Add initial project files including Gradio app, Git LFS configuration, and CI workflows

- Created .gitattributes for Git LFS tracking of image and model files.
- Added .gitignore to exclude common Python artifacts.
- Implemented main Gradio application in app.py for a chatbot interface.
- Included README.md with project details and dependencies.
- Specified required packages in requirements.txt.
- Set up GitHub Actions workflows for Discord notifications, Hugging Face synchronization, and testing.
- Added assets for the chatbot interface and icons.
- Created a smoke test in tests/test_smoke.py to validate API token usage.

.gitattributes

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+# Git LFS tracking for common image formats
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+*.svg filter=lfs diff=lfs merge=lfs -text
+*.ico filter=lfs diff=lfs merge=lfs -text
+
+# Other large files you might want to track
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.tar.gz filter=lfs diff=lfs merge=lfs -text
+*.pdf filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.mov filter=lfs diff=lfs merge=lfs -text
+*.avi filter=lfs diff=lfs merge=lfs -text
+
+# Model files (common in ML projects)
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text

.github/workflows/discord-notification.yml

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+name: Discord Notification
+
+on:
+  push:
+  pull_request:
+  issues:
+  release:
+  create:
+  delete:
+  workflow_run:
+    workflows:
+      - "Sync to Hugging Face hub"
+      - "Run chatbot test"
+    types:
+      - completed
+
+jobs:
+  notify:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Send Discord notification
+        env:
+          DISCORD_WEBHOOK_URL: ${{ secrets.DISCORD_WEBHOOK_URL }} # Set in Github Secrets
+        run: |
+          EVENT_NAME="${{ github.event_name }}"
+
+          case "$EVENT_NAME" in
+            push)
+              SHORT_SHA="${{ github.sha }}"
+              SHORT_SHA="${SHORT_SHA:0:7}"
+              MESSAGE="Commit ($SHORT_SHA) was pushed to ${{ github.ref_name }} branch by $GITHUB_ACTOR: ${{ github.event.head_commit.message }}"
+              ;;
+            pull_request)
+              MESSAGE="Pull request #${{ github.event.pull_request.number }} ${{ github.event.action }} by $GITHUB_ACTOR: ${{ github.event.pull_request.title }} (from ${{ github.event.pull_request.head.ref }} to ${{ github.event.pull_request.base.ref }})"
+              ;;
+            issues)
+              MESSAGE="Issue #${{ github.event.issue.number }} ${{ github.event.action }} by $GITHUB_ACTOR: ${{ github.event.issue.title }}"
+              ;;
+            release)
+              MESSAGE="Release ${{ github.event.release.tag_name }} ${{ github.event.action }} by $GITHUB_ACTOR: ${{ github.event.release.name }}"
+              ;;
+            create)
+              MESSAGE="Created ${{ github.event.ref_type }} ${{ github.event.ref }} by $GITHUB_ACTOR"
+              ;;
+            delete)
+              MESSAGE="Deleted ${{ github.event.ref_type }} ${{ github.event.ref }} by $GITHUB_ACTOR"
+              ;;
+            workflow_run)
+              NAME="${{ github.event.workflow_run.name }}"
+              CONCLUSION="${{ github.event.workflow_run.conclusion }}"
+              BRANCH="${{ github.event.workflow_run.head_branch }}"
+              SHA="${{ github.event.workflow_run.head_sha }}"
+
+              if [ "$CONCLUSION" = "success" ]; then
+                STATUS="PASSED"
+              elif [ "$CONCLUSION" = "failure" ]; then
+                STATUS="FAILED"
+              else
+                STATUS="$CONCLUSION"
+              fi
+
+              SHORT_SHA="${SHA:0:7}"
+              MESSAGE=" - Workflow $NAME $STATUS on $BRANCH (commit $SHORT_SHA)"
+              ;;
+            *)
+              MESSAGE="Event $EVENT_NAME by $GITHUB_ACTOR on ${{ github.repository }} at ${{ github.ref_name }}"
+              ;;
+          esac
+
+          curl -X POST -H "Content-Type: application/json" \
+          -d "{\"content\": \"$MESSAGE\"}" \
+          $DISCORD_WEBHOOK_URL

.github/workflows/hf-sync.yml

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+name: Sync to Hugging Face hub
+on:
+  push:
+
+  # to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          lfs: true
+      - name: Push to hub
+        env:
+          HF_TOKEN: ${{ secrets.Smart_Confidant_Token }}
+        run: git push --force https://heffnt:$HF_TOKEN@huggingface.co/spaces/heffnt/Smart_Confidant HEAD:main

.github/workflows/test.yml

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+name: Run chatbot test
+
+on:
+  push:
+  pull_request:
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install dependencies
+        run: |
+          pip install pytest gradio[oauth] huggingface_hub
+
+      - name: Run pytest with HF token
+        env:
+          HF_TOKEN: ${{ secrets.Smart_Confidant_Token }}
+        run: pytest -q

.gitignore

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+__pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+*.db
+*.sqlite3
+*.log
+*.env

README.md

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+---
+title: CSDS553 Demo
+emoji: 💬
+colorFrom: yellow
+colorTo: purple
+sdk: gradio
+sdk_version: 5.44.1
+app_file: app.py
+pinned: false
+hf_oauth: true
+hf_oauth_scopes:
+- inference-api
+---
+
+An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+
+Increment this to force push to Github: 1243

app.py

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+import gradio as gr
+from huggingface_hub import InferenceClient
+import os
+import base64
+from pathlib import Path
+
+# Configuration
+LOCAL_MODELS = ["tiiuae/Falcon-H1-0.5B-Instruct"]
+API_MODELS = ["openai/gpt-oss-20b"]
+DEFAULT_SYSTEM_MESSAGE = "You are an expert assistant for Magic: The Gathering. You're name is Smart Confidant, but people tend to call you Bob."
+TITLE = "🎓🧙🏻‍♂️ Smart Confidant 🧙🏻‍♂️🎓"
+
+# Create model options with labels
+MODEL_OPTIONS = []
+for model in LOCAL_MODELS:
+    MODEL_OPTIONS.append(f"{model} (local)")
+for model in API_MODELS:
+    MODEL_OPTIONS.append(f"{model} (api)")
+
+pipe = None
+stop_inference = False
+
+ASSETS_DIR = Path(__file__).parent / "assets"
+BACKGROUND_IMAGE_PATH = ASSETS_DIR / "confidant_pattern.png"
+try:
+    with open(BACKGROUND_IMAGE_PATH, "rb") as _img_f:
+        _encoded_img = base64.b64encode(_img_f.read()).decode("ascii")
+        BACKGROUND_DATA_URL = f"data:image/png;base64,{_encoded_img}"
+except Exception as e:
+    print(f"Error loading background image: {e}")
+    BACKGROUND_DATA_URL = ""
+
+# Fancy styling
+fancy_css = f"""
+    html, body, #root {{
+        background-image: url('{BACKGROUND_DATA_URL}');
+        background-repeat: repeat;
+        background-size: auto;
+        background-color: transparent;
+    }}
+    .gradio-container {{
+        max-width: 700px;
+        margin: 0 auto;
+        padding: 20px;
+        background-color: #2d2d2d;
+        box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+        border-radius: 10px;
+        font-family: 'Arial', sans-serif;
+    }}
+    .gr-button {{
+        background-color: #4CAF50;
+        color: white;
+        border: none;
+        border-radius: 5px;
+        padding: 10px 20px;
+        cursor: pointer;
+        transition: background-color 0.3s ease;
+    }}
+    .gr-button:hover {{
+        background-color: #45a049;
+    }}
+    .gr-slider input {{
+        color: #4CAF50;
+    }}
+    .gr-chat {{
+        font-size: 16px;
+    }}
+    #title {{
+        text-align: center;
+        font-size: 2em;
+        margin-bottom: 20px;
+        color: #333;
+    }}
+    """
+
+def respond(
+    message,
+    history: list[dict[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+    hf_token: gr.OAuthToken,
+    selected_model: str,
+):
+    global pipe
+
+    # Build messages from history
+    messages = [{"role": "system", "content": system_message}]
+    messages.extend(history)
+    messages.append({"role": "user", "content": message})
+
+    # Determine if model is local or API and extract model name
+    is_local = selected_model.endswith("(local)")
+    model_name = selected_model.replace(" (local)", "").replace(" (api)", "")
+    
+    response = ""
+
+    if is_local:
+        print(f"[MODE] local - {model_name}")
+        from transformers import pipeline
+        import torch
+        if pipe is None or pipe.model.name_or_path != model_name:
+            pipe = pipeline("text-generation", model=model_name)
+
+        # Build prompt as plain text
+        prompt = "\n".join([f"{m['role']}: {m['content']}" for m in messages])
+
+        outputs = pipe(
+            prompt,
+            max_new_tokens=max_tokens,
+            do_sample=True,
+            temperature=temperature,
+            top_p=top_p,
+        )
+
+        response = outputs[0]["generated_text"][len(prompt):]
+        yield response.strip()
+
+    else:
+        print(f"[MODE] api - {model_name}")
+
+        if hf_token is None or not getattr(hf_token, "token", None):
+            yield "⚠️ Please log in with your Hugging Face account first."
+            return
+
+        client = InferenceClient(token=hf_token.token, model=model_name)
+
+        for chunk in client.chat_completion(
+            messages,
+            max_tokens=max_tokens,
+            stream=True,
+            temperature=temperature,
+            top_p=top_p,
+        ):
+            choices = chunk.choices
+            token = ""
+            if len(choices) and choices[0].delta.content:
+                token = choices[0].delta.content
+            response += token
+            yield response
+
+
+with gr.Blocks(css=fancy_css) as demo:
+    gr.LoginButton()
+    gr.Markdown(f"<h1 style='text-align: center;'>{TITLE}</h1>")
+    
+    # Create custom chatbot with avatar images
+    chatbot = gr.Chatbot(
+        type="messages",
+        avatar_images=(str(ASSETS_DIR / "monster_icon.png"), str(ASSETS_DIR / "smart_confidant_icon.png"))
+    )
+    
+    # Create ChatInterface first, using built-in accordion for additional inputs
+    gr.ChatInterface(
+        fn=respond,
+        chatbot=chatbot,
+        additional_inputs=[
+            gr.Textbox(value=DEFAULT_SYSTEM_MESSAGE, label="System message"),
+            gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+            gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.1, label="Temperature"),
+            gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
+            gr.Radio(choices=MODEL_OPTIONS, label="Select Model", value=MODEL_OPTIONS[0]),
+        ],
+        additional_inputs_accordion="Additional Settings",
+        type="messages",
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+transformers
+torch

tests/test_smoke.py

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+import sys, os
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+
+import app
+
+class Token:
+    def __init__(self, token): self.token = token
+
+def test_api_requires_token():
+    hf_token = os.environ.get("HF_TOKEN")
+    assert hf_token, "HF_TOKEN not set in environment"
+
+    gen = app.respond(
+        message="Hi",
+        history=[],
+        system_message="test",
+        max_tokens=8,
+        temperature=0.2,
+        top_p=0.9,
+        hf_token=Token(hf_token),
+        selected_model="openai/gpt-oss-20b (api)",
+    )
+    first = next(gen)
+    assert "please log in" not in first.lower()  # shouldn't get warning
+    assert isinstance(first, str)