wehub-resource-sync
78 lines
4.3 KiB
Markdown
78 lines
4.3 KiB
Markdown
🚀 Use Cases Examples 🚀
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===============
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**End-to-End Scenarios**
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In this repository, we feature several 'end-to-end' examples that show how to use LLMWare in a complex recipe combining different elements to accomplish a specific objective. While each example is still high-level, it is shared in the spirit of providing a high-level framework 'starting point' that can be developed in more detail for a variety of common use cases. All of these examples use small, specialized models, running locally - 'Small, but Mighty' !
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1. [**Research Automation with Agents and Web Services**](https://www.github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/web_services_slim_fx.py)
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- Prepare a 30-key research analysis on a company
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- Extract key lookup and other information from an earnings press release
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- Automatically use the lookup data for real-time stock information from YFinance
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- Automatically use the lookup date for background company history information in Wikipedia
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- Run LLM prompts to ask key questions of the Wikipedia sources
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- Aggregate into a consolidated research analysis
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- All with local open source models
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2. [**Invoice Processing**](https://www.github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/invoice_processing.py)
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- Parse a batch of invoices (provided as sample files)
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- Extract key information from the invoices
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- Save the prompt state for follow-up review and analysis
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3. [**Analyzing and Extracting Voice Transcripts**](https://www.github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/parsing_great_speeches.py)
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- Voice transcription of 50+ wav files of great speeches of the 20th century
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- Run text queries against the transcribed wav files
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- Execute LLM agent inferences to extract and identify key elements of interest
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- Prepare 'bibliography' with the key extracted points, including time-stamp
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4. [**MSA Processing**](https://www.github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/msa_processing.py)
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- Identify the termination provisions in Master Service Agreements among a larger batch of contracts
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- Parse and query a large batch of contracts and identify the agreements with "Master Service Agreement" on the first page
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- Find the termination provisions in each MSA
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- Prompt LLM to read the termination provisions and answer a key question
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- Run a fact-check and source-check on the LLM response
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- Save all of the responses in CSV and JSON for follow-up review.
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5. [**Querying a CSV**](https://www.github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/agent_with_custom_tables.py)
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- Start running natural language queries on CSVs with Postgres and slim-sql-tool.
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- Load a sample 'customer_table.csv' into Postgres
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- Start running natural language queries that get converted into SQL and query the DB
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6. [**Contract Analysis**](https://www.github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/contract_analysis_on_laptop_with_bling_models.py)
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- Extract key information from set of employment agreement
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- Use a simple retrieval strategy with keyword search to identify key provisions and topic areas
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- Prompt LLM to read the key provisions and answer questions based on those source materials
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7. [**Slicing and Dicing Office Docs**](https://www.github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/slicing_and_dicing_office_docs.py)
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- Shows a variety of advanced parsing techniques with Office document formats packaged in ZIP archives
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- Extracts tables and images, runs OCR against the embedded images, exports the whole library, and creates dataset
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8. **LLMWare Private Inference Server**
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- Set up server in minutes on CPU, GPU or local - [server](https://www.github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/llmware_inference_server.py)
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- Run 3 different modes of client access to the API - [client](https://www.github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/llmware_inference_api_client.py)
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- Supports rapid development, testing and prototyping and flexibility of deployment models for wide range of RAG and Agent use cases
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Check back often - we are updating these examples regularly - and many of these examples have companion videos as well.
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### **Let's get started! 🚀**
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