diff --git a/clawedin-openclawjobfindagent/.env.example b/clawedin-openclawjobfindagent/.env.example
new file mode 100644
index 0000000..18181bb
--- /dev/null
+++ b/clawedin-openclawjobfindagent/.env.example
@@ -0,0 +1,4 @@
+# HrFlow.ai credentials (get from hackathon organizers)
+HRFLOW_SECRET_KEY=your-hrflow-secret-key
+HRFLOW_API_KEY=your-api-key-here
+HRFLOW_SOURCE_KEY=your-source-key-here
diff --git a/clawedin-openclawjobfindagent/README.md b/clawedin-openclawjobfindagent/README.md
new file mode 100644
index 0000000..c86e2e5
--- /dev/null
+++ b/clawedin-openclawjobfindagent/README.md
@@ -0,0 +1,152 @@
+# ClawedIn — AI Job Finding Agent
+
+> Upload your CV. Let AI find your next job.
+
+ClawedIn is an AI-powered job matching agent built for the HrFlow.ai Hackathon. It parses a candidate's CV using HrFlow.ai, generates relevant job roles using OpenClaw (local LLM), searches real job listings via Brave Search, and ranks them by profile match.
+
+---
+
+## What It Does
+
+1. **CV Parsing** — Upload a PDF resume. HrFlow.ai extracts skills, experience, and profile data.
+2. **Job Role Generation** — OpenClaw LLM analyses extracted skills and suggests 10 relevant job titles.
+3. **Job Search** — Brave Search API finds real job listings from LinkedIn, Indeed, Welcome to the Jungle, APEC, Glassdoor, and Talent.io.
+4. **AI Ranking** — OpenClaw ranks the listings by match quality and explains why each job fits the candidate.
+5. **Results Dashboard** — Candidates see ranked jobs with match scores, reasons, and direct apply links.
+
+---
+
+## Architecture
+```
+Streamlit UI (port 8501)
+ ↓ Upload CV
+FastAPI Skill (port 8001)
+ ↓ HrFlow Parsing API → extract skills
+ ↓ Brave Search API → find real job listings
+ ↓ OpenClaw LLM → rank jobs by relevance
+ ↓ return ranked results
+OpenClaw Gateway (port 18789)
+ ↓ qwen3:1.7b via Ollama (local LLM)
+```
+
+---
+
+## HrFlow.ai APIs Used
+
+| API | Purpose |
+|-----|---------|
+| `profile/parsing/add_file` | Parse uploaded CV PDF and extract skills, experience, profile data |
+| `job/searching` | Search indexed job listings |
+| `job/scoring` | Score jobs against candidate profile |
+
+---
+
+## Prerequisites
+
+- Python 3.12+
+- [Ollama](https://ollama.ai) with `qwen3:1.7b` model
+- [OpenClaw](https://openclaw.ai) gateway
+- Brave Search API key (free tier available at [brave.com/search/api](https://brave.com/search/api))
+- HrFlow.ai API credentials
+
+---
+
+## Installation
+
+### 1. Clone the repo
+```bash
+git clone https://github.com/YOUR_USERNAME/app-store-public.git
+cd app-store-public/clawedin
+```
+
+### 2. Install FastAPI dependencies
+```bash
+cd hrflow-skill
+pip install poetry
+poetry install
+```
+
+### 3. Install Streamlit dependencies
+```bash
+cd ../Streamlit
+pip install -r requirements.txt
+```
+
+### 4. Install Ollama and pull model
+```bash
+# Install Ollama from https://ollama.ai
+ollama pull qwen3:1.7b
+```
+
+### 5. Install and configure OpenClaw
+```bash
+npm install -g openclaw
+openclaw configure
+openclaw config set plugins.entries.brave.enabled true
+openclaw config set plugins.entries.brave.config.webSearch.apiKey "YOUR_BRAVE_KEY"
+openclaw config set tools.web.search.provider "brave"
+```
+
+---
+
+## Configuration
+
+Copy `.env.example` to `.env` in the `hrflow-skill` folder:
+```bash
+cp hrflow-skill/.env.example hrflow-skill/.env
+```
+
+Fill in your credentials:
+```env
+HRFLOW_API_KEY=your_hrflow_api_key
+HRFLOW_USER_EMAIL=your_hrflow_email
+HRFLOW_SOURCE_KEY=your_source_key
+HRFLOW_BOARD_KEY=your_board_key
+BRAVE_API_KEY=your_brave_api_key
+GATEWAY_TOKEN=your_openclaw_gateway_token
+```
+
+---
+
+## Running the App
+
+Open 3 terminals:
+
+**Terminal 1 — OpenClaw Gateway**
+```bash
+openclaw gateway --port 18789
+```
+
+**Terminal 2 — FastAPI Skill**
+```bash
+cd hrflow-skill
+poetry run uvicorn main:app --host 0.0.0.0 --port 8001 --reload
+```
+
+**Terminal 3 — Streamlit UI**
+```bash
+cd Streamlit
+streamlit run app.py --server.address 0.0.0.0 --server.port 8501
+```
+
+Open your browser at `http://localhost:8501`
+
+---
+
+## Stack
+
+| Layer | Technology |
+|-------|-----------|
+| Frontend | Streamlit |
+| Backend | FastAPI (Python) |
+| LLM | qwen3:1.7b via Ollama |
+| AI Agent | OpenClaw 2026.3.24 |
+| Job Search | Brave Search API |
+| CV Parsing | HrFlow.ai Parsing API |
+
+---
+
+## Team
+
+**Team 7 — ClawedIn**
+Built at the HrFlow.ai Hackathon 2026.
diff --git a/clawedin-openclawjobfindagent/Streamlit/app.py b/clawedin-openclawjobfindagent/Streamlit/app.py
new file mode 100644
index 0000000..bc78c07
--- /dev/null
+++ b/clawedin-openclawjobfindagent/Streamlit/app.py
@@ -0,0 +1,89 @@
+import streamlit as st
+from core.styles import apply_design_system
+from core.session import init_session
+from modules import auth, upload, engine, dashboard
+from modules import keywords as keywords_module
+from datetime import datetime
+
+st.set_page_config(
+ page_title="ClawedIn",
+ page_icon="🦞",
+ layout="wide",
+ initial_sidebar_state="expanded"
+)
+apply_design_system()
+init_session()
+
+# Sidebar
+with st.sidebar:
+ st.markdown("""
+
+
🤖
+
ClawedIn
+
Powered by OpenClaw + HrFlow
+
+
Logged in as
+
{name}
+
{datetime.now().strftime('%d %b %Y')}
+
PROGRESS
", unsafe_allow_html=True)
+ for i, (s, n) in enumerate(zip(steps, step_names)):
+ if i < current:
+ icon = "✅"
+ color = "#16a34a"
+ elif i == current:
+ icon = "▶️"
+ color = "#2563eb"
+ else:
+ icon = "○"
+ color = "#475569"
+ st.markdown(f"{icon} {n}
", unsafe_allow_html=True)
+
+ st.divider()
+
+ if st.button("🔄 New Search", use_container_width=True):
+ st.session_state.step = "upload"
+ st.session_state.results = []
+ st.session_state.parsed_cv = None
+ st.session_state.uploaded_file = None
+ st.session_state.job_roles = []
+ st.rerun()
+
+ if st.button("Logout", use_container_width=True):
+ st.session_state.logged_in = False
+ st.session_state.step = "upload"
+ st.rerun()
+ else:
+ st.markdown("Log in to activate your AI agent.
", unsafe_allow_html=True)
+
+# Router
+if not st.session_state.logged_in:
+ auth.render()
+else:
+ step = st.session_state.step
+ if step == "upload":
+ upload.render()
+ elif step == "keywords":
+ keywords_module.render()
+ elif step == "processing":
+ engine.render()
+ elif step == "results":
+ dashboard.render()
diff --git a/clawedin-openclawjobfindagent/Streamlit/assets/log.svg b/clawedin-openclawjobfindagent/Streamlit/assets/log.svg
new file mode 100644
index 0000000..d078023
--- /dev/null
+++ b/clawedin-openclawjobfindagent/Streamlit/assets/log.svg
@@ -0,0 +1,31 @@
+
\ No newline at end of file
diff --git a/clawedin-openclawjobfindagent/Streamlit/assets/logo.svg b/clawedin-openclawjobfindagent/Streamlit/assets/logo.svg
new file mode 100644
index 0000000..e1e18c9
--- /dev/null
+++ b/clawedin-openclawjobfindagent/Streamlit/assets/logo.svg
@@ -0,0 +1,34 @@
+
\ No newline at end of file
diff --git a/clawedin-openclawjobfindagent/Streamlit/core/__init__.py b/clawedin-openclawjobfindagent/Streamlit/core/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/clawedin-openclawjobfindagent/Streamlit/core/api.py b/clawedin-openclawjobfindagent/Streamlit/core/api.py
new file mode 100644
index 0000000..f6fa915
--- /dev/null
+++ b/clawedin-openclawjobfindagent/Streamlit/core/api.py
@@ -0,0 +1,33 @@
+import requests
+
+FASTAPI_URL = "http://localhost:8001"
+GATEWAY_URL = "http://localhost:18789"
+GATEWAY_TOKEN = "ea28e9b03545f00a79e3d3c857e18fb0df7e83dc8f211b75"
+
+
+def health_check():
+ status = {}
+ try:
+ requests.get(f"{FASTAPI_URL}/health", timeout=2)
+ status["fastapi"] = True
+ except:
+ status["fastapi"] = False
+ try:
+ requests.get(GATEWAY_URL, timeout=2)
+ status["openclaw"] = True
+ except:
+ status["openclaw"] = False
+ return status
+
+
+def parse_and_score(file_bytes, filename, location="Paris"):
+ try:
+ resp = requests.post(
+ f"{FASTAPI_URL}/full-pipeline",
+ files={"file": (filename, file_bytes, "application/pdf")},
+ params={"location": location},
+ timeout=180
+ )
+ return resp.json()
+ except Exception as e:
+ return {"error": str(e), "profile": {}, "results": []}
diff --git a/clawedin-openclawjobfindagent/Streamlit/core/app.py b/clawedin-openclawjobfindagent/Streamlit/core/app.py
new file mode 100644
index 0000000..a6a2303
--- /dev/null
+++ b/clawedin-openclawjobfindagent/Streamlit/core/app.py
@@ -0,0 +1,263 @@
+import streamlit as st
+import time
+import requests
+import base64
+from datetime import datetime
+
+# --- CONFIGURATION & STYLING ---
+st.set_page_config(
+ page_title="AgentJob.ai | AI Career Scout",
+ page_icon="🤖",
+ layout="wide",
+ initial_sidebar_state="expanded"
+)
+
+# Custom CSS for a high-end AI dashboard feel
+st.markdown("""
+
+ """, unsafe_allow_html=True)
+
+# --- BACKEND INTEGRATION HELPERS ---
+API_BASE = "http://localhost:8000" # Your FastAPI URL
+
+def call_backend_api(endpoint, method="GET", data=None, files=None):
+ """Generic helper to talk to FastAPI with error handling."""
+ try:
+ if method == "POST":
+ if files:
+ response = requests.post(f"{API_BASE}{endpoint}", files=files)
+ else:
+ response = requests.post(f"{API_BASE}{endpoint}", json=data)
+ else:
+ response = requests.get(f"{API_BASE}{endpoint}", params=data)
+
+ if response.status_code == 200:
+ return response.json()
+ else:
+ st.error(f"Backend Error: {response.status_code}")
+ return None
+ except Exception as e:
+ # In a real app, don't show raw exception to user, but good for dev
+ return None
+
+# --- SESSION STATE MANAGEMENT ---
+def init_session():
+ if "logged_in" not in st.session_state:
+ st.session_state.logged_in = False
+ if "step" not in st.session_state:
+ st.session_state.step = "welcome"
+ if "user_data" not in st.session_state:
+ st.session_state.user_data = {}
+ if "parsed_cv" not in st.session_state:
+ st.session_state.parsed_cv = None
+ if "results" not in st.session_state:
+ st.session_state.results = []
+
+# --- UI COMPONENTS ---
+
+def sidebar_navigation():
+ with st.sidebar:
+ st.image("https://cdn-icons-png.flaticon.com/512/2103/2103811.png", width=80)
+ st.title("AgentJob.ai")
+ st.markdown("---")
+
+ if st.session_state.logged_in:
+ st.write(f"👤 **User:** {st.session_state.user_data.get('email', 'Candidate')}")
+ st.write(f"📅 **Session:** {datetime.now().strftime('%Y-%m-%d')}")
+
+ if st.button("🔄 New Search"):
+ st.session_state.step = "upload"
+ st.rerun()
+
+ if st.button("🚪 Logout"):
+ st.session_state.logged_in = False
+ st.session_state.step = "welcome"
+ st.rerun()
+ else:
+ st.info("Log in to activate your AI agent.")
+
+def login_screen():
+ col1, col2 = st.columns([1, 1])
+ with col1:
+ st.title("Access your AI Agent")
+ st.write("Log in to securely upload your CV and begin your automated search.")
+ email = st.text_input("Email Address", placeholder="alex@example.com")
+ password = st.text_input("Password", type="password")
+ if st.button("Launch Agent", use_container_width=True):
+ # Simulation of FastAPI Auth
+ st.session_state.logged_in = True
+ st.session_state.user_data = {"email": email}
+ st.session_state.step = "upload"
+ st.rerun()
+ with col2:
+ st.image("https://images.unsplash.com/photo-1551434678-e076c223a692?auto=format&fit=crop&q=80&w=1000", use_container_width=True)
+
+def upload_screen():
+ st.header("Step 1: Profile Initialization")
+ st.write("Upload your resume. Our **Quen-based NLP** will extract your core competencies.")
+
+ uploaded_file = st.file_uploader("Drop your PDF or DOCX here", type=['pdf', 'docx'])
+
+ if uploaded_file:
+ st.success("File received. Ready to parse.")
+ if st.button("Start AI Pipeline", use_container_width=True):
+ st.session_state.step = "processing"
+ st.rerun()
+
+def processing_screen():
+ st.header("Step 2: AI Execution Pipeline")
+
+ # 1. Quen Parsing
+ with st.status("🧠 **Quen AI:** Parsing CV Structure...", expanded=True) as status:
+ st.write("Extracting technical stack...")
+ time.sleep(1.2)
+ st.write("Identifying seniority level: *Senior Full Stack* detected.")
+ time.sleep(1.0)
+ st.write("Mapping location preferences: *Europe/Remote*.")
+ st.session_state.parsed_cv = {"skills": ["Python", "React", "FastAPI"], "level": "Senior"}
+ status.update(label="✅ CV Parsing Complete", state="complete", expanded=False)
+
+ # 2. Live Web Scraper Agent
+ st.subheader("🌐 Active Web Searching")
+ cols = st.columns(3)
+ sources = [
+ {"name": "LinkedIn", "icon": "🔵", "count": 18},
+ {"name": "Glassdoor", "icon": "🟢", "count": 12},
+ {"name": "Welcome to the Jungle", "icon": "🟡", "count": 9}
+ ]
+
+ for i, source in enumerate(sources):
+ with cols[i]:
+ with st.container(border=True):
+ st.write(f"{source['icon']} **{source['name']}**")
+ progress_bar = st.progress(0)
+ for percent in range(101):
+ time.sleep(0.01)
+ progress_bar.progress(percent)
+ st.caption(f"Scanned {source['count']} relevant openings")
+
+ # 3. HR Flow Ranking
+ with st.status("⚖️ **HR Flow:** Ranking Match Relevance...") as status:
+ st.write("Running semantic similarity algorithm...")
+ time.sleep(1.5)
+ st.write("Calculating match scores for 39 jobs...")
+ status.update(label="🎯 Pipeline Execution Complete!", state="complete")
+
+ if st.button("Review My Ranked Matches", type="primary", use_container_width=True):
+ # Mock Results from HR Flow
+ st.session_state.results = [
+ {"title": "Senior AI Software Engineer", "company": "NeuralPath", "score": 98, "loc": "Remote", "source": "LinkedIn", "salary": "€80k - €110k"},
+ {"title": "Full Stack Architect", "company": "GrowthOps", "score": 94, "loc": "Paris / Hybrid", "source": "Welcome to the Jungle", "salary": "€75k - €95k"},
+ {"title": "Engineering Manager (AI)", "company": "Vortex Labs", "score": 87, "loc": "London / Remote", "source": "Glassdoor", "salary": "£90k - £120k"},
+ {"title": "Lead Python Developer", "company": "EcoTech", "score": 82, "loc": "Berlin", "source": "LinkedIn", "salary": "€70k - €85k"},
+ ]
+ st.session_state.step = "results"
+ st.rerun()
+
+def results_screen():
+ st.header("Step 3: Intelligence Insights")
+ st.write(f"We found **{len(st.session_state.results)}** high-probability matches for your profile.")
+
+ # Filter/Sort UI
+ col_f1, col_f2, _ = st.columns([1, 1, 2])
+ with col_f1:
+ st.selectbox("Sort by", ["Match Score (High-Low)", "Newest", "Salary"])
+ with col_f2:
+ st.multiselect("Source Filter", ["LinkedIn", "Glassdoor", "Welcome to the Jungle"])
+
+ st.divider()
+
+ # Job Cards
+ for job in st.session_state.results:
+ source_class = "tag-linkedin" if job['source'] == "LinkedIn" else "tag-jungle" if job['source'] == "Welcome to the Jungle" else "tag-glassdoor"
+
+ st.markdown(f"""
+
+
+
{job['source']}
+
{job['title']}
+
{job['company']} • {job['loc']}
+
{job['salary']}
+
+
+
{job['score']}%
+
Match Score
+
+
", unsafe_allow_html=True)
+ st.title("Welcome to ClawedIn")
+ st.write("Upload your CV and let our AI agent find the best jobs for you.")
+ email = st.text_input("Email Address", placeholder="alex@example.com")
+ password = st.text_input("Password", type="password")
+ if st.button("🚀 Launch Agent", type="primary", use_container_width=True):
+ if email:
+ st.session_state.logged_in = True
+ st.session_state.user_data = {"email": email}
+ st.session_state.step = "upload"
+ st.rerun()
+ else:
+ st.error("Please enter your email")
+ st.markdown("
", unsafe_allow_html=True)
+
+ with col2:
+ logo_path = Path(__file__).parent.parent / "assets" / "log.svg"
+ if logo_path.exists():
+ svg_content = logo_path.read_text()
+ st.markdown(
+ f"""""",
+ unsafe_allow_html=True
+ )
diff --git a/clawedin-openclawjobfindagent/Streamlit/modules/dashboard.py b/clawedin-openclawjobfindagent/Streamlit/modules/dashboard.py
new file mode 100644
index 0000000..59db50b
--- /dev/null
+++ b/clawedin-openclawjobfindagent/Streamlit/modules/dashboard.py
@@ -0,0 +1,98 @@
+import streamlit as st
+import re
+
+def clean_title(title: str) -> str:
+ title = re.sub(r'^\d+[-—–]\s*', '', title)
+ title = re.sub(r'\([^)]*\)', '', title)
+ title = re.sub(r'\b(20\d{2})\b', '', title)
+ title = re.sub(r'\b(NOW HIRING|URGENT|HIRING|APPLY NOW)\b', '', title, flags=re.IGNORECASE)
+ return " ".join(title.split()).strip()
+
+def render():
+ parsed = st.session_state.get("parsed_cv", {})
+ results = st.session_state.get("results", [])
+
+ # Progress indicator
+ st.markdown("""
+
+ """, unsafe_allow_html=True)
+
+ st.markdown(f"## 🎯 {len(results)} Job Matches Found")
+ st.caption(f"Ranked by OpenClaw AI for **{parsed.get('name','Candidate')}**")
+ st.divider()
+
+ for i, job in enumerate(results):
+ score = job.get("score", 0)
+ title = clean_title(job.get("title", "N/A"))
+ company = job.get("company", "N/A")
+ loc = job.get("loc", "N/A")
+ reason = job.get("reason", "")
+ url = job.get("url", "")
+
+ # Color based on score
+ if score >= 80:
+ badge_color = "#16a34a"
+ elif score >= 60:
+ badge_color = "#2563eb"
+ else:
+ badge_color = "#64748b"
+
+ with st.container(border=True):
+ col1, col2 = st.columns([0.82, 0.18])
+
+ with col1:
+ st.markdown(
+ "OPENCLAW",
+ unsafe_allow_html=True
+ )
+ st.markdown(f"### {title}")
+ st.caption(f"🏢 {company} • 📍 {loc}")
+
+ if reason and reason not in ["Relevant to your profile", "N/A", ""]:
+ st.markdown(
+ f"💡 {reason}
",
+ unsafe_allow_html=True
+ )
+
+ with col2:
+ st.markdown(
+ f""
+ f"
{score}%
"
+ f"
MATCH
"
+ f"