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docs: add pre/post processing docs for langchain python (#2378)
## Description Trigger has been tested corresponding to local changes. Latest successful run: https://pantheon.corp.google.com/cloud-build/builds;region=global/1c37031f-95f1-4c6c-9ef8-0452277599d5?e=13802955&mods=-autopush_coliseum&project=toolbox-testing-438616 Note: After merging, update python pre and post processing sample testing trigger. ## PR Checklist > Thank you for opening a Pull Request! Before submitting your PR, there are a > few things you can do to make sure it goes smoothly: - [x] Make sure you reviewed [CONTRIBUTING.md](https://github.com/googleapis/genai-toolbox/blob/main/CONTRIBUTING.md) - [ ] Make sure to open an issue as a [bug/issue](https://github.com/googleapis/genai-toolbox/issues/new/choose) before writing your code! That way we can discuss the change, evaluate designs, and agree on the general idea - [ ] Ensure the tests and linter pass - [ ] Code coverage does not decrease (if any source code was changed) - [ ] Appropriate docs were updated (if necessary) - [ ] Make sure to add `!` if this involve a breaking change 🛠️ Fixes #<issue_number_goes_here> --------- Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> Co-authored-by: Yuan Teoh <45984206+Yuan325@users.noreply.github.com> Co-authored-by: Averi Kitsch <akitsch@google.com>
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docs/en/samples/pre_post_processing/python/__init__.py
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docs/en/samples/pre_post_processing/python/__init__.py
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# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file makes the 'pre_post_processing/python' directory a Python package.
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# You can include any package-level initialization logic here if needed.
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# For now, this file is empty.
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docs/en/samples/pre_post_processing/python/agent_test.py
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docs/en/samples/pre_post_processing/python/agent_test.py
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# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import asyncio
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import importlib
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import os
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from pathlib import Path
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import pytest
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ORCH_NAME = os.environ.get("ORCH_NAME")
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module_path = f"python.{ORCH_NAME}.agent"
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agent = importlib.import_module(module_path)
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GOLDEN_KEYWORDS = [
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"AI:",
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"Loyalty Points",
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"POLICY CHECK: Intercepting 'update-hotel'",
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]
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# --- Execution Tests ---
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class TestExecution:
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"""Test framework execution and output validation."""
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@pytest.fixture(scope="function")
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def script_output(self, capsys):
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"""Run the agent function and return its output."""
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asyncio.run(agent.main())
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return capsys.readouterr()
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def test_script_runs_without_errors(self, script_output):
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"""Test that the script runs and produces no stderr."""
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assert script_output.err == "", f"Script produced stderr: {script_output.err}"
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def test_keywords_in_output(self, script_output):
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"""Test that expected keywords are present in the script's output."""
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output = script_output.out
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print(f"\nAgent Output:\n{output}\n")
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missing_keywords = [kw for kw in GOLDEN_KEYWORDS if kw not in output]
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assert not missing_keywords, f"Missing keywords in output: {missing_keywords}"
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docs/en/samples/pre_post_processing/python/langchain/agent.py
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docs/en/samples/pre_post_processing/python/langchain/agent.py
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import asyncio
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from datetime import datetime
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from langchain.agents import create_agent
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from langchain.agents.middleware import wrap_tool_call
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from langchain_core.messages import ToolMessage
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from langchain_google_vertexai import ChatVertexAI
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from toolbox_langchain import ToolboxClient
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system_prompt = """
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You're a helpful hotel assistant. You handle hotel searching, booking and
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cancellations. When the user searches for a hotel, mention it's name, id,
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location and price tier. Always mention hotel ids while performing any
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searches. This is very important for any operations. For any bookings or
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cancellations, please provide the appropriate confirmation. Be sure to
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update checkin or checkout dates if mentioned by the user.
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Don't ask for confirmations from the user.
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"""
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# Pre processing
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@wrap_tool_call
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async def enforce_business_rules(request, handler):
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"""
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Business Logic Validation:
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Enforces max stay duration (e.g., max 14 days).
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"""
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tool_call = request.tool_call
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name = tool_call["name"]
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args = tool_call["args"]
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print(f"POLICY CHECK: Intercepting '{name}'")
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if name == "update-hotel":
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if "checkin_date" in args and "checkout_date" in args:
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try:
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start = datetime.fromisoformat(args["checkin_date"])
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end = datetime.fromisoformat(args["checkout_date"])
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duration = (end - start).days
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if duration > 14:
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print("BLOCKED: Stay too long")
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return ToolMessage(
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content="Error: Maximum stay duration is 14 days.",
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tool_call_id=tool_call["id"],
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)
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except ValueError:
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pass # Ignore invalid date formats
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# PRE: Code here runs BEFORE the tool execution
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# EXEC: Execute the tool (or next middleware)
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result = await handler(request)
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# POST: Code here runs AFTER the tool execution
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return result
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# Post processing
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@wrap_tool_call
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async def enrich_response(request, handler):
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"""
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Post-Processing & Enrichment:
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Adds loyalty points information to successful bookings.
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Standardizes output format.
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"""
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# PRE: Code here runs BEFORE the tool execution
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# EXEC: Execute the tool (or next middleware)
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result = await handler(request)
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# POST: Code here runs AFTER the tool execution
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if isinstance(result, ToolMessage):
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content = str(result.content)
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tool_name = request.tool_call["name"]
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if tool_name == "book-hotel" and "Error" not in content:
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loyalty_bonus = 500
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result.content = f"Booking Confirmed!\n You earned {loyalty_bonus} Loyalty Points with this stay.\n\nSystem Details: {content}"
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return result
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async def main():
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async with ToolboxClient("http://127.0.0.1:5000") as client:
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tools = await client.aload_toolset("my-toolset")
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model = ChatVertexAI(model="gemini-2.5-flash")
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agent = create_agent(
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system_prompt=system_prompt,
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model=model,
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tools=tools,
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# add any pre and post processing methods
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middleware=[enforce_business_rules, enrich_response],
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)
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user_input = "Book hotel with id 3."
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response = await agent.ainvoke(
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{"messages": [{"role": "user", "content": user_input}]}
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)
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print("-" * 50)
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last_ai_msg = response["messages"][-1].content
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print(f"AI: {last_ai_msg}")
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# Test Pre-processing
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print("-" * 50)
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user_input = "Update my hotel with id 3 with checkin date 2025-01-18 and checkout date 2025-01-20"
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response = await agent.ainvoke(
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{"messages": [{"role": "user", "content": user_input}]}
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)
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last_ai_msg = response["messages"][-1].content
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print(f"AI: {last_ai_msg}")
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if __name__ == "__main__":
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asyncio.run(main())
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@@ -0,0 +1,3 @@
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langchain==1.2.6
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langchain-google-vertexai==3.2.2
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toolbox-langchain==0.5.8
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