Integrate Cogniswitch for Knowledge Management
Use CogniSwitch to build applications that can consume, organize, and retrieve knowledge. Get started in three simple steps.
Why it matters
Seamlessly integrate your knowledge base with Cogniswitch to build production-ready applications. Alleviate decision-making stress regarding storage and retrieval, and eradicate reliability issues and hallucinations in AI-generated responses.
Outcomes
What it gets done
Instantiate the Cogniswitch ToolSpec with your API credentials.
Store data by providing file paths or URLs to the agent.
Query your knowledge store for answers to specific questions.
Monitor document processing status within the Cogniswitch console.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/li-tool-tools-cogniswitch | bash Capabilities
What this skill does
Chunks, embeds, and indexes documents for semantic retrieval.
Builds and queries entity-relationship graphs.
Pulls structured data fields from unstructured text.
Condenses long documents or threads into key takeaways.
Handles multi-turn conversations within a defined domain.
Overview
os.environ["OPENAI_API_KEY"] = <your openai token>
What it does
CogniSwitch is a tool that helps build applications capable of consuming, organizing, and retrieving knowledge. It assists in selecting storage and retrieval formats and aims to reduce reliability issues and hallucinations in generated responses.
How it connects
Use CogniSwitch when building applications that require knowledge consumption, organization, and retrieval. It is useful for simplifying the process of choosing storage and retrieval formats and for enhancing the reliability of AI-generated responses.
Source README
Cogniswitch ToolSpec
Use CogniSwitch to build production ready applications that can consume, organize and retrieve knowledge flawlessly. Using the framework of your choice, in this case LlamaIndex, CogniSwitch helps alleviate the stress of decision making when it comes to, choosing the right storage and retrieval formats. It also eradicates reliability issues and hallucinations when it comes to responses that are generated. Get started by interacting with your knowledge in just three simple steps
visit https://www.cogniswitch.ai/developer.
Registration:
- Signup with your email and verify your registration
- You will get a mail with a platform token and OAuth token for using the services.
Step 1: Instantiate the Cogniswitch ToolSpec:
- Use your Cogniswitch token, openAI API key, OAuth token to instantiate the toolspec.
Step 2: Instantiate the Agent:
- Instantiate the agent with the list of tools from the toolspec.
Step 3: Cogniswitch Store data:
- Make the call to the agent by giving the file path or url to the agent input.
- The agent will pick the tool and use the file/url and it will be processed and stored in your knowledge store.
- You can check the status of document processing with a call to the agent. Alternatively you can also check in [cogniswitch console](- You can check the status of document processing with a call to the agent. Alternatively you can also check in cogniswitch console.
Step 4: Cogniswitch Answer:
- Make the call to the agent by giving query as agent input.
- You will get the answer from your knowledge as the response.
Import Required Libraries
import warnings
warnings.filterwarnings("ignore")
import os
from llama_index.tools.cogniswitch import CogniswitchToolSpec
from llama_index.core.agent import ReActAgent
Cogniswitch Credentials and OpenAI token
# os.environ["OPENAI_API_KEY"] = <your openai token>
# cs_token = <your cogniswitch platform token>
# oauth_token = <your cogniswitch apikey>
Instantiate the Tool Spec
toolspec = CogniswitchToolSpec(cs_token=cs_token, apiKey=oauth_token)
Get the list of tools
tool_lst = toolspec.to_tool_list()
Instantiate the agent with the tool list
agent = ReActAgent.from_tools(tool_lst)
Use the agent for storing data in cogniswitch with a single call
store_response = agent.chat(
"""
https://cogniswitch.ai/developer
this site is about cogniswitch website for developers.
"""
)
print(store_response)
{'data': {'knowledgeSourceId': 43, 'sourceType': 'https://cogniswitch.ai/developer', 'sourceURL': None, 'sourceFileName': None, 'sourceName': 'Cogniswitch dev', 'sourceDescription': 'This is a cogniswitch website for developers.', 'status': 'UPLOADED'}, 'list': None, 'message': "We're processing your content & will send you an email on completion, hang tight!", 'statusCode': 1000}
Use the agent to know the document status with a single call
response = agent.chat("Tell me the status of Cogniswitch Developer Website")
print(response)
The document "Cogniswitch Developer Website" is currently being processed.
Use the agent for answering a query with a single call
answer_response = agent.chat("tell me about cogniswitch")
print(answer_response)
{'data': {'answer': 'CogniSwitch is a technology platform that enhances the reliability of Generative AI applications for enterprises. It does this by gathering and organizing knowledge from documented sources, eliminating hallucinations and bias in AI responses. The platform uses AI to automatically gather and organize knowledge, which can then be reviewed and curated by experts before being published. The CogniSwitch API enables Gen AI applications to access this knowledge as needed, ensuring reliability. It is specifically designed to complement Generative AI and offers customized solutions for different business functions within an enterprise.'}, 'list': None, 'message': None, 'statusCode': 1000}
The tool is designed to store data and retrieve answers based on the knowledge provided. check out the link for examples.
Discussion
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