88 lines
3.5 KiB
Text
88 lines
3.5 KiB
Text
import Admonition from "@theme/Admonition";
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# Agents
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<Admonition type="warning" title="warning">
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This page may contain outdated information. It will be updated as soon as possible.
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</Admonition>
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Agents are components that use reasoning to make decisions and take actions, designed to autonomously perform tasks or provide services with some degree of agency. LLM chains can only perform hardcoded sequences of actions, while agents use LLMs to reason through which actions to take, and in which order.
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---
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### AgentInitializer
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The `AgentInitializer` constructs a zero-shot agent from a language model (LLM) and additional tools.
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**Parameters**:
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- **LLM:** The language model used by the `AgentInitializer`.
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- **Memory:** Enables memory functionality, allowing the agent to recall and use information from previous interactions.
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- **Tools:** The tools available to the agent.
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- **Agent:** Specifies the type of agent to instantiate. Currently supported types include `zero-shot-react-description`, `react-docstore`, `self-ask-with-search`, `conversational-react-description`, and `openai-functions`.
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---
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### CSVAgent
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The `CSVAgent` interacts with CSV (Comma-Separated Values) files, commonly used to store tabular data. Each row in a CSV file represents a record, and each column represents a field. The CSV agent can read and write CSV files, process data, and perform tasks such as filtering, sorting, and aggregating.
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**Parameters**:
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- **LLM:** The language model used by the `CSVAgent`.
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- **Path:** The file path to the CSV data.
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---
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### JSONAgent
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The `JSONAgent` manages JSON (JavaScript Object Notation) data. This agent, like the CSVAgent, uses a language model (LLM) and a toolkit for JSON manipulation. It can explore a JSON blob to extract needed information, list keys, retrieve values, and navigate through the JSON structure.
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**Parameters**:
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- **LLM:** The language model used by the `JSONAgent`.
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- **Toolkit:** The toolkit available to the agent.
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---
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### SQLAgent
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The `SQLAgent` interacts with SQL databases, capable of querying, retrieving data, and executing SQL statements. It provides insights into the database structure, including tables and schemas, and can perform operations such as insertions, updates, and deletions.
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**Parameters**:
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- **LLM:** The language model used by the `SQLAgent`.
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- **Database URI:** The connection URI for the SQL database.
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---
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### VectorStoreAgent
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The `VectorStoreAgent` operates with a vector store, which is a data structure for storing and querying vector-based data representations. This agent can query the vector store to find information relevant to user inputs.
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**Parameters**:
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- **LLM:** The language model used by the `VectorStoreAgent`.
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- **Vector Store Info:** The `VectorStoreInfo` used by the agent.
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---
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### VectorStoreRouterAgent
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The `VectorStoreRouterAgent` is a custom agent that uses a vector store router. It is typically used to retrieve information from multiple vector stores connected through a `VectorStoreRouterToolkit`.
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**Parameters**:
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- **LLM:** The language model used by the `VectorStoreRouterAgent`.
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- **Vector Store Router Toolkit:** The toolkit used by the agent.
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---
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### ZeroShotAgent
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The `ZeroShotAgent` uses the ReAct framework to decide which tool to use based on the tool's description. It is the most general-purpose action agent, capable of determining the necessary actions and their sequence through an `LLMChain`.
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**Parameters**:
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- **Allowed Tools:** The tools accessible to the agent.
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- **LLM Chain:** The LLM Chain used by the agent.
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