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medicine-ml-chatbot

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erichuber commited on Jun 1, 2025

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Files changed (6) hide show

.gitattributes +1 -0
dockerfile +0 -0
medquad_full.json +3 -0
requirements.txt +8 -0
templates/terminal_chat.html +125 -0
web_terminal_chat.py +60 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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 *.zst filter=lfs diff=lfs merge=lfs -text
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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+medquad_full.json filter=lfs diff=lfs merge=lfs -text

dockerfile ADDED Viewed

File without changes

medquad_full.json ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:0cde0872638b218d30a48cd991ec1d70c3f2a1316fcb8f7bcf93b128eb49c0fe
+size 23093158

requirements.txt ADDED Viewed

	@@ -0,0 +1,8 @@

+fastapi
+uvicorn
+jinja2
+torch
+scikit-learn
+numpy
+python-multipart
+sentence-transformers

templates/terminal_chat.html ADDED Viewed

	@@ -0,0 +1,125 @@

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <title>MedQA Terminal Chatbot</title>
+    <style>
+        body {
+            background: #181818;
+            color: #e0e0e0;
+            font-family: 'Fira Mono', 'Consolas', monospace;
+            margin: 0;
+            padding: 0;
+        }
+        .container {
+            display: flex;
+            height: 100vh;
+        }
+        .chat {
+            flex: 2;
+            border-right: 2px solid #333;
+            padding: 32px 24px 24px 24px;
+            display: flex;
+            flex-direction: column;
+        }
+        .chat-history {
+            flex: 1;
+            overflow-y: auto;
+            margin-bottom: 16px;
+        }
+        .chat-entry {
+            margin-bottom: 18px;
+        }
+        .user {
+            color: #8be9fd;
+        }
+        .bot {
+            color: #50fa7b;
+        }
+        .confidence {
+            color: #ffb86c;
+            font-size: 0.95em;
+        }
+        .matched-q {
+            color: #bfbfbf;
+            font-size: 0.92em;
+            margin-left: 12px;
+        }
+        .input-form {
+            display: flex;
+            gap: 8px;
+        }
+        .input-form input[type="text"] {
+            flex: 1;
+            background: #222;
+            color: #e0e0e0;
+            border: 1px solid #444;
+            border-radius: 4px;
+            padding: 8px 12px;
+            font-size: 1em;
+        }
+        .input-form button {
+            background: #444;
+            color: #fff;
+            border: none;
+            border-radius: 4px;
+            padding: 8px 18px;
+            font-family: inherit;
+            font-size: 1em;
+            cursor: pointer;
+        }
+        .input-form button:hover {
+            background: #666;
+        }
+        .info {
+            flex: 1;
+            padding: 32px 24px 24px 24px;
+            background: #1a1a1a;
+        }
+        .info h2 {
+            color: #ff79c6;
+            font-size: 1.2em;
+            margin-top: 0;
+        }
+        .info pre {
+            background: #222;
+            color: #e0e0e0;
+            padding: 12px;
+            border-radius: 6px;
+            font-size: 0.98em;
+            overflow-x: auto;
+        }
+    </style>
+</head>
+<body>
+<div class="container">
+    <div class="chat">
+        <div class="chat-history">
+            {% for user, bot, conf, matched_q in chat_history %}
+                <div class="chat-entry">
+                    <span class="user">You:</span> {{ user }}<br>
+                    <span class="bot">Bot:</span> {{ bot }} <span class="confidence">(similarity: {{ '%.2f'|format(conf) }})</span><br>
+                    <span class="matched-q">Matched Q: {{ matched_q }}</span>
+                </div>
+            {% else %}
+                <div class="chat-entry bot">Type your medical question below.</div>
+            {% endfor %}
+        </div>
+        <form class="input-form" action="/chat" method="post" autocomplete="off">
+            <input type="text" name="user_input" placeholder="Ask a medical question..." required autofocus>
+            <button type="submit">Send</button>
+        </form>
+    </div>
+    <div class="info">
+        <h2>Info</h2>
+        <pre>
+Model: SentenceTransformer (all-MiniLM-L6-v2)
+Retrieval: Cosine Similarity
+Data: medquad_full.json
+Disclaimer: This is a demo. For real medical advice, consult a professional.
+        </pre>
+    </div>
+</div>
+</body>
+</html>

web_terminal_chat.py ADDED Viewed

	@@ -0,0 +1,60 @@

+import uvicorn
+from fastapi import FastAPI, Request, Form
+from fastapi.responses import HTMLResponse, RedirectResponse
+from fastapi.templating import Jinja2Templates
+import os
+import json
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+import numpy as np
+app = FastAPI()
+# Templates
+BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+templates = Jinja2Templates(directory=os.path.join(BASE_DIR, "templates"))
+# Chatverlauf im Speicher (nur für Demo, nicht persistent)
+chat_history = []
+last_confidence = None
+last_matched_question = None
+# Embedding-Modell und Daten laden
+with open(os.path.join(BASE_DIR, 'medquad_full.json'), 'r', encoding='utf-8') as f:
+    faq_data = json.load(f)
+questions = [item['question'] for item in faq_data]
+answers = [item['answer'] for item in faq_data]
+model = SentenceTransformer('all-MiniLM-L6-v2')
+question_embeddings = model.encode(questions, show_progress_bar=True, convert_to_numpy=True)
+def retrieve_answer(user_question):
+    user_emb = model.encode([user_question], convert_to_numpy=True)
+    sims = cosine_similarity(user_emb, question_embeddings)[0]
+    best_idx = int(np.argmax(sims))
+    best_score = float(sims[best_idx])
+    best_question = questions[best_idx]
+    answer = answers[best_idx]
+    return answer, best_score, best_question
+@app.get("/", response_class=HTMLResponse)
+def index(request: Request):
+    return templates.TemplateResponse("terminal_chat.html", {
+        "request": request,
+        "chat_history": chat_history,
+        "accuracy": None,  # Nicht mehr relevant
+        "last_confidence": last_confidence,
+        "last_matched_question": last_matched_question,
+    })
+@app.post("/chat", response_class=HTMLResponse)
+def chat(request: Request, user_input: str = Form(...)):
+    global last_confidence, last_matched_question
+    answer, conf, matched_q = retrieve_answer(user_input)
+    chat_history.append((user_input, answer, conf, matched_q))
+    last_confidence = conf
+    last_matched_question = matched_q
+    return RedirectResponse("/", status_code=303)
+if __name__ == "__main__":
+    uvicorn.run("web_terminal_chat:app", host="127.0.0.1", port=8000, reload=True)