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Cogniswitch 工具包

CogniSwitch 用于构建生产就绪的应用程序，这些应用程序可以无缝地消费、组织和检索知识。使用您选择的框架，在这种情况下是 Langchain，CogniSwitch 有助于减轻在选择正确的存储和检索格式时的决策压力。它还消除了在生成响应时的可靠性问题和幻觉。

设置​

访问此页面注册Cogniswitch账户。

  • 使用您的电子邮件注册并验证您的注册

  • 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",
)

使用工具包中的LLM​

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.

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