human

app.py

@@ -1,72 +1,50 @@
-import os
-from fastapi import FastAPI, Header, HTTPException, Depends
-from pydantic import BaseModel
-from text_humanizer import TextHumanizer, download_nltk_resources
-from aitext_detector import AdvancedAITextDetector
-import spacy
-
-API_KEY = os.environ.get("API_KEY", "dev-key")
-PORT = int(os.environ.get("PORT", 7860))
-
-app = FastAPI()
-humanizer = None
-detector = None
-
-# =========================
-# Request / Response Models
-# =========================
-class HumanizeReq(BaseModel):
-    text: str
-    use_passive: bool = False
-    use_synonyms: bool = False
-
-class DetectReq(BaseModel):
-    text: str
-
-# =========================
-# API Key verification
-# =========================
-def verify_key(x_api_key: str = Header(None)):
-    if x_api_key != API_KEY:
-        raise HTTPException(status_code=403, detail="Forbidden")
-    return True
-
-# =========================
-# Routes
-# =========================
-@app.get("/")
-def greet_json():
-    return {"Hello": "World!"}
-
-@app.on_event("startup")
-def startup():
-    download_nltk_resources()
-    try:
-        spacy.load("en_core_web_sm")
-    except OSError:
-        spacy.cli.download("en_core_web_sm")
-
-    global humanizer, detector
-    humanizer = TextHumanizer()
-    detector = AdvancedAITextDetector()
-
-@app.post("/humanize")
-def humanize(req: HumanizeReq, _=Depends(verify_key)):
-    return {
-        "humanized": humanizer.humanize_text(
-            req.text,
-            req.use_passive,
-            req.use_synonyms
-        )
-    }
-
-@app.post("/detect")
-def detect(req: DetectReq, _=Depends(verify_key)):
-    """
-    Detect whether the text is AI-generated or human-written.
-    """
-    return detector.detect_ai_text(req.text)
-
-# if __name__ == "__main__":
-#     import uvicorn
-#     uvicorn.run(app, host="0.0.0.0", port=PORT)
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+
+MODEL_NAME = "mistralai/Mistral-7B-Instruct-v0.2"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    device_map="auto",
+    torch_dtype="auto"
+)
+
+generator = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    max_length=512,
+    temperature=0.7,
+    top_p=0.9,
+    repetition_penalty=1.1
+)
+
+def humanize_text(text):
+    if not text.strip():
+        return "⚠️ Please enter some text."
+    
+    prompt = f"""Rewrite the following text to sound natural, fluent, and human-like. 
+Preserve meaning, names, and numbers. Avoid robotic tone. 
+Use contractions, natural sentence flow, and varied structure. 
+Do not explain, only rewrite.
+
+Input: \"\"\"{text}\"\"\"
+Rewritten:"""
+    
+    output = generator(prompt, num_return_sequences=1)[0]["generated_text"]
+    # Strip off prompt echo if model repeats
+    if "Rewritten:" in output:
+        output = output.split("Rewritten:")[-1].strip()
+    return output
+
+demo = gr.Interface(
+    fn=humanize_text,
+    inputs=gr.Textbox(lines=6, placeholder="Paste your text here..."),
+    outputs=gr.Textbox(label="Humanized Output"),
+    title="AI Humanizer",
+    description="Drop text and get a more natural, human-like version. Powered by Mistral-7B-Instruct."
+)
+
+if __name__ == "__main__":
+    demo.launch()

app_old.py

@@ -0,0 +1,72 @@
+import os
+from fastapi import FastAPI, Header, HTTPException, Depends
+from pydantic import BaseModel
+from text_humanizer import TextHumanizer, download_nltk_resources
+from aitext_detector import AdvancedAITextDetector
+import spacy
+
+API_KEY = os.environ.get("API_KEY", "dev-key")
+PORT = int(os.environ.get("PORT", 7860))
+
+app = FastAPI()
+humanizer = None
+detector = None
+
+# =========================
+# Request / Response Models
+# =========================
+class HumanizeReq(BaseModel):
+    text: str
+    use_passive: bool = False
+    use_synonyms: bool = False
+
+class DetectReq(BaseModel):
+    text: str
+
+# =========================
+# API Key verification
+# =========================
+def verify_key(x_api_key: str = Header(None)):
+    if x_api_key != API_KEY:
+        raise HTTPException(status_code=403, detail="Forbidden")
+    return True
+
+# =========================
+# Routes
+# =========================
+@app.get("/")
+def greet_json():
+    return {"Hello": "World!"}
+
+@app.on_event("startup")
+def startup():
+    download_nltk_resources()
+    try:
+        spacy.load("en_core_web_sm")
+    except OSError:
+        spacy.cli.download("en_core_web_sm")
+
+    global humanizer, detector
+    humanizer = TextHumanizer()
+    detector = AdvancedAITextDetector()
+
+@app.post("/humanize")
+def humanize(req: HumanizeReq, _=Depends(verify_key)):
+    return {
+        "humanized": humanizer.humanize_text(
+            req.text,
+            req.use_passive,
+            req.use_synonyms
+        )
+    }
+
+@app.post("/detect")
+def detect(req: DetectReq, _=Depends(verify_key)):
+    """
+    Detect whether the text is AI-generated or human-written.
+    """
+    return detector.detect_ai_text(req.text)
+
+# if __name__ == "__main__":
+#     import uvicorn
+#     uvicorn.run(app, host="0.0.0.0", port=PORT)

requirements.txt

@@ -1,7 +1,9 @@
 fastapi
 uvicorn[standard]
 torch
-transformers
+transformers>=4.40.0
+accelerate
+gradio
 numpy
 scipy
 spacy