feat: extract hard-coded personal references from all app pages via UserProfile
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
parent
5a4d2b6b17
commit
b5b4f37bf7
5 changed files with 74 additions and 55 deletions
10
app/Home.py
10
app/Home.py
|
|
@ -11,6 +11,12 @@ import streamlit as st
|
|||
|
||||
sys.path.insert(0, str(Path(__file__).parent.parent))
|
||||
|
||||
from scripts.user_profile import UserProfile
|
||||
|
||||
_USER_YAML = Path(__file__).parent.parent / "config" / "user.yaml"
|
||||
_profile = UserProfile(_USER_YAML) if UserProfile.exists(_USER_YAML) else None
|
||||
_name = _profile.name if _profile else "Job Seeker"
|
||||
|
||||
from scripts.db import DEFAULT_DB, init_db, get_job_counts, purge_jobs, purge_email_data, \
|
||||
purge_non_remote, archive_jobs, kill_stuck_tasks, get_task_for_job, get_active_tasks, \
|
||||
insert_job, get_existing_urls
|
||||
|
|
@ -64,7 +70,7 @@ def _queue_url_imports(db_path: Path, urls: list) -> int:
|
|||
return queued
|
||||
|
||||
|
||||
st.title("🔍 Meghan's Job Search")
|
||||
st.title(f"🔍 {_name}'s Job Search")
|
||||
st.caption("Discover → Review → Sync to Notion")
|
||||
|
||||
st.divider()
|
||||
|
|
@ -149,7 +155,7 @@ with mid:
|
|||
.get_jobs_by_status(DEFAULT_DB, "pending")
|
||||
if j.get("match_score") is None and j.get("description"))
|
||||
st.subheader("Score Listings")
|
||||
st.caption(f"Run TF-IDF match scoring against Meghan's resume. {unscored} pending job{'s' if unscored != 1 else ''} unscored.")
|
||||
st.caption(f"Run TF-IDF match scoring against {_name}'s resume. {unscored} pending job{'s' if unscored != 1 else ''} unscored.")
|
||||
if st.button("📊 Score All Unscored Jobs", use_container_width=True, type="primary",
|
||||
disabled=unscored == 0):
|
||||
with st.spinner("Scoring…"):
|
||||
|
|
|
|||
|
|
@ -10,6 +10,12 @@ sys.path.insert(0, str(Path(__file__).parent.parent.parent))
|
|||
import streamlit as st
|
||||
import yaml
|
||||
|
||||
from scripts.user_profile import UserProfile
|
||||
|
||||
_USER_YAML = Path(__file__).parent.parent.parent / "config" / "user.yaml"
|
||||
_profile = UserProfile(_USER_YAML) if UserProfile.exists(_USER_YAML) else None
|
||||
_name = _profile.name if _profile else "Job Seeker"
|
||||
|
||||
st.title("⚙️ Settings")
|
||||
|
||||
CONFIG_DIR = Path(__file__).parent.parent.parent / "config"
|
||||
|
|
@ -402,7 +408,6 @@ with tab_services:
|
|||
import subprocess as _sp
|
||||
|
||||
TOKENS_CFG = CONFIG_DIR / "tokens.yaml"
|
||||
PFP_DIR = Path("/Library/Documents/Post Fight Processing")
|
||||
|
||||
# Service definitions: (display_name, port, start_cmd, stop_cmd, notes)
|
||||
SERVICES = [
|
||||
|
|
@ -422,30 +427,14 @@ with tab_services:
|
|||
"cwd": "/",
|
||||
"note": "Local inference engine — systemd service",
|
||||
},
|
||||
{
|
||||
"name": "Claude Code Wrapper",
|
||||
"port": 3009,
|
||||
"start": ["bash", str(PFP_DIR / "manage-services.sh"), "start"],
|
||||
"stop": ["bash", str(PFP_DIR / "manage-services.sh"), "stop"],
|
||||
"cwd": str(PFP_DIR),
|
||||
"note": "OpenAI-compat proxy → Claude Code (port 3009)",
|
||||
},
|
||||
{
|
||||
"name": "GitHub Copilot Wrapper",
|
||||
"port": 3010,
|
||||
"start": ["bash", str(PFP_DIR / "manage-copilot.sh"), "start"],
|
||||
"stop": ["bash", str(PFP_DIR / "manage-copilot.sh"), "stop"],
|
||||
"cwd": str(PFP_DIR),
|
||||
"note": "OpenAI-compat proxy → GitHub Copilot (port 3010)",
|
||||
},
|
||||
{
|
||||
"name": "vLLM Server",
|
||||
"port": 8000,
|
||||
"start": ["bash", str(Path(__file__).parent.parent.parent / "scripts/manage-vllm.sh"), "start"],
|
||||
"stop": ["bash", str(Path(__file__).parent.parent.parent / "scripts/manage-vllm.sh"), "stop"],
|
||||
"cwd": str(Path(__file__).parent.parent.parent),
|
||||
"model_dir": "/Library/Assets/LLM/vllm/models",
|
||||
"note": "Local vLLM inference — Ouro model family (port 8000, GPU 1)",
|
||||
"model_dir": str(_profile.vllm_models_dir) if _profile else str(Path.home() / "models" / "vllm"),
|
||||
"note": "Local vLLM inference (port 8000, GPU 1)",
|
||||
},
|
||||
{
|
||||
"name": "Vision Service (moondream2)",
|
||||
|
|
@ -457,11 +446,11 @@ with tab_services:
|
|||
},
|
||||
{
|
||||
"name": "SearXNG (company scraper)",
|
||||
"port": 8888,
|
||||
"start": ["docker", "compose", "up", "-d"],
|
||||
"stop": ["docker", "compose", "down"],
|
||||
"cwd": str(Path("/Library/Development/scrapers/SearXNG")),
|
||||
"note": "Privacy-respecting meta-search used for company research (port 8888)",
|
||||
"port": _profile._svc["searxng_port"] if _profile else 8888,
|
||||
"start": ["docker", "compose", "--profile", "searxng", "up", "-d", "searxng"],
|
||||
"stop": ["docker", "compose", "stop", "searxng"],
|
||||
"cwd": str(Path(__file__).parent.parent.parent),
|
||||
"note": "Privacy-respecting meta-search for company research",
|
||||
},
|
||||
]
|
||||
|
||||
|
|
@ -583,7 +572,7 @@ with tab_services:
|
|||
# ── Resume Profile tab ────────────────────────────────────────────────────────
|
||||
with tab_resume:
|
||||
st.caption(
|
||||
"Edit Meghan's application profile. "
|
||||
f"Edit {_name}'s application profile. "
|
||||
"Bullets are used as paste-able shortcuts in the Apply Workspace."
|
||||
)
|
||||
|
||||
|
|
@ -728,7 +717,7 @@ with tab_email:
|
|||
EMAIL_EXAMPLE = CONFIG_DIR / "email.yaml.example"
|
||||
|
||||
st.caption(
|
||||
"Connect Meghan's email via IMAP to automatically associate recruitment "
|
||||
f"Connect {_name}'s email via IMAP to automatically associate recruitment "
|
||||
"emails with job applications. Only emails that mention the company name "
|
||||
"AND contain a recruitment keyword are ever imported — no personal emails "
|
||||
"are touched."
|
||||
|
|
@ -789,7 +778,7 @@ with tab_email:
|
|||
with tab_skills:
|
||||
st.subheader("🏷️ Skills & Keywords")
|
||||
st.caption(
|
||||
"These are matched against job descriptions to select Meghan's most relevant "
|
||||
f"These are matched against job descriptions to select {_name}'s most relevant "
|
||||
"experience and highlight keyword overlap in the research brief."
|
||||
)
|
||||
|
||||
|
|
|
|||
|
|
@ -14,6 +14,12 @@ import streamlit as st
|
|||
import streamlit.components.v1 as components
|
||||
import yaml
|
||||
|
||||
from scripts.user_profile import UserProfile
|
||||
|
||||
_USER_YAML = Path(__file__).parent.parent.parent / "config" / "user.yaml"
|
||||
_profile = UserProfile(_USER_YAML) if UserProfile.exists(_USER_YAML) else None
|
||||
_name = _profile.name if _profile else "Job Seeker"
|
||||
|
||||
from scripts.db import (
|
||||
DEFAULT_DB, init_db, get_jobs_by_status,
|
||||
update_cover_letter, mark_applied, update_job_status,
|
||||
|
|
@ -21,7 +27,7 @@ from scripts.db import (
|
|||
)
|
||||
from scripts.task_runner import submit_task
|
||||
|
||||
DOCS_DIR = Path("/Library/Documents/JobSearch")
|
||||
DOCS_DIR = _profile.docs_dir if _profile else Path.home() / "Documents" / "JobSearch"
|
||||
RESUME_YAML = Path(__file__).parent.parent.parent / "aihawk" / "data_folder" / "plain_text_resume.yaml"
|
||||
|
||||
st.title("🚀 Apply Workspace")
|
||||
|
|
@ -70,13 +76,16 @@ def _make_cover_letter_pdf(job: dict, cover_letter: str, output_dir: Path) -> Pa
|
|||
textColor=dark, leading=16, spaceAfter=12, alignment=TA_LEFT,
|
||||
)
|
||||
|
||||
display_name = _profile.name.upper() if _profile else "YOUR NAME"
|
||||
contact_line = " · ".join(filter(None, [
|
||||
_profile.email if _profile else "",
|
||||
_profile.phone if _profile else "",
|
||||
_profile.linkedin if _profile else "",
|
||||
]))
|
||||
|
||||
story = [
|
||||
Paragraph("MEGHAN McCANN", name_style),
|
||||
Paragraph(
|
||||
"meghan.m.mccann@gmail.com · (510) 764-3155 · "
|
||||
"linkedin.com/in/MeghanMcCann · hiremeghanmccann.site",
|
||||
contact_style,
|
||||
),
|
||||
Paragraph(display_name, name_style),
|
||||
Paragraph(contact_line, contact_style),
|
||||
HRFlowable(width="100%", thickness=1, color=teal, spaceBefore=8, spaceAfter=0),
|
||||
Paragraph(datetime.now().strftime("%B %d, %Y"), date_style),
|
||||
]
|
||||
|
|
@ -88,7 +97,7 @@ def _make_cover_letter_pdf(job: dict, cover_letter: str, output_dir: Path) -> Pa
|
|||
|
||||
story += [
|
||||
Spacer(1, 6),
|
||||
Paragraph("Warm regards,<br/><br/>Meghan McCann", body_style),
|
||||
Paragraph(f"Warm regards,<br/><br/>{_profile.name if _profile else 'Your Name'}", body_style),
|
||||
]
|
||||
|
||||
doc.build(story)
|
||||
|
|
@ -96,7 +105,7 @@ def _make_cover_letter_pdf(job: dict, cover_letter: str, output_dir: Path) -> Pa
|
|||
|
||||
# ── Application Q&A helper ─────────────────────────────────────────────────────
|
||||
def _answer_question(job: dict, question: str) -> str:
|
||||
"""Call the LLM to answer an application question in Meghan's voice.
|
||||
"""Call the LLM to answer an application question in the user's voice.
|
||||
|
||||
Uses research_fallback_order (claude_code → vllm → ollama_research)
|
||||
rather than the default cover-letter order — the fine-tuned cover letter
|
||||
|
|
@ -106,21 +115,22 @@ def _answer_question(job: dict, question: str) -> str:
|
|||
router = LLMRouter()
|
||||
fallback = router.config.get("research_fallback_order") or router.config.get("fallback_order")
|
||||
description_snippet = (job.get("description") or "")[:1200].strip()
|
||||
prompt = f"""You are answering job application questions for Meghan McCann, a customer success leader.
|
||||
_persona_summary = (
|
||||
_profile.career_summary[:200] if _profile and _profile.career_summary
|
||||
else "a professional with experience in their field"
|
||||
)
|
||||
prompt = f"""You are answering job application questions for {_name}.
|
||||
|
||||
Background:
|
||||
- 6+ years in customer success, technical account management, and CS leadership
|
||||
- Most recent role: led Americas Customer Success at UpGuard (cybersecurity SaaS), NPS consistently ≥95
|
||||
- Also founder of M3 Consulting, a CS advisory practice for SaaS startups
|
||||
- Based in SF Bay Area; open to remote/hybrid; pronouns: any
|
||||
{_persona_summary}
|
||||
|
||||
Role she's applying to: {job.get("title", "")} at {job.get("company", "")}
|
||||
Role they're applying to: {job.get("title", "")} at {job.get("company", "")}
|
||||
{f"Job description excerpt:{chr(10)}{description_snippet}" if description_snippet else ""}
|
||||
|
||||
Application Question:
|
||||
{question}
|
||||
|
||||
Answer in Meghan's voice — specific, warm, and confident. If the question specifies a word or character limit, respect it. Answer only the question with no preamble or sign-off."""
|
||||
Answer in {_name}'s voice — specific, warm, and confident. If the question specifies a word or character limit, respect it. Answer only the question with no preamble or sign-off."""
|
||||
return router.complete(prompt, fallback_order=fallback).strip()
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -22,6 +22,12 @@ sys.path.insert(0, str(Path(__file__).parent.parent.parent))
|
|||
|
||||
import streamlit as st
|
||||
|
||||
from scripts.user_profile import UserProfile
|
||||
|
||||
_USER_YAML = Path(__file__).parent.parent.parent / "config" / "user.yaml"
|
||||
_profile = UserProfile(_USER_YAML) if UserProfile.exists(_USER_YAML) else None
|
||||
_name = _profile.name if _profile else "Job Seeker"
|
||||
|
||||
from scripts.db import (
|
||||
DEFAULT_DB, init_db,
|
||||
get_interview_jobs, advance_to_stage, reject_at_stage,
|
||||
|
|
@ -186,19 +192,21 @@ def _email_modal(job: dict) -> None:
|
|||
with st.spinner("Drafting…"):
|
||||
try:
|
||||
from scripts.llm_router import complete
|
||||
_persona = (
|
||||
f"{_name} is a {_profile.career_summary[:120] if _profile and _profile.career_summary else 'professional'}"
|
||||
)
|
||||
draft = complete(
|
||||
prompt=(
|
||||
f"Draft a professional, warm reply to this email.\n\n"
|
||||
f"From: {last.get('from_addr', '')}\n"
|
||||
f"Subject: {last.get('subject', '')}\n\n"
|
||||
f"{last.get('body', '')}\n\n"
|
||||
f"Context: Meghan McCann is a Customer Success / "
|
||||
f"Technical Account Manager applying for "
|
||||
f"Context: {_persona} applying for "
|
||||
f"{job.get('title')} at {job.get('company')}."
|
||||
),
|
||||
system=(
|
||||
"You are Meghan McCann's professional email assistant. "
|
||||
"Write concise, warm, and professional replies in her voice. "
|
||||
f"You are {_name}'s professional email assistant. "
|
||||
"Write concise, warm, and professional replies in their voice. "
|
||||
"Keep it to 3–5 sentences unless more is needed."
|
||||
),
|
||||
)
|
||||
|
|
|
|||
|
|
@ -13,6 +13,12 @@ sys.path.insert(0, str(Path(__file__).parent.parent.parent))
|
|||
|
||||
import streamlit as st
|
||||
|
||||
from scripts.user_profile import UserProfile
|
||||
|
||||
_USER_YAML = Path(__file__).parent.parent.parent / "config" / "user.yaml"
|
||||
_profile = UserProfile(_USER_YAML) if UserProfile.exists(_USER_YAML) else None
|
||||
_name = _profile.name if _profile else "Job Seeker"
|
||||
|
||||
from scripts.db import (
|
||||
DEFAULT_DB, init_db,
|
||||
get_interview_jobs, get_contacts, get_research,
|
||||
|
|
@ -231,7 +237,7 @@ with col_prep:
|
|||
system=(
|
||||
f"You are a recruiter at {job.get('company')} conducting "
|
||||
f"a phone screen for the {job.get('title')} role. "
|
||||
f"Ask one question at a time. After Meghan answers, give "
|
||||
f"Ask one question at a time. After {_name} answers, give "
|
||||
f"brief feedback (1–2 sentences), then ask your next question. "
|
||||
f"Be professional but warm."
|
||||
),
|
||||
|
|
@ -253,7 +259,7 @@ with col_prep:
|
|||
"content": (
|
||||
f"You are a recruiter at {job.get('company')} conducting "
|
||||
f"a phone screen for the {job.get('title')} role. "
|
||||
f"Ask one question at a time. After Meghan answers, give "
|
||||
f"Ask one question at a time. After {_name} answers, give "
|
||||
f"brief feedback (1–2 sentences), then ask your next question."
|
||||
),
|
||||
}
|
||||
|
|
@ -265,7 +271,7 @@ with col_prep:
|
|||
router = LLMRouter()
|
||||
# Build prompt from history for single-turn backends
|
||||
convo = "\n\n".join(
|
||||
f"{'Interviewer' if m['role'] == 'assistant' else 'Meghan'}: {m['content']}"
|
||||
f"{'Interviewer' if m['role'] == 'assistant' else _name}: {m['content']}"
|
||||
for m in history
|
||||
)
|
||||
response = router.complete(
|
||||
|
|
@ -331,12 +337,12 @@ with col_context:
|
|||
f"From: {last.get('from_addr', '')}\n"
|
||||
f"Subject: {last.get('subject', '')}\n\n"
|
||||
f"{last.get('body', '')}\n\n"
|
||||
f"Context: Meghan is a CS/TAM professional applying "
|
||||
f"Context: {_name} is a professional applying "
|
||||
f"for {job.get('title')} at {job.get('company')}."
|
||||
),
|
||||
system=(
|
||||
"You are Meghan McCann's professional email assistant. "
|
||||
"Write concise, warm, and professional replies in her voice."
|
||||
f"You are {_name}'s professional email assistant. "
|
||||
"Write concise, warm, and professional replies in their voice."
|
||||
),
|
||||
)
|
||||
st.session_state[f"draft_{selected_id}"] = draft
|
||||
|
|
|
|||
Loading…
Reference in a new issue