Build a 'Chat with website' using Groq Llama 3
Blog post from Firecrawl
A comprehensive guide outlines the process of creating a "Chat with your website" bot using various Python dependencies, including Langchain, Groq, FAISS, Ollama, and Firecrawl-py. The setup involves installing and upgrading these libraries, using Ollama for embeddings, and employing Firecrawl to acquire and format website data. The FirecrawlLoader is utilized to load website data into a document loader, which is then split into manageable chunks for processing. A vectorstore is established using FAISS to store and query embeddings, ensuring efficient retrieval of relevant documents based on user queries. Once the vectorstore is set up, the system conducts a similarity search to find pertinent documents, which are then used to generate responses to user questions via the Groq API. This setup enables the development of a chatbot capable of answering questions using documentation from the targeted website.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 7 | 1,326 | 202 | 88 | -53% |
| LLM | 2 | 3,048 | 361 | 147 | -19% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.