claudeWithRagCommented.ts

import Anthropic from "npm:@anthropic-ai/sdk@0.24.0";

/* This automatically picks up the API key from the ANTHROPIC_API_KEY
environment variable, which we configured in the Val Town settings */
const anthropic = new Anthropic();

async function suggestKeywords(question) {
  // Takes a question like "What is shot-scraper?" and asks 3.5 Sonnet
  // to suggest individual search keywords to help answer the question.
  const message = await anthropic.messages.create({
    max_tokens: 128,
    model: "claude-3-5-sonnet-20240620",
    // The tools option enforces a JSON schema array of strings
    tools: [{
      name: "suggested_search_keywords",
      description: "Suggest individual search keywords to help answer the question.",
      input_schema: {
        type: "object",
        properties: {
          keywords: {
            type: "array",
            items: {
              type: "string",
            },
            description: "List of suggested single word search keywords",
          },
        },
        required: ["keywords"],
      },
    }],
    // This forces it to always run the suggested_search_keywords tool
    tool_choice: { type: "tool", name: "suggested_search_keywords" },
    messages: [
      { role: "user", content: question },
    ],
  });
  // This helped TypeScript complain less about accessing .input.keywords
  // since it knows this object can be one of two different types
  if (message.content[0].type == "text") {
    throw new Error(message.content[0].text);
  }
  return message.content[0].input.keywords;
}

// The SQL query from earlier
const sql = `select
  blog_entry.id,
  blog_entry.title,
  blog_entry.body,
  blog_entry.created
from
  blog_entry
  join blog_entry_fts on blog_entry_fts.rowid = blog_entry.rowid
where
  blog_entry_fts match :search
order by
  rank
limit
  10`;

async function runSearch(keywords) {
  // Turn the keywords into "word1" OR "word2" OR "word3"
  const search = keywords.map(s => `"${s}"`).join(" OR ");
  // Compose the JSON API URL to run the query
  const params = new URLSearchParams({
    search,
    sql,
    _shape: "array",
  });
  const url = "https://datasette.simonwillison.net/simonwillisonblog.json?" + params;
  const result = await (await fetch(url)).json();
  return result;
}

export default async function(req: Request) {
  // This is the Val Town HTTP handler
  const url = new URL(req.url);
  const question = url.searchParams.get("question").slice(0, 40);
  if (!question) {
    return Response.json({ "error": "No question provided" });
  }
  // Turn the question into search terms
  const keywords = await suggestKeywords(question);

  // Run the actual search
  const result = await runSearch(keywords);

  // Strip HTML tags from each body property, modify in-place:
  result.forEach(r => {
    r.body = r.body.replace(/<[^>]*>/g, "");
  });

  // Glue together a string of the title and body properties in one go
  const context = result.map(r => r.title + " " + r.body).join("\n\n");

  // Initially we asked for an answer, now we ask for a whole HTML document
  const message = await anthropic.messages.create({
    max_tokens: 1024,
    model: "claude-3-5-sonnet-20240620", // "claude-3-haiku-20240307",
    system: "Return a full HTML document as your answer, no markdown, make it pretty with exciting relevant CSS",
    messages: [
      { role: "user", content: context },
      { role: "assistant", content: "Thank you for the context, I am ready to answer your question as HTML" },
      { role: "user", content: question },
    ],
  });
  // Return back whatever HTML Claude gave us
  return new Response(message.content[0].text, {
    status: 200,
    headers: { "Content-Type": "text/html" }
  });
}