Google Search API integration with serper.dev (wrapper, tests, docs, … (#909)

Adds Google Search integration with [Serper](https://serper.dev) a
low-cost alternative to SerpAPI (10x cheaper + generous free tier).
Includes documentation, tests and examples. Hopefully I am not missing
anything.

Developers can sign up for a free account at
[serper.dev](https://serper.dev) and obtain an api key.

## Usage

```python
from langchain.utilities import GoogleSerperAPIWrapper
from langchain.llms.openai import OpenAI
from langchain.agents import initialize_agent, Tool

import os
os.environ["SERPER_API_KEY"] = ""
os.environ['OPENAI_API_KEY'] = ""

llm = OpenAI(temperature=0)
search = GoogleSerperAPIWrapper()
tools = [
    Tool(
        name="Intermediate Answer",
        func=search.run
    )
]

self_ask_with_search = initialize_agent(tools, llm, agent="self-ask-with-search", verbose=True)
self_ask_with_search.run("What is the hometown of the reigning men's U.S. Open champion?")
```

### Output
```
Entering new AgentExecutor chain...
 Yes.
Follow up: Who is the reigning men's U.S. Open champion?
Intermediate answer: Current champions Carlos Alcaraz, 2022 men's singles champion.
Follow up: Where is Carlos Alcaraz from?
Intermediate answer: El Palmar, Spain
So the final answer is: El Palmar, Spain

> Finished chain.

'El Palmar, Spain'
```
searx-api
rogerserper 1 year ago committed by GitHub
parent 52753066ef
commit e46cd3b7db
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23

@ -0,0 +1,70 @@
# Google Serper Wrapper
This page covers how to use the [Serper](https://serper.dev) Google Search API within LangChain. Serper is a low-cost Google Search API that can be used to add answer box, knowledge graph, and organic results data from Google Search.
It is broken into two parts: setup, and then references to the specific Google Serper wrapper.
## Setup
- Go to [serper.dev](https://serper.dev) to sign up for a free account
- Get the api key and set it as an environment variable (`SERPER_API_KEY`)
## Wrappers
### Utility
There exists a GoogleSerperAPIWrapper utility which wraps this API. To import this utility:
```python
from langchain.utilities import GoogleSerperAPIWrapper
```
You can use it as part of a Self Ask chain:
```python
from langchain.utilities import GoogleSerperAPIWrapper
from langchain.llms.openai import OpenAI
from langchain.agents import initialize_agent, Tool
import os
os.environ["SERPER_API_KEY"] = ""
os.environ['OPENAI_API_KEY'] = ""
llm = OpenAI(temperature=0)
search = GoogleSerperAPIWrapper()
tools = [
Tool(
name="Intermediate Answer",
func=search.run
)
]
self_ask_with_search = initialize_agent(tools, llm, agent="self-ask-with-search", verbose=True)
self_ask_with_search.run("What is the hometown of the reigning men's U.S. Open champion?")
```
#### Output
```
Entering new AgentExecutor chain...
Yes.
Follow up: Who is the reigning men's U.S. Open champion?
Intermediate answer: Current champions Carlos Alcaraz, 2022 men's singles champion.
Follow up: Where is Carlos Alcaraz from?
Intermediate answer: El Palmar, Spain
So the final answer is: El Palmar, Spain
> Finished chain.
'El Palmar, Spain'
```
For a more detailed walkthrough of this wrapper, see [this notebook](../modules/utils/examples/google_serper.ipynb).
### Tool
You can also easily load this wrapper as a Tool (to use with an Agent).
You can do this with:
```python
from langchain.agents import load_tools
tools = load_tools(["google-serper"])
```
For more information on this, see [this page](../modules/agents/tools.md)

@ -12,9 +12,13 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "e6860c2d",
"metadata": {},
"metadata": {
"pycharm": {
"is_executing": true
}
},
"outputs": [],
"source": [
"from langchain.agents import load_tools\n",
@ -34,39 +38,111 @@
},
{
"cell_type": "markdown",
"id": "a09ca013",
"metadata": {},
"source": [
"## Google Serper API Wrapper\n",
"\n",
"First, let's try to use the Google Serper API tool."
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 4,
"outputs": [],
"source": [
"tools = load_tools([\"google-serper\"], llm=llm)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 5,
"outputs": [],
"source": [
"agent = initialize_agent(tools, llm, agent=\"zero-shot-react-description\", verbose=True)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 6,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n",
"\u001B[32;1m\u001B[1;3m I need to find out what the current weather is in Pomfret.\n",
"Action: Search\n",
"Action Input: \"weather in Pomfret\"\u001B[0m\n",
"Observation: \u001B[36;1m\u001B[1;3mShowers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%.\u001B[0m\n",
"Thought:\u001B[32;1m\u001B[1;3m I now know the current weather in Pomfret.\n",
"Final Answer: Showers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%.\u001B[0m\n",
"\u001B[1m> Finished AgentExecutor chain.\u001B[0m\n"
]
},
{
"data": {
"text/plain": [
"'Showers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%.'"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"agent.run(\"What is the weather in Pomfret?\")"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "markdown",
"source": [
"## SerpAPI\n",
"\n",
"First, let's use the SerpAPI tool."
]
"Now, let's use the SerpAPI tool."
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 4,
"id": "dd4ce6d9",
"metadata": {},
"outputs": [],
"source": [
"tools = load_tools([\"serpapi\"], llm=llm)"
]
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 5,
"id": "ef63bb84",
"metadata": {},
"outputs": [],
"source": [
"agent = initialize_agent(tools, llm, agent=\"zero-shot-react-description\", verbose=True)"
]
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 6,
"id": "53e24f5d",
"metadata": {},
"outputs": [
{
"name": "stdout",
@ -74,14 +150,14 @@
"text": [
"\n",
"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3m I need to find out what the current weather is in Pomfret.\n",
"\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n",
"\u001B[32;1m\u001B[1;3m I need to find out what the current weather is in Pomfret.\n",
"Action: Search\n",
"Action Input: \"weather in Pomfret\"\u001b[0m\n",
"Observation: \u001b[36;1m\u001b[1;3mShowers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%.\u001b[0m\n",
"Thought:\u001b[32;1m\u001b[1;3m I now know the current weather in Pomfret.\n",
"Final Answer: Showers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%.\u001b[0m\n",
"\u001b[1m> Finished AgentExecutor chain.\u001b[0m\n"
"Action Input: \"weather in Pomfret\"\u001B[0m\n",
"Observation: \u001B[36;1m\u001B[1;3mShowers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%.\u001B[0m\n",
"Thought:\u001B[32;1m\u001B[1;3m I now know the current weather in Pomfret.\n",
"Final Answer: Showers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%.\u001B[0m\n",
"\u001B[1m> Finished AgentExecutor chain.\u001B[0m\n"
]
},
{
@ -97,43 +173,47 @@
],
"source": [
"agent.run(\"What is the weather in Pomfret?\")"
]
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "markdown",
"id": "8ef49137",
"metadata": {},
"source": [
"## GoogleSearchAPIWrapper\n",
"\n",
"Now, let's use the official Google Search API Wrapper."
]
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 13,
"id": "3e9c7c20",
"metadata": {},
"outputs": [],
"source": [
"tools = load_tools([\"google-search\"], llm=llm)"
]
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 14,
"id": "b83624dc",
"metadata": {},
"outputs": [],
"source": [
"agent = initialize_agent(tools, llm, agent=\"zero-shot-react-description\", verbose=True)"
]
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 17,
"id": "9d5835e2",
"metadata": {},
"outputs": [
{
"name": "stdout",
@ -141,14 +221,14 @@
"text": [
"\n",
"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3m I should look up the current weather conditions.\n",
"\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n",
"\u001B[32;1m\u001B[1;3m I should look up the current weather conditions.\n",
"Action: Google Search\n",
"Action Input: \"weather in Pomfret\"\u001b[0m\n",
"Observation: \u001b[36;1m\u001b[1;3mShowers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%. Pomfret, CT Weather Forecast, with current conditions, wind, air quality, and what to expect for the next 3 days. Hourly Weather-Pomfret, CT. As of 12:52 am EST. Special Weather Statement +2 ... Hazardous Weather Conditions. Special Weather Statement ... Pomfret CT. Tonight ... National Digital Forecast Database Maximum Temperature Forecast. Pomfret Center Weather Forecasts. Weather Underground provides local & long-range weather forecasts, weatherreports, maps & tropical weather conditions for ... Pomfret, CT 12 hour by hour weather forecast includes precipitation, temperatures, sky conditions, rain chance, dew-point, relative humidity, wind direction ... North Pomfret Weather Forecasts. Weather Underground provides local & long-range weather forecasts, weatherreports, maps & tropical weather conditions for ... Today's Weather - Pomfret, CT. Dec 31, 2022 4:00 PM. Putnam MS. --. Weather forecast icon. Feels like --. Hi --. Lo --. Pomfret, CT temperature trend for the next 14 Days. Find daytime highs and nighttime lows from TheWeatherNetwork.com. Pomfret, MD Weather Forecast Date: 332 PM EST Wed Dec 28 2022. The area/counties/county of: Charles, including the cites of: St. Charles and Waldorf.\u001b[0m\n",
"Thought:\u001b[32;1m\u001b[1;3m I now know the current weather conditions in Pomfret.\n",
"Final Answer: Showers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%.\u001b[0m\n",
"\u001b[1m> Finished AgentExecutor chain.\u001b[0m\n"
"Action Input: \"weather in Pomfret\"\u001B[0m\n",
"Observation: \u001B[36;1m\u001B[1;3mShowers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%. Pomfret, CT Weather Forecast, with current conditions, wind, air quality, and what to expect for the next 3 days. Hourly Weather-Pomfret, CT. As of 12:52 am EST. Special Weather Statement +2 ... Hazardous Weather Conditions. Special Weather Statement ... Pomfret CT. Tonight ... National Digital Forecast Database Maximum Temperature Forecast. Pomfret Center Weather Forecasts. Weather Underground provides local & long-range weather forecasts, weatherreports, maps & tropical weather conditions for ... Pomfret, CT 12 hour by hour weather forecast includes precipitation, temperatures, sky conditions, rain chance, dew-point, relative humidity, wind direction ... North Pomfret Weather Forecasts. Weather Underground provides local & long-range weather forecasts, weatherreports, maps & tropical weather conditions for ... Today's Weather - Pomfret, CT. Dec 31, 2022 4:00 PM. Putnam MS. --. Weather forecast icon. Feels like --. Hi --. Lo --. Pomfret, CT temperature trend for the next 14 Days. Find daytime highs and nighttime lows from TheWeatherNetwork.com. Pomfret, MD Weather Forecast Date: 332 PM EST Wed Dec 28 2022. The area/counties/county of: Charles, including the cites of: St. Charles and Waldorf.\u001B[0m\n",
"Thought:\u001B[32;1m\u001B[1;3m I now know the current weather conditions in Pomfret.\n",
"Final Answer: Showers early becoming a steady light rain later in the day. Near record high temperatures. High around 60F. Winds SW at 10 to 15 mph. Chance of rain 60%.\u001B[0m\n",
"\u001B[1m> Finished AgentExecutor chain.\u001B[0m\n"
]
},
{
@ -164,7 +244,10 @@
],
"source": [
"agent.run(\"What is the weather in Pomfret?\")"
]
],
"metadata": {
"collapsed": false
}
}
],
"metadata": {

@ -119,3 +119,12 @@ Below is a list of all supported tools and relevant information:
- Requires LLM: No
- Extra Parameters: `google_api_key`, `google_cse_id`
- For more information on this, see [this page](../../ecosystem/google_search.md)
**google-serper**
- Tool Name: Search
- Tool Description: A low-cost Google Search API. Useful for when you need to answer questions about current events. Input should be a search query.
- Notes: Calls the [serper.dev](https://serper.dev) Google Search API and then parses results.
- Requires LLM: No
- Extra Parameters: `serper_api_key`
- For more information on this, see [this page](../../ecosystem/google_serper.md)

@ -0,0 +1,157 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "dc23c48e",
"metadata": {},
"source": [
"# Google Serper API\n",
"\n",
"This notebook goes over how to use the Google Serper component to search the web. First you need to sign up for a free account at [serper.dev](https://serper.dev) and get your api key."
]
},
{
"cell_type": "code",
"execution_count": null,
"outputs": [],
"source": [
"import os\n",
"os.environ[\"SERPER_API_KEY\"] = \"\""
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 2,
"id": "54bf5afd",
"metadata": {},
"outputs": [],
"source": [
"from langchain.utilities import GoogleSerperAPIWrapper"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "31f8f382",
"metadata": {},
"outputs": [],
"source": [
"search = GoogleSerperAPIWrapper()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "25ce0225",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "'Barack Hussein Obama II'"
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"search.run(\"Obama's first name?\")"
]
},
{
"cell_type": "markdown",
"source": [
"## As part of a Self Ask With Search Chain"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": null,
"outputs": [],
"source": [
"os.environ['OPENAI_API_KEY'] = \"\""
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 5,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n",
"\u001B[32;1m\u001B[1;3m Yes.\n",
"Follow up: Who is the reigning men's U.S. Open champion?\u001B[0m\n",
"Intermediate answer: \u001B[36;1m\u001B[1;3mCurrent champions Carlos Alcaraz, 2022 men's singles champion.\u001B[0m\n",
"\u001B[32;1m\u001B[1;3mFollow up: Where is Carlos Alcaraz from?\u001B[0m\n",
"Intermediate answer: \u001B[36;1m\u001B[1;3mEl Palmar, Spain\u001B[0m\n",
"\u001B[32;1m\u001B[1;3mSo the final answer is: El Palmar, Spain\u001B[0m\n",
"\n",
"\u001B[1m> Finished chain.\u001B[0m\n"
]
},
{
"data": {
"text/plain": "'El Palmar, Spain'"
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langchain.utilities import GoogleSerperAPIWrapper\n",
"from langchain.llms.openai import OpenAI\n",
"from langchain.agents import initialize_agent, Tool\n",
"\n",
"llm = OpenAI(temperature=0)\n",
"search = GoogleSerperAPIWrapper()\n",
"tools = [\n",
" Tool(\n",
" name=\"Intermediate Answer\",\n",
" func=search.run\n",
" )\n",
"]\n",
"\n",
"self_ask_with_search = initialize_agent(tools, llm, agent=\"self-ask-with-search\", verbose=True)\n",
"self_ask_with_search.run(\"What is the hometown of the reigning men's U.S. Open champion?\")"
],
"metadata": {
"collapsed": false
}
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

@ -42,6 +42,7 @@ from langchain.prompts import (
from langchain.serpapi import SerpAPIChain, SerpAPIWrapper
from langchain.sql_database import SQLDatabase
from langchain.utilities.google_search import GoogleSearchAPIWrapper
from langchain.utilities.google_serper import GoogleSerperAPIWrapper
from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
from langchain.vectorstores import FAISS, ElasticVectorSearch
@ -58,6 +59,7 @@ __all__ = [
"SerpAPIWrapper",
"SerpAPIChain",
"GoogleSearchAPIWrapper",
"GoogleSerperAPIWrapper",
"WolframAlphaAPIWrapper",
"Anthropic",
"CerebriumAI",

@ -13,6 +13,7 @@ from langchain.requests import RequestsWrapper
from langchain.serpapi import SerpAPIWrapper
from langchain.utilities.bash import BashProcess
from langchain.utilities.google_search import GoogleSearchAPIWrapper
from langchain.utilities.google_serper import GoogleSerperAPIWrapper
from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
@ -131,6 +132,14 @@ def _get_google_search(**kwargs: Any) -> Tool:
)
def _get_google_serper(**kwargs: Any) -> Tool:
return Tool(
"Search",
GoogleSerperAPIWrapper(**kwargs).run,
"A low-cost Google Search API. Useful for when you need to answer questions about current events. Input should be a search query.",
)
def _get_serpapi(**kwargs: Any) -> Tool:
return Tool(
name="Search",
@ -147,6 +156,7 @@ _EXTRA_LLM_TOOLS = {
_EXTRA_OPTIONAL_TOOLS = {
"wolfram-alpha": (_get_wolfram_alpha, ["wolfram_alpha_appid"]),
"google-search": (_get_google_search, ["google_api_key", "google_cse_id"]),
"google-serper": (_get_google_serper, ["serper_api_key"]),
"serpapi": (_get_serpapi, ["serpapi_api_key", "aiosession"]),
}

@ -1,5 +1,5 @@
"""Chain that does self ask with search."""
from typing import Any, List, Optional, Tuple
from typing import Any, List, Optional, Tuple, Union
from langchain.agents.agent import Agent, AgentExecutor
from langchain.agents.self_ask_with_search.prompt import PROMPT
@ -7,6 +7,7 @@ from langchain.agents.tools import Tool
from langchain.llms.base import BaseLLM
from langchain.prompts.base import BasePromptTemplate
from langchain.serpapi import SerpAPIWrapper
from langchain.utilities.google_serper import GoogleSerperAPIWrapper
class SelfAskWithSearchAgent(Agent):
@ -74,12 +75,17 @@ class SelfAskWithSearchChain(AgentExecutor):
Example:
.. code-block:: python
from langchain import SelfAskWithSearchChain, OpenAI, SerpAPIWrapper
search_chain = SerpAPIWrapper()
from langchain import SelfAskWithSearchChain, OpenAI, GoogleSerperAPIWrapper
search_chain = GoogleSerperAPIWrapper()
self_ask = SelfAskWithSearchChain(llm=OpenAI(), search_chain=search_chain)
"""
def __init__(self, llm: BaseLLM, search_chain: SerpAPIWrapper, **kwargs: Any):
def __init__(
self,
llm: BaseLLM,
search_chain: Union[GoogleSerperAPIWrapper, SerpAPIWrapper],
**kwargs: Any,
):
"""Initialize with just an LLM and a search chain."""
search_tool = Tool(name="Intermediate Answer", func=search_chain.run)
agent = SelfAskWithSearchAgent.from_llm_and_tools(llm, [search_tool])

@ -5,6 +5,7 @@ from langchain.serpapi import SerpAPIWrapper
from langchain.utilities.bash import BashProcess
from langchain.utilities.bing_search import BingSearchAPIWrapper
from langchain.utilities.google_search import GoogleSearchAPIWrapper
from langchain.utilities.google_serper import GoogleSerperAPIWrapper
from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
__all__ = [
@ -12,6 +13,7 @@ __all__ = [
"RequestsWrapper",
"PythonREPL",
"GoogleSearchAPIWrapper",
"GoogleSerperAPIWrapper",
"WolframAlphaAPIWrapper",
"SerpAPIWrapper",
"BingSearchAPIWrapper",

@ -0,0 +1,94 @@
"""Util that calls Google Search using the Serper.dev API."""
from typing import Dict, Optional
import requests
from pydantic.class_validators import root_validator
from pydantic.main import BaseModel
from langchain.utils import get_from_dict_or_env
class GoogleSerperAPIWrapper(BaseModel):
"""Wrapper around the Serper.dev Google Search API.
You can create a free API key at https://serper.dev.
To use, you should have the environment variable ``SERPER_API_KEY``
set with your API key, or pass `serper_api_key` as a named parameter
to the constructor.
Example:
.. code-block:: python
from langchain import GoogleSerperAPIWrapper
google_serper = GoogleSerperAPIWrapper()
"""
k: int = 10
gl: str = "us"
hl: str = "en"
serper_api_key: Optional[str] = None
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key exists in environment."""
serper_api_key = get_from_dict_or_env(
values, "serper_api_key", "SERPER_API_KEY"
)
values["serper_api_key"] = serper_api_key
return values
def run(self, query: str) -> str:
"""Run query through GoogleSearch and parse result."""
results = self._google_serper_search_results(query, gl=self.gl, hl=self.hl)
return self._parse_results(results)
def _parse_results(self, results: dict) -> str:
snippets = []
if results.get("answerBox"):
answer_box = results.get("answerBox", {})
if answer_box.get("answer"):
return answer_box.get("answer")
elif answer_box.get("snippet"):
return answer_box.get("snippet").replace("\n", " ")
elif answer_box.get("snippetHighlighted"):
return ", ".join(answer_box.get("snippetHighlighted"))
if results.get("knowledgeGraph"):
kg = results.get("knowledgeGraph", {})
title = kg.get("title")
entity_type = kg.get("type")
if entity_type:
snippets.append(f"{title}: {entity_type}.")
description = kg.get("description")
if description:
snippets.append(description)
for attribute, value in kg.get("attributes", {}).items():
snippets.append(f"{title} {attribute}: {value}.")
for result in results["organic"][: self.k]:
if "snippet" in result:
snippets.append(result["snippet"])
for attribute, value in result.get("attributes", {}).items():
snippets.append(f"{attribute}: {value}.")
if len(snippets) == 0:
return "No good Google Search Result was found"
return " ".join(snippets)
def _google_serper_search_results(self, search_term: str, gl: str, hl: str) -> dict:
headers = {
"X-API-KEY": self.serper_api_key or "",
"Content-Type": "application/json",
}
params = {"q": search_term, "gl": gl, "hl": hl}
response = requests.post(
"https://google.serper.dev/search", headers=headers, params=params
)
response.raise_for_status()
search_results = response.json()
return search_results

@ -1,7 +1,7 @@
"""Integration test for self ask with search."""
from langchain.agents.self_ask_with_search.base import SelfAskWithSearchChain
from langchain.llms.openai import OpenAI
from langchain.serpapi import SerpAPIWrapper
from langchain.utilities.google_serper import GoogleSerperAPIWrapper
def test_self_ask_with_search() -> None:
@ -9,7 +9,7 @@ def test_self_ask_with_search() -> None:
question = "What is the hometown of the reigning men's U.S. Open champion?"
chain = SelfAskWithSearchChain(
llm=OpenAI(temperature=0),
search_chain=SerpAPIWrapper(),
search_chain=GoogleSerperAPIWrapper(),
input_key="q",
output_key="a",
)

@ -0,0 +1,9 @@
"""Integration test for Serper.dev's Google Search API Wrapper."""
from langchain.utilities.google_serper import GoogleSerperAPIWrapper
def test_call() -> None:
"""Test that call gives the correct answer."""
search = GoogleSerperAPIWrapper()
output = search.run("What was Obama's first name?")
assert "Barack Hussein Obama II" in output
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