Deploying the App

.gitignore

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+# 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/

Dockerfile

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+# Dockerfile
+
+# Use the official Python image with the desired version
+FROM python:3.9-slim
+
+# Set the working directory inside the container
+WORKDIR /app
+
+# Copy the requirements file to the working directory
+COPY requirements.txt /app
+
+# Install the dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the application code to the working directory
+COPY app.py /app
+
+# Expose the port that Gradio will run on (default is 7860)
+EXPOSE 7860
+
+ENV GRADIO_SERVER_NAME="0.0.0.0"
+
+# Command to run your application
+CMD ["python", "app.py"]

LICENSE

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app.py

@@ -0,0 +1,114 @@
+import os
+
+import gradio as gr
+from llama_index.core import SimpleDirectoryReader, VectorStoreIndex
+from llama_index.embeddings.mixedbreadai import MixedbreadAIEmbedding
+from llama_index.llms.groq import Groq
+from llama_parse import LlamaParse
+
+# API keys
+llama_cloud_key = os.environ.get("LLAMA_CLOUD_API_KEY")
+groq_key = os.environ.get("GROQ_API_KEY")
+mxbai_key = os.environ.get("MXBAI_API_KEY")
+if not (llama_cloud_key and groq_key and mxbai_key):
+    raise ValueError(
+        "API Keys not found! Ensure they are passed to the Docker container."
+    )
+
+# models name
+llm_model_name = "llama-3.1-70b-versatile"
+embed_model_name = "mixedbread-ai/mxbai-embed-large-v1"
+
+# Initialize the parser
+parser = LlamaParse(api_key=llama_cloud_key, result_type="markdown")
+
+# Define file extractor with various common extensions
+file_extractor = {
+    ".pdf": parser,
+    ".docx": parser,
+    ".doc": parser,
+    ".txt": parser,
+    ".csv": parser,
+    ".xlsx": parser,
+    ".pptx": parser,
+    ".html": parser,
+    ".jpg": parser,
+    ".jpeg": parser,
+    ".png": parser,
+    ".webp": parser,
+    ".svg": parser,
+}
+
+# Initialize the embedding model
+embed_model = MixedbreadAIEmbedding(api_key=mxbai_key, model_name=embed_model_name)
+
+# Initialize the LLM
+
+llm = Groq(model="llama-3.1-70b-versatile", api_key=groq_key)
+
+
+# File processing function
+def load_files(file_path: str):
+    global vector_index
+    document = SimpleDirectoryReader(
+        input_files=[file_path], file_extractor=file_extractor
+    ).load_data()
+    vector_index = VectorStoreIndex.from_documents(document, embed_model=embed_model)
+    print(f"Parsing done for {file_path}")
+    filename = os.path.basename(file_path)
+    return f"Ready to provide responses based on {filename}"
+
+
+# Respond function
+def respond(message, history):
+    # Use the preloaded LLM
+    query_engine = vector_index.as_chat_engine(llm=llm)
+    streaming_response = query_engine.stream_chat(message)
+    partial_text = ""
+    for new_text in streaming_response.response_gen:
+        partial_text += new_text
+        # Yield an empty string to cleanup the message textbox and the updated conversation history
+        yield partial_text
+
+
+# UI Setup
+with gr.Blocks(
+    theme=gr.themes.Default(
+        primary_hue="green",
+        secondary_hue="blue",
+        font=[gr.themes.GoogleFont("Poppins")],
+    ),
+    css="footer {visibility: hidden}",
+) as demo:
+    gr.Markdown("# DataCamp Doc Q&A 🤖📃")
+    with gr.Row():
+        with gr.Column(scale=1):
+            file_input = gr.File(
+                file_count="single", type="filepath", label="Upload Document"
+            )
+            with gr.Row():
+                btn = gr.Button("Submit", variant="primary")
+                clear = gr.Button("Clear")
+            output = gr.Textbox(label="Status")
+        with gr.Column(scale=3):
+            chatbot = gr.ChatInterface(
+                fn=respond,
+                chatbot=gr.Chatbot(height=300),
+                theme="soft",
+                show_progress="full",
+                textbox=gr.Textbox(
+                    placeholder="Ask questions about the uploaded document!",
+                    container=False,
+                ),
+            )
+
+    # Set up Gradio interactions
+    btn.click(fn=load_files, inputs=file_input, outputs=output)
+    clear.click(
+        lambda: [None, None],
+        outputs=[file_input, output],
+    )
+
+# Launch the demo
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+llama-index-embeddings-mixedbreadai
+llama-index-llms-groq
+llama-index