
.Python
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build/
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develop-eggs/
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dist/
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downloads/
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+
eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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+
MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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+
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+
# Installer logs
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+
pip-log.txt
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+
pip-delete-this-directory.txt
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+
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+
# Unit test / coverage reports
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+
htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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+
cover/
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+
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# Translations
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+
*.mo
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+
*.pot
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+
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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66 |
+
instance/
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+
.webassets-cache
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+
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+
# Scrapy stuff:
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70 |
+
.scrapy
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+
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# Sphinx documentation
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73 |
+
docs/_build/
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+
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# PyBuilder
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.pybuilder/
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target/
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+
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# Jupyter Notebook
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+
.ipynb_checkpoints
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+
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# IPython
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profile_default/
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ipython_config.py
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+
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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+
celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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app.py
CHANGED
@@ -1,7 +1,50 @@
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import gradio as gr
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def greet(name):
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return "Hello " + name
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from transformers import AutoTokenizer, pipeline
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import gradio as gr
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import cohere
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import os
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from dotenv import load_dotenv, find_dotenv
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_ = load_dotenv(find_dotenv()) # read local .env file
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cohere_api_key = os.environ['COHERE_API']
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co = cohere.Client(cohere_api_key)
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# Load the tokenizer associated with the specified model
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tokenizer = AutoTokenizer.from_pretrained("Intel/dynamic_tinybert", padding=True, truncation=True, max_length=512)
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# Define a question-answering pipeline using the model and tokenizer
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question_answerer = pipeline(
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"question-answering",
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model="Intel/dynamic_tinybert",
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tokenizer=tokenizer,
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return_tensors='pt'
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)
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def generate(question):
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result = co.chat(
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model="command",
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message=question,
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connectors=[{"id": "web-search"}])
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context = result.text
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squad_ex = question_answerer(question = question, context = context)
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return squad_ex['answer']
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def respond(message, chat_history):
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bot_message = generate(message)
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chat_history.append((message, bot_message))
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return "", chat_history
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with gr.Blocks() as demo:
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chatbot = gr.Chatbot(height=240) #just to fit the notebook
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msg = gr.Textbox(label="Ask away")
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btn = gr.Button("Submit")
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clear = gr.ClearButton(components=[msg, chatbot], value="Clear console")
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btn.click(respond, inputs=[msg, chatbot], outputs=[msg, chatbot])
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msg.submit(respond, inputs=[msg, chatbot], outputs=[msg, chatbot]) #Press enter to submit
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demo.queue().launch()
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requirements.txt
ADDED
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transformers[torch]
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gradio
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cohere
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python-dotenv
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