Cogniswitch 工具包
CogniSwitch 用于构建能够完美地使用、组织和检索知识的生产就绪应用程序。使用您选择的框架，在本例中为 Langchain，CogniSwitch 有助于减轻在选择正确的存储和检索格式时做决策的压力。它还消除了在生成响应时出现的可靠性和幻觉问题。
设置
访问 此页面 以注册 Cogniswitch 帐户。
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使用您的电子邮件注册并验证您的注册信息
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您将收到一封包含平台令牌和 OAuth 令牌的邮件，用于使用服务。
%pip install -qU langchain-community
导入必要的库
import warnings
warnings.filterwarnings("ignore")
import os
from langchain.agents.agent_toolkits import create_conversational_retrieval_agent
from langchain_community.agent_toolkits import CogniswitchToolkit
from langchain_openai import ChatOpenAI
Cogniswitch 平台令牌、OAuth 令牌和 OpenAI API 密钥
cs_token = "Your CogniSwitch token"
OAI_token = "Your OpenAI API token"
oauth_token = "Your CogniSwitch authentication token"
os.environ["OPENAI_API_KEY"] = OAI_token
使用凭据实例化 Cogniswitch 工具包
cogniswitch_toolkit = CogniswitchToolkit(
cs_token=cs_token, OAI_token=OAI_token, apiKey=oauth_token
)
获取 Cogniswitch 工具列表
tool_lst = cogniswitch_toolkit.get_tools()
实例化 LLM
llm = ChatOpenAI(
temperature=0,
openai_api_key=OAI_token,
max_tokens=1500,
model_name="gpt-3.5-turbo-0613",
)
将 LLM 与工具包一起使用
使用 LLM 和工具包创建代理
agent_executor = create_conversational_retrieval_agent(llm, tool_lst, verbose=False)
调用代理以上传 URL
response = agent_executor.invoke("upload this url https://cogniswitch.ai/developer")
print(response["output"])
The URL https://cogniswitch.ai/developer has been uploaded successfully. The status of the document is currently being processed. You will receive an email notification once the processing is complete.
调用代理以上传文件
response = agent_executor.invoke("upload this file example_file.txt")
print(response["output"])
The file example_file.txt has been uploaded successfully. The status of the document is currently being processed. You will receive an email notification once the processing is complete.
调用代理以获取文档的状态
response = agent_executor.invoke("Tell me the status of this document example_file.txt")
print(response["output"])
The status of the document example_file.txt is as follows:
- Created On: 2024-01-22T19:07:42.000+00:00
- Modified On: 2024-01-22T19:07:42.000+00:00
- Document Entry ID: 153
- Status: 0 (Processing)
- Original File Name: example_file.txt
- Saved File Name: 1705950460069example_file29393011.txt
The document is currently being processed.
使用查询调用代理并获取答案
response = agent_executor.invoke("How can cogniswitch help develop GenAI applications?")
print(response["output"])
CogniSwitch can help develop GenAI applications in several ways:
1. Knowledge Extraction: CogniSwitch can extract knowledge from various sources such as documents, websites, and databases. It can analyze and store data from these sources, making it easier to access and utilize the information for GenAI applications.
2. Natural Language Processing: CogniSwitch has advanced natural language processing capabilities. It can understand and interpret human language, allowing GenAI applications to interact with users in a more conversational and intuitive manner.
3. Sentiment Analysis: CogniSwitch can analyze the sentiment of text data, such as customer reviews or social media posts. This can be useful in developing GenAI applications that can understand and respond to the emotions and opinions of users.
4. Knowledge Base Integration: CogniSwitch can integrate with existing knowledge bases or create new ones. This allows GenAI applications to access a vast amount of information and provide accurate and relevant responses to user queries.
5. Document Analysis: CogniSwitch can analyze documents and extract key information such as entities, relationships, and concepts. This can be valuable in developing GenAI applications that can understand and process large amounts of textual data.
Overall, CogniSwitch provides a range of AI-powered capabilities that can enhance the development of GenAI applications by enabling knowledge extraction, natural language processing, sentiment analysis, knowledge base integration, and document analysis.