--- layout: default title: Agents parent: Components nav_order: 4 description: overview of the major modules and classes of LLMWare permalink: /components/agents --- # Agents --- Agents with Function Calls and SLIM Models 🔥 llmware has been designed to enable Agent and LLM-based function calls using small language models designed for local and private deployment and the ability to leverage open source models to conduct complex RAG and knowledge-based workflow automation. The key elements in llmware: - **SLIM models** - 18 function-calling small language models, optimized for a specific extraction, classification, generation, or summarization activity, and generate python dictionaries and lists as output. - **LLMfx class** - enables a wide range of agent-based processes. Here is an example to get started: ```python from llmware.agents import LLMfx text = ("Tesla stock fell 8% in premarket trading after reporting fourth-quarter revenue and profit that " "missed analysts’ estimates. The electric vehicle company also warned that vehicle volume growth in " "2024 'may be notably lower' than last year’s growth rate. Automotive revenue, meanwhile, increased " "just 1% from a year earlier, partly because the EVs were selling for less than they had in the past. " "Tesla implemented steep price cuts in the second half of the year around the world. In a Wednesday " "presentation, the company warned investors that it’s 'currently between two major growth waves.'") # create an agent using LLMfx class agent = LLMfx() # load text to process agent.load_work(text) # load 'models' as 'tools' to be used in analysis process agent.load_tool("sentiment") agent.load_tool("extract") agent.load_tool("topics") agent.load_tool("boolean") # run function calls using different tools agent.sentiment() agent.topics() agent.extract(params=["company"]) agent.extract(params=["automotive revenue growth"]) agent.xsum() agent.boolean(params=["is 2024 growth expected to be strong? (explain)"]) # at end of processing, show the report that was automatically aggregated by key report = agent.show_report() # displays a summary of the activity in the process activity_summary = agent.activity_summary() # list of the responses gathered for i, entries in enumerate(agent.response_list): print("update: response analysis: ", i, entries) output = {"report": report, "activity_summary": activity_summary, "journal": agent.journal} ``` Need help or have questions? ============================ Check out the [llmware videos](https://www.youtube.com/@llmware) and [GitHub repository](https://github.com/llmware-ai/llmware). Reach out to us on [GitHub Discussions](https://github.com/llmware-ai/llmware/discussions). # About the project `llmware` is © 2023-{{ "now" | date: "%Y" }} by [AI Bloks](https://www.aibloks.com/home). ## Contributing Please first discuss any change you want to make publicly, for example on GitHub via raising an [issue](https://github.com/llmware-ai/llmware/issues) or starting a [new discussion](https://github.com/llmware-ai/llmware/discussions). You can also write an email or start a discussion on our Discord channel. Read more about becoming a contributor in the [GitHub repo](https://github.com/llmware-ai/llmware/blob/main/CONTRIBUTING.md). ## Code of conduct We welcome everyone into the ``llmware`` community. [View our Code of Conduct](https://github.com/llmware-ai/llmware/blob/main/CODE_OF_CONDUCT.md) in our GitHub repository. ## ``llmware`` and [AI Bloks](https://www.aibloks.com/home) ``llmware`` is an open source project from [AI Bloks](https://www.aibloks.com/home) - the company behind ``llmware``. The company offers a Software as a Service (SaaS) Retrieval Augmented Generation (RAG) service. [AI Bloks](https://www.aibloks.com/home) was founded by [Namee Oberst](https://www.linkedin.com/in/nameeoberst/) and [Darren Oberst](https://www.linkedin.com/in/darren-oberst-34a4b54/) in October 2022. ## License `llmware` is distributed by an [Apache-2.0 license](https://github.com/llmware-ai/llmware/blob/main/LICENSE). ## Thank you to the contributors of ``llmware``! --- ---