Upload folder using huggingface_hub

.github/workflows/sync.yml

@@ -0,0 +1,33 @@
+name: Sync to Hugging Face Hub
+
+on:
+  push:
+    branches: ["main","staging"]
+  # Allows you to manually trigger this workflow from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository assets
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Set up Python environment
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.10'
+
+      - name: Install official Hugging Face CLI tool
+        run: pip install huggingface_hub
+
+      - name: Authenticate and upload project space via dedicated tunnel
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          # Traffic Controller: If the branch is main, use production. Otherwise, use staging.
+          HF_SPACE: ${{ github.ref_name == 'main' && 'catalyst-intelligence/ClariFood' || 'catalyst-intelligence/Staging-ClariFood' }}
+        run: |
+          hf auth login --token $HF_TOKEN
+          hf upload $HF_SPACE . --repo-type space

.gitignore

@@ -0,0 +1,218 @@
+# 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
+*.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
+
+# UV
+#   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
+# pdm.toml
+.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
+*.rdb
+*.aof
+*.pid
+
+# RabbitMQ
+mnesia/
+rabbitmq/
+rabbitmq-data/
+
+# ActiveMQ
+activemq-data/
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.envrc
+.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/
+
+# Abstra
+#   Abstra is an AI-powered process automation framework.
+#   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
+#   and can be added to the global gitignore or merged into this file. However, if you prefer, 
+#   you could uncomment the following to ignore the entire vscode folder
+# .vscode/
+# Temporary file for partial code execution
+tempCodeRunnerFile.py
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
+
+# Marimo
+marimo/_static/
+marimo/_lsp/
+__marimo__/
+
+# Streamlit
+.streamlit/secrets.toml

Dockerfile

@@ -1,20 +1,32 @@
+# Using the official lightweight Python image as a foundation
 FROM python:3.13.5-slim
 
+# Setup the operational directory inside the virtual container
 WORKDIR /app
 
+# Linux system configuration sequence
 RUN apt-get update && apt-get install -y \
     build-essential \
     curl \
     git \
+    libzbar0 \
+    libgl1-mesa-glx \
     && rm -rf /var/lib/apt/lists/*
 
+# Copy requirements map
 COPY requirements.txt ./
-COPY src/ ./src/
 
+# install dependancies
 RUN pip3 install -r requirements.txt
 
+# Copy main application file directly from your root folder
+COPY app.py ./
+
+# Tell container to open the port the app listens to
 EXPOSE 8501
 
+# Health monitoring
 HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
 
-ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+# Boot execution
+ENTRYPOINT ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 Catalyst Intelligence
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,19 +1,11 @@
 ---
-title: Staging ClariFood
-emoji: 🚀
-colorFrom: red
-colorTo: red
+title: ClariFood
+emoji: 🥑
+colorFrom: green
+colorTo: yellow   # "colorTo" must be one of [red, yellow, green, blue, indigo, purple, pink, gray]
 sdk: docker
 app_port: 8501
-tags:
-- streamlit
-pinned: false
-short_description: Beta testing of ClariFood webpage is done here.
 ---
 
-# Welcome to Streamlit!
-
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
-
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+# 🥑 ClariFood
+Conversational diet intelligence platform powered by LLM. Developed under the Catalyst Intelligence collective with the help of AI.

app.py

@@ -0,0 +1,133 @@
+import streamlit as st
+import cv2
+import numpy as np
+from google import genai
+from PIL import Image
+
+# Initialize Gemini Client
+client = genai.Client()
+
+# Force full viewport usage to widen the camera layout frame
+st.set_page_config(page_title="ClariFood", page_icon="🛡️", layout="wide")
+
+st.title("🛡️ ClariFood: Conversational Diet Intelligence")
+st.write("A production-hardened hybrid edge/cloud system with dynamic session memory.")
+
+st.markdown("---")
+
+# --- STEP 1: CONTEXT INJECTION DECK (SIDEBAR) ---
+st.sidebar.header("👤 Dynamic Health Profile")
+
+goal_options = ["Weight Loss", "Muscle Gain / Clean Bulk", "Diabetes Management", "Hypertension Control", "Gluten-Free Induction"]
+selected_goals = st.sidebar.multiselect("Primary Objectives", options=goal_options)
+
+# Custom Goal Input Gate
+custom_goal_active = st.sidebar.checkbox("Inject custom targets?")
+custom_goal_text = ""
+if custom_goal_active:
+    custom_goal_text = st.sidebar.text_input("Type custom health profile constraints:")
+
+allergy_options = ["Dairy", "Nuts", "Gluten", "Soy", "Artificial Sweeteners", "Preservatives"]
+selected_allergies = st.sidebar.multiselect("STRICT Avoidances / Allergies", options=allergy_options)
+
+additional_notes = st.sidebar.text_area("Narrative Clinical Notes (e.g., medical conditions):")
+
+# Construct the master string block
+final_goals = selected_goals + ([custom_goal_text] if custom_goal_text else [])
+user_profile_context = f"""
+USER HEALTH PROFILE DOSSIER:
+- Objectives: {', '.join(final_goals) if final_goals else 'General Fitness Check'}
+- Strict Allergens to Flag: {', '.join(selected_allergies) if selected_allergies else 'None specified'}
+- Medical/Narrative Notes: {additional_notes if additional_notes else 'None provided'}
+"""
+
+# --- STEP 2: CONVERSATIONAL MEMORY INITIALIZATION ---
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = []
+if "vault_images" not in st.session_state:
+    st.session_state.vault_images = []
+
+# --- STEP 3: MULTI-IMAGE ACQUISITION CANVAS ---
+st.subheader("📸 Frame Capture Pipeline")
+col_cam, col_vault = st.columns([2, 3])
+
+with col_cam:
+    captured_file = st.camera_input("Position product packaging in center view")
+    if captured_file is not None:
+        img = Image.open(captured_file)
+        
+        # Guard against duplicates inside the active frame cycle
+        if len(st.session_state.vault_images) == 0 or captured_file.name != st.session_state.get("last_uploaded_name", ""):
+            st.session_state.vault_images.append(img)
+            st.session_state.last_uploaded_name = captured_file.name
+            st.success(f"Frame buffered into system memory! Canvas Count: {len(st.session_state.vault_images)}")
+
+with col_vault:
+    if st.session_state.vault_images:
+        st.write("⚡ **Buffered Frame Stack Active:**")
+        # Render thumbnails of all taken photos side-by-side
+        thumb_cols = st.columns(min(len(st.session_state.vault_images), 4))
+        for idx, thumb_img in enumerate(st.session_state.vault_images):
+            with thumb_cols[idx % 4]:
+                st.image(thumb_img, caption=f"Scan #{idx+1}", width=120)
+        
+        if st.button("🗑️ Clear Image Stack"):
+            st.session_state.vault_images = []
+            st.rerun()
+
+st.markdown("---")
+
+# --- STEP 4: INTERACTIVE CHAT ENGINE LAYOUT ---
+st.subheader("💬 AI Clinical Consultation Stream")
+
+# Render previous conversational statements
+for message in st.session_state.chat_history:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# System Execution Prompter
+if user_message := st.chat_input("Ask a question about your scanned items..."):
+    
+    # 1. Display User Message Instantly
+    st.session_state.chat_history.append({"role": "user", "content": user_message})
+    with st.chat_message("user"):
+        st.markdown(user_message)
+        
+    # 2. Build Multi-modal Prompt Strategy
+    # Construct systemic ground truth logic framework
+    system_logic_prompt = f"""
+    You are an expert digital dietitian. You are analyzing an interactive product scan loop.
+    
+    CRITICAL OPERATION PROTOCOLS:
+    1. Cross-reference all inputs against this profile context: {user_profile_context}
+    2. Analyze the attached sequence of product photos sequentially. 
+    3. If the user's query requires finer granular data that you cannot see in the current image stack, or if a photo is unclear, DO NOT guess. State your initial observation and explicitly request the user to take an additional focused scan.
+    
+    CURRENT CHAT HISTORY DIALOGUE FOR TRACKING CONTEXT:
+    """
+    
+    # Pack background context strings, active image arrays, and current input together
+    payload = [system_logic_prompt]
+    
+    # Compile chat history text strings into payload
+    for msg in st.session_state.chat_history[:-1]:
+        payload.append(f"{msg['role'].upper()}: {msg['content']}\n")
+        
+    # Inject our list of images directly into the multimodal generation array
+    payload.extend(st.session_state.vault_images)
+    
+    # Inject current fresh query prompt
+    payload.append(f"CURRENT USER INQUIRY: {user_message}\nASSISTANT SYSTEM OUTPUT:")
+    
+    # 3. Call Cloud Model Infrastructure
+    with st.chat_message("assistant"):
+        with st.spinner("Analyzing data streams..."):
+            try:
+                response = client.models.generate_content(
+                    model='gemini-2.5-flash',
+                    contents=payload
+                )
+                st.markdown(response.text)
+                st.session_state.chat_history.append({"role": "assistant", "content": response.text})
+            except Exception as e:
+                st.error(f"Execution Error: {e}")

requirements.txt

@@ -1,3 +1,3 @@
-altair
-pandas
-streamlit
+google-genai
+streamlit
+opencv-python-headless