Vibecode Perplexity
track this build5 steps, step by step0%KINDA · weekend project
A retrieval-plus-LLM answer engine is buildable, but Perplexity's search stack, source ranking, UX, mobile/browser surfaces, and model access make full parity hard.
the project pack4 files · fastest path to a working personal build
You are building a lean indie version of Perplexity. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Perplexity indie build ## Goal Build the smallest trustworthy replacement for the core Perplexity workflow for one developer or a tiny team. ## Scope Search the web/API, fetch pages, rank passages, ask an LLM to answer with citations, and store threads. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - search quality - source ranking - model routing - mobile/browser apps - publisher integrations - speed If those capabilities are essential, use Perplexica instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build me a personal answer engine like Perplexity, wrapping real search and LLM APIs, not rebuilding them. Requirements: - A local web app on localhost:3000: Node + Express + htmx, one input box, streamed answers. - Per question: query the Brave Search API (key in .env), fetch the top 6 results with undici, extract readable text with @mozilla/readability + jsdom, then pass the question plus numbered excerpts to Claude or GPT (key in .env) with instructions to answer only from the excerpts and cite as [1][2]. - Render citations as footnote links; show the full source list under every answer. - Follow-up questions stay in the same thread with prior Q&A in the context window. - Threads stored in SQLite via better-sqlite3; a sidebar lists past threads by first question. - If a page fails to fetch or extract, drop it and continue. Never cite a page that was not fetched. - Binds to localhost only; no accounts, no telemetry, only the search and LLM calls leave my machine. - Out of scope: crawling my own web index, model routing, and mobile apps. Answer quality tracks the search API, that is the deal. - README: which keys to get (Brave Search has a free tier) and rough per-query cost. ## Required capabilities - search API - web fetcher/parser - LLM API - citation renderer - hosted backend ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a lean indie version of Perplexity. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Perplexity indie build ## Goal Build the smallest trustworthy replacement for the core Perplexity workflow for one developer or a tiny team. ## Scope Search the web/API, fetch pages, rank passages, ask an LLM to answer with citations, and store threads. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - search quality - source ranking - model routing - mobile/browser apps - publisher integrations - speed If those capabilities are essential, use Perplexica instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build me a personal answer engine like Perplexity, wrapping real search and LLM APIs, not rebuilding them. Requirements: - A local web app on localhost:3000: Node + Express + htmx, one input box, streamed answers. - Per question: query the Brave Search API (key in .env), fetch the top 6 results with undici, extract readable text with @mozilla/readability + jsdom, then pass the question plus numbered excerpts to Claude or GPT (key in .env) with instructions to answer only from the excerpts and cite as [1][2]. - Render citations as footnote links; show the full source list under every answer. - Follow-up questions stay in the same thread with prior Q&A in the context window. - Threads stored in SQLite via better-sqlite3; a sidebar lists past threads by first question. - If a page fails to fetch or extract, drop it and continue. Never cite a page that was not fetched. - Binds to localhost only; no accounts, no telemetry, only the search and LLM calls leave my machine. - Out of scope: crawling my own web index, model routing, and mobile apps. Answer quality tracks the search API, that is the deal. - README: which keys to get (Brave Search has a free tier) and rough per-query cost. ## Required capabilities - search API - web fetcher/parser - LLM API - citation renderer - hosted backend ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a production product version of Perplexity. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== PRODUCT.md ===== # Perplexity product brief ## Problem A retrieval-plus-LLM answer engine is buildable, but Perplexity's search stack, source ranking, UX, mobile/browser surfaces, and model access make full parity hard. ## Product outcome Search the web/API, fetch pages, rank passages, ask an LLM to answer with citations, and store threads. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - search API - web fetcher/parser - LLM API - citation renderer - hosted backend ## Explicit non-goals for v1 - search quality - source ranking - model routing - mobile/browser apps - publisher integrations - speed ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees. ===== ARCHITECTURE.md ===== # Architecture ## Starting brief Build me a personal answer engine like Perplexity, wrapping real search and LLM APIs, not rebuilding them. Requirements: - A local web app on localhost:3000: Node + Express + htmx, one input box, streamed answers. - Per question: query the Brave Search API (key in .env), fetch the top 6 results with undici, extract readable text with @mozilla/readability + jsdom, then pass the question plus numbered excerpts to Claude or GPT (key in .env) with instructions to answer only from the excerpts and cite as [1][2]. - Render citations as footnote links; show the full source list under every answer. - Follow-up questions stay in the same thread with prior Q&A in the context window. - Threads stored in SQLite via better-sqlite3; a sidebar lists past threads by first question. - If a page fails to fetch or extract, drop it and continue. Never cite a page that was not fetched. - Binds to localhost only; no accounts, no telemetry, only the search and LLM calls leave my machine. - Out of scope: crawling my own web index, model routing, and mobile apps. Answer quality tracks the search API, that is the deal. - README: which keys to get (Brave Search has a free tier) and rough per-query cost. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it. ===== AGENTS.md ===== # Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone. ===== MILESTONES.md ===== # Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations. ===== OPERATIONS.md ===== # Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Perplexity capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
README.md
# Perplexity indie build ## Goal Build the smallest trustworthy replacement for the core Perplexity workflow for one developer or a tiny team. ## Scope Search the web/API, fetch pages, rank passages, ask an LLM to answer with citations, and store threads. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - search quality - source ranking - model routing - mobile/browser apps - publisher integrations - speed If those capabilities are essential, use Perplexica instead of pretending the gap is solved.
AGENTS.md
# Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs".
BUILD_PLAN.md
# Build plan ## Original build brief Build me a personal answer engine like Perplexity, wrapping real search and LLM APIs, not rebuilding them. Requirements: - A local web app on localhost:3000: Node + Express + htmx, one input box, streamed answers. - Per question: query the Brave Search API (key in .env), fetch the top 6 results with undici, extract readable text with @mozilla/readability + jsdom, then pass the question plus numbered excerpts to Claude or GPT (key in .env) with instructions to answer only from the excerpts and cite as [1][2]. - Render citations as footnote links; show the full source list under every answer. - Follow-up questions stay in the same thread with prior Q&A in the context window. - Threads stored in SQLite via better-sqlite3; a sidebar lists past threads by first question. - If a page fails to fetch or extract, drop it and continue. Never cite a page that was not fetched. - Binds to localhost only; no accounts, no telemetry, only the search and LLM calls leave my machine. - Out of scope: crawling my own web index, model routing, and mobile apps. Answer quality tracks the search API, that is the deal. - README: which keys to get (Brave Search has a free tier) and rough per-query cost. ## Required capabilities - search API - web fetcher/parser - LLM API - citation renderer - hosted backend ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden.
.env.example
# Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
PRODUCT.md
# Perplexity product brief ## Problem A retrieval-plus-LLM answer engine is buildable, but Perplexity's search stack, source ranking, UX, mobile/browser surfaces, and model access make full parity hard. ## Product outcome Search the web/API, fetch pages, rank passages, ask an LLM to answer with citations, and store threads. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - search API - web fetcher/parser - LLM API - citation renderer - hosted backend ## Explicit non-goals for v1 - search quality - source ranking - model routing - mobile/browser apps - publisher integrations - speed ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees.
ARCHITECTURE.md
# Architecture ## Starting brief Build me a personal answer engine like Perplexity, wrapping real search and LLM APIs, not rebuilding them. Requirements: - A local web app on localhost:3000: Node + Express + htmx, one input box, streamed answers. - Per question: query the Brave Search API (key in .env), fetch the top 6 results with undici, extract readable text with @mozilla/readability + jsdom, then pass the question plus numbered excerpts to Claude or GPT (key in .env) with instructions to answer only from the excerpts and cite as [1][2]. - Render citations as footnote links; show the full source list under every answer. - Follow-up questions stay in the same thread with prior Q&A in the context window. - Threads stored in SQLite via better-sqlite3; a sidebar lists past threads by first question. - If a page fails to fetch or extract, drop it and continue. Never cite a page that was not fetched. - Binds to localhost only; no accounts, no telemetry, only the search and LLM calls leave my machine. - Out of scope: crawling my own web index, model routing, and mobile apps. Answer quality tracks the search API, that is the deal. - README: which keys to get (Brave Search has a free tier) and rough per-query cost. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it.
AGENTS.md
# Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone.
MILESTONES.md
# Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations.
OPERATIONS.md
# Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Perplexity capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
$ choose a build depth, inspect the files, then open the complete pack in your agent · this prompt is generated from the build plan · improve it via PR
They pay because answers arrive fast with sources and fewer query-building chores.
xsearch quality
xsource ranking
xmodel routing
xmobile/browser apps
xpublisher integrations
xspeed
share on X ↗"I just replaced Perplexity ($20/mo) with one prompt"
Don't feel like building it? These folks already made it free.
KhojA personal AI that searches the web and your files; broader than Perplexity, and noticeably heavier to run.open source↗
VanePerplexity with the meter removed: cited answers and deep research, provided you can run one Docker stack.open source↗
GPT ResearcherA research agent rather than a search box; it returns cited reports and a bill from whichever model you chose.open source↗all 5 free alternatives to Perplexity →· no votes, no pay-to-list · just what's real
Perplexity pricing
| plan | monthly | annual (per mo) | what you get |
|---|---|---|---|
| standard | $0 | $0 | 5 Pro Searches/day; 3 file uploads/day; 40 MB/file; practically unlimited basic searches. |
| pro | $20 | $16.67 | Higher Pro Search and file limits; 40 MB/file. |
| education pro | $10/user | — | Discounted Pro access for verified students and educators. |
| max | $200 | $166.67 | 10,000 Computer credits/month. |
| enterprise pro | $40/user | $33.33/user | 500 Computer credits/month; 500 files/project; 15,000 persistent files/user; 100 session uploads/week; 50 MB/file. |
| enterprise max | $325/user | $270.83/user | 15,000 Computer credits/month; 5,000 files/project; 50,000 persistent files/user; 1,000 session uploads/week. |
free tier5 Pro Searches/day; 3 file uploads/day; 40 MB/file
billingmonthly + annual for Pro, Max, and enterprise tiers; Education Pro is monthly; enterprise seats can mix Pro and Max
hidden costsComputer credits expire at the end of each month and do not roll over. Refills and auto-refill are available; 100 credits are priced as $1. Upgrades can be prorated.
verified 2026-08-12 · source ↗
Vibecode Perplexity
Kinda. The core of Perplexity is buildable in a weekend with the prompt on this page, but there are real gaps: search quality, source ranking. Read the honest list above before committing.
How much does Perplexity cost?
Perplexity costs about $20/month (Pro, checked 2026-07-30), which is $240 per year.
What do I lose by replacing Perplexity?
Honestly: search quality; source ranking; model routing; mobile/browser apps; publisher integrations; speed. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Perplexity?
Yes: Khoj (A personal AI that searches the web and your files; broader than Perplexity, and noticeably heavier to run.) Vane (Perplexity with the meter removed: cited answers and deep research, provided you can run one Docker stack.) GPT Researcher (A research agent rather than a search box; it returns cited reports and a bill from whichever model you chose.) All 5 curated free alternatives are at vibecodeit.com/perplexity/alternatives. The prompt is for when you want it exactly your way.