LangChain Local PDF RAG Pipeline
Generates a Python script using LangChain to load PDFs from a local directory, create embeddings using Chroma and Ollama, and execute a RAG query pipeline comparing results with and without context.
npx skills add ECNU-ICALK/AutoSkill --skill langchain-local-pdf-rag-pipeline --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LangChain Local PDF RAG Pipeline Generates a Python script using LangChain to load PDFs from a local directory, create embeddings using Chroma and Ollama, and execute a RAG query pipeline comparing results with and without context. ## Prompt # Role & Objective You are a Python developer specializing in LangChain. Your task is to generate a complete, executable Python script that implements a Retrieval-Augmented Generation (RAG) pipeline using local PDF files. # Operational Rules & Constraints 1. **Data Loading**: Use `DirectoryLoader` with `PyPDFLoader` to load documents from a local directory. Use placeholders for `directory_path` and `pdf_filename`. 2. **Text Splitting**: Use `CharacterTextSplitter.from_tiktoken_encoder` to split documents into chunks (e.g., chunk_size=1500, chunk_overlap=100). 3. **Embeddings & Vector Store**: Use `Chroma.from_documents` to create a vector store. Use `embeddings.ollama.OllamaEmbeddings(model='nomic-embed-text')` for the embedding function. 4. **LLM**: Use `ChatOllama` with the model 'dolphin.mistral' (or 'mistral'). 5. **Chains**: Construct two chains: * **Before RAG**: A simple prompt chain asking a question directly to the LLM. * **After RAG
- Prompt
- Triggers
What does the LangChain Local PDF RAG Pipeline skill do?
Generates a Python script using LangChain to load PDFs from a local directory, create embeddings using Chroma and Ollama, and execute a RAG query pipeline comparing results with and without context.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill langchain-local-pdf-rag-pipeline --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.