280: Rename route, add models supported langages endpoint

nlp/src/base_models.py

@@ -46,3 +46,29 @@ def json(self):
             "metadata": self.metadata,
             "results": self.results
         }
+
+
+class ModelSupportedLanguages(BaseModel):
+    """Response model for used language"""
+    sentiment: List[str]
+    language: List[str]
+    sarcasm: List[str]
+    keywords: List[str]
+    spam: List[str]
+    political: List[str]
+    hateSpeech: List[str]
+    clickbait: List[str]
+    llmDetection: List[str]
+
+    def json(self):
+        return {
+            "sentiment": self.sentiment,
+            "language": self.language,
+            "sarcasm": self.sarcasm,
+            "keywords": self.keywords,
+            "spam": self.spam,
+            "political": self.political,
+            "hateSpeech": self.hateSpeech,
+            "clickbait": self.clickbait,
+            "llmDetection": self.llmDetection
+        }

nlp/src/main.py

@@ -5,6 +5,8 @@
 from contextlib import asynccontextmanager
 from fastapi import FastAPI, HTTPException
 from fastapi.params import Depends
+
+from docs.conf import language
 from src.base_models import *
 from src.logger_config import logger
 from src.models_loading import *
@@ -31,7 +33,7 @@ async def lifespan(application: FastAPI):
         raise
 
     models = [
-        "language", "sentiment", "ai_detector", "sarcasm", "spam",
+        "language", "sentiment", "llm_detection", "sarcasm", "spam",
         "political", "hate_speech", "clickbait", "keywords"
     ]
 
@@ -388,7 +390,7 @@ def process_fn(text):
     ).json()
 
 
-@app.post("/ai-detector", response_model=TextResponse,
+@app.post("/llm-detection", response_model=TextResponse,
           dependencies=[Depends(auth.get_api_key)])
 async def get_ai_bots(request: TextRequest):
     """
@@ -408,11 +410,11 @@ def process_fn(text):
         prediction = gl.ai_detector_pipeline_english(text)
         confidence = prediction[0]["score"]
         if confidence > 0.5:
-            label="AI"
+            label = "AI"
             confidence = confidence_output(confidence)
         else:
-            label="Human"
-            confidence = confidence_output(1-confidence)
+            label = "Human"
+            confidence = confidence_output(1 - confidence)
 
         result = AnalysisResult(
             labels=[label],
@@ -423,9 +425,33 @@ def process_fn(text):
     results, generation_time = measure_execution_time(
         lambda: process_inputs(process_fn, request.text))
 
-
     return TextResponse(
         kind="aiDetector",
         metadata=Metadata(generated_in=generation_time),
         results=results
     ).json()
+
+
+@app.post("/info/langs", response_model=ModelSupportedLanguages,
+          dependencies=[Depends(auth.get_api_key)])
+async def get_languages():
+    """
+    Get languages used in the application.
+
+    Returns:
+        ModelSupportedLanguages: Languages used in the application.
+    """
+    with open("version_models.json", "r") as file:
+        data = json.load(file)
+
+    return ModelSupportedLanguages(
+        sentiment=data.get("sentiment", []),
+        language=data.get("language", []),
+        sarcasm=data.get("sarcasm", []),
+        keywords=data.get("keywords", []),
+        spam=data.get("spam", []),
+        political=data.get("political", []),
+        hateSpeech=data.get("hate_speech", []),
+        clickbait=data.get("clickbait", []),
+        llmDetection=data.get("llm_detection", [])
+    ).json()

nlp/src/models_loading.py

@@ -66,6 +66,6 @@ def load_model(model_name: str):
         elif model_name == "clickbait":
             g.clickbait_pipeline = pipeline("text-classification", model=model,
                                             tokenizer=tokenizer)
-        elif model_name == "ai_detector":
+        elif model_name == "llm_detection":
             g.ai_detector_pipeline_english = pipeline("text-classification",
-                                                   model=model, tokenizer=tokenizer)
+                                                      model=model, tokenizer=tokenizer)

nlp/version_models.json

@@ -1,6 +1,6 @@
 {
   "language": [
-    "english"
+    "all"
   ],
   "sentiment": [
     "english",
@@ -22,7 +22,10 @@
   "clickbait": [
     "english"
   ],
-  "ai_detector": [
+  "llm_detection": [
     "english"
+  ],
+  "keywords": [
+    "all"
   ]
 }