chore: import upstream snapshot with attribution

03-GettingStarted/14-sampling/code/python/server.py

@@ -0,0 +1,69 @@
+from starlette.applications import Starlette
+from starlette.routing import Mount, Host
+
+from mcp.server.fastmcp import Context, FastMCP
+
+from mcp.server.session import ServerSession
+from mcp.types import SamplingMessage, TextContent
+
+import json
+
+
+from uuid import uuid4
+from typing import List
+from pydantic import BaseModel
+
+
+mcp = FastMCP("Blog post generator")
+
+# app = FastAPI()
+
+posts = []
+
+class BlogPost(BaseModel):
+    id: int
+    title: str
+    content: str
+    abstract: str
+
+posts: List[BlogPost] = []
+
+@mcp.tool()
+async def create_blog(title: str, content: str, ctx: Context[ServerSession, None]) -> str:
+    """Create a blog post and generate a summary"""
+
+    post = BlogPost(
+        id=len(posts) + 1,
+        title=title,
+        content=content,
+        abstract=""
+    )
+
+    prompt = f"Create an abstract of the following blog post: title: {title} and draft: {content} "
+
+    result = await ctx.session.create_message(
+        messages=[
+            SamplingMessage(
+                role="user",
+                content=TextContent(type="text", text=prompt),
+            )
+        ],
+        max_tokens=100,
+    )
+
+    post.abstract = result.content.text
+
+    posts.append(post)
+
+    # return the complete blog post
+    return json.dumps({
+        "id": post.title,
+        "abstract": post.abstract
+    })
+
+if __name__ == "__main__":
+    print("Starting server...")
+    # mcp.run()
+    mcp.run(transport="streamable-http")
+
+# run app with: python server.py