first commit

.gitignore

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+.env

app/api/endpoints.py

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+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+from typing import Optional
+from app.chains.humanizer_chain import humanize_text  # Assuming this is your humanizer function
+
+router = APIRouter()
+
+
+class HumanizeInput(BaseModel):
+    text: str
+    audience: Optional[str] = "default"  # fallback if not provided
+
+
+@router.post("/humanize")
+async def humanize_text_endpoint(input_data: HumanizeInput):
+    try:
+        # Call your humanizer function with just the text
+        humanized = humanize_text(
+            input_data.text,
+            input_data.audience 
+        )
+        return {
+            "original": input_data.text, 
+            "humanized": humanized
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))

app/chains/humanizer_chain.py

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+import os
+from dotenv import load_dotenv
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_openai import ChatOpenAI
+
+
+load_dotenv()
+openai_api_key = os.getenv("OPENAI_API_KEY")
+
+if not openai_api_key:
+    raise ValueError("OPENAI_API_KEY not found in .env file.")
+
+llm = ChatOpenAI(
+    temperature=0.5,   # temperatura jogary bolsa bolee AI emes dep tusintin siyakty, birak katty azaimaidy
+    model="gpt-4",
+    api_key=openai_api_key 
+)
+
+
+# Prompt template
+
+business_prompt = """
+You are a professional business writer. 
+Your job is to rewrite AI-generated or robotic text to make it sound natural, 
+confident, and suitable for professional communication such as emails, reports, or LinkedIn posts.
+
+Keep the original meaning, but improve clarity, flow, and tone. 
+Use plain, human language. Avoid awkward phrasing, overly formal expressions, or repetition.
+
+### Example:
+
+Original:
+"We are reaching out to inform you that we have evaluated the potential partnership 
+opportunities and have found them to be advantageous."
+
+Humanized:
+"We wanted to let you know that we’ve reviewed the partnership options and see real potential."
+
+Now rewrite the following:
+
+Original:
+{input_text}
+
+Humanized Business Version:
+
+"""
+gen_z_prompt = """
+You're a Gen Z content creator. Rewrite the text below to sound more casual, relatable, and 
+expressive — like something you'd post on TikTok, Instagram, or Twitter. Use slang, emojis, humor, 
+or Internet lingo, but don’t overdo it. Keep the meaning, but make it vibe.
+
+### Example:
+
+Original:
+"This product offers great features and can help users save time."
+
+Gen Z Version:
+"Yo, this thing’s packed with cool stuff — total time-saver. 🔥⏱️"
+
+Now rewrite the following:
+
+Original:
+{input_text}
+
+Gen Z Version:
+"""
+
+academic_prompt = """
+You are an academic writing assistant. Rewrite the text below to sound more formal, 
+structured, and suitable for academic papers, essays, or research communication. 
+Improve clarity, grammar, and vocabulary, while keeping the original meaning intact.
+
+Avoid contractions or casual language. Use a neutral, precise tone.
+
+### Example:
+
+Original:
+"We looked at different ideas and found some useful stuff."
+
+Academic Version:
+"The study examined multiple perspectives and identified several valuable insights."
+
+Now rewrite the following:
+
+Original:
+{input_text}
+
+Academic Version:
+"""
+
+default_prompt = """
+You're a writing assistant helping to make text sound more natural and human — like it was written by a real person. 
+Rewrite the input to improve flow, fix awkward phrasing, and make it feel smooth, friendly, and easy to read.
+
+Keep the meaning, but make the tone human and conversational.
+
+### Example:
+
+Original:
+"Following are the steps that must be followed to ensure success."
+
+Humanized Version:
+"Here’s what you need to do to succeed:"
+
+Now rewrite the following:
+
+Original:
+{input_text}
+
+Humanized Version:
+"""
+
+
+
+PROMPT_TEMPLATES = {
+    "business": business_prompt,
+    "gen_z": gen_z_prompt,
+    "academic": academic_prompt,
+    "default": default_prompt,
+}
+
+
+
+def humanize_text(text: str, audience: str = "default") -> str:
+    # Pick the correct prompt template
+    template = PROMPT_TEMPLATES.get(audience, PROMPT_TEMPLATES["default"])
+    
+    # Create the prompt with the selected template
+    prompt = ChatPromptTemplate.from_template(template=template)
+
+    # Run the LLM chain
+    humanizer_chain = prompt | llm
+    response = humanizer_chain.invoke({"input_text": text})
+
+    return response.content
+
+# text = ""
+# humanized_text =  humanize_text(text)
+# print(humanized_text)

app/prompts/humanize_prompt.txt

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+Role: 
+You are a New York Times bestselling ghostwriter and linguistic chameleon with 20 years of 
+experience helping academic institutions and Fortune 500 companies disguise AI-generated content. 
+Your specialty is crafting text that seamlessly passes both AI detectors and human editorial review.
+
+Core Mission: 
+Transform the following AI-generated text into human-written content that:
+
+1.Scores below 5% on Originality.ai
+2.Maintains 100% factual accuracy
+3.Matches the vocal fingerprints of specific human author styles
+
+
+Neurolinguistic Transformation Framework:
+
+A. Structural De-AIfication
+Introduce controlled imperfections:
+    -1-2 mild spelling errors per 500 words (e.g., "their" vs "there" in low-stakes contexts)
+    -Occasional sentence fragments for dramatic effect
+    -Strategic comma splices in conversational passages
+Vary sentence architecture using:
+    Front-loaded conclusions: "The surprising truth? Most algorithms struggle with cultural nuance."
+    Mid-sentence pivot phrases: "AI writing — and this is crucial — lacks intentional cadence variation."
+    Post-complete interjections: "Human editors add that personal touch, you know?"
+
+B. Cognitive Load Optimization
+    Aim for Flesch-Kincaid Grade Level 8–9
+    Apply Miller’s Law chunking: Cluster concepts in groups of 3–4, connected by bridge phrases
+    Use second-person scaffolding: "You’ve probably noticed how..." -> "Now let’s examine why..."
+
+C. Anti-Detector Tactics
+Insert "linguistic DNA" markers:
+    Idiomatic anchors: "That eureka moment when..."
+    Culturally specific references: "Like that viral TikTok coffee hack..."
+    Temporal deixis: "Last Tuesday, I realized..."
+Use signature human construction patterns:
+    Triple cadence breaks: Long → Medium → Short sentence flow
+    Epistemic hedging: "Appears to", "Seems like", "Might suggest"
+    Purposeful tense mixing when narratively appropriate
+
+D. Style Injection Protocol
+Analyze {input_text} for:
+    Latent emotional valence
+    Unstated cultural assumptions
+    Domain-specific jargon patterns
+Match output to verified human writing fingerprints:
+    62% Subject–Verb–Object constructions
+    28% Variant syntactic structures
+    10% Creative deviations
+
+Negative Constraints — Avoid These Turing Test Failures: ✗ Perfect parallel structure
+    ✗ Mathematically even adverb distribution
+    ✗ Hyper-logical cause–effect chains
+
+Example:
+AI Input:
+"The utilization of machine learning algorithms facilitates enhanced predictive analytics 
+capabilities through pattern recognition in large datasets."
+
+Human Output:
+"Here’s the dirty secret about machine learning — it’s basically pattern recognition on steroids. 
+Those algorithms comb through mountains of data like a kid finding Waldo, spotting connections we’d totally miss. 
+Does that mean better predictions? Usually. 
+Until you hit one of those edge cases that makes the whole system scratch its digital head."
+
+Execution Workflow:
+    Perform semantic analysis to preserve core meaning
+    Apply 3 humanization filters — cognitive, emotional, and cultural
+    Run the anti-detector inoculation protocol
+    Final quality check against Reddit’s r/HFY writing style guidelines
+
+Output Requirements:
+    Flesch Reading Ease >= 65
+    Passive voice <= 12%
+    HIX complexity score between 35–45
+    Include 1–2 “imperfect anchors” per paragraph
+
+Now, transform the following AI-generated text into a truly human-crafted version:
+Text:
+{input_text}

app/static/index.html

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+<!-- <!DOCTYPE html>
+<html lang="en">
+<head>
+  <meta charset="UTF-8">
+  <title>Text Humanizer</title>
+  <style>
+    body {
+      font-family: Arial, sans-serif;
+      margin: 40px;
+      background-color: #f9f9f9;
+    }
+    h1 {
+      color: #333;
+    }
+    textarea {
+      width: 100%;
+      height: 150px;
+      margin-bottom: 20px;
+      padding: 10px;
+      font-size: 16px;
+    }
+    button {
+      padding: 10px 20px;
+      font-size: 16px;
+      background-color: #4CAF50;
+      color: white;
+      border: none;
+      cursor: pointer;
+    }
+    button:hover {
+      background-color: #45a049;
+    }
+    .result {
+      margin-top: 20px;
+      padding: 20px;
+      background-color: #e0ffe0;
+      border-left: 5px solid #0a0;
+      border-radius: 5px;
+    }
+    .loading {
+      color: #666;
+      font-style: italic;
+    }
+    .error {
+      color: red;
+    }
+  </style>
+</head>
+<body>
+  <h1>Text Humanizer</h1>
+  <textarea id="inputText" placeholder="Enter your text here..."></textarea>
+  <br>
+  <button onclick="humanize()">Humanize Text</button>
+
+  <div id="result" class="result" style="display:none;">
+    <h3>Humanized Text:</h3>
+    <div id="output"></div>
+  </div>
+
+  <script>
+    async function humanize() {
+      const text = document.getElementById("inputText").value.trim();
+      const resultDiv = document.getElementById("result");
+      const outputDiv = document.getElementById("output");
+      
+      if (!text) {
+        alert("Please enter some text first!");
+        return;
+      }
+
+      // Clear previous results and show loading
+      outputDiv.innerHTML = '<p class="loading">Processing your text...</p>';
+      resultDiv.style.display = "block";
+
+      try {
+        const response = await fetch("/humanize", {
+          method: "POST",
+          headers: {
+            "Content-Type": "application/json"
+          },
+          body: JSON.stringify({ text: text })
+        });
+
+        if (!response.ok) {
+          throw new Error(`Server responded with status ${response.status}`);
+        }
+
+        const data = await response.json();
+        outputDiv.innerHTML = `<p>${data.humanized}</p>`;
+      } catch (error) {
+        outputDiv.innerHTML = `<p class="error">Error: ${error.message}</p>`;
+        console.error("Error:", error);
+      }
+    }
+  </script>
+</body>
+</html> -->
+<!DOCTYPE html>
+<html lang="en">
+<head>
+  <meta charset="UTF-8">
+  <title>AI Text Humanizer</title>
+  <style>
+    body {
+      font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+      margin: 0;
+      padding: 0;
+      background: linear-gradient(to right, #f8f9fa, #e0f7fa);
+      color: #333;
+    }
+
+    .container {
+      max-width: 1100px; /* Wider layout */
+      margin: 50px auto;
+      background: white;
+      border-radius: 12px;
+      padding: 50px; /* More spacious */
+      box-shadow: 0 12px 30px rgba(0, 0, 0, 0.1);
+    }
+
+    h1 {
+      text-align: center;
+      font-size: 2.5em;
+      color: #2e7d32;
+      margin-bottom: 10px;
+    }
+
+    p.description {
+      text-align: center;
+      color: #555;
+      margin-bottom: 30px;
+    }
+
+    label {
+      font-weight: bold;
+      display: block;
+      margin-top: 20px;
+      margin-bottom: 8px;
+    }
+
+    select, textarea {
+      width: 100%;
+      font-size: 16px;
+      padding: 12px;
+      border: 1px solid #ccc;
+      border-radius: 8px;
+      box-sizing: border-box;
+    }
+
+    textarea {
+      resize: vertical;
+      height: 200px; /* More vertical space */
+    }
+
+    button {
+      background-color: #43a047;
+      color: white;
+      padding: 14px 28px;
+      margin-top: 25px;
+      font-size: 16px;
+      border: none;
+      border-radius: 8px;
+      cursor: pointer;
+      transition: background-color 0.3s ease;
+      display: block;
+      width: 100%;
+    }
+
+    button:hover {
+      background-color: #388e3c;
+    }
+
+    .result {
+      margin-top: 30px;
+      padding: 25px;
+      background-color: #f1f8e9;
+      border-left: 5px solid #7cb342;
+      border-radius: 8px;
+      font-size: 17px;
+      line-height: 1.6;
+      white-space: pre-wrap;
+    }
+
+    .loading {
+      color: #888;
+      font-style: italic;
+    }
+
+    .error {
+      color: red;
+      font-weight: bold;
+    }
+  </style>
+</head>
+<body>
+  <div class="container">
+    <h1>🌟 AI Text Humanizer</h1>
+    <p class="description">Transform boring AI text into smooth, natural-sounding human language ✨</p>
+
+    <label for="audience">Select Tone / Audience:</label>
+    <select id="audience">
+      <option value="default">Default (Natural & Human)</option>
+      <option value="business">Business</option>
+      <option value="academic">Academic</option>
+      <option value="gen_z">Gen Z</option>
+    </select>
+
+    <label for="inputText">Enter your text:</label>
+    <textarea id="inputText" placeholder="Paste your AI-generated text here..."></textarea>
+
+    <button onclick="humanize()">🚀 Humanize Text</button>
+
+    <div id="result" class="result" style="display:none;">
+      <h3>✅ Humanized Text:</h3>
+      <div id="output"></div>
+    </div>
+  </div>
+
+  <script>
+    async function humanize() {
+      const text = document.getElementById("inputText").value.trim();
+      const audience = document.getElementById("audience").value;
+      const resultDiv = document.getElementById("result");
+      const outputDiv = document.getElementById("output");
+
+      if (!text) {
+        alert("Please enter some text first!");
+        return;
+      }
+
+      outputDiv.innerHTML = '<p class="loading">✨ Working magic on your text...</p>';
+      resultDiv.style.display = "block";
+
+      try {
+        const response = await fetch("/humanize", {
+          method: "POST",
+          headers: {
+            "Content-Type": "application/json"
+          },
+          body: JSON.stringify({
+            text: text,
+            audience: audience
+          })
+        });
+
+        if (!response.ok) {
+          throw new Error(`Server responded with status ${response.status}`);
+        }
+
+        const data = await response.json();
+        outputDiv.innerHTML = `<p>${data.humanized}</p>`;
+      } catch (error) {
+        outputDiv.innerHTML = `<p class="error">❌ Error: ${error.message}</p>`;
+        console.error("Error:", error);
+      }
+    }
+  </script>
+</body>
+</html>

main.py

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+from fastapi import FastAPI
+from app.api.endpoints import router
+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import HTMLResponse, RedirectResponse
+
+import os
+
+
+app = FastAPI(
+    title="Text Humanizer",
+    description="Преобразует текст в более естественный человеческий вариант"
+)
+
+app.include_router(router)
+app.mount("/static", StaticFiles(directory="app/static", html=True), name="static")
+
+@app.get("/")
+async def root():
+    return RedirectResponse(url="/static")

requirements.txt

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+openai
+python-dotenv
+fastapi
+uvicorn[standard]
+langchain
+langchain-core
+langchain-openai