docs/python: fix snippets and is_prime example

1_python/1_getting-started/project-setup.md

@@ -94,7 +94,7 @@ SERVER_API_HOST = "localhost:1234"
 if lms.Client.is_valid_api_host(SERVER_API_HOST):
     print(f"An LM Studio API server instance is available at {SERVER_API_HOST}")
 else:
-    print("No LM Studio API server instance found at {SERVER_API_HOST}")
+    print(f"No LM Studio API server instance found at {SERVER_API_HOST}")
 ```
 
 ```python tab="Python (asynchronous API)"
@@ -106,7 +106,7 @@ SERVER_API_HOST = "localhost:1234"
 if await lms.AsyncClient.is_valid_api_host(SERVER_API_HOST):
     print(f"An LM Studio API server instance is available at {SERVER_API_HOST}")
 else:
-    print("No LM Studio API server instance found at {SERVER_API_HOST}")
+    print(f"No LM Studio API server instance found at {SERVER_API_HOST}")
 ```
 
 ### Determining the default local API server port
@@ -124,7 +124,7 @@ import lmstudio as lms
 api_host = lms.Client.find_default_local_api_host()
 if api_host is not None:
     print(f"An LM Studio API server instance is available at {api_host}")
-  else:
+else:
     print("No LM Studio API server instance found on any of the default local ports")
 ```
 
@@ -136,6 +136,6 @@ import lmstudio as lms
 api_host = await lms.AsyncClient.find_default_local_api_host()
 if api_host is not None:
     print(f"An LM Studio API server instance is available at {api_host}")
-  else:
+else:
     print("No LM Studio API server instance found on any of the default local ports")
 ```

1_python/1_getting-started/repl.md

@@ -15,7 +15,7 @@ which use `with` statements to ensure deterministic cleanup of network communica
 resources).
 
 The convenience API allows the standard Python REPL, or more flexible alternatives like
-Juypter Notebooks, to be used to interact with AI models loaded into LM Studio. For
+Jupyter Notebooks, to be used to interact with AI models loaded into LM Studio. For
 example:
 
 ```python title="Python REPL"
@@ -27,7 +27,6 @@ example:
   0 LLM(identifier='qwen2.5-7b-instruct')
 >>> model = loaded_models[0]
 >>> chat = lms.Chat("You answer questions concisely")
->>> chat = lms.Chat("You answer questions concisely")
 >>> chat.add_user_message("Tell me three fruits")
 UserMessage(content=[TextData(text='Tell me three fruits')])
 >>> print(model.respond(chat, on_message=chat.append))

1_python/2_agent/act.md

@@ -85,7 +85,7 @@ def is_prime(n: int) -> bool:
     if n < 2:
         return False
     sqrt = int(math.sqrt(n))
-    for i in range(2, sqrt):
+    for i in range(2, sqrt + 1):
         if n % i == 0:
             return False
     return True
@@ -116,7 +116,7 @@ def create_file(name: str, content: str):
     try:
         dest_path.write_text(content, encoding="utf-8")
     except Exception as exc:
-        return "Error: {exc!r}"
+        return f"Error: {exc!r}"
     return "File created."
 
 def print_fragment(fragment, round_index=0):

1_python/2_agent/tools.md

@@ -84,7 +84,7 @@ def create_file(name: str, content: str):
     try:
         dest_path.write_text(content, encoding="utf-8")
     except Exception as exc:
-        return "Error: {exc!r}"
+        return f"Error: {exc!r}"
     return "File created."
 ```
 
@@ -124,7 +124,7 @@ def divide(numerator: float, denominator: float) -> float:
     return numerator / denominator
 
 model = lms.llm("qwen2.5-7b-instruct")
-chat = Chat()
+chat = lms.Chat()
 chat.add_user_message(
     "Attempt to divide 1 by 0 using the tool. Explain the result."
 )
@@ -134,7 +134,7 @@ def _raise_exc_in_client(
 ) -> None:
     raise exc
 
-act_result = llm.act(
+act_result = model.act(
     chat,
     [divide],
     handle_invalid_tool_request=_raise_exc_in_client,