Merge pull request #34 from baloise/main

Add a way to set custom values for LLM Backend

src/api/mask.py

@@ -6,6 +6,7 @@
 from src.utils.ano_llm import find_entities as llm_find_entities
 from src.utils.ano_spacy import Anon_Spacy
 from src.utils.ano_regex import find_entities as reg_find_entities
+from src.utils.env import *
 
 router = fastapi.APIRouter()
 
@@ -17,15 +18,31 @@ class BackendType(Enum):
 class MaskRequest(BaseModel):
     text: str
     backendType: BackendType
+    llmURL: str
+    llmModel: str
 
 ano = Anon_Spacy()
 
+def check_parameter(param):
+   if not param:  # This checks if param is empty (None, '', [], etc.)
+        print(f"The parameter is empty. Setting to default value from ENV if existing.")
+        return 0
+   else:
+        print(f"The parameter is not empty: {param}")
+        return 1
+
 @router.post("/mask", response_class=JSONResponse, include_in_schema=True)
 async def mask(request: MaskRequest):
 
     match request.backendType:
         case BackendType.LLM:
-            llm_entities = llm_find_entities(request.text)
+            if check_parameter(request.llmURL) == 0:
+                request.llmURL = OLLAMA_BASE_URL
+
+            if check_parameter(request.llmModel) == 0:
+                request.llmModel = OLLAMA_MODEL
+
+            llm_entities = llm_find_entities(text=request.text, base_url=request.llmURL, model=request.llmModel)
             return {"original_text": request.text, "entities": llm_entities['replace_dict'], "anonymized_text": llm_entities['text']}
         case BackendType.NER:
             spacy_entities = ano.find_entities(request.text)

src/static/scripts/mask.js

@@ -1,9 +1,29 @@
+document.getElementById('backendType').addEventListener('change', function() {
+    var llmInputCheckbox = document.getElementById('LLMcustomLabel');
+    if (this.value === 'LLM') {
+        llmInputCheckbox.style.display = 'flex';
+    } else {
+        llmInputCheckbox.style.display = 'none';
+    }
+});
+
+document.getElementById('LLMcustom').addEventListener('change', function() {
+    var llmInputDiv = document.getElementById('LLMInput'); 
+    if (this.checked === true) {
+        llmInputDiv.style.display = 'flex'; // Show the LLMInput div
+    } else {
+        llmInputDiv.style.display = 'none'; // Hide the LLMInput div
+    }
+});
+
 document.getElementById('inputForm').addEventListener('submit', function(event) {
     event.preventDefault(); // Prevent the default form submission
 
     const inputData = document.getElementById('inputData').value;
     const backendType = document.getElementById('backendType').value;
-
+    const inputLLMurl = document.getElementById('inputLLMurl').value;
+    const inputLLMmodel = document.getElementById('inputLLMmodel').value;
+
     // Use a relative URL for the API endpoint
     const apiEndpoint = '/api/mask'; // Relative URL
 
@@ -13,7 +33,7 @@ document.getElementById('inputForm').addEventListener('submit', function(event)
         headers: {
             'Content-Type': 'application/json',
         },
-        body: JSON.stringify({ text: inputData, "backendType": backendType }), // Send the input text as JSON
+        body: JSON.stringify({ text: inputData, "backendType": backendType, llmURL: inputLLMurl, llmModel: inputLLMmodel}), // Send the input text as JSON
     })
     .then(response => {
         if (!response.ok) {

src/static/styles/style.css

@@ -36,6 +36,14 @@ footer {
     white-space: pre-wrap; /* Preserve whitespace */
 }
 
+#LLMInput {
+    display: none; /* Hide by default */
+}
+
+#LLMcustomLabel {
+    display: none; /* Hide by default */
+}
+
 .flex-container {
     display: flex; /* Use flexbox to align items */
     justify-content: center; /* Center the buttons horizontally */
@@ -95,3 +103,7 @@ footer {
         flex-direction: column; /* Stack items vertically */
     }
 }
+
+.checkbox-label {
+    font-size: 14px;      /* Font size */
+}

src/templates/html/mask.html

@@ -28,18 +28,27 @@ <h3>Input</h3>
             <div class="flex-item">
                 <form id="inputForm">
                     <textarea class="default-textarea" type="text" id="inputData" placeholder="Enter text to anonymize or load text from a file" required></textarea>
-                    <div class="flex-container-row">
+                    <div class="flex-container">
                         <div class="flex-item">
                             <select id="backendType" name="backendType" required>
                                 <option value="REG">REG</option>
                                 <option value="LLM">LLM</option>
                                 <option value="NER">NER</option>
                             </select>
                         </div>
+                        <label class="flex-item checkbox-label" id="LLMcustomLabel"><input type="checkbox" id="LLMcustom" name="LLMcustom">use custom settings</label>
+                        <div id="LLMInput" class="flex-container">
+                            <div class="flex-item">
+                                <input type="text" name="LLMURL" id="inputLLMurl" placeholder="e.g.: http://localhost:11434"></input>
+                            </div>
+                            <div class="flex-item">
+                                <input type="text" name="LLMMODEL" id="inputLLMmodel" placeholder="e.g.: llama3.2:latest"></input>
+                            </div>
+                        </div>
                         <div class="flex-item">
                             <input type="submit" value="Submit">
                         </div>
-                    </div>  
+                    </div>
                 </form>
             </div>
 

src/utils/ano_llm.py

@@ -76,7 +76,6 @@
 Text to anonymize: {text}   
 """
 
-
 def find_entities(text, model=OLLAMA_MODEL, temperature=0.1, template=TEMPLATE,
                   base_url=OLLAMA_BASE_URL, unprettify=True, raw=False):
     """
@@ -89,8 +88,7 @@ def find_entities(text, model=OLLAMA_MODEL, temperature=0.1, template=TEMPLATE,
     :param raw:
     :return:
     """
-
-
+
     prompt = ChatPromptTemplate.from_template(template)
     model = OllamaLLM(model=model, temperature=temperature, base_url=base_url, client_kwargs={"verify": os.getenv("HTTPX_CLIENT_VERIFY", True)})
     chain = prompt | model