first model fixed

backend/app/api/routes.py

@@ -86,14 +86,13 @@ async def analyze(request: AnalysisRequest) -> AnalysisResponse:
                 detail="Text content must be at least 10 characters"
             )
         
-        model = request.model or "yaya36095/xlm-roberta-text-detector"
-        
-        if model not in AVAILABLE_MODELS["text"]:
+        if not AVAILABLE_MODELS["text"]:
             raise HTTPException(
                 status_code=400,
-                detail=f"Model '{model}' is not available for text analysis. Available models: {AVAILABLE_MODELS['text']}"
+                detail="No model available for text analysis"
             )
         
+        model = AVAILABLE_MODELS["text"][0]
         logger.info(f"Received text analysis request, length: {len(request.text)} chars, model: {model}")
         
         try:
@@ -116,20 +115,14 @@ async def analyze(request: AnalysisRequest) -> AnalysisResponse:
     
     elif isinstance(request, ImageAnalysisRequest):
         content_type = "image"
-        model = request.model
         
-        if not model:
+        if not AVAILABLE_MODELS["image"]:
             raise HTTPException(
                 status_code=400,
-                detail=f"No model available for image analysis. Available models: {AVAILABLE_MODELS['image']}"
-            )
-        
-        if model not in AVAILABLE_MODELS["image"]:
-            raise HTTPException(
-                status_code=400,
-                detail=f"Model '{model}' is not available for image analysis. Available models: {AVAILABLE_MODELS['image']}"
+                detail="No model available for image analysis"
             )
         
+        model = AVAILABLE_MODELS["image"][0]
         logger.info(f"Received image analysis request for URL: {request.image_url}, model: {model}")
         
         try:
@@ -160,20 +153,14 @@ async def analyze(request: AnalysisRequest) -> AnalysisResponse:
     
     elif isinstance(request, VideoAnalysisRequest):
         content_type = "video"
-        model = request.model
         
-        if not model:
+        if not AVAILABLE_MODELS["video"]:
             raise HTTPException(
                 status_code=400,
-                detail=f"No model available for video analysis. Available models: {AVAILABLE_MODELS['video']}"
-            )
-        
-        if model not in AVAILABLE_MODELS["video"]:
-            raise HTTPException(
-                status_code=400,
-                detail=f"Model '{model}' is not available for video analysis. Available models: {AVAILABLE_MODELS['video']}"
+                detail="No model available for video analysis"
             )
         
+        model = AVAILABLE_MODELS["video"][0]
         logger.info(f"Received video analysis request for URL: {request.video_url}, model: {model}")
         
         try:
@@ -204,20 +191,14 @@ async def analyze(request: AnalysisRequest) -> AnalysisResponse:
     
     elif isinstance(request, FileAnalysisRequest):
         content_type = "file"
-        model = request.model
-        
-        if not model:
-            raise HTTPException(
-                status_code=400,
-                detail=f"No model available for file analysis. Available models: {AVAILABLE_MODELS['file']}"
-            )
         
-        if model not in AVAILABLE_MODELS["file"]:
+        if not AVAILABLE_MODELS["file"]:
             raise HTTPException(
                 status_code=400,
-                detail=f"Model '{model}' is not available for file analysis. Available models: {AVAILABLE_MODELS['file']}"
+                detail="No model available for file analysis"
             )
         
+        model = AVAILABLE_MODELS["file"][0]
         logger.info(f"Received file analysis request for URL: {request.file_url}, model: {model}")
         
         try:

backend/app/models/schemas.py

@@ -1,18 +1,16 @@
 from pydantic import BaseModel, HttpUrl, Field
-from typing import Optional, Union, Literal
+from typing import Union, Literal, Optional
 
 
 class TextAnalysisRequest(BaseModel):
     content_type: Literal["text"]
     text: str = Field(..., description="Text content to analyze for deepfake detection")
-    model: Optional[str] = Field(None, description="Detector model to use")
     
     class Config:
         json_schema_extra = {
             "example": {
                 "content_type": "text",
-                "text": "Some text that might be AI-generated",
-                "model": "mock"
+                "text": "Some text that might be AI-generated"
             }
         }
 
@@ -20,14 +18,12 @@ class TextAnalysisRequest(BaseModel):
 class ImageAnalysisRequest(BaseModel):
     content_type: Literal["image"]
     image_url: HttpUrl = Field(..., description="URL of the image to analyze")
-    model: Optional[str] = Field(None, description="Detector model to use")
     
     class Config:
         json_schema_extra = {
             "example": {
                 "content_type": "image",
-                "image_url": "https://example.com/image.jpg",
-                "model": "mock"
+                "image_url": "https://example.com/image.jpg"
             }
         }
 
@@ -35,14 +31,12 @@ class ImageAnalysisRequest(BaseModel):
 class VideoAnalysisRequest(BaseModel):
     content_type: Literal["video"]
     video_url: HttpUrl = Field(..., description="URL of the video to analyze")
-    model: Optional[str] = Field(None, description="Detector model to use")
     
     class Config:
         json_schema_extra = {
             "example": {
                 "content_type": "video",
-                "video_url": "https://example.com/video.mp4",
-                "model": "mock"
+                "video_url": "https://example.com/video.mp4"
             }
         }
 
@@ -50,14 +44,12 @@ class VideoAnalysisRequest(BaseModel):
 class FileAnalysisRequest(BaseModel):
     content_type: Literal["file"]
     file_url: HttpUrl = Field(..., description="URL of the file to analyze")
-    model: Optional[str] = Field(None, description="Detector model to use")
     
     class Config:
         json_schema_extra = {
             "example": {
                 "content_type": "file",
-                "file_url": "https://example.com/video.mp4",
-                "model": "mock"
+                "file_url": "https://example.com/video.mp4"
             }
         }
 

backend/requirements.txt

@@ -7,3 +7,5 @@ python-multipart==0.0.6
 transformers==4.41.2
 torch==2.3.1
 numpy==1.26.4
+sentencepiece
+protobuf