Cogniswitch 工具包
CogniSwitch 用于构建可投入生产的应用程序，这些应用程序能够流畅地消费、组织和检索知识。使用您选择的框架，在这种情况下是 Langchain，CogniSwitch 帮助减轻在选择合适的存储和检索格式时的决策压力。它还消除了生成响应时的可靠性和幻觉问题。
设置
访问 此页面 注册 Cogniswitch 账户。
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使用电子邮件进行注册并验证您的账户
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您将收到一封包含平台令牌和OAuth令牌的邮件，以便使用相关服务。
%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
使用凭据实例化认知转换工具包
cogniswitch_toolkit = CogniswitchToolkit(
cs_token=cs_token, OAI_token=OAI_token, apiKey=oauth_token
)
获取认知切换工具列表
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",
)
使用大语言模型与工具包
创建一个使用LLM和工具包的代理
agent_executor = create_conversational_retrieval_agent(llm, tool_lst, verbose=False)
Invoke the agent to upload a 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.
Invoke the agent to upload a File
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.
Invoke the agent to get the status of a document
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.