docs: add pre/post processing docs for langchain python

docs/en/samples/pre_post_processing/python/__init__.py

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+# This file makes the 'pre_post_processing/python' directory a Python package.
+
+# You can include any package-level initialization logic here if needed.
+# For now, this file is empty.

docs/en/samples/pre_post_processing/python/agent_test.py

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+# Copyright 2026 Google LLC
+# 
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+# 
+#      http://www.apache.org/licenses/LICENSE-2.0
+# 
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import pytest
+from pathlib import Path
+import asyncio
+import sys
+import importlib.util
+
+ORCH_NAME = os.environ.get("ORCH_NAME")
+module_path = f"python.{ORCH_NAME}.agent"
+agent = importlib.import_module(module_path)
+
+
+@pytest.fixture(scope="module")
+def golden_keywords():
+    """Loads expected keywords from the golden.txt file."""
+    golden_file_path = Path(__file__).resolve().parent.parent / "golden.txt"
+    if not golden_file_path.exists():
+        pytest.fail(f"Golden file not found: {golden_file_path}")
+    try:
+        with open(golden_file_path, 'r') as f:
+            return [line.strip() for line in f.readlines() if line.strip()]
+    except Exception as e:
+        pytest.fail(f"Could not read golden.txt: {e}")
+
+
+# --- Execution Tests ---
+class TestExecution:
+    """Test framework execution and output validation."""
+
+    @pytest.fixture(scope="function")
+    def script_output(self, capsys):
+        """Run the agent function and return its output."""
+        asyncio.run(agent.main())
+        return capsys.readouterr()
+
+    def test_script_runs_without_errors(self, script_output):
+        """Test that the script runs and produces no stderr."""
+        assert script_output.err == "", f"Script produced stderr: {script_output.err}"
+
+    def test_keywords_in_output(self, script_output, golden_keywords):
+        """Test that expected keywords are present in the script's output."""
+        output = script_output.out
+        missing_keywords = [kw for kw in golden_keywords if kw not in output]
+        assert not missing_keywords, f"Missing keywords in output: {missing_keywords}"

docs/en/samples/pre_post_processing/python/langchain/__init__.py

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+# LangChain sample package

docs/en/samples/pre_post_processing/python/langchain/agent.py

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+import asyncio
+import re
+import json
+from typing import Callable, Any
+from toolbox_langchain import ToolboxClient
+from toolbox_core.protocol import Protocol
+from langchain_google_vertexai import ChatVertexAI
+from langchain_core.messages import ToolMessage, messages_to_dict
+from langchain.agents import create_agent
+from langchain.agents.middleware import (
+    wrap_tool_call,
+    AgentState
+)
+
+system_prompt = """
+  You're a helpful hotel assistant. You handle hotel searching, booking and
+  cancellations. When the user searches for a hotel, mention it's name, id,
+  location and price tier. Always mention hotel ids while performing any
+  searches. This is very important for any operations. For any bookings or
+  cancellations, please provide the appropriate confirmation. Be sure to
+  update checkin or checkout dates if mentioned by the user.
+  Don't ask for confirmations from the user.
+"""
+
+# Pre processing
+@wrap_tool_call
+async def enforce_business_rules(request, handler):
+    """
+    Business Logic Validation:
+    Enforces max stay duration (e.g., max 14 days).
+    """
+    tool_call = request.tool_call
+    name = tool_call["name"]
+    args = tool_call["args"]
+
+    print(f"POLICY CHECK: Intercepting '{name}'")
+
+    if name == "book-hotel":
+        if "duration_days" in args and int(args["duration_days"]) > 14:
+             print("BLOCKED: Stay too long")
+             return ToolMessage(
+                 content="Error: Maximum stay duration is 14 days.",
+                 tool_call_id=tool_call["id"]
+             )
+
+    return await handler(request)
+
+# Post processing
+@wrap_tool_call
+async def enrich_response(request, handler):
+    """
+    Post-Processing & Enrichment:
+    Adds loyalty points information to successful bookings.
+    Standardizes output format.
+    """
+    result = await handler(request)
+
+    if isinstance(result, ToolMessage):
+        content = str(result.content)
+        tool_name = request.tool_call["name"]
+
+        if tool_name == "book-hotel" and "Error" not in content:
+            loyalty_bonus = 500
+            result.content = f"Booking Confirmed! \n You earned {loyalty_bonus} Loyalty Points with this stay.\n\nSystem Details: {content}"
+
+    return result
+
+
+async def main():
+    async with ToolboxClient("http://127.0.0.1:5000") as client:
+        tools = await client.aload_toolset("my-toolset")
+        model = ChatVertexAI(model="gemini-2.5-flash")
+        agent = create_agent(
+            system_prompt=system_prompt,
+            model=model,
+            tools=tools,
+            middleware=[
+                enforce_business_rules,
+                enrich_response
+            ],
+        )
+
+        user_input = "Book hotel with id 3."
+        response = await agent.ainvoke({"messages": [{"role": "user", "content": user_input}]})
+
+        print("-" * 50)
+        print("Final Client Response:")
+        serializable_response = {
+            "messages": messages_to_dict(response["messages"])
+        }
+        last_ai_msg = response["messages"][-1].content
+        print(f"AI: {last_ai_msg}")
+
+if __name__ == "__main__":
+    asyncio.run(main())

docs/en/samples/pre_post_processing/python/langchain/requirements.txt

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+langchain==1.2.6
+toolbox-langchain==0.5.7