Initial commit

templates/python-backend/flask-chat.py

@@ -0,0 +1,119 @@
+"""
+TheSys Generative UI - Flask Backend Example
+
+This example demonstrates how to set up a Flask backend that integrates
+with TheSys C1 API for streaming generative UI responses.
+
+Dependencies:
+    - flask
+    - flask-cors
+    - thesys-genui-sdk
+    - openai
+    - python-dotenv
+"""
+
+from flask import Flask, request, Response, jsonify
+from flask_cors import CORS
+from thesys_genui_sdk import with_c1_response, write_content
+import openai
+import os
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+# Initialize Flask app
+app = Flask(__name__)
+
+# Configure CORS
+CORS(app, resources={
+    r"/api/*": {
+        "origins": "*",  # Configure for your frontend URL in production
+        "allow_headers": "*",
+        "expose_headers": "*"
+    }
+})
+
+# Initialize OpenAI client for TheSys C1 API
+client = openai.OpenAI(
+    base_url="https://api.thesys.dev/v1/embed",
+    api_key=os.getenv("THESYS_API_KEY")
+)
+
+
+@app.route("/")
+def root():
+    """Health check endpoint"""
+    return jsonify({
+        "status": "ok",
+        "message": "TheSys C1 API Backend is running"
+    })
+
+
+@app.route("/api/chat", methods=["POST"])
+@with_c1_response  # Automatically handles streaming headers
+def chat():
+    """
+    Streaming chat endpoint that generates UI components.
+
+    Request JSON:
+        {
+            "prompt": str,
+            "thread_id": str (optional),
+            "response_id": str (optional)
+        }
+
+    Returns:
+        StreamingResponse with C1-formatted UI chunks
+    """
+    try:
+        data = request.get_json()
+        prompt = data.get("prompt")
+
+        if not prompt:
+            return jsonify({"error": "Prompt is required"}), 400
+
+        # Create streaming completion request
+        stream = client.chat.completions.create(
+            model="c1/openai/gpt-5/v-20250930",
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are a helpful AI assistant that creates interactive user interfaces."
+                },
+                {
+                    "role": "user",
+                    "content": prompt
+                }
+            ],
+            stream=True,
+            temperature=0.7,
+            max_tokens=4096
+        )
+
+        # Stream chunks to frontend
+        def generate():
+            for chunk in stream:
+                content = chunk.choices[0].delta.content
+                if content:
+                    yield write_content(content)
+
+        return Response(
+            generate(),
+            mimetype="text/event-stream"
+        )
+
+    except Exception as e:
+        return jsonify({
+            "error": str(e),
+            "message": "Failed to generate response"
+        }), 500
+
+
+if __name__ == "__main__":
+    # Run the server
+    app.run(
+        host="0.0.0.0",
+        port=5000,
+        debug=True
+    )