264 lines
12 KiB
Python
264 lines
12 KiB
Python
"""
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First-run setup wizard — shown by app.py when config/user.yaml is absent.
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Five steps: hardware detection → identity → NDA companies → inference/keys → Notion.
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Writes config/user.yaml (and optionally config/notion.yaml) on completion.
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"""
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import subprocess
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent.parent))
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import streamlit as st
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import yaml
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CONFIG_DIR = Path(__file__).parent.parent.parent / "config"
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USER_CFG = CONFIG_DIR / "user.yaml"
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NOTION_CFG = CONFIG_DIR / "notion.yaml"
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LLM_CFG = CONFIG_DIR / "llm.yaml"
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PROFILES = ["remote", "cpu", "single-gpu", "dual-gpu"]
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def _detect_gpus() -> list[str]:
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"""Return list of GPU names via nvidia-smi, or [] if none."""
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try:
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out = subprocess.check_output(
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["nvidia-smi", "--query-gpu=name", "--format=csv,noheader"],
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text=True, timeout=5
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)
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return [l.strip() for l in out.strip().splitlines() if l.strip()]
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except Exception:
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return []
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def _suggest_profile(gpus: list[str]) -> str:
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if len(gpus) >= 2:
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return "dual-gpu"
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if len(gpus) == 1:
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return "single-gpu"
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return "remote"
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# ── Wizard state ───────────────────────────────────────────────────────────────
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if "wizard_step" not in st.session_state:
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st.session_state.wizard_step = 1
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if "wizard_data" not in st.session_state:
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st.session_state.wizard_data = {}
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step = st.session_state.wizard_step
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data = st.session_state.wizard_data
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st.title("👋 Welcome to Peregrine")
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st.caption("Let's get you set up. This takes about 2 minutes.")
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st.progress(step / 5, text=f"Step {step} of 5")
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st.divider()
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# ── Step 1: Hardware detection ─────────────────────────────────────────────────
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if step == 1:
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st.subheader("Step 1 — Hardware Detection")
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gpus = _detect_gpus()
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suggested = _suggest_profile(gpus)
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if gpus:
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st.success(f"Found {len(gpus)} GPU(s): {', '.join(gpus)}")
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else:
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st.info("No NVIDIA GPUs detected. Remote or CPU mode recommended.")
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profile = st.selectbox(
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"Inference mode",
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PROFILES,
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index=PROFILES.index(suggested),
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help="This controls which Docker services start. You can change it later in Settings → My Profile.",
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)
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if profile in ("single-gpu", "dual-gpu") and not gpus:
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st.warning("No GPUs detected — GPU profiles require NVIDIA Container Toolkit. See the README for install instructions.")
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if st.button("Next →", type="primary"):
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data["inference_profile"] = profile
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data["gpus_detected"] = gpus
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st.session_state.wizard_step = 2
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st.rerun()
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# ── Step 2: Identity ───────────────────────────────────────────────────────────
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elif step == 2:
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st.subheader("Step 2 — Your Identity")
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st.caption("Used in cover letter PDFs, LLM prompts, and the app header.")
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c1, c2 = st.columns(2)
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name = c1.text_input("Full Name *", data.get("name", ""))
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email = c1.text_input("Email *", data.get("email", ""))
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phone = c2.text_input("Phone", data.get("phone", ""))
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linkedin = c2.text_input("LinkedIn URL", data.get("linkedin", ""))
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summary = st.text_area(
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"Career Summary *",
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data.get("career_summary", ""),
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height=120,
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placeholder="Experienced professional with X years in [field]. Specialise in [skills].",
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help="This paragraph is injected into cover letter and research prompts as your professional context.",
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)
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col_back, col_next = st.columns([1, 4])
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if col_back.button("← Back"):
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st.session_state.wizard_step = 1
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st.rerun()
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if col_next.button("Next →", type="primary"):
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if not name or not email or not summary:
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st.error("Name, email, and career summary are required.")
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else:
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data.update({"name": name, "email": email, "phone": phone,
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"linkedin": linkedin, "career_summary": summary})
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st.session_state.wizard_step = 3
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st.rerun()
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# ── Step 3: NDA Companies ──────────────────────────────────────────────────────
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elif step == 3:
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st.subheader("Step 3 — Sensitive Employers (Optional)")
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st.caption(
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"Previous employers listed here will appear as 'previous employer (NDA)' in "
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"research briefs and talking points. Skip if not applicable."
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)
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nda_list = list(data.get("nda_companies", []))
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if nda_list:
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cols = st.columns(min(len(nda_list), 5))
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to_remove = None
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for i, c in enumerate(nda_list):
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if cols[i % 5].button(f"× {c}", key=f"rm_{c}"):
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to_remove = c
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if to_remove:
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nda_list.remove(to_remove)
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data["nda_companies"] = nda_list
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st.rerun()
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nc, nb = st.columns([4, 1])
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new_c = nc.text_input("Add employer", key="new_nda_wiz",
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label_visibility="collapsed", placeholder="Employer name…")
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if nb.button("＋ Add") and new_c.strip():
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nda_list.append(new_c.strip())
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data["nda_companies"] = nda_list
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st.rerun()
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col_back, col_skip, col_next = st.columns([1, 1, 3])
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if col_back.button("← Back"):
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st.session_state.wizard_step = 2
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st.rerun()
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if col_skip.button("Skip"):
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data.setdefault("nda_companies", [])
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st.session_state.wizard_step = 4
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st.rerun()
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if col_next.button("Next →", type="primary"):
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data["nda_companies"] = nda_list
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st.session_state.wizard_step = 4
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st.rerun()
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# ── Step 4: Inference & API Keys ───────────────────────────────────────────────
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elif step == 4:
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profile = data.get("inference_profile", "remote")
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st.subheader("Step 4 — Inference & API Keys")
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if profile == "remote":
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st.info("Remote mode: LLM calls go to external APIs. At least one key is needed.")
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anthropic_key = st.text_input("Anthropic API Key", type="password",
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placeholder="sk-ant-…")
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openai_url = st.text_input("OpenAI-compatible endpoint (optional)",
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placeholder="https://api.together.xyz/v1")
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openai_key = st.text_input("Endpoint API Key (optional)", type="password") if openai_url else ""
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data.update({"anthropic_key": anthropic_key, "openai_url": openai_url,
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"openai_key": openai_key})
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else:
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st.info(f"Local mode ({profile}): Ollama handles cover letters. Configure model below.")
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ollama_model = st.text_input("Cover letter model name",
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data.get("ollama_model", "llama3.2:3b"),
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help="This model will be pulled by Ollama on first start.")
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data["ollama_model"] = ollama_model
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st.divider()
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with st.expander("Advanced — Service Ports & Hosts"):
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st.caption("Change only if services run on non-default ports or remote hosts.")
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svc = data.get("services", {})
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for svc_name, default_host, default_port in [
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("ollama", "localhost", 11434),
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("vllm", "localhost", 8000),
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("searxng", "localhost", 8888),
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]:
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c1, c2, c3, c4 = st.columns([2, 1, 0.5, 0.5])
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svc[f"{svc_name}_host"] = c1.text_input(f"{svc_name} host", svc.get(f"{svc_name}_host", default_host), key=f"adv_{svc_name}_host")
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svc[f"{svc_name}_port"] = int(c2.number_input("port", value=svc.get(f"{svc_name}_port", default_port), step=1, key=f"adv_{svc_name}_port"))
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svc[f"{svc_name}_ssl"] = c3.checkbox("SSL", svc.get(f"{svc_name}_ssl", False), key=f"adv_{svc_name}_ssl")
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svc[f"{svc_name}_ssl_verify"] = c4.checkbox("Verify", svc.get(f"{svc_name}_ssl_verify", True), key=f"adv_{svc_name}_verify")
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data["services"] = svc
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col_back, col_next = st.columns([1, 4])
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if col_back.button("← Back"):
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st.session_state.wizard_step = 3
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st.rerun()
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if col_next.button("Next →", type="primary"):
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st.session_state.wizard_step = 5
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st.rerun()
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# ── Step 5: Notion (optional) ──────────────────────────────────────────────────
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elif step == 5:
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st.subheader("Step 5 — Notion Sync (Optional)")
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st.caption("Syncs approved and applied jobs to a Notion database. Skip if not using Notion.")
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notion_token = st.text_input("Integration Token", type="password", placeholder="secret_…")
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notion_db = st.text_input("Database ID", placeholder="32-character ID from Notion URL")
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if notion_token and notion_db:
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if st.button("🔌 Test connection"):
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with st.spinner("Connecting…"):
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try:
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from notion_client import Client
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db = Client(auth=notion_token).databases.retrieve(notion_db)
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st.success(f"Connected: {db['title'][0]['plain_text']}")
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except Exception as e:
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st.error(f"Connection failed: {e}")
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col_back, col_skip, col_finish = st.columns([1, 1, 3])
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if col_back.button("← Back"):
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st.session_state.wizard_step = 4
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st.rerun()
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def _finish(save_notion: bool) -> None:
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svc_defaults = {
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"streamlit_port": 8501,
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"ollama_host": "localhost", "ollama_port": 11434,
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"ollama_ssl": False, "ollama_ssl_verify": True,
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"vllm_host": "localhost", "vllm_port": 8000,
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"vllm_ssl": False, "vllm_ssl_verify": True,
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"searxng_host": "localhost", "searxng_port": 8888,
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"searxng_ssl": False, "searxng_ssl_verify": True,
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}
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svc_defaults.update(data.get("services", {}))
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user_data = {
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"name": data.get("name", ""),
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"email": data.get("email", ""),
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"phone": data.get("phone", ""),
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"linkedin": data.get("linkedin", ""),
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"career_summary": data.get("career_summary", ""),
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"nda_companies": data.get("nda_companies", []),
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"docs_dir": "~/Documents/JobSearch",
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"ollama_models_dir": "~/models/ollama",
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"vllm_models_dir": "~/models/vllm",
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"inference_profile": data.get("inference_profile", "remote"),
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"services": svc_defaults,
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}
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CONFIG_DIR.mkdir(parents=True, exist_ok=True)
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USER_CFG.write_text(yaml.dump(user_data, default_flow_style=False, allow_unicode=True))
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if LLM_CFG.exists():
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from scripts.user_profile import UserProfile
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from scripts.generate_llm_config import apply_service_urls
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apply_service_urls(UserProfile(USER_CFG), LLM_CFG)
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if save_notion and notion_token and notion_db:
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NOTION_CFG.write_text(yaml.dump({
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"token": notion_token,
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"database_id": notion_db,
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}))
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st.session_state.wizard_step = 1
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st.session_state.wizard_data = {}
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st.success("Setup complete! Redirecting…")
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st.rerun()
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if col_skip.button("Skip & Finish"):
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_finish(save_notion=False)
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if col_finish.button("💾 Save & Finish", type="primary"):
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_finish(save_notion=True)
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