The objective is this repository is to evaluate and extend ChatGPT API, LangChain and LLamaIndex data framework to build applications. These techniques include
- Prompt engineering patterns: Output automater, Persona, Fact checking template and cognitive verifier
- Typed prompt using LangChain chains
- Generative workflow using LangChain, OpenAI and LLama agents.
- Extending LangChain sequences with data types
- ChatGPT Prompt patterns for code generation
- LangChain introduction
- LLama introduction
- Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
- OpenAI ChatGPT
| Package | Version |
|---|---|
| python | 3.9.16 |
| torch | 2.0.1 |
| openai | 0.27.1 |
| matplotlib | 3.7.1 |
| scikit-learn | 1.2.2 |
| numpy | 1.24.3 |
| pandas | 2.0.2 |
| langchain | 0.0.227 |
| polars | 0.17.0 |
| fastapi | 0.97.0 |
| llama index | 0.7.4 |
| Date | Version |
|---|---|
| 06.07.2023 | 0.1 |
| 06.18.2023 | 0.2 |
| Package | Description |
|---|---|
| util | Utilities class |
| openai | Classes related to usage and fine tuning for ChatGPT |
| llm_langchain | Classes related to loader, splitter, chain and agents using LangChain framework |
| llm_llama | Classes related to chain and agents using LLamaIndex framework |
| domain | Domain specific target application code for testing purpose |
From the seminal paper "A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT".
| Name | Overview | Contextual statements |
|---|---|---|
| Persona | Output customization Assign a persona, role or domain expert to LLM. The persona can be expressed as a role, job description, title, historical or known figure. |
- I would like you to ask me questions to achieve X. - You should ask questions until X is achieved or the condition X is met. Ask me questions regarding X one at the time. |
| Template | Output customization Ensure output follows a precise template (i.e. format, URL, example…). This pattern instructs LLM to use a unique format in specific portion of the answer. |
I am going to provide you with a template for your output X is my place holder for content Try to fit the output into one or more of the placeholders that I listed Please preserve the formatting and template I provided Here is the template to follow: PATTERN with PLACEHOLDER. |
| Fact check list | Error identification Request LLM to provide/append a list of facts/assumptions to the answer, so the user may perform due-diligence. |
Generate a set of facts that are contained in the output The set of facts should be inserted/appended to the output The set of facts should be the fundamental facts that could undermine the veracity of the output if any of them are incorrect. |
| Reflection | Error identification Ask LLM to automatically explain the rationale behind a given answers to the user. The pattern clarifies any points of confusion, underlying assumptions, gaps in knowledge…. |
Whenever you generate an answer, explain the reasoning and assumptions behind your answer, so I can improve my question. |
| Output automater | Output customization Having LLM generate a script or automated task that can be execute any steps the LLM recommends. |
Whenever you produce an output with steps, always do this. Produce an executable artifact of type X that will automate these steps. |
| Visualization Generator | Output customization Use generated text to create a visualization as complex concepts are easier to grasp with diagrams and images. The LLM output should create a pathway for the tool to produce imagery. |
Generate an X that I can provide to tool Y to visualize it. |