dodanie

.env

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+SECRET_KEY=MOKO00koko
+PASSWORD_KEY=tZnq1IyFSKeBwaLa0Bx5Ge722GgrJztHHNv3jqXMswo=
+ADMIN_PASSWORD=admin
+MODEL_REPO_URL=https:/git.pathl.pl
+UPLOAD_LIMIT_MB=500
+DEBUG=True

.gitignore

@@ -1,2 +0,0 @@
-.venv/
-.idea/

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml
+# Ignored default folder with query files
+/queries/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
+# Editor-based HTTP Client requests
+/httpRequests/

.idea/Strona AI.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.13 (Strona AI)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/Project_Default.xml

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+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <list>
+          <option value="torch" />
+          <option value="numpy" />
+        </list>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.13 (Strona AI)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.13 (Strona AI)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/Strona AI.iml" filepath="$PROJECT_DIR$/.idea/Strona AI.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

README.md

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+#Pathl.Ai cześc projektu Cafe
+
+Ceo: Maro

app.py

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+from flask import Flask, request, render_template, jsonify, send_from_directory
+import os, json, importlib.util
+from werkzeug.utils import secure_filename
+import markdown
+app = Flask(__name__)
+UPLOAD_FOLDER = "models"
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+ADMIN_KEY = "supersecretadminkey"
+
+MODELS = {}
+
+def load_models():
+    for folder in os.listdir(UPLOAD_FOLDER):
+        path = os.path.join(UPLOAD_FOLDER, folder)
+        if not os.path.isdir(path):
+            continue
+        meta_path = os.path.join(path, "meta.json")
+        if not os.path.exists(meta_path):
+            continue
+        with open(meta_path) as f:
+            meta = json.load(f)
+        func_name = meta.get("function_name")
+        if not func_name:
+            continue
+
+        py_file = os.path.join(path, "model.py")
+        spec = importlib.util.spec_from_file_location("model_module", py_file)
+        module = importlib.util.module_from_spec(spec)
+        spec.loader.exec_module(module)
+
+        func = getattr(module, func_name)
+        MODELS[folder] = {
+            "func": func,
+            "inputs": meta.get("inputs", []),
+            "meta": meta,
+            "path": path
+        }
+
+load_models()
+
+# ---- DASHBOARD ----
+@app.route("/")
+def dashboard():
+    models_with_md = {}
+    for name, model in MODELS.items():
+        md_content = ""
+        try:
+            md_path = os.path.join(model["path"], model["meta"]["description_file"])
+            with open(md_path, "r", encoding="utf-8") as f:
+                md_text = f.read()
+                # konwersja Markdown -> HTML
+                md_content = markdown.markdown(md_text)
+        except Exception:
+            md_content = "<p>Brak opisu.</p>"
+
+        models_with_md[name] = {**model, "md_content": md_content}
+
+    return render_template("user.html", models=models_with_md)
+# ---- PREDICT ----
+@app.route("/predict/<model_name>", methods=["POST"])
+def predict(model_name):
+    model_entry = MODELS.get(model_name)
+    if not model_entry:
+        return jsonify({"output": "Model nie istnieje"}), 404
+
+    func = model_entry["func"]
+    inputs = model_entry["inputs"]
+    kwargs = {}
+    for inp in inputs:
+        kwargs[inp] = request.form.get(inp)
+
+    try:
+        for k in kwargs:
+            try:
+                kwargs[k] = float(kwargs[k])
+            except:
+                pass
+        output = func(**kwargs)
+    except Exception as e:
+        output = str(e)
+
+    return jsonify({"output": str(output)})
+
+# ---- ADD MODEL ----
+@app.route("/add_model", methods=["POST"])
+def add_model():
+    admin_key = request.form.get("admin_key")
+    if admin_key != ADMIN_KEY:
+        return "Brak dostępu", 403
+
+    name = request.form["name"]
+    function_name = request.form["function_name"]
+    inputs = request.form.getlist("inputs")
+    model_py = request.files["model_py"]
+    description_file = request.files["description"]
+
+    folder_name = secure_filename(name)
+    folder_path = os.path.join(UPLOAD_FOLDER, folder_name)
+    os.makedirs(folder_path, exist_ok=True)
+
+    # zapis plików
+    model_py.save(os.path.join(folder_path, "model.py"))
+    description_file.save(os.path.join(folder_path, "description.md"))
+
+    # meta.json
+    meta = {
+        "name": name,
+        "function_name": function_name,
+        "inputs": inputs,
+        "description_file": "description.md",
+        "downloadable": True,  # można pobrać pliki
+        "type": request.form.get("type", "algorithmic")
+    }
+    with open(os.path.join(folder_path, "meta.json"), "w") as f:
+        json.dump(meta, f)
+
+    # załaduj od razu
+    spec = importlib.util.spec_from_file_location("model_module", os.path.join(folder_path, "model.py"))
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    func = getattr(module, function_name)
+
+    MODELS[folder_name] = {
+        "func": func,
+        "inputs": inputs,
+        "meta": meta,
+        "path": folder_path
+    }
+
+    return "Dodano model!"
+
+# ---- DOWNLOAD FILE ----
+@app.route("/download/<model_name>/<file_name>")
+def download_file(model_name, file_name):
+    model_entry = MODELS.get(model_name)
+    if not model_entry:
+        return "Model nie istnieje", 404
+    folder_path = model_entry["path"]
+    if file_name not in ["model.py", "description.md", "meta.json"]:
+        return "Nieprawidłowy plik", 400
+    return send_from_directory(folder_path, file_name, as_attachment=True)
+
+if __name__ == "__main__":
+    app.run(debug=True)

main.py

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-from flask import Flask, request, jsonify
-
-app = Flask(__name__)
-
-# Strona główna
-@app.route("/")
-def home():
-    return "AI Pathl Test działa!"
-
-# Endpoint testowy np. dla promptów AI
-@app.route("/test", methods=["POST"])
-def test_ai():
-    data = request.json
-    prompt = data.get("prompt", "")
-    # Na razie tylko echo promptu
-    response = {"response": f"Otrzymałem Twój prompt: {prompt}"}
-    return jsonify(response)
-
-if __name__ == "__main__":
-    print("server")
-    print("dodanie")
-    app.run(host="0.0.0.0", port=6000)

models/Power/Readme.md

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+#model Power

models/Power/description.md

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+# Model Power
+
+Ten model oblicza potęgę liczby.
+
+## Funkcje:
+
+- `oblicz_potega(x, typ)`
+
+### Parametry:
+
+- `x` (int/float): liczba do podniesienia do potęgi
+- `typ` (str): `"kwadrat"` lub `"sześcian"`
+
+### Przykłady użycia:
+
+```python
+oblicz_potega(3, "kwadrat")   # wynik: 9
+oblicz_potega(2, "sześcian")  # wynik: 8

models/Power/meta.json

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+{
+  "name": "Power",
+  "function_name": "oblicz_potega",
+  "inputs": ["x","typ"],
+  "description_file": "description.md"
+}

models/Power/model.py

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+def oblicz_potega(x, typ):
+    """
+    Funkcja oblicza kwadrat lub sześcian liczby x w zależności od parametru typ.
+    Parametry:
+    x (int/float): liczba, którą chcemy podnieść do potęgi
+    typ (str): "kwadrat" lub "sześcian"
+
+    Zwraca:
+    int/float: wynik działania
+    """
+    if typ == "kwadrat":
+        return x ** 2
+    elif typ == "sześcian":
+        return x ** 3
+    else:
+        return "Niepoprawny typ. Wpisz 'kwadrat' lub 'sześcian'."

static/style.css

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+/* Reset podstawowy */
+* {
+    margin: 0;
+    padding: 0;
+    box-sizing: border-box;
+    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+}
+
+/* Body */
+body {
+    background: #f4f7fc;
+    color: #333;
+    padding: 20px;
+}
+
+/* Nagłówek */
+h2 {
+    text-align: center;
+    margin-bottom: 30px;
+    color: #4a4a4a;
+    font-size: 2em;
+}
+
+/* Kontener modeli */
+#models-container {
+    display: grid;
+    grid-template-columns: repeat(auto-fit, minmax(320px, 1fr));
+    gap: 20px;
+}
+
+/* Karta modelu */
+.model-card {
+    background: #ffffff;
+    border-radius: 15px;
+    padding: 20px;
+    box-shadow: 0 6px 18px rgba(0,0,0,0.08);
+    transition: transform 0.2s, box-shadow 0.2s;
+}
+
+.model-card:hover {
+    transform: translateY(-5px);
+    box-shadow: 0 12px 24px rgba(0,0,0,0.12);
+}
+
+/* Nazwa modelu */
+.model-card h3 {
+    margin-bottom: 15px;
+    color: #1a1a1a;
+    font-size: 1.4em;
+    border-bottom: 1px solid #e0e0e0;
+    padding-bottom: 5px;
+}
+
+/* Opis modelu (.md) */
+.description {
+    font-style: italic;
+    color: #555;
+    margin-bottom: 15px;
+    line-height: 1.5;
+}
+
+/* Formularz */
+form.predict-form {
+    display: flex;
+    flex-direction: column;
+    gap: 10px;
+}
+
+form.predict-form label {
+    font-weight: 600;
+}
+
+form.predict-form input {
+    padding: 8px 12px;
+    border-radius: 8px;
+    border: 1px solid #ccc;
+    font-size: 0.95em;
+    transition: border 0.2s, box-shadow 0.2s;
+}
+
+form.predict-form input:focus {
+    border-color: #6c63ff;
+    box-shadow: 0 0 5px rgba(108, 99, 255, 0.4);
+    outline: none;
+}
+
+/* Przycisk */
+form.predict-form button {
+    padding: 10px 15px;
+    background: #6c63ff;
+    color: #fff;
+    border: none;
+    border-radius: 10px;
+    cursor: pointer;
+    font-weight: bold;
+    transition: background 0.2s, transform 0.2s;
+}
+
+form.predict-form button:hover {
+    background: #574fd6;
+    transform: translateY(-2px);
+}
+
+/* Output */
+.output {
+    margin-top: 10px;
+    font-weight: bold;
+    color: #1a73e8;
+}
+
+/* Download linki */
+.download {
+    margin-top: 15px;
+    font-size: 0.9em;
+}
+
+.download a {
+    text-decoration: none;
+    color: #6c63ff;
+    margin-right: 10px;
+    transition: color 0.2s;
+}
+
+.download a:hover {
+    color: #574fd6;
+    text-decoration: underline;
+}
+
+/* Linie oddzielające karty */
+hr {
+    border: none;
+    height: 1px;
+    background: #e0e0e0;
+    margin: 20px 0;
+}
+
+/* Responsywność */
+@media (max-width: 600px) {
+    h2 {
+        font-size: 1.5em;
+    }
+
+    .model-card {
+        padding: 15px;
+    }
+
+    form.predict-form input, form.predict-form button {
+        font-size: 0.9em;
+    }
+}

templates/user.html

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+<!DOCTYPE html>
+<html>
+<head>
+    <title>AI Models</title>
+  <link rel="stylesheet" href="{{ url_for('static', filename='style.css') }}">
+
+</head>
+<body>
+<h2>Lista modeli AI</h2>
+<div id="models-container">
+  {% for name, model in models.items() %}
+    <div class="model-card" id="model-{{name}}">
+      <h3>{{name}}</h3>
+      <div class="description">
+          {{ model.md_content | safe }}
+      </div>
+
+
+      <form class="predict-form">
+        {% for inp in model.inputs %}
+          <label>{{inp}}:</label>
+          <input name="{{inp}}"><br>
+        {% endfor %}
+        <button type="submit">Wyślij</button>
+      </form>
+      <div class="output" id="output-{{name}}"></div>
+      {% if model.meta.downloadable %}
+        <div class="download">
+          <a href="/download/{{name}}/model.py" target="_blank">Pobierz model.py</a> |
+          <a href="/download/{{name}}/description.md" target="_blank">Pobierz description.md</a> |
+          <a href="/download/{{name}}/meta.json" target="_blank">Pobierz meta.json</a>
+        </div>
+      {% endif %}
+    </div>
+    <hr>
+  {% endfor %}
+</div>
+
+<script>
+document.querySelectorAll(".predict-form").forEach(form => {
+    form.addEventListener("submit", async (e) => {
+        e.preventDefault();
+        const parent = e.target.closest(".model-card");
+        const modelName = parent.id.replace("model-", "");
+        const outputDiv = parent.querySelector(".output");
+
+        const formData = new FormData(form);
+        const response = await fetch(`/predict/${modelName}`, {
+            method: "POST",
+            body: formData
+        });
+
+        const data = await response.json();
+        outputDiv.textContent = data.output;
+    });
+});
+</script>
+</body>
+</html>