Update app.py

app.py

@@ -1,24 +1,9 @@
-# HF Spaces / Gradio app: Vochi CRM call logs + AI analysis
-# ─────────────────────────────────────────────────────────────────────────────
-# How to deploy (short):
-# 1) Create a new Space (Python + Gradio).
-# 2) Add a file named `app.py` with THIS code.
-# 3) Add a file named `requirements.txt` with the lines below.
-# 4) In the Space → Settings → Repository secrets, add:
-#    - VOCHI_BASE_URL (e.g. https://crm.vochi.by/api)
-#    - VOCHI_CLIENT_ID (client id string)
-#    - GOOGLE_API_KEY  (API key)
-#    - VOCHI_UI_PASSWORD (password to unlock the UI)
-
-#
-# UI language: English.
-
 from __future__ import annotations
 import os
 import json
 import datetime as _dt
 from typing import List, Tuple, Optional
-import time  # ← ДАДАНА
+import time
 
 import requests
 import pandas as pd
@@ -181,12 +166,85 @@ def _system_instruction(lang_code: str) -> str:
         return "Reply in English."
     return "Reply in the caller's language; if unclear, use concise professional English."
 
-# ← ДАДАНА: невялікі хелпер для выбару прампту
+
 def _prepare_prompt(template_key: str, custom_prompt: str) -> str:
     if template_key == "custom":
         return (custom_prompt or "").strip() or PROMPT_TEMPLATES["simple"]
     return PROMPT_TEMPLATES.get(template_key, PROMPT_TEMPLATES["simple"])
 
+
+def _today_str():
+    return _dt.date.today().strftime("%Y-%m-%d")
+
+# Time helpers (HH:MM → seconds since midnight)
+_DEF_T_FROM = "00:00"
+_DEF_T_TO   = "23:59"
+
+
+def _parse_hhmm(s: Optional[str]) -> Optional[int]:
+    s = (s or "").strip()
+    if not s:
+        return None
+    try:
+        hh, mm = s.split(":", 1)
+        hh = int(hh)
+        mm = int(mm)
+        if not (0 <= hh <= 23 and 0 <= mm <= 59):
+            return None
+        return hh * 3600 + mm * 60
+    except Exception:
+        return None
+
+
+def _infer_calltype_col(df: pd.DataFrame) -> Optional[str]:
+    for c in df.columns:
+        low = str(c).lower()
+        if low in {"calltype", "call_type", "type"}:
+            return c
+    return None
+
+
+def _normalize_start_to_time(df: pd.DataFrame) -> pd.DataFrame:
+    if "Start" not in df.columns:
+        return df
+    out = df.copy()
+    try:
+        out["_Start_dt"] = pd.to_datetime(out["Start"], errors="coerce")
+        out["_Start_time_sec"] = out["_Start_dt"].dt.hour.fillna(0).astype(int) * 3600 + \
+                                   out["_Start_dt"].dt.minute.fillna(0).astype(int) * 60 + \
+                                   out["_Start_dt"].dt.second.fillna(0).astype(int)
+    except Exception:
+        out["_Start_time_sec"] = np.nan
+    return out
+
+
+def _filter_calls(df: pd.DataFrame, t_from: Optional[str], t_to: Optional[str], calltype: Optional[str]) -> pd.DataFrame:
+    if df is None or df.empty:
+        return df
+
+    tf = _parse_hhmm(t_from) or _parse_hhmm(_DEF_T_FROM) or 0
+    tt = _parse_hhmm(t_to) or _parse_hhmm(_DEF_T_TO) or (24*3600-1)
+    if tt < tf:
+        # Swap if user inverted
+        tf, tt = tt, tf
+
+    work = _normalize_start_to_time(df)
+    mask_time = (work["_Start_time_sec"].fillna(-1).astype(int) >= tf) & (work["_Start_time_sec"].fillna(-1).astype(int) <= tt)
+
+    mask = mask_time
+
+    ct = (calltype or "").strip()
+    if ct:
+        col = _infer_calltype_col(work)
+        if col:
+            # exact match (case-insensitive)
+            mask = mask & (work[col].astype(str).str.lower() == ct.lower())
+        else:
+            # if there is no calltype column, keep only time filter
+            pass
+
+    return work.loc[mask].drop(columns=[c for c in ["_Start_dt", "_Start_time_sec"] if c in work.columns])
+
 # ─────────────────────────────────────────────────────────────────────────────
 # Gradio handlers
 # ─────────────────────────────────────────────────────────────────────────────
@@ -290,9 +348,7 @@ def ui_analyze(selected_idx: Optional[int], df: pd.DataFrame,
 
     # Call model
     try:
-        merged = f"""[SYSTEM INSTRUCTION: {sys_inst}]
-
-{prompt}"""
+        merged = f"""[SYSTEM INSTRUCTION: {sys_inst}]\n\n{prompt}"""
         resp = client.models.generate_content(model=model_name, contents=[uploaded_file, merged])
         text = getattr(resp, "text", None)
         if not text:
@@ -315,21 +371,27 @@ def ui_analyze(selected_idx: Optional[int], df: pd.DataFrame,
         except Exception:
             pass
 
-# ← ДАДАНА: Пакетны аналіз званкоў за дзень/час
+# ────────────────────────────────────��────────────────────────────────────────
+# NEW: Batch analysis with time interval + calltype filter
+# ─────────────────────────────────────────────────────────────────────────────
+
 def ui_analyze_calls_by_date(
     authed: bool,
     date_str: str,
+    t_from: str,
+    t_to: str,
+    calltype: str,
     template_key: str,
     custom_prompt: str,
     lang_code: str,
     model_pref: str,
 ):
     """
-    Fetch calls for the given date and analyze them one-by-one with the same
-    settings/fields as the single-call AI Analysis tab. Save a .txt file and
-    show results on screen.
+    Fetch calls for the given date, filter them by time window and calltype,
+    and analyze one-by-one with the same settings as the single-call tab.
+    Save a .txt file and show results on screen. Also show how many calls matched the filter.
     """
-    # Гейт па паролі
+    # Password gate
     if not authed:
         return (
             "🔒 Увядзіце пароль, каб запусціць аналіз.",  # results_md
@@ -338,11 +400,12 @@ def ui_analyze_calls_by_date(
             gr.update(visible=True),                       # show pwd group
         )
 
-    date_str = (date_str or "").strip()
-    if not date_str:
-        date_str = _today_str()
+    date_str = (date_str or "").strip() or _today_str()
+    t_from = (t_from or _DEF_T_FROM).strip()
+    t_to   = (t_to or _DEF_T_TO).strip()
+    calltype = (calltype or "").strip()
 
-    # 1) Атрымаць спіс званкоў за дату
+    # 1) Fetch list for the date
     try:
         calls = fetch_calllogs(date_str)
         df = pd.DataFrame(calls)
@@ -352,7 +415,15 @@ def ui_analyze_calls_by_date(
     if df.empty:
         return ("За гэты дзень званкоў не знойдзена.", None, "", gr.update())
 
-    # 2) Падрыхтоўка кліента мадэлі і прампту
+    # 2) Filter by time + calltype
+    df_f = _filter_calls(df, t_from, t_to, calltype)
+    total = len(df_f)
+
+    if total == 0:
+        info = f"Па фільтру ({t_from}–{t_to}{' | ' + calltype if calltype else ''}) — 0 званкоў."
+        return (info, None, info, gr.update())
+
+    # 3) Prepare model
     if not _HAS_GENAI:
         return ("❌ google-genai library not found.", None, "", gr.update())
 
@@ -369,16 +440,18 @@ def ui_analyze_calls_by_date(
     sys_inst = _system_instruction(lang_code)
     prompt = _prepare_prompt(template_key, custom_prompt)
 
-    # 3) Пакетны праход: па адным выкліку
-    results_blocks: List[str] = []
+    # 4) Iterate filtered calls
+    results_blocks: List[str] = [
+        f"## Вынікі\nДата: {date_str}\n\nФільтр: {t_from}–{t_to}{' | calltype=' + calltype if calltype else ''}\n\nЗнойдзена званкоў: {total}\n\n---"
+    ]
     analyzed = 0
 
-    for i, row in df.iterrows():
+    for i, row in df_f.reset_index(drop=True).iterrows():
         unique_id = str(row.get("UniqueId", ""))
         if not unique_id:
             continue
 
-        # Скачваем/кэшынгуем mp3
+        # Download/cache mp3
         try:
             mp3_path = f"/tmp/call_{unique_id}.mp3"
             if not os.path.exists(mp3_path) or os.path.getsize(mp3_path) == 0:
@@ -414,7 +487,7 @@ def ui_analyze_calls_by_date(
             except Exception:
                 pass
 
-        # Сфармаваць блок выніку для гэтага званка
+        # Result block
         block = (
             f"### Call {i+1}\n"
             f"- UniqueId: {unique_id}\n"
@@ -429,15 +502,16 @@ def ui_analyze_calls_by_date(
         analyzed += 1
 
     if analyzed == 0:
-        return ("Не атрымалася прааналізаваць ніводнага званка.", None, "", gr.update())
+        info = "Не атрымалася прааналізаваць ніводнага званка."
+        return (info, None, info, gr.update())
 
-    # 4) Захаваць у .txt і вярнуць
+    # 5) Save to .txt and return
     results_text = "\n\n".join(results_blocks)
-    fname = f"/tmp/batch_analysis_{date_str}_{int(time.time())}.txt"
+    fname = f"/tmp/batch_analysis_{date_str}_{t_from.replace(':','')}-{t_to.replace(':','')}_{int(time.time())}.txt"
     with open(fname, "w", encoding="utf-8") as f:
         f.write(results_text)
 
-    status = f"Гатова ✅. Прааналізавана званкоў: {analyzed}."
+    status = f"Гатова ✅. Па фільтру — {total} званкоў. Прааналізавана: {analyzed}."
     return (results_text, fname, status, gr.update(visible=False))
 
 # ───────────────────────────────────────────────────────��─────────────────────
@@ -478,9 +552,6 @@ def ui_fetch_or_auth(date_str: str, authed: bool):
 # Build Gradio UI
 # ─────────────────────────────────────────────────────────────────────────────
 
-def _today_str():
-    return _dt.date.today().strftime("%Y-%m-%d")
-
 with gr.Blocks(title="Vochi CRM Call Logs (Gradio)") as demo:
     gr.Markdown(
         """
@@ -522,10 +593,15 @@ with gr.Blocks(title="Vochi CRM Call Logs (Gradio)") as demo:
             analyze_btn = gr.Button("🧠 Analyze", variant="primary")
             analysis_md = gr.Markdown()
 
-        # ← ДАДАНА: новая ўкладка пакетнага аналізу
+        # NEW: пакетны аналіз з фільтрамі па часе і calltype
         with gr.Tab("Аналіз званкоў за дзень/час"):
             batch_date_inp = gr.Textbox(label="Date", value=_today_str(), scale=1)
 
+            with gr.Row():
+                t_from_inp = gr.Textbox(label="Time from (HH:MM)", value=_DEF_T_FROM)
+                t_to_inp   = gr.Textbox(label="Time to (HH:MM)",   value=_DEF_T_TO)
+                calltype_inp = gr.Textbox(label="calltype (exact)", placeholder="e.g. inbound / outbound")
+
             with gr.Row():
                 tpl_batch_dd = gr.Dropdown(choices=TPL_OPTIONS, value="simple", label="Template")
                 lang_batch_dd = gr.Dropdown(choices=LANG_OPTIONS, value="default", label="Language")
@@ -563,11 +639,11 @@ with gr.Blocks(title="Vochi CRM Call Logs (Gradio)") as demo:
         outputs=[analysis_md],
     )
 
-    # ← ДАДАНА: падзеі для новай укладкі
+    # NEW: events for the new batch tab with filters
     tpl_batch_dd.change(ui_toggle_custom_prompt, inputs=[tpl_batch_dd], outputs=[custom_batch_tb])
     batch_btn.click(
         ui_analyze_calls_by_date,
-        inputs=[authed, batch_date_inp, tpl_batch_dd, custom_batch_tb, lang_batch_dd, model_batch_dd],
+        inputs=[authed, batch_date_inp, t_from_inp, t_to_inp, calltype_inp, tpl_batch_dd, custom_batch_tb, lang_batch_dd, model_batch_dd],
         outputs=[batch_results_md, batch_file_out, batch_status_md, pwd_group],
     )