First commit

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

.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 3.8" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8" 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/textdetectextension.iml" filepath="$PROJECT_DIR$/.idea/textdetectextension.iml" />
+    </modules>
+  </component>
+</project>

.idea/textdetectextension.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="jdk" jdkName="Python 3.8" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/vcs.xml

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

README.md

@@ -1,13 +1,27 @@
----
-title: Textdetectextension
-emoji: 🚀
-colorFrom: blue
-colorTo: gray
-sdk: gradio
-sdk_version: 5.22.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# AI Text Detection API
+
+This API provides endpoints for detecting AI-generated text using the RoBERTa-based model from fakespot-ai.
+
+## API Endpoints
+
+- GET `/`: Health check endpoint
+- POST `/predict`: Predict if text is AI-generated or human-written
+
+### Sample Usage
+
+POST `/predict`
+```json
+{
+    "text": "Your text to analyze"
+}
+```
+
+Response:
+```json
+{
+    "text": "Your text to analyze",
+    "human_probability": 85.5,
+    "ai_probability": 14.5,
+    "prediction": "Human-written"
+}
+```

app.py

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+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import torch
+
+app = FastAPI()
+
+# Add CORS middleware
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # For development - you should restrict this in production
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Load model and tokenizer
+model_name = "fakespot-ai/roberta-base-ai-text-detection-v1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+
+class TextRequest(BaseModel):
+    text: str
+
+
+@app.post("/predict")
+async def predict(request: TextRequest):
+    try:
+        # Tokenize the input text
+        inputs = tokenizer(request.text, return_tensors="pt", truncation=True, max_length=512)
+
+        # Make prediction
+        with torch.no_grad():
+            outputs = model(**inputs)
+            predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
+
+        # Get the probability scores
+        human_prob = predictions[0][0].item()
+        ai_prob = predictions[0][1].item()
+
+        return {
+            "text": request.text,
+            "human_probability": round(human_prob * 100, 2),
+            "ai_probability": round(ai_prob * 100, 2),
+            "prediction": "AI-generated" if ai_prob > human_prob else "Human-written"
+        }
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/")
+async def root():
+    return {"message": "AI Text Detection API is running"}
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="0.0.0.0", port=7860)

requirements.txt

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+transformers
+torch
+fastapi
+uvicorn
+python-multipart