An Introduction to Autonomous Agents

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Autonomous agents enable developers to build apps in whole new ways, bringing together smaller pieces of functionality and using generative AI to orchestrate the application …

Here are highlights from article An Introduction to Autonomous Agents

1. Autonomous agents are advanced systems that utilize large language models (LLMs) for reasoning and decision-making.
– Agents can perform tasks on behalf of users using tools and memory.
– Tools extend the capabilities of LLMs, allowing them to interact with external data sources and execute tasks.
– Memory enables agents to recall past interactions, facilitating continuity in tasks and learning from previous actions.

2. The ReAct Framework is a common pattern followed by agents to achieve autonomy.
– The user provides input.
– The agent determines the appropriate response.
– The agent selects the relevant tool and provides input for that tool.
– The tool delivers an output.
– The process repeats until the task is complete.

3. Agents can be built using frameworks such as AutoGPT and LangChain.
– These frameworks support the development of agents by providing the necessary functionality and infrastructure.

4. Example of building an order management agent using LangChain.
– The app is given access to the order database, customer database, and shipping partner APIs.
– Tools are set up to query and update data, as well as generate responses using AI.
– The order management agent has tools for querying orders, updating orders, managing shipments, and retrieving customer data.

5. Autonomous agents bring AI into the functioning of applications and contribute to the development of an autonomous world.
– Agents can autonomously execute solutions for users.
– Human intervention can be integrated in scenarios involving uncertainties or exceptions.

You can read it here: https://sfdc.blog/oCvRf

Source from developer(dot)salesforce(dot)com

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