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A [100-line](pocketflow/__init__.py) minimalist LLM framework for ([Multi-](https://the-pocket.github.io/PocketFlow/multi_agent.html))[Agents](https://the-pocket.github.io/PocketFlow/agent.html), [Prompt Chaining](https://the-pocket.github.io/PocketFlow/decomp.html), [RAG](https://the-pocket.github.io/PocketFlow/rag.html), etc.
-- βοΈ Install via ```pip install pocketflow```, or just copy the [source code](pocketflow/__init__.py) (only 100 lines)
+- Install via ```pip install pocketflow```, or just copy the [source code](pocketflow/__init__.py) (only 100 lines)
-- π If the 100 lines feel terse and youβd prefer a friendlier intro, [check this out](https://chatgpt.com/share/678564bd-1ba4-8000-98e4-a6ffe363c1b8)
+- If the 100 lines are terse, check out a [friendlier intro](https://chatgpt.com/share/678564bd-1ba4-8000-98e4-a6ffe363c1b8)
-- π Documentation: https://the-pocket.github.io/PocketFlow/
+- Documentation: https://the-pocket.github.io/PocketFlow/
## Why Pocket Flow? Let LLM Agents Build LLM Agents for you!
Pocket Flow is designed to be **the framework used by LLM Agents**:
-- π§ Human users specify project requirements and provide high-level guidance
+- π§ Human users only need to specify LLM project requirements
-- π€ LLM Agents build and maintain LLM projects for you, using *Pocket Flow*
+- π€ LLM Agents build the LLM project for you, using *Pocket Flow*
-To build LLM projects with LLMs Agents (ChatGPT, Claude, Cursor.ai, etc.):
+To build LLM projects with LLM Agents (Cursor, ChatGPT, Claude, etc.):
-(π«΅ Click to expand) Use Claude to build LLM apps
- - Create a [project](https://www.anthropic.com/news/projects) and upload the [docs](docs) to project knowledge
+ - **[Cursor Rules](https://docs.cursor.com/context/rules-for-ai)**: Copy and paste the [.cursorrule](https://github.com/The-Pocket/PocketFlow/blob/main/assets/.cursorrules) (created from [docs](docs)) into the root of your project.
- - Set project custom instructions. For example:
- ```
- 1. check "tool.md" and "llm.md" for the required functions.
- 2. design the high-level (batch) flow and nodes in artifact using mermaid
- 3. design the shared memory structure: define its fields, data structures, and how they will be updated.
- Think out aloud for above first and ask users if your design makes sense.
- 4. Finally, implement. Start with simple, minimalistic codes without, for example, typing. Write the codes in artifact.
- ```
- - Ask it to build LLM apps (Sonnet 3.5 strongly recommended)!
- ```
- Help me build a chatbot based on a directory of PDFs.
- ```
-
-
- (π«΅ Click to expand) Use ChatGPT to build LLM apps
-
- - Try the [GPT assistant](https://chatgpt.com/g/g-677464af36588191b9eba4901946557b-mini-llm-flow-assistant). However, it uses older models, which are good for explaining but not that good at coding.
-
-
-