이 가이드는 Reka chat models 시작하기에 대한 간단한 개요를 제공합니다. Reka는 여러 chat model을 제공합니다. 최신 모델과 비용, context window, 지원되는 입력 타입에 대한 정보는 Reka docs에서 확인할 수 있습니다.

​
Overview

​
Integration details

ClassPackageLocalSerializableJS supportDownloadsVersion
[ChatReka]langchain_community✅❌❌PyPI - DownloadsPyPI - Version

​
Model features

Tool callingStructured outputJSON modeImage inputAudio inputVideo inputToken-level streamingNative asyncToken usageLogprobs
✅❌❌✅✅✅✅✅❌❌

​
Setup

Reka 모델에 접근하려면 Reka 개발자 계정을 생성하고, API key를 발급받고, langchain_community integration package와 ‘pip install reka-api’를 통해 reka python package를 설치해야 합니다.

​
Credentials

platform.reka.ai/로 이동하여 Reka에 가입하고 API key를 생성하세요. 완료한 후 REKA_API_KEY environment variable을 설정하세요:

​
Installation

LangChain ModuleName integration은 langchain_community package에 있습니다: 
pip install -qU langchain_community reka-api

Note: you may need to restart the kernel to use updated packages.

​
Instantiation

import getpass
import os

os.environ["REKA_API_KEY"] = getpass.getpass("Enter your Reka API key: ")
선택사항: LangSmith를 사용하여 모델 실행을 추적합니다 
import getpass
import os

os.environ["LANGSMITH_TRACING"] = "true"
os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")

from langchain_community.chat_models import ChatReka

model = ChatReka()

​
Invocation

model.invoke("hi")

AIMessage(content=' Hello! How can I help you today? If you have a question, need assistance, or just want to chat, feel free to let me know. Have a great day!\n\n', additional_kwargs={}, response_metadata={}, id='run-61522ec2-0587-4fd5-a492-5b205fd8860c-0')

​
Images input

from langchain.messages import HumanMessage

image_url = "https://v0.docs.reka.ai/_images/000000245576.jpg"

message = HumanMessage(
    content=[
        {"type": "text", "text": "describe the weather in this image"},
        {
            "type": "image_url",
            "image_url": {"url": image_url},
        },
    ],
)
response = model.invoke([message])
print(response.content)

 The image shows an indoor setting with no visible windows or natural light, and there are no indicators of weather conditions. The focus is on a cat sitting on a computer keyboard, and the background includes a computer monitor and various office supplies.

​
Multiple images as input

message = HumanMessage(
    content=[
        {"type": "text", "text": "What are the difference between the two images? "},
        {
            "type": "image_url",
            "image_url": {
                "url": "https://cdn.pixabay.com/photo/2019/07/23/13/51/shepherd-dog-4357790_1280.jpg"
            },
        },
        {
            "type": "image_url",
            "image_url": {
                "url": "https://cdn.pixabay.com/photo/2024/02/17/00/18/cat-8578562_1280.jpg"
            },
        },
    ],
)
response = model.invoke([message])
print(response.content)

 The first image features two German Shepherds, one adult and one puppy, in a vibrant, lush green setting. The adult dog is carrying a large stick in its mouth, running through what appears to be a grassy field, with the puppy following close behind. Both dogs exhibit striking physical characteristics typical of the breed, such as pointed ears and dense fur.

The second image shows a close-up of a single cat with striking blue eyes, likely a breed like the Siberian or Maine Coon, in a natural outdoor setting. The cat's fur is lighter, possibly a mix of white and gray, and it has a more subdued expression compared to the dogs. The background is blurred, suggesting a focus on the cat's face.

Overall, the differences lie in the subjects (two dogs vs. one cat), the setting (lush, vibrant grassy field vs. a more muted outdoor background), and the overall mood and activity depicted (playful and active vs. serene and focused).

​
Chaining

from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate(
    [
        (
            "system",
            "You are a helpful assistant that translates {input_language} to {output_language}.",
        ),
        ("human", "{input}"),
    ]
)

chain = prompt | model
chain.invoke(
    {
        "input_language": "English",
        "output_language": "German",
        "input": "I love programming.",
    }
)

AIMessage(content=' Ich liebe Programmieren.\n\n', additional_kwargs={}, response_metadata={}, id='run-ffc4ace1-b73a-4fb3-ad0f-57e60a0f9b8d-0')
Tavily api search와 함께 사용

​
Tool use and agent creation

​
Define the tools

먼저 사용할 tool을 생성해야 합니다. 주요 tool은 검색 엔진인 Tavily입니다. LangChain에는 Tavily 검색 엔진을 tool로 쉽게 사용할 수 있는 내장 tool이 있습니다. 
import getpass
import os

os.environ["TAVILY_API_KEY"] = getpass.getpass("Enter your Tavily API key: ")

from langchain_community.tools.tavily_search import TavilySearchResults

search = TavilySearchResults(max_results=2)
search_results = search.invoke("what is the weather in SF")
print(search_results)
# If we want, we can create other tools.
# Once we have all the tools we want, we can put them in a list that we will reference later.
tools = [search]

[{'url': 'https://www.weatherapi.com/', 'content': "{'location': {'name': 'San Francisco', 'region': 'California', 'country': 'United States of America', 'lat': 37.775, 'lon': -122.4183, 'tz_id': 'America/Los_Angeles', 'localtime_epoch': 1730484342, 'localtime': '2024-11-01 11:05'}, 'current': {'last_updated_epoch': 1730484000, 'last_updated': '2024-11-01 11:00', 'temp_c': 11.1, 'temp_f': 52.0, 'is_day': 1, 'condition': {'text': 'Mist', 'icon': '//cdn.weatherapi.com/weather/64x64/day/143.png', 'code': 1030}, 'wind_mph': 2.9, 'wind_kph': 4.7, 'wind_degree': 247, 'wind_dir': 'WSW', 'pressure_mb': 1019.0, 'pressure_in': 30.08, 'precip_mm': 0.0, 'precip_in': 0.0, 'humidity': 100, 'cloud': 100, 'feelslike_c': 11.1, 'feelslike_f': 52.0, 'windchill_c': 10.3, 'windchill_f': 50.5, 'heatindex_c': 10.8, 'heatindex_f': 51.5, 'dewpoint_c': 10.4, 'dewpoint_f': 50.6, 'vis_km': 2.8, 'vis_miles': 1.0, 'uv': 3.0, 'gust_mph': 3.8, 'gust_kph': 6.1}}"}, {'url': 'https://weatherspark.com/h/m/557/2024/1/Historical-Weather-in-January-2024-in-San-Francisco-California-United-States', 'content': 'San Francisco Temperature History January 2024\nHourly Temperature in January 2024 in San Francisco\nCompare San Francisco to another city:\nCloud Cover in January 2024 in San Francisco\nDaily Precipitation in January 2024 in San Francisco\nObserved Weather in January 2024 in San Francisco\nHours of Daylight and Twilight in January 2024 in San Francisco\nSunrise & Sunset with Twilight in January 2024 in San Francisco\nSolar Elevation and Azimuth in January 2024 in San Francisco\nMoon Rise, Set & Phases in January 2024 in San Francisco\nHumidity Comfort Levels in January 2024 in San Francisco\nWind Speed in January 2024 in San Francisco\nHourly Wind Speed in January 2024 in San Francisco\nHourly Wind Direction in 2024 in San Francisco\nAtmospheric Pressure in January 2024 in San Francisco\nData Sources\n See all nearby weather stations\nLatest Report — 1:56 PM\nFri, Jan 12, 2024\xa0\xa0\xa0\xa04 min ago\xa0\xa0\xa0\xa0UTC 21:56\nCall Sign KSFO\nTemp.\n54.0°F\nPrecipitation\nNo Report\nWind\n8.1 mph\nCloud Cover\nMostly Cloudy\n14,000 ft\nRaw: KSFO 122156Z 08007KT 10SM FEW030 SCT050 BKN140 12/07 A3022 While having the tremendous advantages of temporal and spatial completeness, these reconstructions: (1) are based on computer models that may have model-based errors, (2) are coarsely sampled on a 50 km grid and are therefore unable to reconstruct the local variations of many microclimates, and (3) have particular difficulty with the weather in some coastal areas, especially small islands.\n We further caution that our travel scores are only as good as the data that underpin them, that weather conditions at any given location and time are unpredictable and variable, and that the definition of the scores reflects a particular set of preferences that may not agree with those of any particular reader.\n January 2024 Weather History in San Francisco California, United States\nThe data for this report comes from the San Francisco International Airport.'}]
이제 이 모델이 tool calling을 수행하도록 활성화하는 것이 어떤지 확인할 수 있습니다. 이를 활성화하기 위해 .bind_tools를 사용하여 language model에 이러한 tool에 대한 지식을 제공합니다 
model_with_tools = model.bind_tools(tools)
이제 모델을 호출할 수 있습니다. 먼저 일반 메시지로 호출하고 어떻게 응답하는지 확인해 봅시다. content 필드와 tool_calls 필드를 모두 살펴볼 수 있습니다. 
from langchain.messages import HumanMessage

response = model_with_tools.invoke([HumanMessage(content="Hi!")])

print(f"ContentString: {response.content}")
print(f"ToolCalls: {response.tool_calls}")

ContentString:  Hello! How can I help you today? If you have a question or need information on a specific topic, feel free to ask. Just type your search query and I'll do my best to assist using the available function.


ToolCalls: []
이제 tool이 호출될 것으로 예상되는 입력으로 호출해 봅시다. 
response = model_with_tools.invoke([HumanMessage(content="What's the weather in SF?")])

print(f"ContentString: {response.content}")
print(f"ToolCalls: {response.tool_calls}")

ContentString:
ToolCalls: [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in SF'}, 'id': '2548c622-3553-42df-8220-39fde0632bdb', 'type': 'tool_call'}]
이제 텍스트 content는 없지만 tool call이 있는 것을 볼 수 있습니다! Tavily Search tool을 호출하라고 요청하고 있습니다. 이것은 아직 해당 tool을 호출하는 것이 아니라 호출하라고 알려주는 것입니다. 실제로 호출하려면 agent를 생성해야 합니다.

​
Create the agent

이제 tool과 LLM을 정의했으므로 agent를 생성할 수 있습니다. LangGraph를 사용하여 agent를 구성할 것입니다. 현재는 agent를 구성하기 위해 high level interface를 사용하고 있지만, LangGraph의 장점은 이 high-level interface가 low-level의 고도로 제어 가능한 API로 뒷받침된다는 것입니다. agent 로직을 수정하고 싶을 때 유용합니다. 이제 LLM과 tool로 agent를 초기화할 수 있습니다. model_with_tools가 아닌 model을 전달하고 있다는 점에 유의하세요. 이는 create_agent가 내부적으로 .bind_tools를 호출하기 때문입니다. 
from langchain.agents import create_agent


agent_executor = create_agent(model, tools)
이제 tool을 호출해야 하는 예제에서 시도해 봅시다 
response = agent_executor.invoke({"messages": [HumanMessage(content="hi!")]})

response["messages"]

[HumanMessage(content='hi!', additional_kwargs={}, response_metadata={}, id='0ab1f3c7-9079-42d4-8a8a-13af5f6c226b'),
 AIMessage(content=' Hello! How can I help you today? If you have a question or need information on a specific topic, feel free to ask. For example, you can start with a search query like "latest news on climate change" or "biography of Albert Einstein".\n\n', additional_kwargs={}, response_metadata={}, id='run-276d9dcd-13f3-481d-b562-8fe3962d9ba1-0')]
내부에서 정확히 무슨 일이 일어나고 있는지 확인하기 위해(그리고 tool을 호출하지 않는지 확인하기 위해) LangSmith trace를 살펴볼 수 있습니다: smith.langchain.com/public/2372d9c5-855a-45ee-80f2-94b63493563d/r 
response = agent_executor.invoke(
    {"messages": [HumanMessage(content="whats the weather in sf?")]}
)
response["messages"]

[HumanMessage(content='whats the weather in sf?', additional_kwargs={}, response_metadata={}, id='af276c61-3df7-4241-8cb0-81d1f1477bb3'),
 AIMessage(content='', additional_kwargs={'tool_calls': [{'id': '86da84b8-0d44-444f-8448-7f134f9afa41', 'type': 'function', 'function': {'name': 'tavily_search_results_json', 'arguments': '{"query": "weather in SF"}'}}]}, response_metadata={}, id='run-abe1b8e2-98a6-4f69-8f95-278ac8c141ff-0', tool_calls=[{'name': 'tavily_search_results_json', 'args': {'query': 'weather in SF'}, 'id': '86da84b8-0d44-444f-8448-7f134f9afa41', 'type': 'tool_call'}]),
 ToolMessage(content='[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'San Francisco\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 37.775, \'lon\': -122.4183, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1730483436, \'localtime\': \'2024-11-01 10:50\'}, \'current\': {\'last_updated_epoch\': 1730483100, \'last_updated\': \'2024-11-01 10:45\', \'temp_c\': 11.4, \'temp_f\': 52.5, \'is_day\': 1, \'condition\': {\'text\': \'Mist\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/143.png\', \'code\': 1030}, \'wind_mph\': 2.2, \'wind_kph\': 3.6, \'wind_degree\': 237, \'wind_dir\': \'WSW\', \'pressure_mb\': 1019.0, \'pressure_in\': 30.08, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 100, \'cloud\': 100, \'feelslike_c\': 11.8, \'feelslike_f\': 53.2, \'windchill_c\': 11.2, \'windchill_f\': 52.1, \'heatindex_c\': 11.7, \'heatindex_f\': 53.0, \'dewpoint_c\': 10.1, \'dewpoint_f\': 50.1, \'vis_km\': 2.8, \'vis_miles\': 1.0, \'uv\': 3.0, \'gust_mph\': 3.0, \'gust_kph\': 4.9}}"}, {"url": "https://www.timeanddate.com/weather/@z-us-94134/ext", "content": "Forecasted weather conditions the coming 2 weeks for San Francisco. Sign in. News. News Home; Astronomy News; Time Zone News ... 01 pm: Mon Nov 11: 60 / 53 °F: Tstorms early. Broken clouds. 54 °F: 19 mph: ↑: 70%: 58%: 0.20\\" 0 (Low) 6:46 am: 5:00 pm * Updated Monday, October 28, 2024 2:24:10 pm San Francisco time - Weather by CustomWeather"}]', name='tavily_search_results_json', id='de8c8d78-ae24-4a8a-9c73-795c1e4fdd41', tool_call_id='86da84b8-0d44-444f-8448-7f134f9afa41', artifact={'query': 'weather in SF', 'follow_up_questions': None, 'answer': None, 'images': [], 'results': [{'title': 'Weather in San Francisco', 'url': 'https://www.weatherapi.com/', 'content': "{'location': {'name': 'San Francisco', 'region': 'California', 'country': 'United States of America', 'lat': 37.775, 'lon': -122.4183, 'tz_id': 'America/Los_Angeles', 'localtime_epoch': 1730483436, 'localtime': '2024-11-01 10:50'}, 'current': {'last_updated_epoch': 1730483100, 'last_updated': '2024-11-01 10:45', 'temp_c': 11.4, 'temp_f': 52.5, 'is_day': 1, 'condition': {'text': 'Mist', 'icon': '//cdn.weatherapi.com/weather/64x64/day/143.png', 'code': 1030}, 'wind_mph': 2.2, 'wind_kph': 3.6, 'wind_degree': 237, 'wind_dir': 'WSW', 'pressure_mb': 1019.0, 'pressure_in': 30.08, 'precip_mm': 0.0, 'precip_in': 0.0, 'humidity': 100, 'cloud': 100, 'feelslike_c': 11.8, 'feelslike_f': 53.2, 'windchill_c': 11.2, 'windchill_f': 52.1, 'heatindex_c': 11.7, 'heatindex_f': 53.0, 'dewpoint_c': 10.1, 'dewpoint_f': 50.1, 'vis_km': 2.8, 'vis_miles': 1.0, 'uv': 3.0, 'gust_mph': 3.0, 'gust_kph': 4.9}}", 'score': 0.9989501, 'raw_content': None}, {'title': 'San Francisco, USA 14 day weather forecast - timeanddate.com', 'url': 'https://www.timeanddate.com/weather/@z-us-94134/ext', 'content': 'Forecasted weather conditions the coming 2 weeks for San Francisco. Sign in. News. News Home; Astronomy News; Time Zone News ... 01 pm: Mon Nov 11: 60 / 53 °F: Tstorms early. Broken clouds. 54 °F: 19 mph: ↑: 70%: 58%: 0.20" 0 (Low) 6:46 am: 5:00 pm * Updated Monday, October 28, 2024 2:24:10 pm San Francisco time - Weather by CustomWeather', 'score': 0.9938309, 'raw_content': None}], 'response_time': 3.56}),
 AIMessage(content=' The current weather in San Francisco is mist with a temperature of 11.4°C (52.5°F). There is a 100% humidity and the wind is blowing at 2.2 mph from the WSW direction. The forecast for the coming weeks shows a mix of cloudy and partly cloudy days with some chances of thunderstorms. Temperatures are expected to range between 53°F and 60°F.\n\n', additional_kwargs={}, response_metadata={}, id='run-de4207d6-e8e8-4382-ad16-4de0dcf0812a-0')]
LangSmith trace를 확인하여 search tool을 효과적으로 호출하고 있는지 확인할 수 있습니다. smith.langchain.com/public/013ef704-654b-4447-8428-637b343d646e/r agent가 invoke로 호출되어 최종 응답을 얻는 방법을 살펴보았습니다. agent가 여러 단계를 실행하는 경우 시간이 걸릴 수 있습니다. 중간 진행 상황을 표시하려면 메시지가 발생할 때 스트리밍할 수 있습니다. 
for chunk in agent_executor.stream(
    {"messages": [HumanMessage(content="whats the weather in sf?")]}
):
    print(chunk)
    print("----")

{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': '2457d3ea-f001-4b8c-a1ed-3dc3d1381639', 'type': 'function', 'function': {'name': 'tavily_search_results_json', 'arguments': '{"query": "weather in San Francisco"}'}}]}, response_metadata={}, id='run-0363deab-84d2-4319-bb1e-b55b47fe2274-0', tool_calls=[{'name': 'tavily_search_results_json', 'args': {'query': 'weather in San Francisco'}, 'id': '2457d3ea-f001-4b8c-a1ed-3dc3d1381639', 'type': 'tool_call'}])]}}
----
{'tools': {'messages': [ToolMessage(content='[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'San Francisco\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 37.775, \'lon\': -122.4183, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1730483636, \'localtime\': \'2024-11-01 10:53\'}, \'current\': {\'last_updated_epoch\': 1730483100, \'last_updated\': \'2024-11-01 10:45\', \'temp_c\': 11.4, \'temp_f\': 52.5, \'is_day\': 1, \'condition\': {\'text\': \'Mist\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/143.png\', \'code\': 1030}, \'wind_mph\': 2.2, \'wind_kph\': 3.6, \'wind_degree\': 237, \'wind_dir\': \'WSW\', \'pressure_mb\': 1019.0, \'pressure_in\': 30.08, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 100, \'cloud\': 100, \'feelslike_c\': 11.8, \'feelslike_f\': 53.2, \'windchill_c\': 11.2, \'windchill_f\': 52.1, \'heatindex_c\': 11.7, \'heatindex_f\': 53.0, \'dewpoint_c\': 10.1, \'dewpoint_f\': 50.1, \'vis_km\': 2.8, \'vis_miles\': 1.0, \'uv\': 3.0, \'gust_mph\': 3.0, \'gust_kph\': 4.9}}"}, {"url": "https://weather.com/weather/monthly/l/69bedc6a5b6e977993fb3e5344e3c06d8bc36a1fb6754c3ddfb5310a3c6d6c87", "content": "Weather.com brings you the most accurate monthly weather forecast for San Francisco, CA with average/record and high/low temperatures, precipitation and more. ... 11. 66 ° 55 ° 12. 69 ° 60"}]', name='tavily_search_results_json', id='e675f99b-130f-4e98-8477-badd45938d9d', tool_call_id='2457d3ea-f001-4b8c-a1ed-3dc3d1381639', artifact={'query': 'weather in San Francisco', 'follow_up_questions': None, 'answer': None, 'images': [], 'results': [{'title': 'Weather in San Francisco', 'url': 'https://www.weatherapi.com/', 'content': "{'location': {'name': 'San Francisco', 'region': 'California', 'country': 'United States of America', 'lat': 37.775, 'lon': -122.4183, 'tz_id': 'America/Los_Angeles', 'localtime_epoch': 1730483636, 'localtime': '2024-11-01 10:53'}, 'current': {'last_updated_epoch': 1730483100, 'last_updated': '2024-11-01 10:45', 'temp_c': 11.4, 'temp_f': 52.5, 'is_day': 1, 'condition': {'text': 'Mist', 'icon': '//cdn.weatherapi.com/weather/64x64/day/143.png', 'code': 1030}, 'wind_mph': 2.2, 'wind_kph': 3.6, 'wind_degree': 237, 'wind_dir': 'WSW', 'pressure_mb': 1019.0, 'pressure_in': 30.08, 'precip_mm': 0.0, 'precip_in': 0.0, 'humidity': 100, 'cloud': 100, 'feelslike_c': 11.8, 'feelslike_f': 53.2, 'windchill_c': 11.2, 'windchill_f': 52.1, 'heatindex_c': 11.7, 'heatindex_f': 53.0, 'dewpoint_c': 10.1, 'dewpoint_f': 50.1, 'vis_km': 2.8, 'vis_miles': 1.0, 'uv': 3.0, 'gust_mph': 3.0, 'gust_kph': 4.9}}", 'score': 0.9968992, 'raw_content': None}, {'title': 'Monthly Weather Forecast for San Francisco, CA - weather.com', 'url': 'https://weather.com/weather/monthly/l/69bedc6a5b6e977993fb3e5344e3c06d8bc36a1fb6754c3ddfb5310a3c6d6c87', 'content': 'Weather.com brings you the most accurate monthly weather forecast for San Francisco, CA with average/record and high/low temperatures, precipitation and more. ... 11. 66 ° 55 ° 12. 69 ° 60', 'score': 0.97644573, 'raw_content': None}], 'response_time': 3.16})]}}
----
{'agent': {'messages': [AIMessage(content=' The current weather in San Francisco is misty with a temperature of 11.4°C (52.5°F). The wind is blowing at 2.2 mph (3.6 kph) from the WSW direction. The humidity is at 100%, and the visibility is 2.8 km (1.0 miles). The monthly forecast shows average temperatures ranging from 55°F to 66°F (13°C to 19°C) with some precipitation expected.\n\n', additional_kwargs={}, response_metadata={}, id='run-99ccf444-d286-4244-a5a5-7b1b511153a6-0')]}}
----

​
API reference

docs.reka.ai/quick-start
Edit the source of this page on GitHub.
Connect these docs programmatically to Claude, VSCode, and more via MCP for real-time answers.
⌘I