"""
Manager Intelligence Agent
Free HF Inference API (Llama-3-8B) — no paid API key needed
Deploy on Hugging Face Spaces (Gradio)
"""
import os, re, json, shutil, pickle, hashlib, datetime, logging
from pathlib import Path
import gradio as gr
logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s")
log = logging.getLogger(__name__)
# ── CONFIG ───────────────────────────────────────────────────────
INDEX_DIR = os.path.join(os.path.expanduser("~"), "manager_agent_index")
TASKS_FILE = os.path.join(INDEX_DIR, "_tasks.json")
EVENTS_FILE = os.path.join(INDEX_DIR, "_events.json")
os.makedirs(INDEX_DIR, exist_ok=True)
SUPPORTED = {".pdf",".docx",".doc",".xlsx",".xls",".csv",".txt",".eml",".rtf",".pptx",".ppt"}
MAX_MB = 50
ICONS = {".pdf":"📕",".docx":"📘",".doc":"📘",".xlsx":"📗",".xls":"📗",
".csv":"📊",".pptx":"📙",".ppt":"📙",".txt":"📄",".eml":"📧",".msg":"📧"}
HF_TOKEN = os.environ.get("HF_TOKEN", "") # optional — removes rate limits
HF_MODEL = "meta-llama/Meta-Llama-3-8B-Instruct"
# ── AI BACKEND ───────────────────────────────────────────────────
def get_client():
try:
from huggingface_hub import InferenceClient
return InferenceClient(model=HF_MODEL, token=HF_TOKEN if HF_TOKEN else None)
except Exception as e:
log.error(f"InferenceClient init: {e}")
return None
def ai_status():
try:
from huggingface_hub import InferenceClient
return "✅ HF Inference (Llama-3-8B) — Free"
except:
return "⚠️ huggingface_hub not installed"
def call_llm(prompt, system=None, history=None):
client = get_client()
if not client:
return "❌ Could not connect to HF Inference API."
messages = []
if system:
messages.append({"role": "system", "content": system})
if history:
for u, b in history[-6:]:
messages += [{"role":"user","content":str(u)},
{"role":"assistant","content":str(b)}]
messages.append({"role": "user", "content": prompt})
try:
resp = client.chat_completion(messages=messages, max_tokens=1024, temperature=0.7)
return resp.choices[0].message.content.strip()
except Exception as e:
log.error(f"call_llm: {e}")
return f"❌ Inference error: {e}"
def do_generate(prompt):
return call_llm(prompt)
def do_chat_llm(prompt, context, history):
system = ("You are an elite executive assistant AI with access to the manager's document archive. "
"Answer precisely using the provided context. Cite document names. "
"Use bullet points. Flag deadlines and action items proactively.")
return call_llm(f"{prompt}\n\n--- Document Context ---\n{context}", system=system, history=history)
# ── TEXT EXTRACTION ──────────────────────────────────────────────
def extract(fp):
ext = Path(fp).suffix.lower()
try:
if ext == ".pdf":
import pdfplumber
with pdfplumber.open(fp) as pdf:
return "\n".join(p.extract_text() or "" for p in pdf.pages)
if ext in (".docx", ".doc"):
from docx import Document
doc = Document(fp)
parts = [p.text for p in doc.paragraphs if p.text.strip()]
for t in doc.tables:
for row in t.rows:
parts.append(" | ".join(c.text.strip() for c in row.cells if c.text.strip()))
return "\n".join(parts)
if ext in (".xlsx", ".xls"):
import pandas as pd
xl = pd.ExcelFile(fp)
return "\n\n".join(f"[{s}]\n{xl.parse(s).head(200).to_string(index=False)}" for s in xl.sheet_names)
if ext == ".csv":
import pandas as pd
return pd.read_csv(fp, encoding="utf-8", errors="ignore").to_string(index=False)
if ext in (".pptx", ".ppt"):
from pptx import Presentation
prs = Presentation(fp)
return "\n".join(" ".join(s.text for s in sl.shapes if hasattr(s,"text")) for sl in prs.slides)
return open(fp, "r", encoding="utf-8", errors="ignore").read()
except Exception as e:
log.warning(f"extract({fp}): {e}")
return ""
# ── INDEXING ─────────────────────────────────────────────────────
def fhash(fp):
return hashlib.md5(f"{fp}{os.path.getmtime(fp)}".encode()).hexdigest()[:12]
def is_indexed(fp):
return os.path.exists(f"{INDEX_DIR}/{fhash(fp)}.pkl")
def make_chunks(text, fname, size=350, overlap=70):
words = re.sub(r'\s+', ' ', text).strip().split()
chunks = []
for s in range(0, len(words), size - overlap):
e = min(s + size, len(words))
c = " ".join(words[s:e])
if len(c) > 50:
chunks.append({"text": c, "source": fname, "preview": c[:200]})
if e == len(words): break
return chunks
def index_file(fp):
fname = Path(fp).name
try:
size_mb = os.path.getsize(fp) / (1024*1024)
except Exception as e:
return False, f"Cannot read: {e}"
if size_mb > MAX_MB:
return False, f">{MAX_MB}MB skipped"
text = extract(fp)
if not text or len(text.strip()) < 30:
return False, "No text extracted"
chunks = make_chunks(text, fname)
if not chunks:
return False, "No chunks"
fh = fhash(fp)
meta = {"filename": fname, "filepath": str(fp),
"ftype": Path(fp).suffix.upper().strip("."),
"words": len(text.split()),
"mb": round(size_mb, 2),
"date": datetime.datetime.fromtimestamp(os.path.getmtime(fp)).strftime("%Y-%m-%d")}
with open(f"{INDEX_DIR}/{fh}.pkl", "wb") as f:
pickle.dump({"chunks": chunks, "meta": meta}, f)
return True, f"{len(chunks)} chunks indexed"
# ── SEARCH ───────────────────────────────────────────────────────
def load_all():
chunks = []
for ff in os.listdir(INDEX_DIR):
if not ff.endswith(".pkl") or ff.startswith("_"):
continue
try:
with open(f"{INDEX_DIR}/{ff}", "rb") as f:
data = pickle.load(f)
for c in data["chunks"]:
c = c.copy(); c["meta"] = data["meta"]; chunks.append(c)
except Exception as e:
log.warning(f"load_all {ff}: {e}")
return chunks
def keyword_search(query, chunks):
stop = {"the","a","an","is","in","on","at","to","for","of","and","or","it","was","are","with","this","that"}
kws = {w.lower() for w in re.findall(r'\w+', query) if len(w) > 2} - stop
if not kws: return {}
seen = {}
for c in chunks:
kh = sum(1 for kw in kws if kw in c["text"].lower())
if kh == 0: continue
fn = c["source"]
if fn not in seen or seen[fn]["kw"] < kh:
seen[fn] = {"chunk": c, "score": kh * 0.1, "kw": kh}
return seen
def run_search(query):
EMPTY = gr.Dropdown(choices=[], value=None, label="Select result")
if not query.strip():
return "Enter a search query.
", [], EMPTY
chunks = load_all()
if not chunks:
return "❌ No files indexed. Upload files in Documents tab.
", [], EMPTY
stop = {"the","a","an","is","in","on","at","to","for","of","and","or","it","was","are","with","this","that"}
kws = {w.lower() for w in re.findall(r'\w+', query) if len(w) > 2} - stop
seen = keyword_search(query, chunks)
if not seen:
all_fnames = list(dict.fromkeys(c["source"] for c in chunks))
cards = "".join(f"""""" for fn in all_fnames)
return (f""
f"No matches for: {query}
Try shorter words.
"
f"All indexed files ({len(all_fnames)}):
" + cards,
all_fnames, gr.Dropdown(choices=all_fnames, value=None, label="Select a file"))
results = sorted(seen.items(), key=lambda x: -x[1]["score"])[:8]
html = f"✅ {len(results)} documents for: {query}
"
choices = []
for fname, v in results:
m = v["chunk"]["meta"]
icon = ICONS.get("." + m.get("ftype","").lower(), "📄")
prev = v["chunk"]["preview"]
for kw in kws:
prev = re.sub(f"({re.escape(kw)})",
r"\1",
prev, flags=re.IGNORECASE)
html += f"""
{icon}
{fname}
{m.get("ftype","")} · {m.get("mb",0)} MB · {m.get("words",0):,} words · {m.get("date","")}
🔑 {v["kw"]} hits
{prev}…
"""
choices.append(fname)
return html, choices, gr.Dropdown(choices=choices, value=choices[0], label="📂 Select a file to preview")
# ── DOCUMENT HELPERS ─────────────────────────────────────────────
def get_text(fname):
for ff in os.listdir(INDEX_DIR):
if not ff.endswith(".pkl"): continue
try:
with open(f"{INDEX_DIR}/{ff}", "rb") as f: data = pickle.load(f)
if data["meta"]["filename"] == fname:
return "\n\n".join(c["text"] for c in data["chunks"])
except: pass
return ""
def all_meta():
docs = []
for ff in os.listdir(INDEX_DIR):
if not ff.endswith(".pkl"): continue
try:
with open(f"{INDEX_DIR}/{ff}", "rb") as f: data = pickle.load(f)
docs.append(data["meta"])
except: pass
return sorted(docs, key=lambda x: x.get("date",""), reverse=True)
def all_names(): return [d["filename"] for d in all_meta()]
def lib_stats():
docs = all_meta()
if not docs: return "*No files indexed yet.*"
tw = sum(d.get("words",0) for d in docs)
lines = [f"**📚 {len(docs)} files · {tw:,} words**\n"]
for d in docs[:40]:
icon = ICONS.get("." + d.get("ftype","").lower(), "📄")
lines.append(f"{icon} **{d['filename']}** · {d.get('words',0):,}w · {d.get('date','')} · {d.get('ftype','')}")
if len(docs) > 40: lines.append(f"*...and {len(docs)-40} more*")
return "\n".join(lines)
# ── TASKS ────────────────────────────────────────────────────────
def load_tasks():
try:
if os.path.exists(TASKS_FILE):
with open(TASKS_FILE) as f: return json.load(f)
except: pass
return []
def save_tasks(t):
with open(TASKS_FILE, "w") as f: json.dump(t, f, indent=2)
def tasks_html():
tasks = load_tasks(); today = datetime.date.today().isoformat()
if not tasks:
return "No tasks yet.
"
rows = ""
for i, t in enumerate(tasks):
done = t.get("done", False)
due = t.get("due", "")
ov = due and due < today and not done
bg = "#fef2f2" if ov else ("#f9fafb" if done else "#fff")
bl = "#dc2626" if ov else ("#d1d5db" if done else "#1d4ed8")
pri = t.get("priority","medium")
pc = {"high":"#dc2626","medium":"#d97706","low":"#15803d"}.get(pri,"#6b7280")
rows += f"""
#{i}
{t['text']}
{f'
📅 {due}{" ⚠️ OVERDUE" if ov else ""}
' if due else ''}
{pri.upper()}
"""
return rows + "Use task # to toggle/delete
"
# ── EVENTS ───────────────────────────────────────────────────────
def load_events():
try:
if os.path.exists(EVENTS_FILE):
with open(EVENTS_FILE) as f: return json.load(f)
except: pass
return []
def save_events(e):
with open(EVENTS_FILE, "w") as f: json.dump(e, f, indent=2)
def events_html():
evs = load_events(); today = datetime.date.today().isoformat()
up = sorted([e for e in evs if e.get("date","") >= today], key=lambda x: x["date"])
past = sorted([e for e in evs if e.get("date","") < today], key=lambda x: x["date"], reverse=True)[:3]
if not up and not past:
return "No events yet.
"
def row(e, old=False):
try: day=datetime.datetime.strptime(e["date"],"%Y-%m-%d").strftime("%d"); mon=datetime.datetime.strptime(e["date"],"%Y-%m-%d").strftime("%b %Y")
except: day=e.get("date",""); mon=""
return f"""
{e['title']}
{f'
🕐 {e["time"]}
' if e.get("time") else ''}
{f'
{e["note"]}
' if e.get("note") else ''}
"""
html = ""
if up:
html += "📅 Upcoming
"
html += "".join(row(e) for e in up[:10])
if past:
html += "Past
"
html += "".join(row(e, True) for e in past)
return html
# ── DASHBOARD ────────────────────────────────────────────────────
def dashboard_html():
tasks = load_tasks(); today = datetime.date.today().isoformat()
today_s = datetime.date.today().strftime("%A, %B %d, %Y")
hr = datetime.datetime.now().hour
greet = "Good morning" if hr < 12 else "Good afternoon" if hr < 17 else "Good evening"
pending = [t for t in tasks if not t.get("done")]
overdue = [t for t in pending if t.get("due","") and t["due"] < today]
hi = [t for t in pending if t.get("priority") == "high"]
evs = load_events()
up = sorted([e for e in evs if e.get("date","") >= today], key=lambda x: x["date"])[:5]
docs = all_meta(); recent = docs[:6]
def stat(n, lbl, bg, tc, bc):
return f""""""
stats = f"""
{stat(len(docs),"Indexed Docs","#eff6ff","#1d4ed8","#bfdbfe")}
{stat(len(pending),"Pending Tasks","#fffbeb","#d97706","#fde68a")}
{stat(len(overdue),"Overdue","#fef2f2" if overdue else "#f0fdf4","#dc2626" if overdue else "#15803d","#fecaca" if overdue else "#bbf7d0")}
{stat(len(hi),"High Priority","#fef2f2" if hi else "#f0fdf4","#dc2626" if hi else "#15803d","#fecaca" if hi else "#bbf7d0")}
{stat(len(up),"Upcoming Events","#f5f3ff","#7c3aed","#ddd6fe")}
"""
def card(title, rows_html, empty_msg):
return f"""
{title}
{rows_html or f'
{empty_msg}
'}
"""
def drow(icon, text, meta):
return f"""
{icon}{text}
{meta}
"""
task_rows = "".join(drow("⬜", t["text"][:45], t.get("due","")) for t in pending[:5])
ev_rows = "".join(drow("📅", e["title"][:45], e["date"]) for e in up)
doc_rows = "".join(drow(ICONS.get("."+d.get("ftype","").lower(),"📄"), d["filename"][:45], d.get("date","")) for d in recent)
return f"""
{greet}, Manager
{today_s}
{stats}
{card("📋 Active Tasks", task_rows, "All tasks complete! 🎉")}
{card("🗓️ Upcoming Events", ev_rows, "No upcoming events")}
{card("📁 Recent Documents", doc_rows, "No documents indexed yet")}
"""
# ── CHAT ─────────────────────────────────────────────────────────
def do_chat(message, history, focus):
if not message.strip(): return history, ""
ctx = []
if focus and focus not in ("", "— All Documents —"):
t = get_text(focus)
if t: ctx.append(f"[{focus}]\n{t[:3000]}")
else:
chunks = load_all()
kw = keyword_search(message, chunks)
for fn, v in sorted(kw.items(), key=lambda x:-x[1]["kw"])[:5]:
t = get_text(fn)
if t: ctx.append(f"[{fn}]\n{t[:800]}")
context = "\n\n---\n\n".join(ctx) if ctx else "No documents indexed yet."
try:
ans = do_chat_llm(message, context, [(h[0],h[1]) for h in history[-8:]])
except Exception as e:
ans = f"❌ {e}"
return history + [[message, ans]], ""
def do_analyze(filename):
if not filename: return [["","⚠️ Select a document first."]], []
text = get_text(filename)
if not text: return [[f'❌',f"'{filename}' not in index."]], []
prompt = f"""Analyze this document as an executive assistant.
# {filename}
## Executive Summary
## Key People
## Important Dates
## Financial Data
## Decisions & Action Items
## Risks & Flags
Document:\n{text[:4000]}"""
try:
return [[f"📊 {filename}", do_generate(prompt)]], []
except Exception as e:
return [[f"📊 {filename}", f"❌ {e}"]], []
# ── EMAIL ────────────────────────────────────────────────────────
def do_email(instructions, doc, tone):
if not instructions.strip(): return "⚠️ Describe the email first."
ctx = ""
if doc and doc not in ("", "— None —"):
t = get_text(doc)
if t: ctx = f"\n\nDocument context ({doc}):\n{t[:2000]}"
tones = {"Formal & Executive":"formal, authoritative",
"Professional & Warm":"professional, warm",
"Concise & Direct":"very concise, direct",
"Diplomatic":"diplomatic, nuanced"}
prompt = f"""Write a complete professional business email.
Tone: {tones.get(tone,"formal")}
Instructions: {instructions}{ctx}
Format:
Subject: [subject]
Dear [Recipient],
[body]
Best regards,
[Manager Name]"""
try: return do_generate(prompt)
except Exception as e: return f"❌ {e}"
# ── TASK HANDLERS ────────────────────────────────────────────────
def add_task(txt, due, pri, note):
if not txt.strip(): return tasks_html(), "⚠️ Enter task text", "", "", "medium", ""
t = load_tasks()
t.append({"text":txt.strip(),"due":due.strip(),"priority":pri,"note":note,
"done":False,"created":datetime.date.today().isoformat()})
save_tasks(t); return tasks_html(), "", "", "", "medium", ""
def toggle_task(idx):
t = load_tasks()
try:
i = int(idx.strip())
if 0 <= i < len(t): t[i]["done"] = not t[i]["done"]
save_tasks(t)
except: pass
return tasks_html(), ""
def delete_task(idx):
t = load_tasks()
try:
i = int(idx.strip())
if 0 <= i < len(t): t.pop(i)
save_tasks(t)
except: pass
return tasks_html(), ""
# ── EVENT HANDLERS ───────────────────────────────────────────────
def add_event(title, date, time, note):
if not title.strip() or not date.strip():
return events_html(), "⚠️ Title and date required", "", "", "", ""
e = load_events()
e.append({"title":title.strip(),"date":date.strip(),"time":time.strip(),"note":note.strip()})
save_events(e); return events_html(), "", "", "", "", ""
def delete_event(idx):
e = load_events()
try:
i = int(idx.strip())
if 0 <= i < len(e): e.pop(i)
save_events(e)
except: pass
return events_html(), ""
# ── INDEX HANDLERS ───────────────────────────────────────────────
def do_upload(files, progress=gr.Progress()):
if not files: return "⚠️ No files selected.", lib_stats()
results = []
for i, f in enumerate(files):
progress(i / len(files), desc=f"Indexing {Path(f.name).name}")
good, msg = index_file(f.name)
results.append(f"{'✅' if good else '⚠️'} {Path(f.name).name} — {msg}")
return "\n".join(results), lib_stats()
def do_clear():
shutil.rmtree(INDEX_DIR, ignore_errors=True)
os.makedirs(INDEX_DIR, exist_ok=True)
return "🗑️ Index cleared.", lib_stats()
def do_load(fname):
if not fname: return "*Select a file.*", ""
text = get_text(fname)
if not text: return f"❌ '{fname}' not found.", ""
for ff in os.listdir(INDEX_DIR):
if not ff.endswith(".pkl"): continue
try:
with open(f"{INDEX_DIR}/{ff}", "rb") as f: data = pickle.load(f)
if data["meta"]["filename"] == fname:
m = data["meta"]
return f"**{fname}** · {m.get('words',0):,} words · {m.get('mb',0)} MB · {m.get('date','')}", text
except: pass
return f"**{fname}**", text
# ── CSS ──────────────────────────────────────────────────────────
CSS = """
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700;800&display=swap');
body, .gradio-container{background:#f0f4f8!important;font-family:'Inter',sans-serif!important;color:#111827!important}
.gradio-container{max-width:100%!important;padding:0!important}
textarea,input[type=text]{background:#fff!important;border:1.5px solid #d1d5db!important;border-radius:8px!important;color:#111827!important;font-family:'Inter',sans-serif!important;font-size:.86rem!important}
textarea:focus,input:focus{border-color:#1d4ed8!important;outline:none!important;box-shadow:0 0 0 3px rgba(29,78,216,.1)!important}
.gr-button{font-family:'Inter',sans-serif!important;font-weight:600!important;border-radius:8px!important;font-size:.83rem!important}
.gr-button.primary{background:#1d4ed8!important;color:#fff!important;border:none!important}
.gr-button.primary:hover{background:#1e40af!important}
.gr-button.secondary{background:#fff!important;color:#374151!important;border:1.5px solid #d1d5db!important}
::-webkit-scrollbar{width:5px;height:5px}
::-webkit-scrollbar-thumb{background:#d1d5db;border-radius:3px}
"""
# ── UI ───────────────────────────────────────────────────────────
_ok = True
_badge = ai_status()
with gr.Blocks(title="Manager Intelligence Agent", css=CSS) as demo:
HIST = gr.State([])
gr.HTML(f"""
🧠
Manager Intelligence Agent
Executive OS · Free AI · Hugging Face Spaces
🦙 Llama-3-8B
PDF · DOCX · XLSX · CSV · PPTX
{_badge}
""")
with gr.Tabs():
with gr.Tab("🏠 Dashboard"):
dash = gr.HTML(dashboard_html())
gr.Button("🔄 Refresh", variant="secondary").click(dashboard_html, outputs=[dash])
gr.HTML("""
Getting started: Go to Documents → upload files → click Index.
Then use Search or Chat to work with your documents.
""")
with gr.Tab("🔍 Search"):
with gr.Row():
s_q = gr.Textbox(label="Search", placeholder='"Ahmed Al-Rashidi 2023" · "Q3 budget" · "contract renewal"', lines=1, scale=5)
s_btn = gr.Button("🔍 Search", variant="primary", scale=1)
s_sum = gr.Markdown("*Enter a query and click Search.*")
s_html = gr.HTML("")
s_dd = gr.Dropdown(label="📂 Select a file to preview", choices=[], value=None)
def do_search_all(q):
html, choices, dd = run_search(q)
return html, f"🔑 Found **{len(choices)}** results for: *{q}*" if choices else "*No results.*", dd
s_btn.click(do_search_all, inputs=[s_q], outputs=[s_html, s_sum, s_dd])
s_q.submit(do_search_all, inputs=[s_q], outputs=[s_html, s_sum, s_dd])
with gr.Tab("💬 Chat & Intelligence"):
with gr.Row():
with gr.Column(scale=1, min_width=260):
c_focus = gr.Dropdown(label="Focus on file (optional)",
choices=["— All Documents —"] + all_names(), value="— All Documents —")
gr.Button("🔄 Refresh Files", variant="secondary").click(
lambda: gr.Dropdown(choices=["— All Documents —"] + all_names()), outputs=[c_focus])
gr.HTML("""
Try asking:
• Find all records for Ahmed Hassan
• Summarize the Q3 financial report
• List all salary changes 2020–2024
• Who approved the merger?
• What contracts expire this year?
""")
gr.HTML("⚡ Document Analysis
")
a_file = gr.Dropdown(label="Select document", choices=all_names())
gr.Button("🔄", variant="secondary").click(lambda: gr.Dropdown(choices=all_names()), outputs=[a_file])
a_btn = gr.Button("📊 Full Analysis", variant="primary")
with gr.Column(scale=3):
chatbot = gr.Chatbot(label="", height=460, show_label=False)
with gr.Row():
c_in = gr.Textbox(label="", show_label=False, placeholder="Ask anything about your documents...", lines=2, scale=5)
with gr.Column(scale=1, min_width=90):
c_send = gr.Button("Send ↑", variant="primary")
c_clear = gr.Button("Clear", variant="secondary")
def chat_fn(msg, hist, focus):
new_hist, _ = do_chat(msg, hist, focus)
return new_hist, "", new_hist
c_send.click(chat_fn, inputs=[c_in, HIST, c_focus], outputs=[HIST, c_in, chatbot])
c_in.submit(chat_fn, inputs=[c_in, HIST, c_focus], outputs=[HIST, c_in, chatbot])
c_clear.click(lambda: ([], []), outputs=[HIST, chatbot])
a_btn.click(do_analyze, inputs=[a_file], outputs=[chatbot, HIST])
with gr.Tab("✉️ Email Drafts"):
with gr.Row():
with gr.Column(scale=1):
e_tone = gr.Dropdown(label="Tone",
choices=["Formal & Executive","Professional & Warm","Concise & Direct","Diplomatic"],
value="Formal & Executive")
e_doc = gr.Dropdown(label="Reference document (optional)",
choices=["— None —"] + all_names(), value="— None —")
gr.Button("🔄 Refresh", variant="secondary").click(
lambda: gr.Dropdown(choices=["— None —"] + all_names()), outputs=[e_doc])
with gr.Column(scale=2):
e_inst = gr.Textbox(label="Email instructions", placeholder="e.g. Write email to HR requesting 2 new engineers...", lines=5)
e_btn = gr.Button("✉️ Draft Email", variant="primary")
e_out = gr.Textbox(label="Email Draft — copy and send", lines=20, max_lines=35)
e_btn.click(do_email, inputs=[e_inst, e_doc, e_tone], outputs=[e_out])
with gr.Tab("📋 Tasks & Calendar"):
with gr.Row():
with gr.Column(scale=1):
gr.HTML("📋 Task Manager
")
with gr.Row():
t_txt = gr.Textbox(label="Task", placeholder="What needs to be done?", scale=3)
t_due = gr.Textbox(label="Due (YYYY-MM-DD)", placeholder="2025-12-31", scale=2)
with gr.Row():
t_pri = gr.Dropdown(label="Priority", choices=["high","medium","low"], value="medium", scale=1)
t_note = gr.Textbox(label="Note", scale=2)
with gr.Row():
t_add = gr.Button("➕ Add Task", variant="primary")
t_msg = gr.Markdown("")
t_disp = gr.HTML(tasks_html())
with gr.Row():
t_idx = gr.Textbox(label="Task #", placeholder="0", scale=1)
gr.Button("✅ Toggle", variant="secondary", scale=1).click(toggle_task, inputs=[t_idx], outputs=[t_disp, t_msg])
gr.Button("🗑️ Delete", variant="secondary", scale=1).click(delete_task, inputs=[t_idx], outputs=[t_disp, t_msg])
with gr.Column(scale=1):
gr.HTML("🗓️ Calendar & Events
")
with gr.Row():
ev_t = gr.Textbox(label="Event title", scale=3)
ev_d = gr.Textbox(label="Date (YYYY-MM-DD)", scale=2)
with gr.Row():
ev_time = gr.Textbox(label="Time", placeholder="14:00", scale=1)
ev_note = gr.Textbox(label="Note", scale=2)
with gr.Row():
ev_add = gr.Button("📅 Add Event", variant="primary")
ev_msg = gr.Markdown("")
ev_disp = gr.HTML(events_html())
with gr.Row():
ev_idx = gr.Textbox(label="Event # to delete", placeholder="0", scale=1)
gr.Button("🗑️ Delete", variant="secondary", scale=2).click(delete_event, inputs=[ev_idx], outputs=[ev_disp, ev_msg])
t_add.click(add_task, inputs=[t_txt, t_due, t_pri, t_note], outputs=[t_disp, t_msg, t_txt, t_due, t_pri, t_note])
ev_add.click(add_event, inputs=[ev_t, ev_d, ev_time, ev_note], outputs=[ev_disp, ev_msg, ev_t, ev_d, ev_time, ev_note])
with gr.Tab("📁 Documents"):
with gr.Tabs():
with gr.Tab("⬆️ Upload & Index"):
gr.HTML("""
Upload your files. Supported: PDF, DOCX, XLSX, CSV, PPTX, TXT, EML.
⚠️ HF free tier = storage resets on restart. Re-upload files after restart.
""")
with gr.Row():
with gr.Column(scale=1):
f_up = gr.File(label="Select files", file_count="multiple",
file_types=[".pdf",".docx",".doc",".xlsx",".xls",".csv",".txt",".pptx",".ppt",".eml",".rtf"])
f_upbtn = gr.Button("⚡ Index Uploaded Files", variant="primary")
f_clr = gr.Button("🗑️ Clear Index", variant="secondary")
with gr.Column(scale=1):
f_log = gr.Markdown("*Upload files then click Index.*")
f_stats = gr.Markdown(lib_stats())
f_upbtn.click(do_upload, inputs=[f_up], outputs=[f_log, f_stats])
f_clr.click(do_clear, outputs=[f_log, f_stats])
with gr.Tab("📄 Preview"):
with gr.Row():
p_sel = gr.Dropdown(label="Select document", choices=all_names(), scale=4)
p_load = gr.Button("📄 Load", variant="primary", scale=1)
gr.Button("🔄", variant="secondary", scale=1).click(lambda: gr.Dropdown(choices=all_names()), outputs=[p_sel])
p_info = gr.Markdown("*Select a file and click Load.*")
p_text = gr.Textbox(label="Document content", lines=28, max_lines=60)
p_load.click(do_load, inputs=[p_sel], outputs=[p_info, p_text])
with gr.Tab("⚙️ Setup"):
gr.Markdown(f"""
## Configuration
**AI Backend:** HF Inference API · `{HF_MODEL}` · **100% Free**
### Optional: Add HF Token (removes rate limits)
1. [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens) → New token → Role: **Read**
2. Space → **Settings → Secrets** → add `HF_TOKEN`
3. Restart Space
**Current status:** {_badge}
### Supported Files
| Type | Extensions |
|------|-----------|
| Documents | .pdf .docx .doc .rtf |
| Spreadsheets | .xlsx .xls .csv |
| Presentations | .pptx .ppt |
| Text / Email | .txt .eml |
### Storage Note
Free tier = ephemeral. Files reset on restart. Re-upload or connect HF Dataset for persistence.
""")
gr.HTML("""
Manager Intelligence Agent · Free AI · Llama-3-8B · Hugging Face Spaces
""")
if __name__ == "__main__":
print(f"\n{'='*50}\n Manager Intelligence Agent\n AI: {ai_status()}\n{'='*50}\n")
demo.launch(server_name="0.0.0.0", server_port=7860, ssr_mode=False)