1

app.py

@@ -1,19 +1,18 @@
 import streamlit as st, pandas as pd, numpy as np
 
-st.set_page_config(layout="wide", page_title="Предсказание V", page_icon="🦋") # set_page_config() can only be called once per app page, and must be called as the first Streamlit command in your script.
+st.set_page_config(page_title="Предсказание V", page_icon="🦋", layout="wide") # set_page_config() can only be called once per app page, and must be called as the first Streamlit command in your script.
 
 import my_static_methods as my_stm
-st.markdown(my_stm.STYLE_CORRECTION, unsafe_allow_html=True)
+st.html(my_stm.STYLE_CORRECTION)
 
-st.sidebar.markdown("# Стартовая страница 💎")
+st.sidebar.markdown("💎 Стартовая страница")
 
 df = pd.DataFrame([
         {"command": "st.selectbox", "rating": 4, "is_widget": True},
         {"command": "st.balloons", "rating": 5, "is_widget": False},
         {"command": "st.time_input", "rating": 3, "is_widget": True},
 ])
-edited_df = st.data_editor(df, num_rows="dynamic")
 
+edited_df = st.sidebar.data_editor(df, num_rows="dynamic")
 favorite_command = edited_df.loc[edited_df["rating"].idxmax()]["command"]
-
-st.markdown(f"Your favorite command is **{favorite_command}** 🎚️")
+st.sidebar.markdown(f"Your favorite command is **{favorite_command}** 🎚️")

my_static_methods.py

@@ -1,9 +1,11 @@
+from typing import Union
 import os, io
-import pandas as pd, numpy as np
+import pandas as pd
+import numpy as np
 import plotly.express as px
-from typing import Union
 import huggingface_hub
 
+
 ### remove decoration and popup menu button at top
 STYLE_CORRECTION = " ".join([
     "<style>",
@@ -46,11 +48,12 @@ def df_process_v_column(df: pd.DataFrame) -> pd.DataFrame:
 
 
 ###
-def load_gaziev_from_hf(repo_Id: str, lstTestFiles: list[str]) -> {str, pd.DataFrame}:
+def load_dataframes_from_hf(repo_id: str, lstCsvFiles: list[str], hftoken: str) -> {str, pd.DataFrame}:
+    """ load dataframes from hf """
     #https://huggingface.co/datasets/f64k/gaziev/blob/main/TestData3_2204_noAB_gaziev.zip
     dict_res = {}
-    for fl_name in lstTestFiles:
-        file_loaded = huggingface_hub.hf_hub_download(repo_id=repo_Id, filename=fl_name, repo_type="dataset")
+    for fl_name in lstCsvFiles:
+        file_loaded = huggingface_hub.hf_hub_download(repo_id=repo_id, filename=fl_name, repo_type="dataset", token=hftoken)
         if os.path.exists(file_loaded):
             df_loaded = pd.read_csv(file_loaded, sep=";", encoding = "utf-8", compression="zip")
             dict_res[file_loaded] = df_process_v_column(df_loaded)
@@ -58,14 +61,16 @@ def load_gaziev_from_hf(repo_Id: str, lstTestFiles: list[str]) -> {str, pd.DataF
 
 ### список файлов (без уровня вложенности) в репо dataset
 ### https://huggingface.co/docs/huggingface_hub/en/guides/hf_file_system
-def list_files_hf(repo_Id: str) -> list[str]:
-    fs = huggingface_hub.HfFileSystem()
-    path_hf = f"datasets/{repo_Id}"
+def list_files_hf(repo_id: str, hftoken: str) -> list[str]:
+    """ List files in HF repo """
+    fs = huggingface_hub.HfFileSystem(token=hftoken)
+    path_hf = f"datasets/{repo_id}"
     lst = fs.ls(path_hf, detail=False)
     lst = [fname for fname in map(os.path.basename, lst) if fname[0] != "."]
     return lst
 
 def plotly_xyzv_scatter_gray(df3D):
+    """  """
     color_discrete_map = dict(o='rgb(220,220,220)', p='rgb(90,1,1)', n='rgb(1,1,90)')
     fig = px.scatter_3d(df3D, x='X', y='Y', z='Z', color="Vposneg", opacity=0.4, height=800, color_discrete_map=color_discrete_map)
     fig.update_scenes(xaxis={"gridcolor":"rgba(30, 0, 0, 0.2)","color":"rgb(100, 0, 0)","showbackground":False},

pages/4_Просмотр_CSV.py

@@ -12,7 +12,7 @@ st.html(my_stm.STYLE_CORRECTION)
 REPO_ID = "f64k/gaziev"
 st.sidebar.info("💽 сохраненные\n таблицы CSV")
 
-lstTestFiles = my_stm.list_files_hf(REPO_ID)
+lstTestFiles = my_stm.list_files_hf(REPO_ID, st.secrets["HF_WRITE"])
 #dictXYZV = my_stm.load_gaziev_from_hf(REPO_ID, lstTestFiles)
 
 cols = st.columns(2)
@@ -20,7 +20,7 @@ cols = st.columns(2)
 #key_xyz = st.selectbox("Выберите файл данных для просмотра таблицы и точек", dictXYZV.keys())
 one_file_selected = cols[0].selectbox("Выберите файл данных для просмотра таблицы и точек", lstTestFiles)
 if one_file_selected:
-    dict_ONE_XYZV = my_stm.load_gaziev_from_hf(REPO_ID, [one_file_selected])
+    dict_ONE_XYZV = my_stm.load_dataframes_from_hf(REPO_ID, [one_file_selected], st.secrets["HF_WRITE"])
     df_xyz = list(dict_ONE_XYZV.values())[0] #df_xyz = dictXYZV[key_xyz]
     fig = my_stm.plotly_xyzv_scatter_gray(df_xyz)
 

pages/8_Chat.py

@@ -1,10 +1,18 @@
+import os, re, sys, time, math, shutil, urllib, string, random, pickle, zipfile, datetime
 import streamlit as st, pandas as pd, numpy as np
 import my_static_methods as my_stm
+from faker import Faker
 st.markdown(my_stm.STYLE_CORRECTION, unsafe_allow_html=True)
 st.sidebar.markdown("# Переговоры 💬")
 
-# with st.sidebar:
+fake = Faker()
+fakeRU = Faker("ru_RU")
+
 messages = st.container() # height=300
 if prompt := st.chat_input("Спрашивайте тут : "):
     messages.chat_message("user").write(prompt)
-    messages.chat_message("boss").write(f">>> {prompt[::-1]}") # assistant
+    answer = prompt[::-1]
+    strEnFakeText = fake.paragraph(nb_sentences=4, variable_nb_sentences=False)
+    strRuFakeText = fakeRU.paragraph(nb_sentences=4, variable_nb_sentences=False)
+    answer = f"{datetime.datetime.now():%d.%m.%Y %H:%M:%S}\n {strEnFakeText}\n {strRuFakeText}"
+    messages.chat_message("boss").write(f"{answer}") # assistant

requirements.txt

@@ -4,4 +4,5 @@ datasets
 scikit-learn
 plotly
 pandas
-numpy
+numpy
+faker