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47 lines
1.2 KiB
Markdown
47 lines
1.2 KiB
Markdown
# RAG Pipeline for Language Specification Exploration
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This project implements a RAG-based AI chat agent to explore the ECMAScript specification and its implementation in `engine262`.
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## Prerequisites
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- **Node.js**: Version 18+
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- **Ollama**: Installed locally with an embedding model (e.g., `nomic-embed-text`)
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- **OpenAI-compatible Endpoint**: A hosted or local LLM service
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## Setup
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1. **Install dependencies**:
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```bash
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npm install
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```
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2. **Prepare environment**:
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```bash
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export OPENAI_API_BASE="your_endpoint_base_url"
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export OPENAI_API_KEY="your_api_key"
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```
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3. **Clone specification**:
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(Ensure `./spec-built/multipage` contains the HTML files)
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4. **Ingest data**:
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```bash
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node ingest.mjs
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```
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*Note: This will take significant time as it generates local embeddings via Ollama for both the spec and the implementation.*
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5. **Build graph**:
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```bash
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node build_graph.mjs
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```
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## Usage
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Ask the agent questions about how code relates to the specification:
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```bash
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node agent.mjs "Explain how the 'if' statement works and show its implementation."
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```
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The agent will use tools to search the specification, explore the implementation code, and navigate the relationships between them using the graph.
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