Using langchain to get response from large json data

[pappitito]

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Example Code

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Description

please i am trying to integrate langchain openai api with large amount of JSON data, in such a way that it can still answer generic questions unrelated to the data.

System Info

"yarn info langchain"
platform ( mac)

[dosubot[bot]]

Hey @pappitito! Great to see you back with another interesting challenge. How have you been?

To integrate the LangChain OpenAI API with a large amount of JSON data while still allowing it to answer generic questions unrelated to the data, you can follow these steps:

1. Create Custom Tools for JSON Data Processing: You can create custom tools that can process your specific JSON data. These tools should implement logic to parse, analyze, and extract information from your JSON data based on the input queries.

2. Incorporate JSON Data Tools into the Assistant: When creating an instance of OpenAIAssistantRunnable, include your custom tools in the tools array alongside any other tools you might need for generic questions. This setup allows the assistant to use these tools to access and process the JSON data.

3. Define Instructions for Handling Both Data Types: In the instructions parameter of OpenAIAssistantRunnable.createAssistant, clearly define how the assistant should use the provided tools to answer questions. You should specify how it should handle queries related to your JSON data and how to address generic questions. This might involve instructing the assistant to first attempt to find answers using the custom tools and then fall back to its general knowledge base for other queries.

4. Use AgentExecutor for Query Processing: Utilize AgentExecutor to invoke the assistant with queries. This executor will manage the interaction between the assistant and the tools, ensuring that queries are processed correctly, whether they require access to the JSON data or are generic questions.

Here's a simplified example, assuming you have created a custom tool named JsonDataTool for processing your JSON data:

// Assuming JsonDataTool is a custom tool you've created for handling your JSON data
class JsonDataTool extends StructuredTool {
  // Implementation of your tool...
}

// Create an instance of OpenAIAssistantRunnable with both custom and generic tools
const tools = [new WeatherTool(), new HumanReadableChecker(), new JsonDataTool()];
const agent = await OpenAIAssistantRunnable.createAssistant({
  model: "gpt-3.5-turbo-1106",
  instructions: "Use the provided tools to answer questions about the weather, process JSON data, or answer generic questions.",
  name: "Enhanced Assistant",
  tools,
  asAgent: true,
});

// Use AgentExecutor to process queries
const agentExecutor = AgentExecutor.fromAgentAndTools({
  agent,
  tools,
});
const assistantResponse = await agentExecutor.invoke({
  content: "What's the weather in San Francisco and Tokyo? Also, process this specific JSON data query...",
});

console.log(assistantResponse);

This approach allows you to leverage the LangChain OpenAI API to process both specific JSON data and answer generic questions by defining custom tools and clear instructions for the assistant.

Please note that the JsonDataTool class is not defined in the LangChain JS codebase. It's an example of a custom tool you might create to handle your specific JSON data. The actual implementation of this tool would depend on the structure and requirements of your JSON data.

For more information, you can refer to the langchain/src/experimental/openai_assistant/tests/openai_assistant.int.test.ts file in the LangChain JS repository.

Sources

• langchain/src/experimental/openai_assistant/tests/openai_assistant.int.test.ts
• langchain/src/tools/json.ts

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