Cogniswitch 工具組
CogniSwitch 用於構建可無縫消耗、組織和檢索知識的生產就緒型應用程式。 在您選擇的框架（在本例中為 Langchain）中，CogniSwitch 有助於減輕在選擇正確的儲存和檢索格式時的決策壓力。 它還消除了在產生回應時的可靠性問題和幻覺。
設定
請訪問此頁面以註冊 Cogniswitch 帳戶。
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使用您的電子郵件註冊並驗證您的註冊
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您將收到一封包含平台令牌和 oauth 令牌的郵件，用於使用這些服務。
%pip install -qU langchain-community
匯入必要的函式庫
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 金鑰
cs_token = "Your CogniSwitch token"
OAI_token = "Your OpenAI API token"
oauth_token = "Your CogniSwitch authentication token"
os.environ["OPENAI_API_KEY"] = OAI_token
使用憑證實例化 cogniswitch 工具包
cogniswitch_toolkit = CogniswitchToolkit(
cs_token=cs_token, OAI_token=OAI_token, apiKey=oauth_token
)
取得 cogniswitch 工具清單
tool_lst = cogniswitch_toolkit.get_tools()
實例化 LLM
llm = ChatOpenAI(
temperature=0,
openai_api_key=OAI_token,
max_tokens=1500,
model_name="gpt-3.5-turbo-0613",
)
將 LLM 與工具包一起使用
使用 LLM 和工具包建立代理程式
agent_executor = create_conversational_retrieval_agent(llm, tool_lst, verbose=False)
呼叫代理程式上傳 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.
呼叫代理程式上傳檔案
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.
呼叫代理程式以取得文件狀態
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.
使用查詢呼叫代理程式並取得答案
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.