18082025

imdb_parsen/imdb_top_250_movies.csv

@@ -0,0 +1 @@
+

imdb_parsen/main.py

@@ -0,0 +1,23 @@
+# print(the_matrix.get('tech'))
+from imdb import Cinemagoer
+
+# create an instance of the Cinemagoer class
+ia = Cinemagoer()
+
+# get a movie
+movie = ia.get_movie('0133093')
+
+# print the names of the directors of the movie
+print('Directors:')
+for director in movie['directors']:
+    print(director['name'])
+
+# print the genres of the movie
+print('Genres:')
+for genre in movie['genres']:
+    print(genre)
+
+# search for a person name
+people = ia.search_person('Mel Gibson')
+for person in people:
+    print(person.personID, person['name'])

imdb_parsen/test.py

@@ -0,0 +1,48 @@
+from bs4 import BeautifulSoup
+import requests
+import re
+import pandas as pd
+
+
+# Downloading imdb top 250 movie's data
+url = 'http://www.imdb.com/chart/top'
+response = requests.get(url)
+soup = BeautifulSoup(response.text, "html.parser")
+movies = soup.select('td.titleColumn')
+crew = [a.attrs.get('title') for a in soup.select('td.titleColumn a')]
+ratings = [b.attrs.get('data-value')
+           for b in soup.select('td.posterColumn span[name=ir]')]
+
+
+# create a empty list for storing
+# movie information
+list = []
+
+# Iterating over movies to extract
+# each movie's details
+for index in range(0, len(movies)):
+
+    # Separating movie into: 'place',
+    # 'title', 'year'
+    movie_string = movies[index].get_text()
+    movie = (' '.join(movie_string.split()).replace('.', ''))
+    movie_title = movie[len(str(index))+1:-7]
+    # year = re.search('\((.*?)\)', movie_string).group(1)
+    place = movie[:len(str(index))-(len(movie))]
+    data = {"place": place,
+            "movie_title": movie_title,
+            "rating": ratings[index],
+            # "year": year,
+            "star_cast": crew[index],
+            }
+    list.append(data)
+
+# printing movie details with its rating.
+for movie in list:
+    print(movie['place'], '-', movie['movie_title'],
+          'Starring:', movie['star_cast'], movie['rating'])
+
+
+## .......##
+df = pd.DataFrame(list)
+df.to_csv('imdb_top_250_movies.csv', index=False)

movie-db/main.py

@@ -19,6 +19,7 @@ def add_movie():
         data=moviedb_func.all_select(),
         data_medium=moviedb_func.all_select(what_select="medium"),
         data_regie=moviedb_func.all_select(what_select="regie"),
+        data_all=moviedb_func.show_movie_list()
     )
 
 

movie-db/moviedb_func.py

@@ -158,9 +158,9 @@ def show_movie_list(db_name="movie_db.db"):
     db = sqlite3.connect(db_name)
     SELCET_VALUE = pd.read_sql(SQL_PARAM, db)
     return_list_dict = []
-    for id, titel, genre, regie_surname, regie_lastname in zip(SELCET_VALUE["id"], SELCET_VALUE["titel"], SELCET_VALUE["genre"], SELCET_VALUE["regie_surname"], SELCET_VALUE["regie_lastname"]):
+    for id, titel, genre, regie_surname, regie_lastname, medium in zip(SELCET_VALUE["id"], SELCET_VALUE["titel"], SELCET_VALUE["genre"], SELCET_VALUE["regie_surname"], SELCET_VALUE["regie_lastname"], SELCET_VALUE["medium"]):
         return_list_dict.append(
-            {"id": id, "titel": titel, "genre": genre, "regie": regie_surname + " " + regie_lastname})
+            {"id": id, "titel": titel, "genre": genre, "regie": regie_surname + " " + regie_lastname, "medium": medium})
     return return_list_dict
 
 
@@ -171,4 +171,5 @@ if __name__ == "__main__":
     #    search_name="DVD", select_from="medium", select_where="medium")
     add_movie_to_list(movie_name="Schlumpfland",
                       genre_id=1, regie_id=1, medium_id=1)
-    print(show_movie_list())
+    for test in show_movie_list():
+        print(test.get("id"), test.get("medium"))

movie-db/templates/add_movie.html

@@ -25,7 +25,26 @@
     </select>
       &nbsp;
     <button type="submit"> Eingabe </button> 
-
-
   </form>
+  <br>
+
+ <table border="1" width="50%">
+      <tr>
+        <th>Id</th>
+        <th>Name</th>
+        <th>Genre</th>
+        <th>Regie</th>
+        <th>Medium</th>
+      </tr>
+      {% for list_all in data_all %}
+        <tr>
+          <td>{{list_all.get("id")}}</td>
+          <td>{{list_all.get("titel")}}</td>
+          <td>{{list_all.get("genre")}}</td>
+          <td>{{list_all.get("regie")}}</td>
+          <td>{{list_all.get("medium")}}</td>
+        </tr>
+      {% endfor %}
+</table>
+
 {% endblock %}

ollama_remote_query/ollama_prompt.py

@@ -0,0 +1,37 @@
+#! /usr/bin/env python
+from ollama import Client
+import datetime
+import os
+
+output_folder = "output"
+
+if not os.path.exists(output_folder):
+    os.makedirs(output_folder)
+
+# Create_Timestamp
+now = int(datetime.datetime.now().timestamp())
+# res = int(now.timestamp())
+
+# PROMT
+prompt = input("Was möchtest du Fragen: ")
+
+client = Client(
+    host='http://localhost:11434',
+    headers={'x-some-header': 'some-value'}
+)
+
+response = client.chat(
+    model='gemma3n:e2b',
+    messages=[
+        {
+            'role': 'user',
+            'content': prompt,
+        }],
+    stream=True)
+
+for chunk in response:
+    print(chunk['message']["content"], end='', flush=True)
+    with open(str(output_folder + "/ollama_output_" + str(now) + ".md"), "a") as dm:
+        print(chunk['message']["content"], end='', flush=True, file=dm)
+
+# with open("test.md", "w") as dm:

ollama_remote_query/output/ollama_output_1755524506.md

@@ -0,0 +1,6 @@
+Okay, I'm exiting. Have a good one! 
+
+If you need anything in the future, feel free to ask. 😊
+
+
+

ollama_remote_query/translate_func.py

@@ -0,0 +1,38 @@
+# %% packages
+# from langchain_openai import ChatOpenAI
+import langchain_ollama
+from langchain_core.prompts import ChatPromptTemplate
+# from dotenv import load_dotenv
+from langchain_core.output_parsers import StrOutputParser
+# load_dotenv('.env')
+
+
+def translate_func(select_lang="Germany", target_lang="English", query_trans="prompt"):
+    if query_trans == "prompt":
+        query_trans = input("Was soll Übersetzt werden ? ")
+    # %% set up prompt template
+    prompt_template = ChatPromptTemplate.from_messages([
+        ("system", f"You are an AI assistant that translates {
+            select_lang} into another language."),
+        ("user", "Translate this sentence: '{input}' into {target_language}"),
+    ])
+
+    # %% model
+    model = langchain_ollama.llms.OllamaLLM(base_url='http://localhost:11434', model="gemma3n:e2b",
+                                            temperature=0)
+
+    # %% chain
+    chain = prompt_template | model | StrOutputParser()
+
+    # %% invoke chain
+    res = chain.invoke({"input": query_trans,
+                        "target_language": target_lang})
+    print(res)
+
+    # %%
+
+
+if __name__ == "__main__":
+    select_lang = "Germany"
+    target_lang = "English"
+    translate_func(select_lang=target_lang, target_lang=select_lang)