With CVS File

.gitignore

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+### Python template
+# 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/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

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+import gradio as gr
+from transformers import pipeline
+import pandas as pd
+import io
+import csv
+import os
+
+# Initialize the zero-shot classification pipeline
+classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
+
+# Define the candidate labels for sentiment analysis
+candidate_labels = ["positive", "negative", "neutral"]
+
+def analyze_sentiment(text):
+    """
+    Analyze sentiment of a single post using zero-shot classification
+    """
+    result = classifier(text, candidate_labels)
+    # Get the label with highest score
+    sentiment = result['labels'][0]
+    return sentiment
+
+def process_csv(file):
+    """
+    Process posts from CSV file and return results as a CSV file
+    """
+    try:
+        # Read the input CSV file
+        df = pd.read_csv(file.name)
+
+        # Verify required columns exist
+        if 'post_id' not in df.columns or 'text' not in df.columns:
+            return None, "Error: CSV must contain 'post_id' and 'text' columns"
+
+        # Apply sentiment analysis to each row
+        df['sentiment'] = df['text'].apply(analyze_sentiment)
+
+        # Create output CSV file
+        output_file = "sentiment_analysis_results.csv"
+        df.to_csv(output_file, index=False)
+
+        return output_file, "Analysis completed successfully!"
+
+    except Exception as e:
+        return None, f"Error processing CSV: {str(e)}"
+
+# Create example CSV file
+def create_example_file():
+    """
+    Create an example CSV file for demonstration
+    """
+    example_data = {
+        'post_id': [1, 2, 3],
+        'text': [
+            "I absolutely love this product! Best purchase ever!",
+            "This is terrible service, never coming back.",
+            "The weather is quite nice today."
+        ]
+    }
+    df = pd.DataFrame(example_data)
+    example_file = "example_input.csv"
+    df.to_csv(example_file, index=False)
+    return example_file
+
+# Create the example file before launching the interface
+example_file = create_example_file()
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=process_csv,
+    inputs=[
+        gr.File(
+            label="Upload CSV file",
+            file_types=[".csv"]
+        )
+    ],
+    outputs=[
+        gr.File(label="Download Results"),
+        gr.Textbox(label="Status")
+    ],
+    title="Social Media Sentiment Analyzer",
+    description="""
+    Analyze the sentiment of multiple social media posts using zero-shot classification.
+
+    Input CSV format:
+    - Required columns: 'post_id', 'text'
+    - Each row should contain a unique post ID and the post text
+
+    Output CSV will contain:
+    - post_id: Original post ID
+    - text: Original post text
+    - sentiment: Analyzed sentiment (positive/negative/neutral)
+    """,
+    examples=[
+        [example_file]  # Use the created example file
+    ]
+)
+
+if __name__ == "__main__":
+    # Clean up example file when the program exits
+    try:
+        iface.launch()
+    finally:
+        if os.path.exists(example_file):
+            os.remove(example_file)

mockup_feedback_posts.csv

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+post_id,text
+1,"I love the new update to the platform! It's amazing."
+2,"This app is terrible, it crashes every time I try to use it."
+3,"The customer service was very helpful, I feel satisfied with the response."
+4,"I had a great experience shopping here, will definitely come back."
+5,"The product quality is not what I expected, very disappointed."
+6,"Absolutely wonderful experience, everything went smoothly."
+7,I had to wait for a long time before someone attended to me.
+8,"This is just okay, not the best service I've had."
+9,Great value for money! I'm really happy with my purchase.
+10,"I don't think the app is user-friendly, it's too confusing."

requirements.txt

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+transformers>=4.46.2
+gradio>=5.5.0
+pandas>=2.2.3