From 8be3c88711c46b5275912db23f3cdbcc66f64fb2 Mon Sep 17 00:00:00 2001 From: Swifty Date: Fri, 5 Dec 2025 16:08:37 +0100 Subject: [PATCH] feat(backend): add default store agents for seeding test databases (#11552) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit This PR adds a collection of pre-built store agents that can be loaded into test databases for development and testing purposes. ### Changes 🏗️ - Add 17 exported agent JSON files in `backend/agents/` directory - Add `StoreAgent_rows.csv` containing store listing metadata (titles, descriptions, categories, images) - Add `load_store_agents.py` script to load agents into the test database - Add `load-store-agents` Makefile target for easy execution **Included Agents:** - Flux AI Image Generator - YouTube Transcription Scraper - Decision Maker Lead Finder - Smart Meeting Prep - Automated Support Agent - Unspirational Poster Maker - AI Video Generator - Automated SEO Blog Writer - Lead Finder (Local Businesses) - LinkedIn Post Generator - YouTube to LinkedIn Post Converter - Personal Newsletter - Email Scout - Contact Finder Assistant - YouTube Video to SEO Blog Writer - AI Webpage Copy Improver - Domain Name Finder - AI Function ### Checklist 📋 #### For code changes: - [x] I have clearly listed my changes in the PR description - [x] I have made a test plan - [x] I have tested my changes according to the test plan: - [x] Run `make load-store-agents` and verify agents are loaded into the database - [x] Verify store listings appear correctly with metadata from CSV - [x] Confirm no sensitive information (API keys, secrets) is included in the exported agents #### For configuration changes: - [x] `.env.default` is updated or already compatible with my changes - [x] `docker-compose.yml` is updated or already compatible with my changes - [x] I have included a list of my configuration changes in the PR description (under **Changes**) No configuration changes required - this only adds test data and a loading script. --- autogpt_platform/Makefile | 10 +- .../backend/agents/StoreAgent_rows.csv | 242 + ..._00fdd42c-a14c-4d19-a567-65374ea0e87f.json | 3559 ++++++++ ..._31daf49d-31d3-476b-aa4c-099abc59b458.json | 590 ++ ..._415b7352-0dc6-4214-9d87-0ad3751b711d.json | 4953 +++++++++++ ..._516d813b-d1bc-470f-add7-c63a4b2c2bad.json | 447 + ..._55d40473-0f31-4ada-9e40-d3a7139fcbd4.json | 7222 +++++++++++++++++ ..._6e16e65a-ad34-4108-b4fd-4a23fced5ea2.json | 1795 ++++ ..._a03b0d8c-4751-43d6-a54e-c3b7856ba4e3.json | 1656 ++++ ..._a548e507-09a7-4b30-909c-f63fcda10fff.json | 1886 +++++ ..._b6f6f0d3-49f4-4e3b-8155-ffe9141b32c0.json | 1676 ++++ ..._b8ceb480-a7a2-4c90-8513-181a49f7071f.json | 5032 ++++++++++++ ..._c775f60d-b99f-418b-8fe0-53172258c3ce.json | 1005 +++ ..._d85882b8-633f-44ce-a315-c20a8c123d19.json | 403 + ..._e437cc95-e671-489d-b915-76561fba8c7f.json | 1064 +++ ..._e7bb29a1-23c7-4fee-aa3b-5426174b8c52.json | 1094 +++ ..._eafa21d3-bf14-4f63-a97f-a5ee41df83b3.json | 1560 ++++ ..._f2cc74bb-f43f-4395-9c35-ecb30b5b4fc9.json | 505 ++ ..._fc2c9976-0962-4625-a27b-d316573a9e7f.json | 615 ++ autogpt_platform/backend/pyproject.toml | 1 + .../backend/test/load_store_agents.py | 455 ++ 21 files changed, 35767 insertions(+), 3 deletions(-) create mode 100644 autogpt_platform/backend/agents/StoreAgent_rows.csv create mode 100644 autogpt_platform/backend/agents/agent_00fdd42c-a14c-4d19-a567-65374ea0e87f.json create mode 100644 autogpt_platform/backend/agents/agent_31daf49d-31d3-476b-aa4c-099abc59b458.json create mode 100644 autogpt_platform/backend/agents/agent_415b7352-0dc6-4214-9d87-0ad3751b711d.json create mode 100644 autogpt_platform/backend/agents/agent_516d813b-d1bc-470f-add7-c63a4b2c2bad.json create mode 100644 autogpt_platform/backend/agents/agent_55d40473-0f31-4ada-9e40-d3a7139fcbd4.json create mode 100644 autogpt_platform/backend/agents/agent_6e16e65a-ad34-4108-b4fd-4a23fced5ea2.json create mode 100644 autogpt_platform/backend/agents/agent_a03b0d8c-4751-43d6-a54e-c3b7856ba4e3.json create mode 100644 autogpt_platform/backend/agents/agent_a548e507-09a7-4b30-909c-f63fcda10fff.json create mode 100644 autogpt_platform/backend/agents/agent_b6f6f0d3-49f4-4e3b-8155-ffe9141b32c0.json create mode 100644 autogpt_platform/backend/agents/agent_b8ceb480-a7a2-4c90-8513-181a49f7071f.json create mode 100644 autogpt_platform/backend/agents/agent_c775f60d-b99f-418b-8fe0-53172258c3ce.json create mode 100644 autogpt_platform/backend/agents/agent_d85882b8-633f-44ce-a315-c20a8c123d19.json create mode 100644 autogpt_platform/backend/agents/agent_e437cc95-e671-489d-b915-76561fba8c7f.json create mode 100644 autogpt_platform/backend/agents/agent_e7bb29a1-23c7-4fee-aa3b-5426174b8c52.json create mode 100644 autogpt_platform/backend/agents/agent_eafa21d3-bf14-4f63-a97f-a5ee41df83b3.json create mode 100644 autogpt_platform/backend/agents/agent_f2cc74bb-f43f-4395-9c35-ecb30b5b4fc9.json create mode 100644 autogpt_platform/backend/agents/agent_fc2c9976-0962-4625-a27b-d316573a9e7f.json create mode 100644 autogpt_platform/backend/test/load_store_agents.py diff --git a/autogpt_platform/Makefile b/autogpt_platform/Makefile index 8b4732edd2..d99fee49d7 100644 --- a/autogpt_platform/Makefile +++ b/autogpt_platform/Makefile @@ -1,4 +1,4 @@ -.PHONY: start-core stop-core logs-core format lint migrate run-backend run-frontend +.PHONY: start-core stop-core logs-core format lint migrate run-backend run-frontend load-store-agents # Run just Supabase + Redis + RabbitMQ start-core: @@ -42,7 +42,10 @@ run-frontend: test-data: cd backend && poetry run python test/test_data_creator.py - + +load-store-agents: + cd backend && poetry run load-store-agents + help: @echo "Usage: make " @echo "Targets:" @@ -54,4 +57,5 @@ help: @echo " migrate - Run backend database migrations" @echo " run-backend - Run the backend FastAPI server" @echo " run-frontend - Run the frontend Next.js development server" - @echo " test-data - Run the test data creator" \ No newline at end of file + @echo " test-data - Run the test data creator" + @echo " load-store-agents - Load store agents from agents/ folder into test database" \ No newline at end of file diff --git a/autogpt_platform/backend/agents/StoreAgent_rows.csv b/autogpt_platform/backend/agents/StoreAgent_rows.csv new file mode 100644 index 0000000000..44a5e052fc --- /dev/null +++ b/autogpt_platform/backend/agents/StoreAgent_rows.csv @@ -0,0 +1,242 @@ +listing_id,storeListingVersionId,slug,agent_name,agent_video,agent_image,featured,sub_heading,description,categories,useForOnboarding,is_available +6e60a900-9d7d-490e-9af2-a194827ed632,d85882b8-633f-44ce-a315-c20a8c123d19,flux-ai-image-generator,Flux AI Image Generator,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/ca154dd1-140e-454c-91bd-2d8a00de3f08.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/577d995d-bc38-40a9-a23f-1f30f5774bdb.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/415db1b7-115c-43ab-bd6c-4e9f7ef95be1.jpg""]",false,Transform ideas into breathtaking images,"Transform ideas into breathtaking images with this AI-powered Image Generator. Using cutting-edge Flux AI technology, the tool crafts highly detailed, photorealistic visuals from simple text prompts. Perfect for artists, marketers, and content creators, this generator produces unique images tailored to user specifications. From fantastical scenes to lifelike portraits, users can unleash creativity with professional-quality results in seconds. Easy to use and endlessly versatile, bring imagination to life with the AI Image Generator today!","[""creative""]",false,true +f11fc6e9-6166-4676-ac5d-f07127b270c1,c775f60d-b99f-418b-8fe0-53172258c3ce,youtube-transcription-scraper,YouTube Transcription Scraper,https://youtu.be/H8S3pU68lGE,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/65bce54b-0124-4b0d-9e3e-f9b89d0dc99e.jpg""]",false,Fetch the transcriptions from the most popular YouTube videos in your chosen topic,"Effortlessly gather transcriptions from multiple YouTube videos with this agent. It scrapes and compiles video transcripts into a clean, organized list, making it easy to extract insights, quotes, or content from various sources in one go. Ideal for researchers, content creators, and marketers looking to quickly analyze or repurpose video content.","[""writing""]",false,true +17908889-b599-4010-8e4f-bed19b8f3446,6e16e65a-ad34-4108-b4fd-4a23fced5ea2,business-ownerceo-finder,Decision Maker Lead Finder,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/1020d94e-b6a2-4fa7-bbdf-2c218b0de563.jpg""]",false,Contact CEOs today,"Find the key decision-makers you need, fast. + +This agent identifies business owners or CEOs of local companies in any area you choose. Simply enter what kind of businesses you’re looking for and where, and it will: + +* Search the area and gather public information +* Return names, roles, and contact details when available +* Provide smart Google search suggestions if details aren’t found + +Perfect for: + +* B2B sales teams seeking verified leads +* Recruiters sourcing local talent +* Researchers looking to connect with business leaders + +Save hours of manual searching and get straight to the people who matter most.","[""business""]",true,true +72beca1d-45ea-4403-a7ce-e2af168ee428,415b7352-0dc6-4214-9d87-0ad3751b711d,smart-meeting-brief,Smart Meeting Prep,https://youtu.be/9ydZR2hkxaY,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/2f116ce1-63ae-4d39-a5cd-f514defc2b97.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/0a71a60a-2263-4f12-9836-9c76ab49f155.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/95327695-9184-403c-907a-a9d3bdafa6a5.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/2bc77788-790b-47d4-8a61-ce97b695e9f5.png""]",true,Business meeting briefings delivered daily,"Never walk into a meeting unprepared again. Every day at 4 pm, the Smart Meeting Prep Agent scans your calendar for tomorrow's external meetings. It reviews your past email exchanges, researches each participant's background and role, and compiles the insights into a concise briefing, so you can close your workday ready for tomorrow's calls. + +How It Works +1. At 4 pm, the agent scans your calendar and identifies external meetings scheduled for the next day. +2. It reviews recent email threads with each participant to surface key relationship history and communication context. +3. It conducts online research to gather publicly available information on roles, company backgrounds, and relevant professional data. +4. It produces a unified briefing for each participant, including past exchange highlights, profile notes, and strategic conversation points.","[""personal""]",true,true +9fa5697a-617b-4fae-aea0-7dbbed279976,b8ceb480-a7a2-4c90-8513-181a49f7071f,automated-support-ai,Automated Support Agent,https://youtu.be/nBMfu_5sgDA,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/ed56febc-2205-4179-9e7e-505d8500b66c.png""]",true,Automate up to 80 percent of inbound support emails,"Overview: +Support teams spend countless hours on basic tickets. This agent automates repetitive customer support tasks. It reads incoming requests, researches your knowledge base, and responds automatically when confident. When unsure, it escalates to a human for final resolution. + +How it Works: +New support emails are routed to the agent. +The agent checks internal documentation for answers. +It measures confidence in the answer found and either replies directly or escalates to a human. + +Business Value: +Automating the easy 80 percent of support tickets allows your team to focus on high-value, complex customer issues, improving efficiency and response times.","[""business""]",false,true +2bdac92b-a12c-4131-bb46-0e3b89f61413,31daf49d-31d3-476b-aa4c-099abc59b458,unspirational-poster-maker,Unspirational Poster Maker,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/6a490dac-27e5-405f-a4c4-8d1c55b85060.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/d343fbb5-478c-4e38-94df-4337293b61f1.jpg""]",false,Because adulting is hard,"This witty AI agent generates hilariously relatable ""motivational"" posters that tackle the everyday struggles of procrastination, overthinking, and workplace chaos with a blend of absurdity and sarcasm. From goldfish facing impossible tasks to cats in existential crises, The Unspirational Poster Maker designs tongue-in-cheek graphics and captions that mock productivity clichés and embrace our collective struggles to ""get it together."" Perfect for adding a touch of humour to the workday, these posters remind us that sometimes, all we can do is laugh at the chaos.","[""creative""]",false,true +9adf005e-2854-4cc7-98cf-f7103b92a7b7,a03b0d8c-4751-43d6-a54e-c3b7856ba4e3,ai-shortform-video-generator-create-viral-ready-content,AI Video Generator,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/8d2670b9-fea5-4966-a597-0a4511bffdc3.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/aabe8aec-0110-4ce7-a259-4f86fe8fe07d.png""]",false,Create Viral-Ready Shorts Content in Seconds,"OVERVIEW +Transform any trending headline or broad topic into a polished, vertical short-form video in a single run. +The agent automates research, scriptwriting, metadata creation, and Revid.ai rendering, returning one ready-to-publish MP4 plus its title, script and hashtags. + +HOW IT WORKS +1. Input a topic or an exact news headline. +2. The agent fetches live search results and selects the most engaging related story. +3. Key facts are summarised into concise research notes. +4. Claude writes a 30–35 second script with visual cues, a three-second hook, tension loops, and a call-to-action. +5. GPT-4o generates an eye-catching title and one or two discoverability hashtags. +6. The script is sent to a state-of-the-art AI video generator to render a single 9:16 MP4 (default: 720 p, 30 fps, voice “Brian”, style “movingImage”, music “Bladerunner 2049”). + – All voice, style and resolution settings can be adjusted in the Builder before you press ""Run"". +7. Output delivered: Title, Script, Hashtags, Video URL. + +KEY USE CASES +- Broad-topic explainers (e.g. “Artificial Intelligence” or “Climate Tech”). +- Real-time newsjacking with a specific breaking headline. +- Product-launch spotlights and quick event recaps while interest is high. + +BUSINESS VALUE +- One-click speed: from idea to finished video in minutes. +- Consistent brand look: Revid presets keep voice, style and aspect ratio on spec. +- No-code workflow: marketers create social video without design or development queues. +- Cloud convenience: Auto-GPT Cloud users are pre-configured with all required keys. + Self-hosted users simply add OpenAI, Anthropic, Perplexity (OpenRouter/Jina) and Revid keys once. + +IMPORTANT NOTES +- The agent outputs exactly one video per execution. Run it again for additional shorts. +- Video rendering time varies; AI-generated footage may take several minutes.","[""writing""]",false,true +864e48ef-fee5-42c1-b6a4-2ae139db9fc1,55d40473-0f31-4ada-9e40-d3a7139fcbd4,automated-blog-writer,Automated SEO Blog Writer,https://youtu.be/nKcDCbDVobs,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/2dd5f95b-5b30-4bf8-a11b-bac776c5141a.jpg""]",true,"Automate research, writing, and publishing for high-ranking blog posts","Scale your blog with a fully automated content engine. The Automated SEO Blog Writer learns your brand voice, finds high-demand keywords, and creates SEO-optimized articles that attract organic traffic and boost visibility. + +How it works: + +1. Share your pitch, website, and values. +2. The agent studies your site and uncovers proven SEO opportunities. +3. It spends two hours researching and drafting each post. +4. You set the cadence—publishing runs on autopilot. + +Business value: Consistently publish research-backed, optimized posts that build domain authority, rankings, and thought leadership while you focus on what matters most. + +Use cases: +• Founders: Keep your blog active with no time drain. +• Agencies: Deliver scalable SEO content for clients. +• Strategists: Automate execution, focus on strategy. +• Marketers: Drive steady organic growth. +• Local businesses: Capture nearby search traffic.","[""writing""]",false,true +6046f42e-eb84-406f-bae0-8e052064a4fa,a548e507-09a7-4b30-909c-f63fcda10fff,lead-finder-local-businesses,Lead Finder,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/abd6605f-d5f8-426b-af36-052e8ba5044f.webp""]",false,Auto-Prospect Like a Pro,"Turbo-charge your local lead generation with the AutoGPT Marketplace’s top Google Maps prospecting agent. “Lead Finder: Local Businesses” delivers verified, ready-to-contact prospects in any niche and city—so you can focus on closing, not searching. + +**WHAT IT DOES** +• Searches Google Maps via the official API (no scraping) +• Prompts like “dentists in Chicago” or “coffee shops near me” +• Returns: Name, Website, Rating, Reviews, **Phone & Address** +• Exports instantly to your CRM, sheet, or outreach workflow + +**WHY YOU’LL LOVE IT** +✓ Hyper-targeted leads in minutes +✓ Unlimited searches & locations +✓ Zero CAPTCHAs or IP blocks +✓ Works on AutoGPT Cloud or self-hosted (with your API key) +✓ Cut prospecting time by 90% + +**PERFECT FOR** +— Marketers & PPC agencies +— SEO consultants & designers +— SaaS founders & sales teams + +Stop scrolling directories—start filling your pipeline. Start now and let AI prospect while you profit. + +→ Click *Add to Library* and own your market today.","[""business""]",true,true +f623c862-24e9-44fc-8ce8-d8282bb51ad2,eafa21d3-bf14-4f63-a97f-a5ee41df83b3,linkedin-post-generator,LinkedIn Post Generator,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/297f6a8e-81a8-43e2-b106-c7ad4a5662df.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/fceebdc1-aef6-4000-97fc-4ef587f56bda.png""]",false,Auto‑craft LinkedIn gold,"Create research‑driven, high‑impact LinkedIn posts in minutes. This agent searches YouTube for the best videos on your chosen topic, pulls their transcripts, and distils the most valuable insights into a polished post ready for your company page or personal feed. + +FEATURES +• Automated YouTube research – discovers and analyses top‑ranked videos so you don’t have to +• AI‑curated synthesis – combines multiple transcripts into one authoritative narrative +• Full creative control – adjust style, tone, objective, opinion, clarity, target word count and number of videos +• LinkedIn‑optimised output – hook, 2‑3 key points, CTA, strategic line breaks, 3‑5 hashtags, no markdown +• One‑click publish – returns a ready‑to‑post text block (≤1 300 characters) + +HOW IT WORKS +1. Enter a topic and your preferred writing parameters. +2. The agent builds a YouTube search, fetches the page, and extracts the top N video URLs. +3. It pulls each transcript, then feeds them—plus your settings—into Claude 3.5 Sonnet. +4. The model writes a concise, engaging post designed for maximum LinkedIn engagement. + +USE CASES +• Thought‑leadership updates backed by fresh video research +• Rapid industry summaries after major events, webinars, or conferences +• Consistent LinkedIn content for busy founders, marketers, and creators + +WHY YOU’LL LOVE IT +Save hours of manual research, avoid surface‑level hot‑takes, and publish posts that showcase real expertise—without the heavy lift.","[""writing""]",true,true +7d4120ad-b6b3-4419-8bdb-7dd7d350ef32,e7bb29a1-23c7-4fee-aa3b-5426174b8c52,youtube-to-linkedin-post-converter,YouTube to LinkedIn Post Converter,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/f084b326-a708-4396-be51-7ba59ad2ef32.png""]",false,Transform Your YouTube Videos into Engaging LinkedIn Posts with AI,"WHAT IT DOES: +This agent converts YouTube video content into a LinkedIn post by analyzing the video's transcript. It provides you with a tailored post that reflects the core ideas, key takeaways, and tone of the original video, optimizing it for engagement on LinkedIn. + +HOW IT WORKS: +- You provide the URL to the YouTube video (required) +- You can choose the structure for the LinkedIn post (e.g., Personal Achievement Story, Lesson Learned, Thought Leadership, etc.) +- You can also select the tone (e.g., Inspirational, Analytical, Conversational, etc.) +- The transcript of the video is analyzed by the GPT-4 model and the Claude 3.5 Sonnet model +- The models extract key insights, memorable quotes, and the main points from the video +- You’ll receive a LinkedIn post, formatted according to your chosen structure and tone, optimized for professional engagement + +INPUTS: +- Source YouTube Video – Provide the URL to the YouTube video +- Structure – Choose the post format (e.g., Personal Achievement Story, Thought Leadership, etc.) +- Content – Specify the main message or idea of the post (e.g., Hot Take, Key Takeaways, etc.) +- Tone – Select the tone for the post (e.g., Conversational, Inspirational, etc.) + +OUTPUT: +- LinkedIn Post – A well-crafted, AI-generated LinkedIn post with a professional tone, based on the video content and your specified preferences + +Perfect for content creators, marketers, and professionals who want to repurpose YouTube videos for LinkedIn and boost their professional branding.","[""writing""]",false,true +c61d6a83-ea48-4df8-b447-3da2d9fe5814,00fdd42c-a14c-4d19-a567-65374ea0e87f,personalized-morning-coffee-newsletter,Personal Newsletter,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/f4b38e4c-8166-4caf-9411-96c9c4c82d4c.png""]",false,Start your day with personalized AI newsletters that deliver credibility and context for every interest or mood.,"This Personal Newsletter Agent provides a bespoke daily digest on your favorite topics and tone. Whether you prefer industry insights, lighthearted reads, or breaking news, this agent crafts your own unique newsletter to keep you informed and entertained. + + +How It Works +1. Enter your favorite topics, industries, or areas of interest. +2. Choose your tone—professional, casual, or humorous. +3. Set your preferred delivery cadence: daily or weekly. +4. The agent scans top sources and compiles 3–5 engaging stories, insights, and fun facts into a conversational newsletter. + +Skip the morning scroll and enjoy a thoughtfully curated newsletter designed just for you. Stay ahead of trends, spark creative ideas, and enjoy an effortless, informed start to your day. + + +Use Cases +• Executives: Get a daily digest of market updates and leadership insights. +• Marketers: Receive curated creative trends and campaign inspiration. +• Entrepreneurs: Stay updated on your industry without information overload.","[""research""]",true,true +e2e49cfc-4a39-4d62-a6b3-c095f6d025ff,fc2c9976-0962-4625-a27b-d316573a9e7f,email-address-finder,Email Scout - Contact Finder Assistant,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/da8a690a-7a8b-4c1d-b6f8-e2f840c0205d.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/6a2ac25c-1609-4881-8140-e6da2421afb3.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/26179263-fe06-45bd-b6a0-0754660a0a46.jpg""]",false,Find contact details from name and location using AI search,"Finding someone's professional email address can be time-consuming and frustrating. Manual searching across multiple websites, social profiles, and business directories often leads to dead ends or outdated information. + +Email Scout automates this process by intelligently searching across publicly available sources when you provide a person's name and location. Simply input basic information like ""Tim Cook, USA"" or ""Sarah Smith, London"" and let the AI assistant do the work of finding potential contact details. + +Key Features: +- Quick search from just name and location +- Scans multiple public sources +- Automated AI-powered search process +- Easy to use with simple inputs + +Perfect for recruiters, business development professionals, researchers, and anyone needing to establish professional contact. + +Note: This tool searches only publicly available information. Search results depend on what contact information people have made public. Some searches may not yield results if the information isn't publicly accessible.","[""""]",false,true +81bcc372-0922-4a36-bc35-f7b1e51d6939,e437cc95-e671-489d-b915-76561fba8c7f,ai-youtube-to-blog-converter,YouTube Video to SEO Blog Writer,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/239e5a41-2515-4e1c-96ef-31d0d37ecbeb.webp"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/c7d96966-786f-4be6-ad7d-3a51c84efc0e.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/0275a74c-e2c2-4e29-a6e4-3a616c3c35dd.png""]",false,One link. One click. One powerful blog post.,"Effortlessly transform your YouTube videos into high-quality, SEO-optimized blog posts. + +Your videos deserve a second life—in writing. +Make your content work twice as hard by repurposing it into engaging, searchable articles. + +Perfect for content creators, marketers, and bloggers, this tool analyzes video content and generates well-structured blog posts tailored to your tone, audience, and word count. Just paste a YouTube URL and let the AI handle the rest. + +FEATURES + +• CONTENT ANALYSIS + Extracts key points from the video while preserving your message and intent. + +• CUSTOMIZABLE OUTPUT + Select a tone that fits your audience: casual, professional, educational, or formal. + +• SEO OPTIMIZATION + Automatically creates engaging titles and structured subheadings for better search visibility. + +• USER-FRIENDLY + Repurpose your videos into written content to expand your reach and improve accessibility. + +Whether you're looking to grow your blog, boost SEO, or simply get more out of your content, the AI YouTube-to-Blog Converter makes it effortless. +","[""writing""]",true,true +5c3510d2-fc8b-4053-8e19-67f53c86eb1a,f2cc74bb-f43f-4395-9c35-ecb30b5b4fc9,ai-webpage-copy-improver,AI Webpage Copy Improver,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/d562d26f-5891-4b09-8859-fbb205972313.jpg""]",false,Boost Your Website's Search Engine Performance,"Elevate your web content with this powerful AI Webpage Copy Improver. Designed for marketers, SEO specialists, and web developers, this tool analyses and enhances website copy for maximum impact. Using advanced language models, it optimizes text for better clarity, SEO performance, and increased conversion rates. The AI examines your existing content, identifies areas for improvement, and generates refined copy that maintains your brand voice while boosting engagement. From homepage headlines to product descriptions, transform your web presence with AI-driven insights. Improve readability, incorporate targeted keywords, and craft compelling calls-to-action - all with the click of a button. Take your digital marketing to the next level with the AI Webpage Copy Improver.","[""marketing""]",true,true +94d03bd3-7d44-4d47-b60c-edb2f89508d6,b6f6f0d3-49f4-4e3b-8155-ffe9141b32c0,domain-name-finder,Domain Name Finder,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/28545e09-b2b8-4916-b4c6-67f982510a78.jpeg""]",false,Instantly generate brand-ready domain names that are actually available,"Overview: +Finding a domain name that fits your brand shouldn’t take hours of searching and failed checks. The Domain Name Finder Agent turns your pitch into hundreds of creative, brand-ready domain ideas—filtered by live availability so every result is actionable. + +How It Works +1. Input your product pitch, company name, or core keywords. +2. The agent analyzes brand tone, audience, and industry context. +3. It generates a list of unique, memorable domains that match your criteria. +4. All names are pre-filtered for real-time availability, so you can register immediately. + + +Business Value +Save hours of guesswork and eliminate dead ends. Accelerate brand launches, startup naming, and campaign creation with ready-to-claim domains. + + +Key Use Cases +• Startup Founders: Quickly find brand-ready domains for MVP launches or rebrands. +• Marketers: Test name options across campaigns with instant availability data. +• Entrepreneurs: Validate ideas faster with instant domain options.","[""business""]",false,true +7a831906-daab-426f-9d66-bcf98d869426,516d813b-d1bc-470f-add7-c63a4b2c2bad,ai-function,AI Function,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/620e8117-2ee1-4384-89e6-c2ef4ec3d9c9.webp"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/476259e2-5a79-4a7b-8e70-deeebfca70d7.png""]",false,Never Code Again,"AI FUNCTION MAGIC +Your AI‑powered assistant for turning plain‑English descriptions into working Python functions. + +HOW IT WORKS +1. Describe what the function should do. +2. Specify the inputs it needs. +3. Receive the generated Python code. + +FEATURES +- Effortless Function Generation: convert natural‑language specs into complete functions. +- Customizable Inputs: define the parameters that matter to you. +- Versatile Use Cases: simulate data, automate tasks, prototype ideas. +- Seamless Integration: add the generated function directly to your codebase. + +EXAMPLE +Request: “Create a function that generates 20 examples of fake people, each with a name, date of birth, job title, and age.” +Input parameter: number_of_people (default 20) +Result: a list of dictionaries such as +[ + { ""name"": ""Emma Martinez"", ""date_of_birth"": ""1992‑11‑03"", ""job_title"": ""Data Analyst"", ""age"": 32 }, + { ""name"": ""Liam O’Connor"", ""date_of_birth"": ""1985‑07‑19"", ""job_title"": ""Marketing Manager"", ""age"": 39 }, + …18 more entries… +]","[""development""]",false,true diff --git a/autogpt_platform/backend/agents/agent_00fdd42c-a14c-4d19-a567-65374ea0e87f.json b/autogpt_platform/backend/agents/agent_00fdd42c-a14c-4d19-a567-65374ea0e87f.json new file mode 100644 index 0000000000..75d4886813 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_00fdd42c-a14c-4d19-a567-65374ea0e87f.json @@ -0,0 +1,3559 @@ +{ + "id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "version": 58, + "is_active": true, + "name": "Personal Newsletter", + "description": "This Personal Newsletter Agent provides a bespoke daily digest on your favorite topics and tone. Whether you prefer industry insights, lighthearted reads, or breaking news, this agent crafts your own unique newsletter to keep you informed and entertained.\n\n\nHow It Works\n1. Enter your favorite topics, industries, or areas of interest.\n2. Choose your tone\u2014professional, casual, or humorous.\n3. Set your preferred delivery cadence: daily or weekly.\n4. The agent scans top sources and compiles 3\u20135 engaging stories, insights, and fun facts into a conversational newsletter.\n\nSkip the morning scroll and enjoy a thoughtfully curated newsletter designed just for you. Stay ahead of trends, spark creative ideas, and enjoy an effortless, informed start to your day.\n\n\nUse Cases\n\u2022 Executives: Get a daily digest of market updates and leadership insights.\n\u2022 Marketers: Receive curated creative trends and campaign inspiration.\n\u2022 Entrepreneurs: Stay updated on your industry without information overload.", + "instructions": "1. 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`) allowed only if light gray (`#eee`) and with generous vertical spacing.\n* Features images clearly grouped with their relevant text, small caption text below the image where available.\n\n---\n\n### \ud83e\udded **Sections**\n\nEach section should feel distinct through typography and whitespace, not hard dividers.\n\nExample section pattern:\n\n* Title \u2192 body \u2192 small callout or quote\n* Use **a single accent element** per section (highlighted text, tinted background block, or colored link).\n* No boxes around \u201cWhy it matters\u201d\u2013style callouts; instead, lightly tinted background or italicized text block.\n\n---\n\n### \ud83d\udcf1 **Responsiveness**\n\n* Ensure readability on mobile:\n\n * Maintain 16px font minimum\n * Auto-scale images and block widths\n * Increase line spacing slightly on mobile (`line-height: 1.8`)\n\n---\n\n### \ud83e\uddfe **Footer**\n\n* Simple and unintrusive.\n* Muted gray text, small font size (14px).\n* Optional subtle top border (`#eee`) or generous top margin (40\u201348px).\n\n---\n\n### \ud83d\udca1 **Design Keywords**\n\n> Warm \u2022 Minimal \u2022 Human \u2022 Editorial \u2022 Spacious \u2022 Typographically-driven \u2022 Confident \u2022 Soft" + }, + "user_id": "b3e41ea4-2f4c-4964-927c-fe682d857bad", + "graph_id": "b29bb8a9-d0ab-4858-adfa-af6baa7a81d9", + "input_schema": { + "type": "object", + "required": [ + "Report Text", + "Recipient Email", + "Email Subject" + ], + "properties": { + "Report Text": { + "anyOf": [ + { + "type": "string", + "format": "long-text" + }, + { + "type": "null" + } + ], + "title": "Report Text", + "secret": false, + "advanced": false + }, + "Email Subject": { + "anyOf": [ + { + "type": "string", + "format": "short-text" + }, + { + "type": "null" + } + ], + "title": "Email Subject", + "secret": false, + "advanced": false, + "description": "The subject line for the email. i.e. \"Your Report\"" + }, + "Recipient Email": { + "anyOf": [ + { + "type": "string", + "format": "short-text" + }, + { + "type": "null" + } + ], + "title": "Recipient Email", + "secret": false, + "advanced": false, + "description": "The Email Address to send the report to. i.e. your@email.com" + }, + "Report Design Brief": { + "anyOf": [ + { + "type": "string", + "format": "long-text" + }, + { + "type": "null" + } + ], + "title": "Report Design Brief", + "secret": false, + "default": "default", + "advanced": true, + "description": "(optional) Briefly describe how you would like your report to look.\n\nFor example \"Style this like a Stripe documentation page\" or \"Make it look like a high-end medical journal\"" + } + } + }, + "graph_version": 6, + "output_schema": { + "type": "object", + "required": [ + "Error", + "Raw HTML", + "Email Status" + ], + "properties": { + "Error": { + "title": "Error", + "secret": false, + "advanced": false + }, + "Raw HTML": { + "title": "Raw HTML", + "secret": false, + "advanced": false + }, + "Email Status": { + "title": "Email Status", + "secret": false, + "advanced": false + } + } + } + }, + "metadata": { + "position": { + "x": 9278.160782058398, + "y": 2084.7289729862423 + }, + "customized_name": "Send Pretty Email" + }, + "input_links": [ + { + "id": "8beb2cbe-4f77-431f-b376-33cfde908629", + "source_id": "fe3b8cd6-2c09-4d8b-98d3-70e2df92de41", + "sink_id": "1da0b365-a483-4677-ac3c-ea99270ad92e", + "source_name": "response", + "sink_name": "Report Text", + "is_static": false + }, + { + "id": "ab679265-5b24-4a02-af4d-cf12619ec793", + "source_id": "2b478887-fbf1-4128-8de8-26028cb7c8e3", + "sink_id": "1da0b365-a483-4677-ac3c-ea99270ad92e", + "source_name": "result", + "sink_name": "Recipient Email", + "is_static": true + }, + { + "id": "7b5b9a0d-df5f-4af1-9b8f-38441f299037", + "source_id": "8380fb24-95dc-439e-bd42-3454cfffbba7", + "sink_id": "1da0b365-a483-4677-ac3c-ea99270ad92e", + "source_name": "output", + "sink_name": "Email Subject", + "is_static": false + } + ], + "output_links": [], + "graph_id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "graph_version": 58, + "webhook_id": null, + "webhook": null + }, + { + "id": "65e276b6-18c0-4176-84a0-011d1b20859c", + "block_id": "286380af-9529-4b55-8be0-1d7c854abdb5", + "input_default": {}, + "metadata": { + "position": { + "x": -737.8058814655014, + "y": 32.186899799402624 + } + }, + "input_links": [ + { + "id": "ca49f19b-1a82-411e-b3ed-aaf0d8c8eec8", + "source_id": "e4eecf3d-fbd0-4095-b844-38794e6b4e7b", + "sink_id": "65e276b6-18c0-4176-84a0-011d1b20859c", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + } + ], + "output_links": [ + { + "id": "97d2344e-91e5-4358-8b43-42d278a06996", + "source_id": "65e276b6-18c0-4176-84a0-011d1b20859c", + "sink_id": "a50c18bc-508e-4b89-aa59-e908a7b7db4e", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "f56853c2-3ccc-467d-9eda-767ee4d7352f", + "source_id": "65e276b6-18c0-4176-84a0-011d1b20859c", + "sink_id": "b3cd6910-8252-4ff2-9983-335279774213", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + }, + { + "id": "e221a5a2-1b51-4c23-8019-e9bee5dc4ea0", + "source_id": "65e276b6-18c0-4176-84a0-011d1b20859c", + "sink_id": "8380fb24-95dc-439e-bd42-3454cfffbba7", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + } + ], + "graph_id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "graph_version": 58, + "webhook_id": null, + "webhook": null + }, + { + "id": "b3cd6910-8252-4ff2-9983-335279774213", + "block_id": "0e50422c-6dee-4145-83d6-3a5a392f65de", + "input_default": { + "key": "body" + }, + "metadata": { + "position": { + "x": -146.05704448321512, + "y": 39.89591730848741 + } + }, + "input_links": [ + { + "id": "f56853c2-3ccc-467d-9eda-767ee4d7352f", + "source_id": "65e276b6-18c0-4176-84a0-011d1b20859c", + "sink_id": "b3cd6910-8252-4ff2-9983-335279774213", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + } + ], + "output_links": [ + { + "id": "635f3112-295b-436e-8b07-6f67ef7cf0e2", + "source_id": "b3cd6910-8252-4ff2-9983-335279774213", + "sink_id": "0a54faab-7d56-4826-8408-f1b00042fccd", + "source_name": "output", + "sink_name": "prompt_values_#_newsletter", + "is_static": false + }, + { + "id": "b82e12d4-aef0-4675-a1f5-6ae375e41710", + "source_id": "b3cd6910-8252-4ff2-9983-335279774213", + "sink_id": "fe3b8cd6-2c09-4d8b-98d3-70e2df92de41", + "source_name": "output", + "sink_name": "prompt_values_#_newsletter", + "is_static": false + }, + { + "id": "efb10adb-9a77-4430-bc51-9a8adaf80ef2", + "source_id": "b3cd6910-8252-4ff2-9983-335279774213", + "sink_id": "a50c18bc-508e-4b89-aa59-e908a7b7db4e", + "source_name": "missing", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "graph_version": 58, + "webhook_id": null, + "webhook": null + }, + { + "id": "8380fb24-95dc-439e-bd42-3454cfffbba7", + "block_id": "0e50422c-6dee-4145-83d6-3a5a392f65de", + "input_default": { + "key": "title" + }, + "metadata": { + "position": { + "x": -139.42904518013256, + "y": 2235.26145151658 + } + }, + "input_links": [ + { + "id": "e221a5a2-1b51-4c23-8019-e9bee5dc4ea0", + "source_id": "65e276b6-18c0-4176-84a0-011d1b20859c", + "sink_id": "8380fb24-95dc-439e-bd42-3454cfffbba7", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + } + ], + "output_links": [ + { + "id": "7b5b9a0d-df5f-4af1-9b8f-38441f299037", + "source_id": "8380fb24-95dc-439e-bd42-3454cfffbba7", + "sink_id": "1da0b365-a483-4677-ac3c-ea99270ad92e", + "source_name": "output", + "sink_name": "Email Subject", + "is_static": false + } + ], + "graph_id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "graph_version": 58, + "webhook_id": null, + "webhook": null + }, + { + "id": "2b478887-fbf1-4128-8de8-26028cb7c8e3", + "block_id": "7fcd3bcb-8e1b-4e69-903d-32d3d4a92158", + "input_default": { + "name": "Your Email Address", + "secret": false, + "advanced": false, + "description": "Enter the email address at which you would like to receive the newsletter.", + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -3498.8900990289535, + "y": 563.204100068285 + } + }, + "input_links": [], + "output_links": [ + { + "id": "ab679265-5b24-4a02-af4d-cf12619ec793", + "source_id": "2b478887-fbf1-4128-8de8-26028cb7c8e3", + "sink_id": "1da0b365-a483-4677-ac3c-ea99270ad92e", + "source_name": "result", + "sink_name": "Recipient Email", + "is_static": true + } + ], + "graph_id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "graph_version": 58, + "webhook_id": null, + "webhook": null + }, + { + "id": "6c6cff92-b759-41be-a5a1-cd3976e05b24", + "block_id": "7fcd3bcb-8e1b-4e69-903d-32d3d4a92158", + "input_default": { + "name": "What time range would you like each newsletter edition to cover?", + "secret": false, + "advanced": false, + "description": "For example, you could say one day to only receive news stories that happened in the past 24 hours before at the time of sending the newsletter, or you could say one week to receive news from that week", + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -3504.8879543920716, + "y": 1362.1657779029272 + } + }, + "input_links": [], + "output_links": [ + { + "id": "628cb3f7-ec28-4d7e-a506-6dc14194452b", + "source_id": "6c6cff92-b759-41be-a5a1-cd3976e05b24", + "sink_id": "e4eecf3d-fbd0-4095-b844-38794e6b4e7b", + "source_name": "result", + "sink_name": "prompt_values_#_recency", + "is_static": true + }, + { + "id": "a8915dbf-6caf-42f7-9cef-8401fcf291ff", + "source_id": "6c6cff92-b759-41be-a5a1-cd3976e05b24", + "sink_id": "68883c29-9a9e-4c97-99ee-945920bfeab7", + "source_name": "result", + "sink_name": "prompt_values_#_recency", + "is_static": true + } + ], + "graph_id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "graph_version": 58, + "webhook_id": null, + "webhook": null + }, + { + "id": "0a54faab-7d56-4826-8408-f1b00042fccd", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-5-2025-08-07", + "retry": 3, + "prompt": "Extract and list the individual stories mentioned in the following newsletter which you believe would benefit from an accompanying picture.\nWhen making this decision, consider which stories are likely to have the best pictures available online. Do not just select every story. Consider how many images would be appropriate for a newsletter.\nFor each story you choose, output a clear, descriptive title that would make sense as a search query \u2014 not necessarily the original headline. \n\nOutput the results in XML format as follows:\n\n\n Man lands on the moon\n NASA announces next Mars mission\n\n\nHere is the newsletter content:\n\n{{newsletter | safe}}\n", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 705.45366413491, + "y": -31.198002095433587 + }, + "customized_name": "Pick Stories that need Images" + }, + "input_links": [ + { + "id": "635f3112-295b-436e-8b07-6f67ef7cf0e2", + "source_id": "b3cd6910-8252-4ff2-9983-335279774213", + "sink_id": "0a54faab-7d56-4826-8408-f1b00042fccd", + "source_name": "output", + "sink_name": "prompt_values_#_newsletter", + "is_static": false + } + ], + "output_links": [ + { + "id": "115037c7-c122-4895-8598-f5b238d2eb11", + "source_id": "0a54faab-7d56-4826-8408-f1b00042fccd", + "sink_id": "a50c18bc-508e-4b89-aa59-e908a7b7db4e", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "730b0a8f-91e7-444c-a9e3-2b93df7ab6b1", + "source_id": "0a54faab-7d56-4826-8408-f1b00042fccd", + "sink_id": "e94bcdb4-67a8-40ea-9bc1-e6672a4bd87a", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + } + ], + "graph_id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "graph_version": 58, + "webhook_id": null, + "webhook": null + }, + { + "id": "e94bcdb4-67a8-40ea-9bc1-e6672a4bd87a", + "block_id": "286380af-9529-4b55-8be0-1d7c854abdb5", + "input_default": {}, + "metadata": { + "position": { + "x": 1325.4881632458146, + "y": -30.03409103591575 + } + }, + "input_links": [ + { + "id": "730b0a8f-91e7-444c-a9e3-2b93df7ab6b1", + "source_id": "0a54faab-7d56-4826-8408-f1b00042fccd", + "sink_id": "e94bcdb4-67a8-40ea-9bc1-e6672a4bd87a", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + } + ], + "output_links": [ + { + "id": "bdc99d05-b6f8-4b2f-8741-c4ab5d2c188e", + "source_id": "e94bcdb4-67a8-40ea-9bc1-e6672a4bd87a", + "sink_id": "58df8a79-a41a-4c83-8adc-6bb517b4eb43", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + }, + { + "id": "7d4464f3-87bf-4d58-b16a-232a9123f0c3", + "source_id": "e94bcdb4-67a8-40ea-9bc1-e6672a4bd87a", + "sink_id": "a50c18bc-508e-4b89-aa59-e908a7b7db4e", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "graph_version": 58, + "webhook_id": null, + "webhook": null + }, + { + "id": "fe3b8cd6-2c09-4d8b-98d3-70e2df92de41", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-5-2025-08-07", + "retry": 3, + "prompt": "You are given a newsletter. Each story includes an associated image URL. While not every image needs to be used (as too many may overcrowd the layout), it might also make sense to include them all\u2014use your judgment.\n\nYour task is to reproduce the newsletter **verbatim** in markdown format, inserting the image URLs where they fit best. \n\nDo not alter or reword the newsletter text in any way\u2014this is absolutely critical. Simply return the unedited newsletter text with the image URLs appropriately placed. Include no extra commentary, explanation, or decoration\u2014only the final markdown output.\n\n\nHere is the newsletter and the URLs:\n\n\n{{newsletter | safe}}\n\n\n\n{{image_urls | safe}}\n\n\nNow, respond with the final newsletter text with no additional commentary, explanation, or decoration. ", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 8400.349484389619, + "y": -8.39926280284628 + }, + "customized_name": "Insert Images into Newsletter" + }, + "input_links": [ + { + "id": "fc9ae566-2a36-4ae9-ac2c-c5fdb7ae7a03", + "source_id": "131f496c-544c-48e5-ac63-0fa2b6554d1e", + "sink_id": "fe3b8cd6-2c09-4d8b-98d3-70e2df92de41", + "source_name": "value", + "sink_name": "prompt_values_#_image_urls", + "is_static": false + }, + { + "id": "b82e12d4-aef0-4675-a1f5-6ae375e41710", + "source_id": "b3cd6910-8252-4ff2-9983-335279774213", + "sink_id": "fe3b8cd6-2c09-4d8b-98d3-70e2df92de41", + "source_name": "output", + "sink_name": "prompt_values_#_newsletter", + "is_static": false + } + ], + "output_links": [ + { + "id": "8d8ffa53-6012-4d5a-934b-96a732f384f3", + "source_id": "fe3b8cd6-2c09-4d8b-98d3-70e2df92de41", + "sink_id": "a50c18bc-508e-4b89-aa59-e908a7b7db4e", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "16a4267d-aaf5-4636-95f9-bdb2c5e83385", + "source_id": "fe3b8cd6-2c09-4d8b-98d3-70e2df92de41", + "sink_id": "bb142109-ea01-4917-b32d-2848716bd154", + "source_name": "response", + "sink_name": "value", + "is_static": false + }, + { + "id": "8beb2cbe-4f77-431f-b376-33cfde908629", + "source_id": "fe3b8cd6-2c09-4d8b-98d3-70e2df92de41", + "sink_id": "1da0b365-a483-4677-ac3c-ea99270ad92e", + "source_name": "response", + "sink_name": "Report Text", + "is_static": false + } + ], + "graph_id": "6cf51c3a-25dd-4189-bd50-5ee05a5f7794", + "graph_version": 58, + "webhook_id": null, + "webhook": null + }, + { + "id": "a95ad0cb-9644-4fa5-b2d3-4ae80a9f75c0", + "block_id": "31d1064e-7446-4693-a7d4-65e5ca1180d1", + "input_default": { + "entries": {}, + "dictionary": {} + }, + "metadata": { + "position": { + "x": 4312.272039894743, + "y": 13.125548418915074 + } + }, + "input_links": [ + { + "id": "6ba524c6-3227-43e2-89a8-a2795b21f275", + "source_id": "5c52e32d-f1c8-4400-a107-85bb4ebb218d", + "sink_id": "a95ad0cb-9644-4fa5-b2d3-4ae80a9f75c0", + "source_name": "output", + "sink_name": "key", + "is_static": false + }, + { + "id": "9daa4f4e-2cf7-4ec6-b57d-cde111b1a596", + "source_id": "2d0abd00-ca63-4bf7-9a65-730e356eb52a", + "sink_id": "a95ad0cb-9644-4fa5-b2d3-4ae80a9f75c0", + "source_name": "Error", + "sink_name": "value", + "is_static": false + }, + { + "id": "0a0265e8-47be-4a1c-8da0-9e346f2f7787", + "source_id": "2d0abd00-ca63-4bf7-9a65-730e356eb52a", + "sink_id": "a95ad0cb-9644-4fa5-b2d3-4ae80a9f75c0", + "source_name": "URLs", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [ + { + "id": "f5763443-3bd7-4a6c-8688-9bc288dc1fed", + "source_id": "a95ad0cb-9644-4fa5-b2d3-4ae80a9f75c0", + "sink_id": "fb8d7f23-43eb-486e-8fbd-15de021c06d4", + "source_name": "updated_dictionary", + "sink_name": "entry", + "is_static": false + }, + { + "id": "25e097a1-df65-43c9-bb20-cd73b4fb7cc3", + "source_id": 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or you could say one week to receive news from that week" + } + }, + "required": [ + "Your Email Address", + "What time range would you like each newsletter edition to cover?" + ] + }, + "output_schema": { + "type": "object", + "properties": { + "Newsletter": { + "advanced": false, + "secret": false, + "title": "Newsletter" + }, + "Error": { + "advanced": false, + "secret": false, + "title": "Error" + } + }, + "required": [ + "Newsletter", + "Error" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": 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"microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "claude-sonnet-4-20250514" + ] + }, + "google_oauth2_credentials": { + "credentials_provider": [ + "google" + ], + "credentials_types": [ + "oauth2" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "google", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "oauth2", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['oauth2']]", + "type": "object", + "credentials_scopes": [ + "https://www.googleapis.com/auth/gmail.send" + ], + "discriminator_values": [] + }, + "jina_api_key_credentials": { + "credentials_provider": [ + "jina" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "jina", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + } + }, + "required": [ + "openai_api_key_credentials", + "open_router_api_key_credentials", + "anthropic_api_key_credentials", + "google_oauth2_credentials", + "jina_api_key_credentials" + ], + "title": "PersonalNewsletterCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_31daf49d-31d3-476b-aa4c-099abc59b458.json b/autogpt_platform/backend/agents/agent_31daf49d-31d3-476b-aa4c-099abc59b458.json new file mode 100644 index 0000000000..c796083b28 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_31daf49d-31d3-476b-aa4c-099abc59b458.json 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From goldfish facing impossible tasks to cats in existential crises, The Unspirational Poster Maker designs tongue-in-cheek graphics and captions that mock productivity clich\u00e9s and embrace our collective struggles to \"get it together.\" Perfect for adding a touch of humour to the workday, these posters remind us that sometimes, all we can do is laugh at the chaos.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "5ac3727a-1ea7-436b-a902-ef1bfd883a30", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Generated Image", + "description": "The resulting generated image ready for you to review and post." + }, + "metadata": { + "position": { + "x": 2329.937006807125, + "y": 80.49068076698347 + } + }, + "input_links": [ + { + "id": "c6c511e8-e6a4-4969-9bc8-f67d60c1e229", + "source_id": "86665e90-ffbf-48fb-ad3f-e5d31fd50c51", + "sink_id": "5ac3727a-1ea7-436b-a902-ef1bfd883a30", + "source_name": "result", + 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Text Overlay: \"Chaos is a career path. 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The keyboard is on top of a laptop with a blank spreadsheet open. A to-do list is placed beside the laptop, with the top item written as \"Do literally anything\". 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"sink_name": "prompt", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "sub_graphs": [], + "user_id": "", + "created_at": "2024-12-20T19:58:34.390Z", + "input_schema": { + "type": "object", + "properties": { + "Theme": { + "advanced": false, + "secret": false, + "title": "Theme", + "default": "Cooking" + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "Generated Image": { + "advanced": false, + "secret": false, + "title": "Generated Image", + "description": "The resulting generated image ready for you to review and post." + } + }, + "required": [ + "Generated Image" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "ideogram_api_key_credentials": { + "credentials_provider": [ + "ideogram" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "ideogram", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + }, + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "gpt-4o" + ] + } + }, + "required": [ + "ideogram_api_key_credentials", + "openai_api_key_credentials" + ], + "title": "UnspirationalPosterMakerCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_415b7352-0dc6-4214-9d87-0ad3751b711d.json b/autogpt_platform/backend/agents/agent_415b7352-0dc6-4214-9d87-0ad3751b711d.json new file mode 100644 index 0000000000..3b52477795 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_415b7352-0dc6-4214-9d87-0ad3751b711d.json @@ -0,0 +1,4953 @@ +{ + "id": "5231292e-9f27-4ac0-bda6-b67daf1fa765", + "version": 145, + "is_active": true, + "name": "Smart Meeting Prep", + "description": "Never walk into a meeting unprepared again. Every day at 4 pm, the Smart Meeting Prep Agent scans your calendar for tomorrow's external meetings. It reviews your past email exchanges, researches each participant's background and role, and compiles the insights into a concise briefing, so you can close your workday ready for tomorrow's calls.\n\nHow It Works\n1. At 4 pm, the agent scans your calendar and identifies external meetings scheduled for the next day.\n2. It reviews recent email threads with each participant to surface key relationship history and communication context.\n3. It conducts online research to gather publicly available information on roles, company backgrounds, and relevant professional data.\n4. 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"480fb04f-089a-42f4-ba0a-04903d90c953", + "sink_id": "9b83fe30-6887-438a-816f-a03eb0910bc3", + "source_name": "result", + "sink_name": "values_#_email", + "is_static": true + }, + { + "id": "d03d0f61-8d43-4285-b460-ede1ef85706b", + "source_id": "480fb04f-089a-42f4-ba0a-04903d90c953", + "sink_id": "f26280fe-3296-4ce6-83ab-3c5213a43716", + "source_name": "result", + "sink_name": "prompt_values_#_target_email", + "is_static": true + }, + { + "id": "90f08627-a930-4405-8053-f2d6175d5386", + "source_id": "480fb04f-089a-42f4-ba0a-04903d90c953", + "sink_id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "source_name": "result", + "sink_name": "prompt_values_#_target_email", + "is_static": true + }, + { + "id": "32a2b355-8c6a-4872-8902-e7bbd8e11a8b", + "source_id": "480fb04f-089a-42f4-ba0a-04903d90c953", + "sink_id": "8101e732-9400-42b6-84c1-235dfcc7274c", + "source_name": "result", + "sink_name": "prompt_values_#_target_email", + "is_static": true + } + ] + }, + { + "id": "8ae2698f-1bd8-42fc-976a-3167717ce8d2", + "block_id": "25310c70-b89b-43ba-b25c-4dfa7e2a481c", + "input_default": { + "query": "is:unread", + "max_results": 30 + }, + "metadata": { + "position": { + "x": -4643.9226948203395, + "y": 2172.989467947373 + } + }, + "input_links": [ + { + "id": "20e29442-d609-48b5-918e-919ff87280c5", + "source_id": "9b83fe30-6887-438a-816f-a03eb0910bc3", + "sink_id": "8ae2698f-1bd8-42fc-976a-3167717ce8d2", + "source_name": "output", + "sink_name": "query", + "is_static": false + } + ], + "output_links": [ + { + "id": "596f14d0-7270-429b-b779-479c8fc978be", + "source_id": "8ae2698f-1bd8-42fc-976a-3167717ce8d2", + "sink_id": "5356c145-be3d-4b38-a553-78ec99fb7261", + "source_name": "emails", + "sink_name": "value", + "is_static": false + }, + { + "id": "c614173a-9b4e-4e52-987b-dc60118bb2e4", + "source_id": "8ae2698f-1bd8-42fc-976a-3167717ce8d2", + "sink_id": "347fad9f-d49f-46f3-8c49-cbcf67387052", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ] + }, + { + "id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-5-2025-08-07", + "retry": 3, + "prompt": "Identify the owner of \"{{target_email | safe}}\" from the following data. \n\nProvide their full name and any additional information that can be gleaned about their identity from the data (i.e role, company, skills/characteristics, accounts/online profile links etc). \n\nDo not make any assumptions when doing this, provide only what you can verify. \n\nIf there are any meeting notes or written emails present, use them to provide notes on the relationship between me (\"{{user_email | safe}}\") and \"{{target_email | safe}}\", and to remind me of things that it would be beneficial for me to remember regarding them and things they've told me.\n\n\n{{RAW_DATA | safe}}\n", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": -3445.1320373310455, + "y": 2153.301716589669 + } + }, + "input_links": [ + { + "id": "fb24b852-da8d-4cb7-bd2d-e92ff4c3ef9b", + "source_id": "a906c063-c42f-4535-b607-c21ec0ff3ea2", + "sink_id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "source_name": "result", + "sink_name": "prompt_values_#_user_email", + "is_static": true + }, + { + "id": "6706cc77-d18c-4a5d-a27c-583648482d9d", + "source_id": "5356c145-be3d-4b38-a553-78ec99fb7261", + "sink_id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "source_name": "value", + "sink_name": "prompt_values_#_RAW_DATA", + "is_static": false + }, + { + "id": "90f08627-a930-4405-8053-f2d6175d5386", + "source_id": "480fb04f-089a-42f4-ba0a-04903d90c953", + "sink_id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "source_name": "result", + "sink_name": "prompt_values_#_target_email", + "is_static": true + } + ], + "output_links": [ + { + "id": "5b703b2d-36ec-46dd-8a52-e5ee7bb415c1", + "source_id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "sink_id": "347fad9f-d49f-46f3-8c49-cbcf67387052", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "e46395fa-cc9e-4e41-9f01-2a38bee74bb3", + "source_id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "sink_id": "f26280fe-3296-4ce6-83ab-3c5213a43716", + "source_name": "response", + "sink_name": "prompt_values_#_research", + "is_static": false + } + ] + }, + { + "id": "5356c145-be3d-4b38-a553-78ec99fb7261", + "block_id": "95d1b990-ce13-4d88-9737-ba5c2070c97b", + "input_default": { + "type": "string" + }, + "metadata": { + "position": { + "x": -4044.709675038533, + "y": 2154.011502560513 + } + }, + "input_links": [ + { + "id": "596f14d0-7270-429b-b779-479c8fc978be", + "source_id": "8ae2698f-1bd8-42fc-976a-3167717ce8d2", + "sink_id": "5356c145-be3d-4b38-a553-78ec99fb7261", + "source_name": "emails", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [ + { + "id": "6706cc77-d18c-4a5d-a27c-583648482d9d", + "source_id": "5356c145-be3d-4b38-a553-78ec99fb7261", + "sink_id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "source_name": "value", + "sink_name": "prompt_values_#_RAW_DATA", + "is_static": false + }, + { + "id": "0ed18996-cb91-4cf6-b55c-af2a94daad78", + "source_id": "5356c145-be3d-4b38-a553-78ec99fb7261", + "sink_id": "347fad9f-d49f-46f3-8c49-cbcf67387052", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "531d9ab3-cdd2-4f8c-ac54-9065db1647ed", + "source_id": "5356c145-be3d-4b38-a553-78ec99fb7261", + "sink_id": "8101e732-9400-42b6-84c1-235dfcc7274c", + "source_name": "value", + "sink_name": "prompt_values_#_RAW_DATA", + "is_static": false + } + ] + }, + { + "id": "9b83fe30-6887-438a-816f-a03eb0910bc3", + "block_id": "db7d8f02-2f44-4c55-ab7a-eae0941f0c30", + "input_default": { + "format": "from:{{email | safe}} OR to:{{email | safe}} OR \"{{email | safe}}\"", + "values": {} + }, + "metadata": { + "position": { + "x": -5261.837850853275, + "y": 2145.29281130474 + } + }, + "input_links": [ + { + "id": "7ffdbe78-88fd-4a53-83ce-7c04d146afef", + "source_id": "480fb04f-089a-42f4-ba0a-04903d90c953", + "sink_id": "9b83fe30-6887-438a-816f-a03eb0910bc3", + "source_name": "result", + "sink_name": "values_#_email", + "is_static": true + } + ], + "output_links": [ + { + "id": "20e29442-d609-48b5-918e-919ff87280c5", + "source_id": "9b83fe30-6887-438a-816f-a03eb0910bc3", + "sink_id": "8ae2698f-1bd8-42fc-976a-3167717ce8d2", + "source_name": "output", + "sink_name": "query", + "is_static": false + } + ] + }, + { + "id": "a906c063-c42f-4535-b607-c21ec0ff3ea2", + "block_id": "7fcd3bcb-8e1b-4e69-903d-32d3d4a92158", + "input_default": { + "name": "Your Email", + "secret": false, + "advanced": false, + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -6011.4052138380575, + "y": 2147.1415239684898 + } + }, + "input_links": [], + "output_links": [ + { + "id": "fb24b852-da8d-4cb7-bd2d-e92ff4c3ef9b", + "source_id": "a906c063-c42f-4535-b607-c21ec0ff3ea2", + "sink_id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "source_name": "result", + "sink_name": "prompt_values_#_user_email", + "is_static": true + }, + { + "id": "3dd822a9-10c7-4b42-b925-b983185adcc2", + "source_id": "a906c063-c42f-4535-b607-c21ec0ff3ea2", + "sink_id": "8101e732-9400-42b6-84c1-235dfcc7274c", + "source_name": "result", + "sink_name": "prompt_values_#_user_email", + "is_static": true + } + ] + }, + { + "id": "f26280fe-3296-4ce6-83ab-3c5213a43716", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-5-2025-08-07", + "retry": 3, + "prompt": "You are a brilliant prompt-writer. \nYour job is to WRITE a Deep Research prompt for Perplexity\u2019s Deep Research Agent in order to identify the owner of \"email\" that will only produce a dossier if identity is verified to a high bar.\n\nWHAT WE KNOW SO FAR (FROM THE USER'S INBOX)\n\n{{research | safe}}\n\n\nGOAL\nFrom the research above, extract {{target_email | safe}}'s identity, then GENERATE a ready-to-send Perplexity request that:\n1) Forces identity confirmation first (no guessing; return AMBIGUOUS if unsure).\n2) Avoids revealing or using private emails/meeting links in the public search.\n3) Pins the search to the correct human (disambiguates homonyms).\n4) If verified, finds out as much VERIFIABLY accurate information about the person as possible.\n\nDO NOT do any web research yourself. Only WRITE the Perplexity request.\n\nDISAMBIGUATION HEURISTICS (for the request you write)\nHave Perplexity accept a candidate ONLY if \u22652 of:\n1) The public profile is clearly software/AI/engineering related (exclude unrelated homonyms like musicians unless they ALSO meet #2). \n2) Signals of agents/LLMs/dev tooling/startups or affiliation with a named org you infer from public sources. \n3) Geography consistent with hints (time zone/region) \u2014 weak alone; must pair with #1 or #2. \n4) Cross-source agreement across \u22652 reputable, independent sources (e.g., LinkedIn + GitHub, company site + conf bio).\n\nWHAT TO OUTPUT (Prompt ONLY, no prose, no markdown)\n- A single set of ... xml tags containing your given prompt text for the deep research request.\n- DO NOT include any xml tags inside of these ... tags. Any additional use of whatsoever will break the xml parsing setup.", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": -2797.215927245378, + "y": 2141.7155411686153 + } + }, + "input_links": [ + { + "id": "d03d0f61-8d43-4285-b460-ede1ef85706b", + "source_id": "480fb04f-089a-42f4-ba0a-04903d90c953", + "sink_id": "f26280fe-3296-4ce6-83ab-3c5213a43716", + "source_name": "result", + "sink_name": "prompt_values_#_target_email", + "is_static": true + }, + { + "id": "e46395fa-cc9e-4e41-9f01-2a38bee74bb3", + "source_id": "e007dd2d-6b22-42d6-b1d7-f955017e0830", + "sink_id": "f26280fe-3296-4ce6-83ab-3c5213a43716", + "source_name": "response", + "sink_name": "prompt_values_#_research", + "is_static": false + } + ], + "output_links": [ + { + "id": "56fa8329-98d3-4ac4-aafc-80b26767f45f", + "source_id": "f26280fe-3296-4ce6-83ab-3c5213a43716", + "sink_id": "347fad9f-d49f-46f3-8c49-cbcf67387052", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "eec6a3b5-7f34-49ae-9d49-231c7fa31b9d", + "source_id": "f26280fe-3296-4ce6-83ab-3c5213a43716", + "sink_id": "0835f399-b960-4adb-8ea0-316a61632106", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + } + ] + }, + { + "id": "cdac63f1-eee2-4e99-818d-c7c9f2560d18", + "block_id": "e189baac-8c20-45a1-94a7-55177ea42565", + "input_default": { + "inputs": {}, + "user_id": "b3e41ea4-2f4c-4964-927c-fe682d857bad", + "graph_id": "f89ac5a2-fbd0-476e-8666-23e2574236ca", + "input_schema": { + "type": "object", + "required": [ + "Question" + ], + "properties": { + "Question": { + "anyOf": [ + { + "type": "string", + "format": "short-text" + }, + { + "type": "null" + } + ], + "title": "Question", + "secret": false, + "advanced": false + } + } + }, + "graph_version": 4, + "output_schema": { + "type": "object", + "required": [ + "Answer", + "Error" + ], + "properties": { + "Error": { + "title": "Error", + "secret": false, + "advanced": false + }, + "Answer": { + "title": "Answer", + "secret": false, + "advanced": false + } + } + } + }, + "metadata": { + "position": { + "x": -1028.193817200345, + "y": 2166.664113149024 + } + }, + "input_links": [ + { + "id": "dec10a13-fcd8-40dd-abdd-3cc8f61df5f5", + "source_id": "c3fc4d6d-8ae7-44b4-a4cb-771f20a2f448", + "sink_id": "cdac63f1-eee2-4e99-818d-c7c9f2560d18", + "source_name": "output", + "sink_name": "Question", + "is_static": false + } + ], + "output_links": [ + { + "id": "cb61f771-fc15-4aba-852d-6e0984f26c41", + "source_id": "cdac63f1-eee2-4e99-818d-c7c9f2560d18", + "sink_id": "0c8e7071-4424-409b-af01-4892ddc5b4fa", + "source_name": "Answer", + "sink_name": "value", + "is_static": false + }, + { + "id": "c09a29f7-e91a-416d-bfb4-6d4da3047133", + "source_id": "cdac63f1-eee2-4e99-818d-c7c9f2560d18", + "sink_id": "347fad9f-d49f-46f3-8c49-cbcf67387052", + "source_name": "Error", + "sink_name": "value", + "is_static": false + } + ] + }, + { + "id": "0835f399-b960-4adb-8ea0-316a61632106", + "block_id": "286380af-9529-4b55-8be0-1d7c854abdb5", + "input_default": {}, + "metadata": { + "position": { + "x": -2198.193790964403, + "y": 2141.6640881280887 + } + }, + "input_links": [ + { + "id": "eec6a3b5-7f34-49ae-9d49-231c7fa31b9d", + "source_id": "f26280fe-3296-4ce6-83ab-3c5213a43716", + "sink_id": "0835f399-b960-4adb-8ea0-316a61632106", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + } + ], + "output_links": [ + { + "id": "f79a3f6a-f6ad-4d5a-adc9-c2abed207d30", + "source_id": "0835f399-b960-4adb-8ea0-316a61632106", + "sink_id": "347fad9f-d49f-46f3-8c49-cbcf67387052", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "2ff7d45e-269d-4321-8c43-00532892dd0d", + "source_id": "0835f399-b960-4adb-8ea0-316a61632106", + "sink_id": "c3fc4d6d-8ae7-44b4-a4cb-771f20a2f448", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + } + ] + }, + { + "id": 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"e4d9c513-ab2d-4435-ba54-62545932710a", + "sink_id": "55232481-5336-4046-a7e7-f1ba843698c9", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "8cf832f2-d113-4e48-a443-c1842bde9335", + "source_id": "231ed59c-eb30-436f-bdb4-52c1512518cf", + "sink_id": "e4d9c513-ab2d-4435-ba54-62545932710a", + "source_name": "result", + "sink_name": "prompt", + "is_static": true + }, + { + "id": "094fa24b-5634-4bc8-9a5e-2222ab433c11", + "source_id": "e4d9c513-ab2d-4435-ba54-62545932710a", + "sink_id": "7e7a642f-f1e9-4a28-82ae-fa133bafa28b", + "source_name": "response", + "sink_name": "value", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "input_schema": { + "type": "object", + "properties": { + "Question": { + "advanced": false, + "anyOf": [ + { + "format": "short-text", + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Question" + } + }, + "required": [ + "Question" + ] + }, + "output_schema": { + "type": "object", + "properties": { + "Answer": { + "advanced": false, + "secret": false, + "title": "Answer" + }, + "Error": { + "advanced": false, + "secret": false, + "title": "Error" + } + }, + "required": [ + "Answer", + "Error" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null + } + ], + "user_id": "", + "created_at": "2025-08-30T10:24:03.147Z", + "input_schema": { + "type": "object", + "properties": { + "Your email address": { + "advanced": false, + "anyOf": [ + { + "format": "short-text", + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Your email address", + "description": "The work email address you use for your meetings. \nYour daily briefings will be sent to you here." + } + }, + "required": [ + "Your email address" + ] + }, + "output_schema": { + "type": "object", + "properties": { + "Meeting Prep Report Text": { + "advanced": false, + "secret": false, + "title": "Meeting Prep Report Text", + "description": "Plain Text Report, the full report was emailed to you." + }, + "Error": { + "advanced": false, + "secret": false, + "title": "Error" + }, + "Internal Only Meeting": { + "advanced": false, + "secret": false, + "title": "Internal Only Meeting", + "description": "At least one internal meeting was detected, I won't brief you for it as I'm assuming you already have background info on your colleagues." + }, + "Email Status": { + "advanced": false, + "secret": false, + "title": "Email Status", + "description": "Whether or not the briefing was successfully sent" + }, + "No Meetings Found": { + "advanced": false, + "secret": false, + "title": "No Meetings Found" + }, + "Meeting Prep Report Error": { + "advanced": false, + "secret": false, + "title": "Meeting Prep Report Error", + "description": "Error generating or emailing the final report - please email contact@agpt.co" + } + }, + "required": [ + "Meeting Prep Report Text", + "Error", + "Internal Only Meeting", + "Email Status", + "No Meetings Found", + "Meeting Prep Report Error" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "google_oauth2_credentials": { + "credentials_provider": [ + "google" + ], + "credentials_types": [ + "oauth2" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "google", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "oauth2", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['oauth2']]", + "type": "object", + "credentials_scopes": [ + "https://www.googleapis.com/auth/gmail.send", + "https://www.googleapis.com/auth/calendar.readonly", + "https://www.googleapis.com/auth/gmail.readonly" + ], + "discriminator_values": [] + }, + "anthropic_api_key_credentials": { + "credentials_provider": [ + "anthropic" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "anthropic", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "claude-sonnet-4-20250514" + ] + }, + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "gpt-5-2025-08-07" + ] + }, + "open_router_api_key_credentials": { + "credentials_provider": [ + "open_router" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "open_router", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "perplexity/sonar-deep-research" + ] + } + }, + "required": [ + "google_oauth2_credentials", + "anthropic_api_key_credentials", + "openai_api_key_credentials", + "open_router_api_key_credentials" + ], + "title": "SmartMeetingPrepCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_516d813b-d1bc-470f-add7-c63a4b2c2bad.json b/autogpt_platform/backend/agents/agent_516d813b-d1bc-470f-add7-c63a4b2c2bad.json new file mode 100644 index 0000000000..028e4249e7 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_516d813b-d1bc-470f-add7-c63a4b2c2bad.json @@ -0,0 +1,447 @@ +{ + "id": "622849a7-5848-4838-894d-01f8f07e3fad", + "version": 18, + "is_active": true, + "name": "AI Function", + "description": "## AI-Powered Function Magic: Never code again!\nProvide a description of a python function and your inputs and AI will provide the results.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "26ff2973-3f9a-451d-b902-d45e5da0a7fe", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "return", + "title": null, + "value": null, + "format": "", + "secret": false, + "advanced": false, + "description": "The value returned by the function" + }, + "metadata": { + "position": { + "x": 1598.8622921127233, + "y": 291.59140862204725 + } + }, + "input_links": [ + { + "id": "caecc1de-fdbc-4fd9-9570-074057bb15f9", + "source_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "sink_id": "26ff2973-3f9a-451d-b902-d45e5da0a7fe", + "source_name": "response", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "622849a7-5848-4838-894d-01f8f07e3fad", + "graph_version": 18, + "webhook_id": null, + "webhook": null + }, + { + "id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "o3-mini", + "retry": 3, + "prompt": "{{ARGS}}", + "sys_prompt": "You are now the following python function:\n\n```\n# {{DESCRIPTION}}\n{{FUNCTION}}\n```\n\nThe user will provide your input arguments.\nOnly respond with your `return` value.\nDo not include any commentary or additional text in your response. \nDo not include ``` backticks or any other decorators.", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 995, + "y": 290.50000000000006 + } + }, + "input_links": [ + { + "id": "dc7cb15f-76cc-4533-b96c-dd9e3f7f75ed", + "source_id": "4eab3a55-20f2-4c1d-804c-7377ba8202d2", + "sink_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "source_name": "result", + "sink_name": "prompt_values_#_FUNCTION", + "is_static": true + }, + { + "id": "093bdca5-9f44-42f9-8e1c-276dd2971675", + "source_id": "844530de-2354-46d8-b748-67306b7bbca1", + "sink_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "source_name": "result", + "sink_name": "prompt_values_#_ARGS", + "is_static": true + }, + { + "id": "6c63d8ee-b63d-4ff6-bae0-7db8f99bb7af", + "source_id": "0fd6ef54-c1cd-478d-b764-17e40f882b99", + "sink_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "source_name": "result", + "sink_name": "prompt_values_#_DESCRIPTION", + "is_static": true + } + ], + "output_links": [ + { + "id": "caecc1de-fdbc-4fd9-9570-074057bb15f9", + "source_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "sink_id": "26ff2973-3f9a-451d-b902-d45e5da0a7fe", + "source_name": "response", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "622849a7-5848-4838-894d-01f8f07e3fad", + "graph_version": 18, + "webhook_id": null, + "webhook": null + }, + { + "id": "4eab3a55-20f2-4c1d-804c-7377ba8202d2", + "block_id": "7fcd3bcb-8e1b-4e69-903d-32d3d4a92158", + "input_default": { + "name": "Function Definition", + "title": null, + "value": "def fake_people(n: int) -> list[dict]:", + "secret": false, + "advanced": false, + "description": "The function definition (text). This is what you would type on the first line of the function when programming.\n\ne.g \"def fake_people(n: int) -> list[dict]:\"", + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -672.6908629664215, + "y": 302.42044359789116 + } + }, + "input_links": [], + "output_links": [ + { + "id": "dc7cb15f-76cc-4533-b96c-dd9e3f7f75ed", + "source_id": "4eab3a55-20f2-4c1d-804c-7377ba8202d2", + "sink_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "source_name": "result", + "sink_name": "prompt_values_#_FUNCTION", + "is_static": true + } + ], + "graph_id": "622849a7-5848-4838-894d-01f8f07e3fad", + "graph_version": 18, + "webhook_id": null, + "webhook": null + }, + { + "id": "844530de-2354-46d8-b748-67306b7bbca1", + "block_id": "7fcd3bcb-8e1b-4e69-903d-32d3d4a92158", + "input_default": { + "name": "Arguments", + "title": null, + "value": "20", + "secret": false, + "advanced": false, + "description": "The function's inputs\n\ne.g \"20\"", + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -158.1623599617334, + "y": 295.410856928333 + } + }, + "input_links": [], + "output_links": [ + { + "id": "093bdca5-9f44-42f9-8e1c-276dd2971675", + "source_id": "844530de-2354-46d8-b748-67306b7bbca1", + "sink_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "source_name": "result", + "sink_name": "prompt_values_#_ARGS", + "is_static": true + } + ], + "graph_id": "622849a7-5848-4838-894d-01f8f07e3fad", + "graph_version": 18, + "webhook_id": null, + "webhook": null + }, + { + "id": "0fd6ef54-c1cd-478d-b764-17e40f882b99", + "block_id": "90a56ffb-7024-4b2b-ab50-e26c5e5ab8ba", + "input_default": { + "name": "Description", + "title": null, + "value": "Generates n examples of fake data representing people, each with a name, DoB, Job title, and an age.", + "secret": false, + "advanced": false, + "description": "Describe what the function does.\n\ne.g \"Generates n examples of fake data representing people, each with a name, DoB, Job title, and an age.\"", + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": 374.4548658057796, + "y": 290.3779121974126 + } + }, + "input_links": [], + "output_links": [ + { + "id": "6c63d8ee-b63d-4ff6-bae0-7db8f99bb7af", + "source_id": "0fd6ef54-c1cd-478d-b764-17e40f882b99", + "sink_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "source_name": "result", + "sink_name": "prompt_values_#_DESCRIPTION", + "is_static": true + } + ], + "graph_id": "622849a7-5848-4838-894d-01f8f07e3fad", + "graph_version": 18, + "webhook_id": null, + "webhook": null + } + ], + "links": [ + { + "id": "caecc1de-fdbc-4fd9-9570-074057bb15f9", + "source_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "sink_id": "26ff2973-3f9a-451d-b902-d45e5da0a7fe", + "source_name": "response", + "sink_name": "value", + "is_static": false + }, + { + "id": "6c63d8ee-b63d-4ff6-bae0-7db8f99bb7af", + "source_id": "0fd6ef54-c1cd-478d-b764-17e40f882b99", + "sink_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "source_name": "result", + "sink_name": "prompt_values_#_DESCRIPTION", + "is_static": true + }, + { + "id": "093bdca5-9f44-42f9-8e1c-276dd2971675", + "source_id": "844530de-2354-46d8-b748-67306b7bbca1", + "sink_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "source_name": "result", + "sink_name": "prompt_values_#_ARGS", + "is_static": true + }, + { + "id": "dc7cb15f-76cc-4533-b96c-dd9e3f7f75ed", + "source_id": "4eab3a55-20f2-4c1d-804c-7377ba8202d2", + "sink_id": "c5d16ee4-de9e-4d93-bf32-ac2d15760d5b", + "source_name": "result", + "sink_name": "prompt_values_#_FUNCTION", + "is_static": true + } + ], + "forked_from_id": null, + "forked_from_version": null, + "sub_graphs": [], + "user_id": "", + "created_at": "2025-04-19T17:10:48.857Z", + "input_schema": { + "type": "object", + "properties": { + "Function Definition": { + "advanced": false, + "anyOf": [ + { + "format": "short-text", + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Function Definition", + "description": "The function definition (text). This is what you would type on the first line of the function when programming.\n\ne.g \"def fake_people(n: int) -> list[dict]:\"", + "default": "def fake_people(n: int) -> list[dict]:" + }, + "Arguments": { + "advanced": false, + "anyOf": [ + { + "format": "short-text", + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Arguments", + "description": "The function's inputs\n\ne.g \"20\"", + "default": "20" + }, + "Description": { + "advanced": false, + "anyOf": [ + { + "format": "long-text", + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Description", + "description": "Describe what the function does.\n\ne.g \"Generates n examples of fake data representing people, each with a name, DoB, Job title, and an age.\"", + "default": "Generates n examples of fake data representing people, each with a name, DoB, Job title, and an age." + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "return": { + "advanced": false, + "secret": false, + "title": "return", + "description": "The value returned by the function" + } + }, + "required": [ + "return" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "o3-mini" + ] + } + }, + "required": [ + "openai_api_key_credentials" + ], + "title": "AIFunctionCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_55d40473-0f31-4ada-9e40-d3a7139fcbd4.json b/autogpt_platform/backend/agents/agent_55d40473-0f31-4ada-9e40-d3a7139fcbd4.json new file mode 100644 index 0000000000..8dcc1a4478 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_55d40473-0f31-4ada-9e40-d3a7139fcbd4.json @@ -0,0 +1,7222 @@ +{ + "id": "9dfa5527-15f3-4769-b173-1dd9ecfe19da", + "version": 246, + "is_active": false, + "name": "Automated SEO Blog Writer", + "description": "Scale your blog with a fully automated content engine. The Automated SEO Blog Writer learns your brand voice, finds high-demand keywords, and creates SEO-optimized articles that attract organic traffic and boost visibility.\n\nHow it works:\n\n1. Share your pitch, website, and values.\n2. The agent studies your site and uncovers proven SEO opportunities.\n3. It spends two hours researching and drafting each post.\n4. You set the cadence\u2014publishing runs on autopilot.\n\nBusiness value: Consistently publish research-backed, optimized posts that build domain authority, rankings, and thought leadership while you focus on what matters most.\n\nUse cases:\n\u2022 Founders: Keep your blog active with no time drain.\n\u2022 Agencies: Deliver scalable SEO content for clients.\n\u2022 Strategists: Automate execution, focus on strategy.\n\u2022 Marketers: Drive steady organic growth.\n\u2022 Local businesses: Capture nearby search traffic.", + "instructions": "This agent takes up to two hours to craft a highly researched, SEO-driven blog post that has a strong likelihood of performing well and driving traffic to your site, thereby increasing the chances of your website appearing on Google's front page. It accomplishes this by conducting keyword research with a subagent, which is an SEO expert. You can schedule this agent according to your publishing frequency, whether that's once a day, every four days, or once a week\u2014whatever suits your blogging needs. \n\nAlthough it is necessary to use WordPress for managing the blog posts, you can design and build a website with WordPress as the back-end by clicking this link, where I have provided a pre-filled Lovable prompt to guide you: https://tinyurl.com/loveable-wordpress-frontend\n\nNote: This agent will automatically publish the posts it creates directly to your WordPress site.", + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "6429fe92-aeff-4a14-be9f-9d2d5021bad4", + "block_id": "655d6fdf-a334-421c-b733-520549c07cd1", + "input_default": { + "name": "brand_tone", + "title": "Brand Tone", + "value": null, + "secret": false, + "advanced": false, + "description": "The voice and style for your content - choose the tone that best matches your brand and audience", + "placeholder_values": [ + "Friendly", + "Professional", + "Technical", + "Casual" + ] + }, + "metadata": { + "position": { + "x": -4959.765499130381, + "y": -2179.9447502570065 + }, + "customized_name": "Brand Tone" + }, + "input_links": [], + "output_links": [ + { + "id": "ac0da1b7-1680-4748-8334-f832d2063899", + "source_id": "6429fe92-aeff-4a14-be9f-9d2d5021bad4", + "sink_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "source_name": "result", + "sink_name": "prompt_values_#_brand_tone", + "is_static": true + } + ], + "graph_id": "9dfa5527-15f3-4769-b173-1dd9ecfe19da", + "graph_version": 246, + "webhook_id": null, + "webhook": null + }, + { + "id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "block_id": "ed55ac19-356e-4243-a6cb-bc599e9b716f", + "input_default": { + "model": "gpt-5-2025-08-07", + "retry": 3, + "prompt": "Write a comprehensive, SEO-optimized blog post about \"{{keyword | safe}}\".\n\nBLOG POST TARGET LENGTH: \"{{target_word_count | safe}} words\"\nWRITING STYLE & TONE: \"{{brand_tone | safe}}\"\n\nKEYWORD DATA - This tells you what people are searching for; what they want.\nPRIMARY KEYWORD: {{keyword}}\n\n{{keyword_data | safe}}\n\n\nSEO EXPERT RESEARCH:\nWe hired an SEO expert to choose this keyword after lots of research.\nKeyword: \"{{keyword}}\"\nThey left a note for you as to why they chose it:\n\n{{seo_expert_reason | safe}}\n\nThey also had a suggestion for the title, but it's up to you what title you choose:\n\"{{seo_expert_proposed_title | safe}}\"\n\nTOPIC RESEARCH:\n\n{{research_notes | safe}}\n\n\nREQUIREMENTS:\n- Title: Create an engaging, SEO-friendly title (under 60 characters), making sure to include the main keyword \"{{keyword | safe}}\"\n- Length: {{target_word_count | safe}} words\n- Tone: Write in a {{brand_tone | safe}} tone throughout the content\n- Format: Clean HTML only (no markdown, no code blocks)\n- Structure: Use proper HTML tags (

,

,

,

    ,
  • )\n- Content: Scale sections appropriately for the target length:\n * 500 words: Introduction + 2 main sections + conclusion\n * 1,000 words: Introduction + 3-4 main sections + conclusion \n * 1,500 words: Introduction + 4-5 main sections + conclusion\n * 2,000 words: Introduction + 5-6 main sections + conclusion\n- SEO: Naturally incorporate the primary keyword and relevant secondary keywords throughout the content. Choose keywords intelligently and avoid forced or unnatural usage.\n- Value: Provide actionable, helpful information for readers. Focus on creating content that genuinely answers user questions and solves problems.\n- Flow: Ensure the content flows naturally. Do not directly reference parts of your instructions or prompt in the output.\n- Pay special attention to avoiding robotic keyword insertion and unnatural phrasing. Do not directly reference or comment on the keyword data in the blog post.\n\nHTML STRUCTURE:\n- Do NOT include

    tag - provide title separately\n- Start content with

    for introduction paragraph\n- Use

    for main sections\n- Use

    for subsections if needed\n- Use

    for paragraphs\n- Use

      and
    • for lists\n- No , , or tags needed\n\nOUTPUT FORMAT:\nProvide your response as a JSON object with these fields:\n{\n \"h1\": \"Your SEO-friendly blog post title\",\n \"body\": \"Your complete HTML blog content\",\n \"image_prompt\": \"Detailed prompt for generating a professional blog header image that complements this article\"\n}\n", + "sys_prompt": "You are an expert SEO blog writer that creates high-quality, engaging content optimized for search engines. You always return clean HTML formatted content that is ready to publish. You follow SEO best practices including proper heading structure, keyword optimization, and user-focused content. You write in a conversational yet informative tone that provides real value to readers.", + "list_result": false, + "ollama_host": "localhost:11434", + "prompt_values": {}, + "expected_format": { + "title": "SEO-optimized blog post title (under 60 characters) that will be used as the WordPress post title", + "content": "The generated blog post content in clean HTML format, ready for WordPress publishing", + "image_prompt": "Detailed string for a ultra high quality photographic image generation prompt. Your best work ever." + }, + "conversation_history": [], + "compress_prompt_to_fit": true + }, + "metadata": { + "position": { + "x": 7056.547945728113, + "y": -488.792306881219 + }, + "customized_name": "Write the Blogpost 1st Draft" + }, + "input_links": [ + { + "id": "325265ca-819c-4fdd-a69f-1b75d2da03f7", + "source_id": "3800e8a5-e648-4686-988d-61eae960f126", + "sink_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "source_name": "response", + "sink_name": "prompt_values_#_research_notes", + "is_static": false + }, + { + "id": "ac0da1b7-1680-4748-8334-f832d2063899", + "source_id": "6429fe92-aeff-4a14-be9f-9d2d5021bad4", + "sink_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "source_name": "result", + "sink_name": "prompt_values_#_brand_tone", + "is_static": true + }, + { + "id": "d1ba66d5-158f-44ec-adb3-158775365f3e", + "source_id": "951f011a-0f21-43a2-91b4-3b8734a4fc53", + "sink_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "source_name": "Proposed Title", + "sink_name": "prompt_values_#_seo_expert_proposed_title", + "is_static": false + }, + { + "id": "dd201eb6-26bf-4133-acd0-cb8cc94ee739", + "source_id": "9e4e8cc7-8f72-40c8-93a4-5e73504fbff1", + "sink_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "source_name": "no_output", + "sink_name": "prompt_values_#_keyword_data", + "is_static": false + }, + { + "id": "d240ea3d-3104-44a5-9714-c255ab5dc99d", + "source_id": "7cbb535f-bb8c-49d3-9392-883c4eaa9372", + "sink_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "source_name": "result", + "sink_name": "prompt_values_#_target_word_count", + "is_static": true + }, + { + "id": "b42dc4c7-e7ba-4c20-9c10-3275867cc22d", + "source_id": "951f011a-0f21-43a2-91b4-3b8734a4fc53", + "sink_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "source_name": "Justification", + "sink_name": "prompt_values_#_seo_expert_reason", + "is_static": false + }, + { + "id": "b2b664e7-cf87-4651-bb5c-1256be2db489", + "source_id": "951f011a-0f21-43a2-91b4-3b8734a4fc53", + "sink_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "source_name": "Primary Keyword", + "sink_name": "prompt_values_#_keyword", + "is_static": false + } + ], + "output_links": [ + { + "id": "6af59cf6-3a24-4f4e-a940-7ae8b455c4a1", + "source_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "sink_id": "6fde0a6a-ef7e-439a-ba65-9b78ca0fd5ae", + "source_name": "response", + "sink_name": "input", + "is_static": false + }, + { + "id": "959f0fb4-02bd-4e93-b0b4-d187b10773ba", + "source_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "sink_id": "79d2d459-08ff-4ad3-a084-174243f4fb5e", + "source_name": "response", + "sink_name": "input", + "is_static": false + }, + { + "id": "2149a96a-c3ac-4d45-98f4-1c926ceae5b2", + "source_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "sink_id": "ddb9e490-56a6-4203-8f1b-d944e30c253b", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "c6280938-afc1-40a6-8493-80c234ccb6a0", + "source_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "sink_id": "233293ef-ce18-45b0-ab68-37d17d8bc6f9", + "source_name": "response", + "sink_name": "input", + "is_static": false + } + ], + "graph_id": "9dfa5527-15f3-4769-b173-1dd9ecfe19da", + "graph_version": 246, + "webhook_id": null, + "webhook": null + }, + { + "id": "7cbb535f-bb8c-49d3-9392-883c4eaa9372", + "block_id": "655d6fdf-a334-421c-b733-520549c07cd1", + "input_default": { + "name": "target_word_count", + "title": "Blog Post Length", + "value": null, + "secret": false, + "advanced": false, + "description": "Blog post length (500=quick reads, 1000=standard posts, 1500=detailed guides, 2000=comprehensive content)", + "placeholder_values": [ + "500", + "1000", + "1500", + "2000" + ] + }, + "metadata": { + "position": { + "x": -5506.114503217936, + "y": -2181.569356300228 + }, + "customized_name": "Word Count" + }, + "input_links": [], + "output_links": [ + { + "id": "d240ea3d-3104-44a5-9714-c255ab5dc99d", + "source_id": "7cbb535f-bb8c-49d3-9392-883c4eaa9372", + "sink_id": 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This may occur due to LLM API issues, invalid keyword input, or content policy restrictions. The agent cannot proceed with publishing without generated content." + }, + "metadata": { + "position": { + "x": 8216.687484594391, + "y": 4663.903323732193 + } + }, + "input_links": [ + { + "id": "2149a96a-c3ac-4d45-98f4-1c926ceae5b2", + "source_id": "bee9a01e-2ea8-4a0c-9a44-6150e7d6512b", + "sink_id": "ddb9e490-56a6-4203-8f1b-d944e30c253b", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "9dfa5527-15f3-4769-b173-1dd9ecfe19da", + "graph_version": 246, + "webhook_id": null, + "webhook": null + }, + { + "id": "d9a537f7-930d-4526-8eca-8279d9ea747a", + "block_id": "b29c1b50-5d0e-4d9f-8f9d-1b0e6fcbf0b1", + "input_default": { + "offset": 0, + "trigger": "go", + "format_type": { + "format": "%Y-%m-%d", + "timezone": "UTC", + "discriminator": "strftime" + } + }, + "metadata": { + "position": { + "x": 13975.209945423716, + "y": -566.406791021141 + } + }, + "input_links": [], + "output_links": [ + { + "id": "74e11c3f-2d41-4049-993b-142b362f5cd4", + "source_id": "d9a537f7-930d-4526-8eca-8279d9ea747a", + "sink_id": "de461596-8a75-4b0e-ae2e-09206e48fdc3", + "source_name": "date", + "sink_name": "values_#_Date", + "is_static": false + } + ], + "graph_id": "9dfa5527-15f3-4769-b173-1dd9ecfe19da", + "graph_version": 246, + "webhook_id": null, + "webhook": null + }, + { + "id": "1d0294f2-456a-493e-91fe-317ec29de58b", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "DICTIONARY_CREATE_FAILED", + "title": null, + "value": null, + "format": "", + "secret": false, + "advanced": false, + "description": null + }, + "metadata": { + "position": { + "x": 16569.880611942004, + "y": 4617.380527385684 + } + }, + "input_links": [ + { + "id": "83f01bb1-581d-4a5e-a7cd-29f6a6686585", + "source_id": "de461596-8a75-4b0e-ae2e-09206e48fdc3", + "sink_id": "1d0294f2-456a-493e-91fe-317ec29de58b", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "9dfa5527-15f3-4769-b173-1dd9ecfe19da", + "graph_version": 246, + "webhook_id": null, + "webhook": null + }, + { + "id": "da04c7e3-0a1e-4360-8feb-3cd6a76eec55", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "BLOG_PUBLISHED_SUCCESS", + "title": "Blog Post Published Successfully", + "value": null, + "format": "", + "secret": false, + "advanced": false, + "description": "The blog post has been successfully generated, published to WordPress, and logged to Airtable. 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"source_id": "083a9d96-7683-4963-b18e-26bc68841f7c", + "sink_id": "0bc3c929-2493-4d0c-9a77-3d831e193385", + "source_name": "missing", + "sink_name": "value", + "is_static": false + }, + { + "id": "02de7dc8-6cd0-4880-8e3d-b8723b26ce47", + "source_id": "c80e0834-fc0e-4841-9d9d-8c0c0ccd06c5", + "sink_id": "0bc3c929-2493-4d0c-9a77-3d831e193385", + "source_name": "missing", + "sink_name": "value", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "input_schema": { + "type": "object", + "properties": { + "Wordpress Blog URL": { + "advanced": false, + "anyOf": [ + { + "format": "short-text", + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Wordpress Blog URL", + "description": "e.g aiespresso.wordpress.com - no \"http://\" or \"/\"s" + } + }, + "required": [ + "Wordpress Blog URL" + ] + }, + "output_schema": { + "type": "object", + "properties": { + "Blog Post Titles": { + "advanced": false, + "secret": false, + "title": "Blog Post Titles" + }, + "Error": { + "advanced": false, + "secret": false, + "title": "Error" + } + }, + "required": [ + "Blog Post Titles", + "Error" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null + }, + { + "id": "d43270ae-9538-4f4d-bf40-0e842ea42bbc", + "version": 15, + "is_active": true, + "name": "Text Humanizer", + "description": "Put in AI Generated text, this tool will attempt to make it appear less obviously AI generated.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "block_id": "0b02b072-abe7-11ef-8372-fb5d162dd712", + "input_default": { + "timeout": 300, + "language": "python", + "setup_commands": [] + }, + "metadata": { + "position": { + "x": 1396.3000357443748, + "y": 610.461992453033 + } + }, + "input_links": [ + { + "id": "5eeb3e7d-130a-46a9-8939-af9fbb1db3d4", + "source_id": "8a844481-e687-469c-a4c6-6135a4fa7fd9", + "sink_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "source_name": "output", + "sink_name": "code", + "is_static": false + } + ], + "output_links": [ + { + "id": "341de54d-aba8-4f6f-b0f3-225e12f54dee", + "source_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "sink_id": "b72a68e2-95bc-4b6a-b012-cad51ce891e9", + "source_name": "stderr_logs", + "sink_name": "value", + "is_static": false + }, + { + "id": "d0cda6db-96b1-4cae-9a3b-89a7c786ed55", + "source_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "sink_id": "b72a68e2-95bc-4b6a-b012-cad51ce891e9", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "68a7ac5c-0204-4d37-bd29-33d03c4a8b16", + "source_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "sink_id": "64b313dc-0b6f-41c0-9c37-3bab18538c5a", + "source_name": "stdout_logs", + "sink_name": "value", + "is_static": false + } + ] + }, + { + "id": "8a844481-e687-469c-a4c6-6135a4fa7fd9", + "block_id": "db7d8f02-2f44-4c55-ab7a-eae0941f0c30", + "input_default": { + "format": "import re\n\nRE = re.compile(r\"[\u201c\u201d\u2018\u2019\u2014\u2013\u2026\u2032\u2033\u2212\u00d7\u00f7\u2264\u2265\u2260\u00b1\u2248\u2192\u2190\u2194\u21d2\u21d0\u2022\u00b7\u00a9\u00ae\u2122\u00bd\u00bc\u00be\u2153\u2154\u215b\u215c\u215d\u215e\u00ab\u00bb\u2039\u203a\\u00A0\\u2010\\u2011\\u2012\\u00AD]\")\n\nMAP = {\n \"\u201c\": '\"', \"\u201d\": '\"',\n \"\u2018\": \"'\", \"\u2019\": \"'\",\n \"\u2014\": \" - \", \"\u2013\": \"-\",\n \"\u2026\": \"...\",\n \"\u2032\": \"'\", \"\u2033\": '\"',\n \"\u2212\": \"-\", # U+2212 minus\n \"\u00d7\": \"x\", \"\u00f7\": \"/\",\n \"\u2264\": \"<=\", \"\u2265\": \">=\", \"\u2260\": \"!=\",\n \"\u00b1\": \"+/-\", \"\u2248\": \"~\",\n \"\u2192\": \"->\", \"\u2190\": \"<-\", \"\u2194\": \"<->\",\n \"\u21d2\": \"=>\", \"\u21d0\": \"<=\",\n \"\u2022\": \"*\", \"\u00b7\": \".\",\n \"\u00a9\": \"(C)\", \"\u00ae\": \"(R)\", \"\u2122\": \"(TM)\",\n \"\u00bd\": \"1/2\", \"\u00bc\": \"1/4\", \"\u00be\": \"3/4\",\n \"\u2153\": \"1/3\", \"\u2154\": \"2/3\",\n \"\u215b\": \"1/8\", \"\u215c\": \"3/8\", \"\u215d\": \"5/8\", \"\u215e\": \"7/8\",\n \"\u00ab\": \"<<\", \"\u00bb\": \">>\", \"\u2039\": \"<\", \"\u203a\": \">\",\n \"\\u00A0\": \" \", # NBSP -> space\n \"\\u2010\": \"-\", # HYPHEN\n \"\\u2011\": \"-\", # NON-BREAKING HYPHEN\n \"\\u2012\": \"-\", # FIGURE DASH\n \"\\u00AD\": \"\", # SOFT HYPHEN\n}\n\ninput_string = \"\"\"{{text | safe}}\"\"\"\nprint(RE.sub(lambda m: MAP[m.group(0)], input_string))\n", + "values": {} + }, + "metadata": { + "position": { + "x": 798.0204985759965, + "y": 604.6283090015096 + } + }, + "input_links": [ + { + "id": "f5c80b8e-c9b5-46f3-a1d1-c78ed476ced9", + "source_id": "2c805606-23e3-479f-a1dc-b3a1649dac4d", + "sink_id": "8a844481-e687-469c-a4c6-6135a4fa7fd9", + "source_name": "result", + "sink_name": "values_#_text", + "is_static": true + } + ], + "output_links": [ + { + "id": "5eeb3e7d-130a-46a9-8939-af9fbb1db3d4", + "source_id": "8a844481-e687-469c-a4c6-6135a4fa7fd9", + "sink_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "source_name": "output", + "sink_name": "code", + "is_static": false + } + ] + }, + { + "id": "2c805606-23e3-479f-a1dc-b3a1649dac4d", + "block_id": "90a56ffb-7024-4b2b-ab50-e26c5e5ab8ba", + "input_default": { + "name": "AI Generated Text", + "secret": false, + "advanced": false, + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": 205.77212429609472, + "y": 602.9791272931379 + } + }, + "input_links": [], + "output_links": [ + { + "id": "f5c80b8e-c9b5-46f3-a1d1-c78ed476ced9", + "source_id": "2c805606-23e3-479f-a1dc-b3a1649dac4d", + "sink_id": "8a844481-e687-469c-a4c6-6135a4fa7fd9", + "source_name": "result", + "sink_name": "values_#_text", + "is_static": true + } + ] + }, + { + "id": "64b313dc-0b6f-41c0-9c37-3bab18538c5a", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Humanized Text", + "secret": false, + "advanced": false + }, + "metadata": { + "position": { + "x": 2551.9887740433414, + "y": 617.3378904696456 + } + }, + "input_links": [ + { + "id": "68a7ac5c-0204-4d37-bd29-33d03c4a8b16", + "source_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "sink_id": "64b313dc-0b6f-41c0-9c37-3bab18538c5a", + "source_name": "stdout_logs", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [] + }, + { + "id": "b72a68e2-95bc-4b6a-b012-cad51ce891e9", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Error", + "secret": false, + "advanced": false + }, + "metadata": { + "position": { + "x": 3111.9890459714757, + "y": 617.3379217231886 + } + }, + "input_links": [ + { + "id": "341de54d-aba8-4f6f-b0f3-225e12f54dee", + "source_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "sink_id": "b72a68e2-95bc-4b6a-b012-cad51ce891e9", + "source_name": "stderr_logs", + "sink_name": "value", + "is_static": false + }, + { + "id": "d0cda6db-96b1-4cae-9a3b-89a7c786ed55", + "source_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "sink_id": "b72a68e2-95bc-4b6a-b012-cad51ce891e9", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [] + } + ], + "links": [ + { + "id": "f5c80b8e-c9b5-46f3-a1d1-c78ed476ced9", + "source_id": "2c805606-23e3-479f-a1dc-b3a1649dac4d", + "sink_id": "8a844481-e687-469c-a4c6-6135a4fa7fd9", + "source_name": "result", + "sink_name": "values_#_text", + "is_static": true + }, + { + "id": "5eeb3e7d-130a-46a9-8939-af9fbb1db3d4", + "source_id": "8a844481-e687-469c-a4c6-6135a4fa7fd9", + "sink_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "source_name": "output", + "sink_name": "code", + "is_static": false + }, + { + "id": "341de54d-aba8-4f6f-b0f3-225e12f54dee", + "source_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "sink_id": "b72a68e2-95bc-4b6a-b012-cad51ce891e9", + "source_name": "stderr_logs", + "sink_name": "value", + "is_static": false + }, + { + "id": "d0cda6db-96b1-4cae-9a3b-89a7c786ed55", + "source_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "sink_id": "b72a68e2-95bc-4b6a-b012-cad51ce891e9", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "68a7ac5c-0204-4d37-bd29-33d03c4a8b16", + "source_id": "15886b0c-1525-44b3-8b52-4b1be4fc4c18", + "sink_id": "64b313dc-0b6f-41c0-9c37-3bab18538c5a", + "source_name": "stdout_logs", + "sink_name": "value", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "input_schema": { + "type": "object", + "properties": { + "AI Generated Text": { + "advanced": false, + "anyOf": [ + { + "format": "long-text", + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "AI Generated Text" + } + }, + "required": [ + "AI Generated Text" + ] + }, + "output_schema": { + "type": "object", + "properties": { + "Humanized Text": { + "advanced": false, + "secret": false, + "title": "Humanized Text" + }, + "Error": { + "advanced": false, + "secret": false, + "title": "Error" + } + }, + "required": [ + "Humanized Text", + "Error" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null + }, + { + "id": "062c0dfe-15c2-48ae-bf3a-4ec36d818d08", + "version": 38, + "is_active": false, + "name": "Keyword SEO Expert", + "description": "takes the guesswork out of SEO by analyzing your website with top keyword research tools, then recommending the most valuable keyword to target based on your domain and niche \u2014 so you know exactly where to focus for maximum search impact.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "542e391b-121c-4ca1-8327-7fef6f8fac12", + "block_id": "3b191d9f-356f-482d-8238-ba04b6d18381", + "input_default": { + "model": "gpt-5-2025-08-07", + "retry": 3, + "prompt": "You are a seasoned SEO strategist, hired to perform expert quality SEO research, in order to select the next blog post topic for this website.\n\nYou must:\n- Treat this as a serious, high-stakes SEO decision where the site's growth depends on your choice. Pick the highest volume, low difficulty keyword possible which is relevant to the website.\n- Work like a real SEO expert would: explore multiple angles, refine ideas, and check underserved niches before making a recommendation.\n- Prefer extra research over premature completion. Continue until you are confident, based on the evidence gathered, that no stronger keyword opportunity exists.\n\nTools Available:\n1) Get Related Search Keywords \u2014 related keywords from Google SERP \u201csearches related to\u201d.\n2) Get Autocomplete Keyword Suggestions \u2014 autocomplete ideas with words before, after, or within the seed keyword.\n\nInputs:\n\n{{DOMAIN | safe}}\n\n\n{{SITE_TOPIC | safe}}\n\n\n{{SITE_DESC | safe}}\n\n\n{{POSTS | safe}}\n\n\nProcess:\n1) Generate multiple broad seed keyword ideas for the site\u2019s niche.\n2) For each seed:\n - Use BOTH tools to gather suggestions.\n - Merge/deduplicate results; note volume/intent/fit if available.\n3) After each round, reflect explicitly:\n \u201cDo I have enough evidence to pick the best keyword, or could I improve by exploring another angle or refining a seed?\u201d\n If improvement is possible, keep researching.\n4) Only when further research is unlikely to yield a better opportunity:\n - Select ONE Primary Keyword.\n - Propose a compelling blog title that includes the Primary Keyword.\n - Summarize the evidence and reasoning that supports the choice.\n\nOUTPUT FORMAT (strict):\nReturn EXACTLY seven XML blocks, plain text inside each, no nesting and no other content outside these tags:\n1) \u2026 \u2014 a chronological log of seeds tried, which tool(s) were used, notable findings.\n2) \u2026 \u2014 why certain keywords were kept or discarded; how they map to site goals/gaps.\n3) \u2026 \u2014 the chosen primary keyword (plain text only).\n4) \u2026 \u2014 the proposed blog title including the primary keyword.\n5) \u2026 \u2014 keyword difficulty for the chosen primary keyword (numeric if available; otherwise \u201cunknown\u201d).\n6) \u2026 \u2014 monthly search volume for the chosen primary keyword (numeric if available; otherwise \u201cunknown\u201d).\n7) \u2026 \u2014 brief evidence-backed rationale for the selection.\n\nRules:\n- Do not include any XML tags other than: research_log, selection_notes, primary_keyword, proposed_title, kd, sv, justification.\n- Do not nest or add attributes.\n- Keep kd and sv to a single value each (no units; plain number or \u201cunknown\u201d).\n- Keep all other structure as plain text lines and bullet points only.\n- Use as many tool calls as necessary to complete your task to a very high degree of quality.\n- Avoid repeating topics covered in previous_posts. Duplicate or overly similar topics must always be avoided.\n", + "sys_prompt": "Thinking carefully step by step decide which function to call. \n\nAlways choose a function call from the list of function signatures, and always provide the complete argument provided with the type matching the required jsonschema signature, no missing argument is allowed. \n\nIf you have already completed the task objective, you can end the task by providing the end result of your work as a finish message. \n\nCritical Reminder: All function parameters must always be be provided, you can't put \"null\" or nothing. \nNEVER provide `null` as an input to a tool, you must always fill out every tool input on your chosen tool\n\nYou may make as many sequential tool calls as needed to complete the research before providing the final output - the vast majority of tasks require many sequential tool calls to achieve. \nContinue using tools until you have high confidence in your choice, as defined by the main prompt.\nAlways call a tool with each message unless you are providing your final response. As soon as you call without a tall the task will be permanently ended.\n\nThe following note is regarding PARALLEL tool calls (multiple sequential is okay and heavily encouraged):\n", + "ollama_host": "localhost:11434", + "prompt_values": { + "DOMAIN": "aiespresso.wordpress.com", + "SITE_DESC": "A blog that makes AI approachable and easy to benefit from for the average person", + "SITE_TOPIC": "AI for Everyday People" + }, + "last_tool_output": null, + "multiple_tool_calls": false, + "conversation_history": [] + }, + "metadata": { + "position": { + "x": 352.68980628394695, + "y": 259.96845909220383 + } + }, + "input_links": [ + { + "id": "c08f8540-1033-458a-9bbd-19bfc8877bb8", + "source_id": "55548d2f-6f9d-45d1-aa42-88c259b0d87c", + "sink_id": "542e391b-121c-4ca1-8327-7fef6f8fac12", + "source_name": "result", + "sink_name": "prompt_values_#_DOMAIN", + "is_static": true + }, + { + "id": "642c7991-3941-44bd-8787-d3b1176f33b1", + "source_id": "1d7ec99e-e1c3-4fca-b8f7-c5dc8bc5d36e", + 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"format": "import json\n\ndef parse_loose_json(raw: str):\n raw = raw.strip()\n if not raw.startswith('['):\n raw = '[' + raw.rstrip(', \\n') + ']'\n return json.loads(raw)\n\ndef filter_keywords(items, min_volume: int, max_difficulty: int):\n filtered = [\n row for row in items\n if isinstance(row.get('search_volume'), (int, float))\n and isinstance(row.get('keyword_difficulty'), (int, float))\n and row['search_volume'] >= min_volume\n and row['keyword_difficulty'] <= max_difficulty\n ]\n filtered.sort(key=lambda r: (-r['search_volume'], r['keyword_difficulty']))\n return filtered\n\ndef _fmt(v):\n if v is None:\n return ''\n if isinstance(v, float):\n s = ('%.6f' % v).rstrip('0').rstrip('.')\n return s\n return str(v)\n\ndef to_markdown(rows, columns):\n def esc(x: str) -> str:\n return x.replace('|', r'\\|').replace('\\n', ' ').replace('\\r', ' ')\n header = '| ' + ' | '.join(columns) + ' |'\n sep = '| ' + ' | '.join('---' for _ in columns) + ' |'\n out = [header, sep]\n for r in rows:\n out.append('| ' + ' | '.join(esc(_fmt(r.get(c, ''))) for c in columns) + ' |')\n return '\\n'.join(out)\n\n# --- run ---\nraw = \"\"\"{{data | safe}}\"\"\"\ndata = parse_loose_json(raw)\nrecords = filter_keywords(data, min_volume={{min_sv | safe}}, max_difficulty={{max_kd | safe}})\n\n# Print Markdown Table\ncolumns = ['keyword','search_volume','keyword_difficulty','cpc','competition','serp_info','clickstream_data']\nprint(to_markdown(records, columns))\n", + "values": {} + }, + "metadata": { + "position": { + "x": 1093.6145350526099, + "y": 560.7299035903276 + } + }, + "input_links": [ + { + "id": "601ede07-b921-4ae5-8c78-d58d2524416d", + "source_id": "23a17cfd-61f3-44ad-8b14-9ffdd36316af", + "sink_id": "c9f70151-fc39-48b6-8a38-085549c91cd7", + "source_name": "result", + "sink_name": "values_#_max_kd", + "is_static": true + }, + { + "id": "62fe4ed9-9d11-47d6-bbc9-46f6fffe5995", + "source_id": "f71cd722-4873-4073-a5e4-a9ab3a61b0cc", + "sink_id": 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Try using broader filters or a different keyword." + }, + "metadata": { + "position": { + "x": 2543.9397489616244, + "y": 4112.758322808854 + } + }, + "input_links": [ + { + "id": "01bc10f6-a73d-42b2-a01c-d79335c62dd3", + "source_id": "6ba3fdca-0c73-4e13-ab76-03e6dcdb979b", + "sink_id": "66c9c470-236c-4ed4-9a85-d3cfcd8c690d", + "source_name": "yes_output", + "sink_name": "input", + "is_static": false + } + ], + "output_links": [ + { + "id": "fc63c957-2ed8-42c9-ac52-fa72212aa250", + "source_id": "66c9c470-236c-4ed4-9a85-d3cfcd8c690d", + "sink_id": "7ccad556-6933-4c85-bce6-2b7623b6f749", + "source_name": "output", + "sink_name": "value", + "is_static": true + } + ] + }, + { + "id": "473ff4a2-8683-4114-968f-3c7c4368cfa5", + "block_id": "73c3e7c4-2b3f-4e9f-9e3e-8f7a5c3e2d45", + "input_default": { + "limit": 100, + "language_code": "en", + "location_code": 2840, + "include_serp_info": false, + "include_seed_keyword": true, + "include_clickstream_data": false + }, + "metadata": { + 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float))\n and row['search_volume'] >= min_volume\n and row['keyword_difficulty'] <= max_difficulty\n ]\n filtered.sort(key=lambda r: (-r['search_volume'], r['keyword_difficulty']))\n return filtered\n\ndef _fmt(v):\n if v is None:\n return ''\n if isinstance(v, float):\n s = ('%.6f' % v).rstrip('0').rstrip('.')\n return s\n return str(v)\n\ndef to_markdown(rows, columns):\n def esc(x: str) -> str:\n return x.replace('|', r'\\|').replace('\\n', ' ').replace('\\r', ' ')\n header = '| ' + ' | '.join(columns) + ' |'\n sep = '| ' + ' | '.join('---' for _ in columns) + ' |'\n out = [header, sep]\n for r in rows:\n out.append('| ' + ' | '.join(esc(_fmt(r.get(c, ''))) for c in columns) + ' |')\n return '\\n'.join(out)\n\n# --- run ---\nraw = \"\"\"{{data | safe}}\"\"\"\ndata = parse_loose_json(raw)\nrecords = filter_keywords(data, min_volume={{min_sv | safe}}, max_difficulty={{max_kd | safe}})\n\n# Print Markdown Table\ncolumns = ['keyword','search_volume','keyword_difficulty','cpc','competition','serp_info','clickstream_data']\nprint(to_markdown(records, columns))\n", + "values": {} + }, + "metadata": { + "position": { + "x": 3434.126540813802, + "y": 2621.3523194621266 + } + }, + "input_links": [ + { + "id": "70dec687-6ab2-4ed9-b8f3-fe105647b973", + "source_id": "763702a4-65fa-4a07-a639-14a8042820a1", + "sink_id": "f7045b4b-cda6-452f-abb1-c520e6592d37", + "source_name": "value", + "sink_name": "values_#_data", + "is_static": false + }, + { + "id": "eaa8a11a-e30f-4682-83e8-90ba5d5ceabe", + "source_id": "df083135-7bd5-4454-a914-b2347918ea86", + "sink_id": "f7045b4b-cda6-452f-abb1-c520e6592d37", + "source_name": "result", + "sink_name": "values_#_min_sv", + "is_static": true + }, + { + "id": "70a1308e-12d9-4f18-a917-1598fdd4251b", + "source_id": "de25381e-bd13-4888-966c-7202e6062214", + "sink_id": "f7045b4b-cda6-452f-abb1-c520e6592d37", + "source_name": "result", + "sink_name": "values_#_max_kd", + "is_static": 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"Max Keyword Difficulty": { + "advanced": false, + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Max Keyword Difficulty", + "description": "Positive whole number, range from 0 to 100", + "default": 100 + } + }, + "required": [ + "Keyword" + ] + }, + "output_schema": { + "type": "object", + "properties": { + "Keyword Data": { + "advanced": false, + "secret": false, + "title": "Keyword Data" + }, + "No Keywords Found": { + "advanced": false, + "secret": false, + "title": "No Keywords Found" + }, + "Error": { + "advanced": false, + "secret": false, + "title": "Error" + } + }, + "required": [ + "Keyword Data", + "No Keywords Found", + "Error" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null + } + ], + "user_id": "", + "created_at": "2025-09-30T13:29:21.415Z", + "input_schema": { + "type": "object", + "properties": { + "brand_tone": { + "advanced": false, + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Brand Tone", + "enum": [ + "Friendly", + "Professional", + "Technical", + "Casual" + ], + "description": "The voice and style for your content - choose the tone that best matches your brand and audience" + }, + "target_word_count": { + "advanced": false, + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Blog Post Length", + "enum": [ + "500", + "1000", + "1500", + "2000" + ], + "description": "Blog post length (500=quick reads, 1000=standard posts, 1500=detailed guides, 2000=comprehensive content)" + }, + "blog_url": { + "advanced": false, + "secret": false, + "title": "WordPress Blog URL", + "description": "Your WordPress.com blog URL (e.g., https://yourblog.wordpress.com) - used for posting content via API" + }, + "Website Primary Topic": { + "advanced": false, + "secret": false, + "title": "Website Primary Topic", + "description": "The main subject or theme your blog is about (e.g., 'AI Automation', 'Viral Marketing')" + }, + "Website Description": { + "advanced": false, + "secret": false, + "title": "Website Description", + "description": "Describe your website, including its purpose, tone, and approach. \n\nFor example: \"A blog that makes AI approachable for the average person. We share clear, easy-to-follow guides and curated recommendations on which models and tools to use.\"" + } + }, + "required": [ + "brand_tone", + "target_word_count", + "blog_url", + "Website Primary Topic", + "Website Description" + ] + }, + "output_schema": { + "type": "object", + "properties": { + "CONTENT_GENERATION_FAILED": { + "advanced": false, + "secret": false, + "title": "Content Generation Failed", + "description": "The AI was unable to generate the blog article content. This may occur due to LLM API issues, invalid keyword input, or content policy restrictions. The agent cannot proceed with publishing without generated content.", + "default": "CONTENT_GENERATION_FAILED" + }, + "DICTIONARY_CREATE_FAILED": { + "advanced": false, + "secret": false, + "title": "DICTIONARY_CREATE_FAILED" + }, + "BLOG_PUBLISHED_SUCCESS": { + "advanced": false, + "secret": false, + "title": "Blog Post Published Successfully", + "description": "The blog post has been successfully generated, published to WordPress, and logged to Airtable. The SEO-optimized article is now live and tracking data has been recorded." + }, + "ERROR_CONVERTING_TYPE": { + "advanced": false, + "secret": false, + "title": "ERROR_CONVERTING_TYPE" + }, + "ERROR_DEEP_RESEARCH": { + "advanced": false, + "secret": false, + "title": "ERROR_DEEP_RESEARCH" + }, + "ERROR_GENERATING_IMAGE": { + "advanced": false, + "secret": false, + "title": "ERROR_GENERATING_IMAGE" + }, + "Error Humanizing Text": { + "advanced": false, + "secret": false, + "title": "Error Humanizing Text" + }, + "Hmm\u2026 that doesn\u2019t look like a valid WordPress blog address. \nIt should look like this: yourname.wordpress.com": { + "advanced": false, + "secret": false, + "title": "Hmm\u2026 that doesn\u2019t look like a valid WordPress blog address. \nIt should look like this: yourname.wordpress.com" + }, + "Secondary Keyword Error": { + "advanced": false, + "secret": false, + "title": "Secondary Keyword Error" + }, + "Error": { + "advanced": false, + "secret": false, + "title": "Error" + } + }, + "required": [ + "DICTIONARY_CREATE_FAILED", + "BLOG_PUBLISHED_SUCCESS", + "ERROR_CONVERTING_TYPE", + "ERROR_CONVERTING_TYPE", + "ERROR_DEEP_RESEARCH", + "ERROR_GENERATING_IMAGE", + "Error Humanizing Text", + "Hmm\u2026 that doesn\u2019t look like a valid WordPress blog address. \nIt should look like this: yourname.wordpress.com", + "Secondary Keyword Error", + "Error" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "gpt-5-2025-08-07" + ] + }, + "open_router_api_key_credentials": { + "credentials_provider": [ + "open_router" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "open_router", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "perplexity/sonar-deep-research" + ] + }, + "replicate_api_key_credentials": { + "credentials_provider": [ + "replicate" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "replicate", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + }, + "wordpress_oauth2_credentials": { + "credentials_provider": [ + "wordpress" + ], + "credentials_types": [ + "oauth2" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "wordpress", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "oauth2", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['oauth2']]", + "type": "object", + "discriminator_values": [] + }, + "dataforseo_user_password_credentials": { + "credentials_provider": [ + "dataforseo" + ], + "credentials_types": [ + "user_password" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "dataforseo", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "user_password", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['user_password']]", + "type": "object", + "discriminator_values": [] + }, + "e2b_api_key_credentials": { + "credentials_provider": [ + "e2b" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "e2b", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + } + }, + "required": [ + "openai_api_key_credentials", + "open_router_api_key_credentials", + "replicate_api_key_credentials", + "wordpress_oauth2_credentials", + "dataforseo_user_password_credentials", + "e2b_api_key_credentials" + ], + "title": "AutomatedSEOBlogWriterCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_6e16e65a-ad34-4108-b4fd-4a23fced5ea2.json b/autogpt_platform/backend/agents/agent_6e16e65a-ad34-4108-b4fd-4a23fced5ea2.json new file mode 100644 index 0000000000..d25da2f332 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_6e16e65a-ad34-4108-b4fd-4a23fced5ea2.json @@ -0,0 +1,1795 @@ +{ + "id": "f6138aaf-4f85-48d5-b905-db11a2ff82f3", + "version": 173, + "is_active": true, + "name": "Decision Maker Lead Finder", + "description": "Find the key decision-makers you need, fast.\n\nThis agent identifies business owners or CEOs of local companies in any area you choose. Simply enter what kind of businesses you\u2019re looking for and where, and it will:\n\n* Search the area and gather public information\n* Return names, roles, and contact details when available\n* Provide smart Google search suggestions if details aren\u2019t found\n\nPerfect for:\n\n* B2B sales teams seeking verified leads\n* Recruiters sourcing local talent\n* Researchers looking to connect with business leaders\n\nSave hours of manual searching and get straight to the people who matter most.", + "instructions": "Input the type of businesses that you'd like to contact and a target location and the agent will find you leads.\n\nStart off with a small number and increase the search results once you're happy.", + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "7d2177fa-7974-4058-8da2-4247c4aae83f", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Results", + "secret": false, + "advanced": false, + "escape_html": false + }, + "metadata": { + "position": { + "x": 3460.582732906506, + "y": 274.71786838896395 + } + }, + "input_links": [ + { + "id": "5121e8ff-68ff-4eee-a4f7-bdef9590da73", + "source_id": "0bc5330b-96da-4f43-8085-94d09d4dc4ea", + "sink_id": "7d2177fa-7974-4058-8da2-4247c4aae83f", + "source_name": "output", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "f6138aaf-4f85-48d5-b905-db11a2ff82f3", + "graph_version": 173, + "webhook_id": null, + "webhook": null + }, + { + "id": "1bd025e0-3ccf-4e63-a960-03325f4a6e42", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Here we do the initial google search to get back the results" + }, + "metadata": { + "position": { + "x": 445.7289615198955, + "y": -122.37319867142689 + } + }, + "input_links": [], + "output_links": [], + "graph_id": "f6138aaf-4f85-48d5-b905-db11a2ff82f3", + "graph_version": 173, + "webhook_id": null, + "webhook": null + }, + { + "id": "5119cbae-3244-4b5c-a5df-8ff949391e5f", + "block_id": "7fcd3bcb-8e1b-4e69-903d-32d3d4a92158", + "input_default": { + "name": "Location", + "value": "Edinburgh", + "secret": false, + "advanced": false, + "description": "Enter a specific location (e.g. city, neighborhood, or address). 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"openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "perplexity/sonar-pro" + ] + } + }, + "required": [ + "google_maps_api_key_credentials", + "openai_api_key_credentials", + "open_router_api_key_credentials" + ], + "title": "DecisionMakerLeadFinderCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git 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Perfect for content creators, social media managers, and marketers looking to capitalize on the latest news and viral trends. 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The AI Shortform Video Generator streamlines your content creation process, allowing you to stay ahead of trends and consistently produce viral-worthy videos that resonate with your audience.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "ca4397f3-3146-4721-8d45-027581169210", + "block_id": "3146e4fe-2cdd-4f29-bd12-0c9d5bb4deb0", + "input_default": { + "group": 1, + "dot_all": true, + "pattern": "(.*?)<\\/title>", + "find_all": false, + "case_sensitive": true + }, + "metadata": { + "position": { + "x": 4943.271705805728, + "y": 2591.4971054942084 + } + }, + "input_links": [ + { + "id": "dd046be2-e8a3-461b-9ca9-ff60d00c89e6", + "source_id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "sink_id": "ca4397f3-3146-4721-8d45-027581169210", + "source_name": "response", + "sink_name": "text", + "is_static": false + } + ], + "output_links": [ + { + "id": "0c3311b3-fbcc-45db-bf90-f4ca892bdfbf", + "source_id": "ca4397f3-3146-4721-8d45-027581169210", + 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Your task is to take an input story and turn it into a concise Google search term that can be used for further research on the topic. Here is the input story:\n\n<story>\n{{STORY}}\n</story>\n\nTo create an effective search term:\n1. Identify the main topic or key elements of the story\n2. Choose 2-5 words or short phrases that best represent these elements\n3. Arrange these words in a logical order\n4. Avoid unnecessary words like articles (a, an, the) or conjunctions (and, or, but)\n\nYour output should be only the search term, without any additional explanation or commentary. The search term should be concise enough to be used in a Google search bar but descriptive enough to yield relevant results for further research on the story's topic.\n\nRespond with just your generated search term with no additional commentary or text.", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 18.004348090716576, + "y": -32.85966357648664 + } + }, + "input_links": [ + { + "id": "f7fd1362-8653-4283-a39c-201d177bc80e", + "source_id": "682e6436-c45e-44e4-a643-1562564302a2", + "sink_id": "d5ec4382-2bca-4655-bf38-5c6f65010b75", + "source_name": "positive", + "sink_name": "prompt_values_#_STORY", + "is_static": false + } + ], + "output_links": [ + { + "id": "287bc030-1ce3-433a-bef7-5936eff22f62", + "source_id": "d5ec4382-2bca-4655-bf38-5c6f65010b75", + "sink_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "source_name": "response", + "sink_name": "prompt_values_#_TOPIC", + "is_static": false + }, + { + "id": 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return just the most widely used headline of that story.", + "values": {} + }, + "metadata": { + "position": { + "x": -3240.1630809703283, + "y": -26.788488530455936 + } + }, + "input_links": [ + { + "id": "9164e2ea-7207-4c1d-88ea-32ae8bf0a429", + "source_id": "7168de4f-206f-43bc-8e36-55df20656b84", + "sink_id": "06ff48a2-101e-4e20-ae92-b8ab94ad9df9", + "source_name": "result", + "sink_name": "values_#_TOPIC", + "is_static": true + } + ], + "output_links": [ + { + "id": "9c1fdb9d-a860-4645-8e78-13b1c6a961e9", + "source_id": "06ff48a2-101e-4e20-ae92-b8ab94ad9df9", + "sink_id": "cab3dbde-1473-465a-8bf4-71ba69e5a5de", + "source_name": "output", + "sink_name": "prompt", + "is_static": false + } + ], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "7168de4f-206f-43bc-8e36-55df20656b84", + "block_id": "7fcd3bcb-8e1b-4e69-903d-32d3d4a92158", + "input_default": { + "name": "Video Topic / Headline", + "value": 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"graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "6d53ddf1-b39d-4dbc-931a-aeae658f9edd", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Optimised Hashtags", + "secret": false, + "advanced": false, + "description": "One or two high-reach hashtags to boost discoverability." + }, + "metadata": { + "position": { + "x": 5546.663436566226, + "y": 4294.468802152407 + } + }, + "input_links": [ + { + "id": "ff3d2c2d-d0c4-48ac-a147-09518f3c920b", + "source_id": "c1edbb59-d97d-4f13-aaaf-9f089280e6d6", + "sink_id": "6d53ddf1-b39d-4dbc-931a-aeae658f9edd", + "source_name": "positive", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "c1edbb59-d97d-4f13-aaaf-9f089280e6d6", + "block_id": "3146e4fe-2cdd-4f29-bd12-0c9d5bb4deb0", + "input_default": { + "group": 1, + "dot_all": true, + "pattern": "<hashtags>(.*?)<\\/hashtags>", + "find_all": false, + "case_sensitive": true + }, + "metadata": { + "position": { + "x": 4989.880194526019, + "y": 4288.181263622385 + } + }, + "input_links": [ + { + "id": "348a7031-04b5-43c8-b20a-560772b6f8b4", + "source_id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "sink_id": "c1edbb59-d97d-4f13-aaaf-9f089280e6d6", + "source_name": "response", + "sink_name": "text", + "is_static": false + } + ], + "output_links": [ + { + "id": "ff3d2c2d-d0c4-48ac-a147-09518f3c920b", + "source_id": "c1edbb59-d97d-4f13-aaaf-9f089280e6d6", + "sink_id": "6d53ddf1-b39d-4dbc-931a-aeae658f9edd", + "source_name": "positive", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "681a5773-4e22-4ba7-b972-8864110ee106", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Video", + "secret": false, + "advanced": false, + "description": "The finished video created by the Agent" + }, + "metadata": { + "position": { + "x": 5416.720683710664, + "y": -176.92102066765722 + } + }, + "input_links": [ + { + "id": "8e93cfb8-5338-475c-8bab-4b4d3912a913", + "source_id": "6dbef347-9a49-4f24-9d1c-3d39c384f354", + "sink_id": "681a5773-4e22-4ba7-b972-8864110ee106", + "source_name": "video_url", + "sink_name": "value", + "is_static": false + }, + { + "id": "b751321b-4688-4ab7-af14-e8d15ae8e786", + "source_id": "6dbef347-9a49-4f24-9d1c-3d39c384f354", + "sink_id": "681a5773-4e22-4ba7-b972-8864110ee106", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "bcc0c964-c614-4ce4-977e-36eff68a82a9", + "block_id": "87840993-2053-44b7-8da4-187ad4ee518c", + "input_default": {}, + "metadata": { + "position": { + "x": 594.3494633641187, + "y": -26.67385432381235 + } + }, + "input_links": [ + { + "id": "336cf54b-f639-4ff0-bafd-fce3328d2046", + "source_id": "d5ec4382-2bca-4655-bf38-5c6f65010b75", + "sink_id": "bcc0c964-c614-4ce4-977e-36eff68a82a9", + "source_name": "response", + "sink_name": "query", + "is_static": false + } + ], + "output_links": [ + { + "id": "3a679d8a-c62d-498b-a83d-8b7241449526", + "source_id": "bcc0c964-c614-4ce4-977e-36eff68a82a9", + "sink_id": "46cca925-1e4a-47ca-b2d3-ff2ef07ee917", + "source_name": "results", + "sink_name": "text", + "is_static": false + } + ], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "d7591a9b-daa7-4f03-852f-fb8d26fab57e", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "WARNING: Depending on the settings you select and the length of the script, video generation can take a long time. In Extreme cases 10 minutes.\n\nSettings such as AI video take longer than stock footage." + }, + "metadata": { + "position": { + "x": 5055.294942637052, + "y": 495.83618794207337 + } + }, + "input_links": [], + "output_links": [], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "a6eb119e-833c-4702-b0d1-c6e01fa79df5", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Ask Perplexity (live web-searching answer AI)" + }, + "metadata": { + "position": { + "x": -2825.229479767265, + "y": -428.19471165159075 + } + }, + "input_links": [], + "output_links": [], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "c6d73929-e112-4c02-8d49-686ceda1fabd", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Select the news Story to make a video about" + }, + "metadata": { + "position": { + "x": -1394.0304079884431, + "y": -437.4027905400797 + } + }, + "input_links": [], + "output_links": [], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "fadf0fcc-6506-4423-8f0b-e8bb606524e2", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Conduct background research on the chosen news story" + }, + "metadata": { + "position": { + "x": 670.5595728367297, + "y": -440.5403142618513 + } + }, + "input_links": [], + "output_links": [], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "d38b848f-e8ed-40ed-ad89-31664875373d", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Write a highly virality optimised script using proven methods. \n\nThis step also directs the visuals." + }, + "metadata": { + "position": { + "x": 2798.2437838618944, + "y": -446.598452987355 + } + }, + "input_links": [], + "output_links": [], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "08db983c-3312-4a79-b195-9207a27f44f9", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Create the video!" + }, + "metadata": { + "position": { + "x": 4579.82086567059, + "y": -517.3760892955992 + } + }, + "input_links": [], + "output_links": [], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "7dc90a26-3094-472f-9441-f0a8eb5e4ac8", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Generate metadata for the video such as the title and hashtags." + }, + "metadata": { + "position": { + "x": 4239.2662913385075, + "y": 2486.858941366123 + } + }, + "input_links": [], + "output_links": [], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "cab3dbde-1473-465a-8bf4-71ba69e5a5de", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "perplexity/sonar-pro", + "retry": 3, + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": -2670.231626894567, + "y": -42.249645219997035 + } + }, + "input_links": [ + { + "id": "9c1fdb9d-a860-4645-8e78-13b1c6a961e9", + "source_id": "06ff48a2-101e-4e20-ae92-b8ab94ad9df9", + "sink_id": "cab3dbde-1473-465a-8bf4-71ba69e5a5de", + "source_name": "output", + "sink_name": "prompt", + "is_static": false + } + ], + "output_links": [ + { + "id": "afb2edf8-8f05-4a6c-af7d-86c9ae0009b6", + "source_id": "cab3dbde-1473-465a-8bf4-71ba69e5a5de", + "sink_id": "6f373ad2-ff4f-44be-9328-27519f47afe3", + "source_name": "response", + "sink_name": "prompt_values_#_RESULTS", + "is_static": false + } + ], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "claude-sonnet-4-5-20250929", + "retry": 3, + "prompt": "Write a shortform video script about this news story\n<story>\n{{TOPIC}}\n---\n{{FULL_STORY}}\n</story>\n\nUsing this in depth research:\n<research>\n{{RESEARCH}}\n</research>\n\nWhen writing your script, remember that today's date is {{DATE}}. Don't mention this, but take it into account when positioning events related to the story in time.\nEnsure what you write about is true and does not include any assumptions to avoid creating fake news.\nYour video should be from the perspective of reporting on the story.", + "sys_prompt": "You are a shortform video script writer. Write a short form video script based on the user's topic that exactly complies with the following guide, and uses the example script below for reference on format, detail level and quality. \n\nKey shortform video guide:\n```\nWriting:\n\n1. Hooks:\n - Keep hooks under 3 seconds, absolutely no longer\n - Make them visually pleasing and understandable without sound - test by watching on mute\n - Use foreshadowing to tease the video's conclusion, but don't reveal everything\n - Example: Start with a reaction to a $5 gift, but don't show the gift itself until the end\n - Ensure the hook is so visually strong it could be used as a thumbnail for a long-form video\n\n2. Storytelling:\n - \"But so\" storytelling: Constantly set up and resolve conflicts\n Example: \"I was at home but I got bored, so I ended up going for a walk, but it started raining, so I ended up trying to figure out what to do.\"\n - Dual narrative storytelling:\n - Voice: Focus on the main action or process\n - Visuals: Add emotional depth or context without explicitly stating it\n Example: Talking about making a $5 Valentine's gift while showing photos of grandma with late grandpa\n - Create multiple \"but\" moments to repeatedly grab attention\n\n3. Language:\n - Be ruthlessly concise - cut any word that doesn't add value\n - Use \"but\" and \"so\" frequently to create micro-cliffhangers\n - Avoid explaining what's visually obvious\n\n4. Content:\n - Address 2-3 potential viewer questions in each video\n - Provide multiple reasons for viewers to care (e.g., health benefits AND weight loss for a diet video)\n - Use numbered lists (e.g., \"3 reasons why\") to create clear structure and expectation\n\nDirecting:\n\n1. Visual Composition:\n - Center all important elements in the frame\n - Limit to 2-3 objects max in any given shot\n - First frame must be thumbnail-worthy - test this specifically\n\n2. Pacing:\n - Hook: 1-3 seconds, ultra-fast\n - Middle: Medium pace, but with micro-variations to maintain interest\n - Peak: Place a clear high point (joke, reveal, etc.) around 60-70% through\n - Quick ending: Last 2-3 seconds should wrap up decisively\n\n3. Emotional Journey:\n - Plan 3-4 distinct emotional beats in each video\n - Ensure the peak emotion (whether humor, surprise, etc.) is crystal clear\n - End on the second-strongest emotional beat\n\n4. Speaking:\n - Speak at a normal pace, but cut out all filler words\n - After every dense information bit, pause for 0.5-1 second\n - Vary tone to emphasize key points - don't be monotonous\n\n5. Visuals:\n - Every 2-3 seconds should have a visual change (new shot, text overlay, etc.)\n - Use visual metaphors to explain complex ideas quickly\n - Incorporate progress indicators (e.g., step counters) to maintain viewer orientation\n\nStructure:\n\n1. Overall Structure:\n - Hook (1-3 seconds): Instantly grab attention\n - Context (2-4 seconds): Quickly establish what's happening\n - Main content (20-25 seconds): Deliver value in bite-sized chunks\n - Peak (3-5 seconds): Clear climax or punchline\n - Ending (1-2 seconds): Swift wrap-up\n\n2. Retention Tactics:\n - Every single line must progress the story - ruthlessly cut any that don't\n - Place \"but\" moments every 5-7 seconds to maintain tension\n - Use visual progress indicators that are always on screen (e.g., step counter in corner)\n\n3. Length:\n - Aim for 30-35 seconds initially (Jenny's sweet spot is 34 seconds)\n - Test variations of +/- 5 seconds to find your ideal length\n\n4. Call-to-Action (CTA):\n - Place CTA at 50-60% mark in the video\n - Integrate CTA into the story (e.g., \"Subscribe to see what happened next\")\n - Keep CTA under 2 seconds\n\n5. Ending:\n - Last 1-2 seconds should be quick and decisive\n - Consider a cliffhanger ending to encourage rewatches\n - If part of a series, tease the next video in the last second\n\n6. Content Buckets:\n - Develop 2-4 distinct series with near-identical structures\n - Use exact same title format for each video in a series\n - Example bucket: \"$1 [food item] vs Restaurant version\"\n\n7. Testing and Iteration:\n - Create at least 3 versions of each video, changing only one element\n - Analyze first 24-48 hours of performance rigorously\n - Look for patterns in top 10% of videos and double down on those elements\n```\n\nExample Script:\nHere's an example Full Script with Visual Direction (full_script) for a video titled \"How many flavors can I get for $1\":\n```\n[close-up of ice cream machine with multiple flavors visible] How many flavors can you get with a dollar? \n[pan to show a full ice cream cup, price tag visible] That's going to be $20, and it's just vanilla. \n[Jenny holding a tiny cup, moving towards ice cream machine] So I brought a tiny cup to get every flavor without spending more than a dollar. \n[close-up of tiny cup under ice cream dispenser] What do these levers do? \n[Jenny's mom entering frame, looking concerned] Jenny, they're gonna kick you out! \n[cup filling with multiple colors of ice cream] I'm more concerned that the more flavors I added, the less space I had in my cup. \n[Jenny eating some ice cream from the cup] Oh my goodness, I put the same flavor twice on accident. \n[Jenny looking around furtively] Testing to make extra room. \n[store employee walking by in background] They're gonna kick us out. Look, I called the cops! \n[text overlay \"Subscribe for more challenges!\"] All this for one subscriber. \n[close-up of ice cream machine with multiple levers] So I hurry through the final flavors by pressing a special button that adds two flavors at once. \n[cup overflowing slightly, Jenny looking panicked] That's more than a dollar! Hurry up! \n[Jenny holding the overfilled cup, moving to cashier] 14 ice cream flavors... is it gonna be a dollar? \n[cash register display showing price] $2.48 \n[Jenny's disappointed face, quick cut to black] No ice cream for you... again. \n```\n\nThis script follows the key principles of:\n- A quick, visually appealing hook\n- Constant progression and conflict\n- Dual narrative storytelling (spoken story about getting flavors, visual story about potentially getting in trouble)\n- Foreshadowing the ending (mentioning \"again\" to hint at a previous video)\n- Quick, impactful ending\nRemember, every single second and line serves a purpose in moving the story forward and maintaining viewer engagement.\n\n- [text between brackets] will be used to guide the the visuals and ignored by the speaker\n- Breaking lines to force clip separation and media change\n\nEverything written outside of [ ] will be spoken aloud, so never include non-spoken words like \"*sigh*\" and just leave empty lines rather than marking sections as \"None\".\n\nOutput only the full script with no commentary or additional text, titles or parenthesis.", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 2757.2350969970985, + "y": -47.24840953640182 + } + }, + "input_links": [ + { + "id": "2f6c6627-e243-47b0-a78a-f65a4b0ba665", + "source_id": "75d91ec6-e3ff-4013-9a6d-43ea023e4989", + "sink_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "source_name": "date", + "sink_name": "prompt_values_#_DATE", + "is_static": false + }, + { + "id": "287bc030-1ce3-433a-bef7-5936eff22f62", + "source_id": "d5ec4382-2bca-4655-bf38-5c6f65010b75", + "sink_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "source_name": "response", + "sink_name": "prompt_values_#_TOPIC", + "is_static": false + }, + { + "id": "58c628e0-c1bb-4f7c-bcaa-a7cac3c53c4c", + "source_id": "682e6436-c45e-44e4-a643-1562564302a2", + "sink_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "source_name": "positive", + "sink_name": "prompt_values_#_FULL_STORY", + "is_static": false + }, + { + "id": "476a4503-87f1-40a4-8dd7-c188061a4870", + "source_id": "46cca925-1e4a-47ca-b2d3-ff2ef07ee917", + "sink_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "source_name": "summary", + "sink_name": "prompt_values_#_RESEARCH", + "is_static": false + } + ], + "output_links": [ + { + "id": "e2a7904d-fe01-49b4-bd10-e1fd23a31678", + "source_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "sink_id": "6dbef347-9a49-4f24-9d1c-3d39c384f354", + "source_name": "response", + "sink_name": "script", + "is_static": false + }, + { + "id": "a11e06c0-5592-41c1-97c8-6fb12ff29164", + "source_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "sink_id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "source_name": "response", + "sink_name": "prompt_values_#_SCRIPT", + "is_static": false + }, + { + "id": "c4a903cd-1d79-4ff8-b0f1-a112ec11a714", + "source_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "sink_id": "d9e779dc-8f71-4234-b91b-7e1c041e89a4", + "source_name": "response", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "6f373ad2-ff4f-44be-9328-27519f47afe3", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "claude-sonnet-4-5-20250929", + "retry": 3, + "prompt": "Extract the News Story from the search results that people would find most engaging and interesting. The story you select must be related to the topic {{TOPIC}}.\n\n <search_results>\n{{RESULTS}}\n</search_results> \n\nOutput your concise analysis inside <analysis> tags, then output your final unambiguous choice of news story inside <news_story> tags in the following format:\n\n<news_story>\nTitle: [TITLE]\nDate of event: [Date/N/A]\nStory: [Story Text]\n</news_story>", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": -1726.816139381607, + "y": -19.133506652531025 + } + }, + "input_links": [ + { + "id": "afb2edf8-8f05-4a6c-af7d-86c9ae0009b6", + "source_id": "cab3dbde-1473-465a-8bf4-71ba69e5a5de", + "sink_id": "6f373ad2-ff4f-44be-9328-27519f47afe3", + "source_name": "response", + "sink_name": "prompt_values_#_RESULTS", + "is_static": false + } + ], + "output_links": [ + { + "id": "fef2729e-95cc-4963-a956-95d33aa3bbc4", + "source_id": "6f373ad2-ff4f-44be-9328-27519f47afe3", + "sink_id": "682e6436-c45e-44e4-a643-1562564302a2", + "source_name": "response", + "sink_name": "text", + "is_static": false + } + ], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + }, + { + "id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "claude-sonnet-4-5-20250929", + "retry": 3, + "prompt": "You are an expert in creating engaging, viral shortform content. Your task is to analyze a given video script and generate an interesting title and relevant hashtags for it.\n\nHere is the video script you will be working with:\n\n<video_script>\n{{SCRIPT}}\n</video_script>\n\nCarefully read and analyze the script, paying attention to:\n- The main topic or theme\n- Key points or messages\n- Unique or attention-grabbing elements\n- The overall tone or style\n- The target audience\n\nAfter analyzing the script, follow these steps:\n\n1. Generate your thoughts on the script and potential titles/hashtags. Consider what would make the video stand out and appeal to the target audience. Write your thoughts inside <thoughts> tags.\n\n2. Create an unambiguous, interesting, and engaging title for the video. The title should:\n - Accurately reflect the content of the video\n - Be concise and attention-grabbing\n - Use language that resonates with the target audience\n - Potentially include a hook or create curiosity\n\n3. Generate 1-2 relevant hashtags for the video. The hashtags should:\n - Be closely related to the video's content\n - Be popular or trending (if applicable)\n - Help increase the video's discoverability\n\nProvide your output in the following format:\n<thoughts>\nYour analysis and thoughts on the script, potential titles, and hashtags\n</thoughts>\n\n<title>Your final, unambiguous, interesting, and engaging title for the video\n\nYour 1-2 most relevant hashtags, separated by a single space if using multiple", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 4160.482363056444, + "y": 2861.811609434119 + } + }, + "input_links": [ + { + "id": "a11e06c0-5592-41c1-97c8-6fb12ff29164", + "source_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "sink_id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "source_name": "response", + "sink_name": "prompt_values_#_SCRIPT", + "is_static": false + } + ], + "output_links": [ + { + "id": "348a7031-04b5-43c8-b20a-560772b6f8b4", + "source_id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "sink_id": "c1edbb59-d97d-4f13-aaaf-9f089280e6d6", + "source_name": "response", + "sink_name": "text", + "is_static": false + }, + { + "id": "dd046be2-e8a3-461b-9ca9-ff60d00c89e6", + "source_id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "sink_id": "ca4397f3-3146-4721-8d45-027581169210", + "source_name": "response", + "sink_name": "text", + "is_static": false + } + ], + "graph_id": "6a6f8fcd-857d-469c-a98b-e90950a7851b", + "graph_version": 57, + "webhook_id": null, + "webhook": null + } + ], + "links": [ + { + "id": "c4a903cd-1d79-4ff8-b0f1-a112ec11a714", + "source_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "sink_id": "d9e779dc-8f71-4234-b91b-7e1c041e89a4", + "source_name": "response", + "sink_name": "value", + "is_static": false + }, + { + "id": "b751321b-4688-4ab7-af14-e8d15ae8e786", + "source_id": "6dbef347-9a49-4f24-9d1c-3d39c384f354", + "sink_id": "681a5773-4e22-4ba7-b972-8864110ee106", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "e2a7904d-fe01-49b4-bd10-e1fd23a31678", + "source_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "sink_id": "6dbef347-9a49-4f24-9d1c-3d39c384f354", + "source_name": "response", + "sink_name": "script", + "is_static": false + }, + { + "id": "287bc030-1ce3-433a-bef7-5936eff22f62", + "source_id": "d5ec4382-2bca-4655-bf38-5c6f65010b75", + "sink_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "source_name": "response", + "sink_name": "prompt_values_#_TOPIC", + "is_static": false + }, + { + "id": "476a4503-87f1-40a4-8dd7-c188061a4870", + "source_id": "46cca925-1e4a-47ca-b2d3-ff2ef07ee917", + "sink_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "source_name": "summary", + "sink_name": "prompt_values_#_RESEARCH", + "is_static": false + }, + { + "id": "dd046be2-e8a3-461b-9ca9-ff60d00c89e6", + "source_id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "sink_id": "ca4397f3-3146-4721-8d45-027581169210", + "source_name": "response", + "sink_name": "text", + "is_static": false + }, + { + "id": "0c3311b3-fbcc-45db-bf90-f4ca892bdfbf", + "source_id": "ca4397f3-3146-4721-8d45-027581169210", + "sink_id": "98d315de-2f53-4f28-aec1-d254c307b86b", + "source_name": "positive", + "sink_name": "value", + "is_static": false + }, + { + "id": "9c1fdb9d-a860-4645-8e78-13b1c6a961e9", + "source_id": "06ff48a2-101e-4e20-ae92-b8ab94ad9df9", + "sink_id": "cab3dbde-1473-465a-8bf4-71ba69e5a5de", + "source_name": "output", + "sink_name": "prompt", + "is_static": false + }, + { + "id": "a11e06c0-5592-41c1-97c8-6fb12ff29164", + "source_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "sink_id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "source_name": "response", + "sink_name": "prompt_values_#_SCRIPT", + "is_static": false + }, + { + "id": "336cf54b-f639-4ff0-bafd-fce3328d2046", + "source_id": "d5ec4382-2bca-4655-bf38-5c6f65010b75", + "sink_id": "bcc0c964-c614-4ce4-977e-36eff68a82a9", + "source_name": "response", + "sink_name": "query", + "is_static": false + }, + { + "id": "ff3d2c2d-d0c4-48ac-a147-09518f3c920b", + "source_id": "c1edbb59-d97d-4f13-aaaf-9f089280e6d6", + "sink_id": "6d53ddf1-b39d-4dbc-931a-aeae658f9edd", + "source_name": "positive", + "sink_name": "value", + "is_static": false + }, + { + "id": "8e93cfb8-5338-475c-8bab-4b4d3912a913", + "source_id": "6dbef347-9a49-4f24-9d1c-3d39c384f354", + "sink_id": "681a5773-4e22-4ba7-b972-8864110ee106", + "source_name": "video_url", + "sink_name": "value", + "is_static": false + }, + { + "id": "9164e2ea-7207-4c1d-88ea-32ae8bf0a429", + "source_id": "7168de4f-206f-43bc-8e36-55df20656b84", + "sink_id": "06ff48a2-101e-4e20-ae92-b8ab94ad9df9", + "source_name": "result", + "sink_name": "values_#_TOPIC", + "is_static": true + }, + { + "id": "ea10a20b-f133-44fb-aa9d-e4cffd7d96c7", + "source_id": "d5ec4382-2bca-4655-bf38-5c6f65010b75", + "sink_id": "46cca925-1e4a-47ca-b2d3-ff2ef07ee917", + "source_name": "response", + "sink_name": "focus", + "is_static": false + }, + { + "id": "afb2edf8-8f05-4a6c-af7d-86c9ae0009b6", + "source_id": "cab3dbde-1473-465a-8bf4-71ba69e5a5de", + "sink_id": "6f373ad2-ff4f-44be-9328-27519f47afe3", + "source_name": "response", + "sink_name": "prompt_values_#_RESULTS", + "is_static": false + }, + { + "id": "3a679d8a-c62d-498b-a83d-8b7241449526", + "source_id": "bcc0c964-c614-4ce4-977e-36eff68a82a9", + "sink_id": "46cca925-1e4a-47ca-b2d3-ff2ef07ee917", + "source_name": "results", + "sink_name": "text", + "is_static": false + }, + { + "id": "fef2729e-95cc-4963-a956-95d33aa3bbc4", + "source_id": "6f373ad2-ff4f-44be-9328-27519f47afe3", + "sink_id": "682e6436-c45e-44e4-a643-1562564302a2", + "source_name": "response", + "sink_name": "text", + "is_static": false + }, + { + "id": "2f6c6627-e243-47b0-a78a-f65a4b0ba665", + "source_id": "75d91ec6-e3ff-4013-9a6d-43ea023e4989", + "sink_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "source_name": "date", + "sink_name": "prompt_values_#_DATE", + "is_static": false + }, + { + "id": "348a7031-04b5-43c8-b20a-560772b6f8b4", + "source_id": "f7c30e6b-4b42-4fa4-8c31-32475db03833", + "sink_id": "c1edbb59-d97d-4f13-aaaf-9f089280e6d6", + "source_name": "response", + "sink_name": "text", + "is_static": false + }, + { + "id": "58c628e0-c1bb-4f7c-bcaa-a7cac3c53c4c", + "source_id": "682e6436-c45e-44e4-a643-1562564302a2", + "sink_id": "6ffba701-9296-4203-bbde-3c2c1a1247dd", + "source_name": "positive", + "sink_name": "prompt_values_#_FULL_STORY", + "is_static": false + }, + { + "id": "f7fd1362-8653-4283-a39c-201d177bc80e", + "source_id": "682e6436-c45e-44e4-a643-1562564302a2", + "sink_id": "d5ec4382-2bca-4655-bf38-5c6f65010b75", + "source_name": "positive", + "sink_name": "prompt_values_#_STORY", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "sub_graphs": [], + "user_id": "", + "created_at": "2025-04-28T13:04:18.367Z", + "input_schema": { + "type": "object", + "properties": { + "Video Topic / Headline": { + "advanced": false, + "anyOf": [ + { + "format": "short-text", + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Video Topic / Headline", + "description": "Type a broad topic (e.g. \u2018Climate Tech\u2019) or paste an exact headline (e.g. \u2018IBM unveils quantum roadmap\u2019) to generate a short-form video about it.", + "default": "AutoGPT" + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "Short-Form Video Title": { + "advanced": false, + "secret": false, + "title": "Short-Form Video Title", + "description": "Hook-driven title optimised for TikTok, Instagram Reels & YouTube Shorts." + }, + "Video Script (+Visual Cues)": { + "advanced": false, + "secret": false, + "title": "Video Script (+Visual Cues)", + "description": "Complete spoken script with [visual directions] for your short-form video." + }, + "Optimised Hashtags": { + "advanced": false, + "secret": false, + "title": "Optimised Hashtags", + "description": "One or two high-reach hashtags to boost discoverability." + }, + "Video": { + "advanced": false, + "secret": false, + "title": "Video", + "description": "The finished video created by the Agent" + } + }, + "required": [ + "Short-Form Video Title", + "Video Script (+Visual Cues)", + "Optimised Hashtags", + "Video" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "revid_api_key_credentials": { + "credentials_provider": [ + "revid" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "revid", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + }, + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "gpt-4.1-2025-04-14", + "gpt-4o" + ] + }, + "jina_api_key_credentials": { + "credentials_provider": [ + "jina" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "jina", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + }, + "open_router_api_key_credentials": { + "credentials_provider": [ + "open_router" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "open_router", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "perplexity/sonar-pro" + ] + }, + "anthropic_api_key_credentials": { + "credentials_provider": [ + "anthropic" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "anthropic", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "claude-sonnet-4-5-20250929" + ] + } + }, + "required": [ + "revid_api_key_credentials", + "openai_api_key_credentials", + "jina_api_key_credentials", + "open_router_api_key_credentials", + "anthropic_api_key_credentials" + ], + "title": "AIVideoGenerator:CreateViral-ReadyContentinSecondsCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_a548e507-09a7-4b30-909c-f63fcda10fff.json b/autogpt_platform/backend/agents/agent_a548e507-09a7-4b30-909c-f63fcda10fff.json new file mode 100644 index 0000000000..f86b6f0826 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_a548e507-09a7-4b30-909c-f63fcda10fff.json @@ -0,0 +1,1886 @@ +{ + "id": "e25b5ce7-e807-4b5a-8708-cb94fa0e2ace", + "version": 81, + "is_active": true, + "name": "Lead Finder", + "description": "Turbo-charge your local lead generation with the AutoGPT Marketplace\u2019s top Google Maps prospecting agent. \u201cLead Finder: Local Businesses\u201d delivers verified, ready-to-contact prospects in any niche and city\u2014so you can focus on closing, not searching.\n\n**WHAT IT DOES**\n\u2022 Searches Google Maps via the official API (no scraping)\n\u2022 Prompts like \u201cdentists in Chicago\u201d or \u201ccoffee shops near me\u201d\n\u2022 Returns: Name, Website, Rating, Reviews, **Phone & Address**\n\u2022 Exports instantly to your CRM, sheet, or outreach workflow\n\n**WHY YOU\u2019LL LOVE IT**\n\u2713 Hyper-targeted leads in minutes\n\u2713 Unlimited searches & locations\n\u2713 Zero CAPTCHAs or IP blocks\n\u2713 Works on AutoGPT Cloud or self-hosted (with your API key)\n\u2713 Cut prospecting time by 90%\n\n**PERFECT FOR**\n\u2014 Marketers & PPC agencies\n\u2014 SEO consultants & designers\n\u2014 SaaS founders & sales teams\n\nStop scrolling directories\u2014start filling your pipeline. Start now and let AI prospect while you profit.\n\n\u2192 Click *Add to Library* and own your market today.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "f0610fef-5f2f-4e98-8b45-3ac56dab56c6", + "block_id": "3146e4fe-2cdd-4f29-bd12-0c9d5bb4deb0", + "input_default": { + "group": 0, + "dot_all": true, + "pattern": "^(?!\\s*$).+", + "find_all": false, + "case_sensitive": true + }, + "metadata": { + "position": { + "x": 1697.320236665491, + "y": -2066.289253119125 + } + }, + "input_links": [ + { + "id": "2cfa5d5e-fb60-4e56-a51d-347a37ee982b", + "source_id": "7d54d6b5-d70d-4393-83c2-c434794ce9a7", + "sink_id": "f0610fef-5f2f-4e98-8b45-3ac56dab56c6", + "source_name": "output", + "sink_name": "text", + "is_static": false + } + ], + "output_links": [ + { + "id": "1580f5c8-1dc1-43a4-abdc-3a82e6805db2", + "source_id": "f0610fef-5f2f-4e98-8b45-3ac56dab56c6", + "sink_id": "5f26aa29-e3b4-45e6-9dbc-cefcb4209207", + "source_name": "negative", + "sink_name": 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(max 60).", + "default": 3 + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "Name": { + "advanced": false, + "secret": false, + "title": "Name" + }, + "Website": { + "advanced": false, + "secret": false, + "title": "Website" + }, + "Rating": { + "advanced": false, + "secret": false, + "title": "Rating" + }, + "Number of Reviews": { + "advanced": false, + "secret": false, + "title": "Number of Reviews" + }, + "Phone Number": { + "advanced": false, + "secret": false, + "title": "Phone Number" + }, + "Address": { + "advanced": false, + "secret": false, + "title": "Address" + } + }, + "required": [ + "Name", + "Website", + "Rating", + "Number of Reviews", + "Phone Number", + "Address" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "google_maps_api_key_credentials": { + "credentials_provider": [ + "google_maps" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "google_maps", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + } + }, + "required": [ + "google_maps_api_key_credentials" + ], + "title": "LeadFinderCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_b6f6f0d3-49f4-4e3b-8155-ffe9141b32c0.json b/autogpt_platform/backend/agents/agent_b6f6f0d3-49f4-4e3b-8155-ffe9141b32c0.json new file mode 100644 index 0000000000..02e4fd463f --- /dev/null +++ b/autogpt_platform/backend/agents/agent_b6f6f0d3-49f4-4e3b-8155-ffe9141b32c0.json @@ -0,0 +1,1676 @@ +{ + "id": "f410b776-3603-4f84-8348-e5db9c551322", + "version": 31, + "is_active": true, + "name": "Domain Name Finder", + "description": "Overview:\nFinding a domain name that fits your brand shouldn\u2019t take hours of searching and failed checks. The Domain Name Finder Agent turns your pitch into hundreds of creative, brand-ready domain ideas\u2014filtered by live availability so every result is actionable.\n\nHow It Works\n1. Input your product pitch, company name, or core keywords.\n2. The agent analyzes brand tone, audience, and industry context.\n3. It generates a list of unique, memorable domains that match your criteria.\n4. All names are pre-filtered for real-time availability, so you can register immediately.\n\n\nBusiness Value\nSave hours of guesswork and eliminate dead ends. Accelerate brand launches, startup naming, and campaign creation with ready-to-claim domains.\n\n\nKey Use Cases\n\u2022 Startup Founders: Quickly find brand-ready domains for MVP launches or rebrands.\n\u2022 Marketers: Test name options across campaigns with instant availability data.\n\u2022 Entrepreneurs: Validate ideas faster with instant domain options.", + "instructions": "Pitch your website idea, run the agent, then check back in 10 mins for your bespoke set of unregistered domain names - ranked by estimated valuation and relevance to your pitch.", + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "570c679c-676d-448f-bb1c-b347f36970aa", + "block_id": "0e50422c-6dee-4145-83d6-3a5a392f65de", + "input_default": { + "key": "domains" + }, + "metadata": { + "position": { + "x": 1923.7273090275667, + "y": 465.50008994458585 + } + }, + "input_links": [ + { + "id": "4e403abc-3a34-414c-9240-7a30b6f22ac5", + "source_id": "63c243b9-7c2d-4d55-9693-7eca2e66fb67", + "sink_id": "570c679c-676d-448f-bb1c-b347f36970aa", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + } + ], + "output_links": [ + { + "id": "486aae4d-b3db-4008-842c-05f966f00b5b", + "source_id": "570c679c-676d-448f-bb1c-b347f36970aa", + "sink_id": "7e00122a-ad6b-4e0f-92e4-d079a2173fae", + "source_name": "missing", + "sink_name": "value", + "is_static": false + }, + { + "id": "c70b4120-64a3-44d0-a960-3674735314ff", + "source_id": "570c679c-676d-448f-bb1c-b347f36970aa", + "sink_id": "f3feafe5-4971-4604-9cfa-caf8e0cf60d8", + "source_name": "output", + "sink_name": "values_#_DOMAINS", + "is_static": false + } + ], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "2105e9c1-0698-4a01-9d02-02d791364498", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-5-2025-08-07", + "retry": 3, + "prompt": "Generate a creative and relevant list of possible domain names that could be available (unregistered) for the product described by the given product pitch. Prioritize short, single-word English .com domains that closely relate to the product or its key features, as these are the most valuable. Only suggest .com domains. Avoid suggesting long or awkward names; names that sound like real English words but may be invented are acceptable if memorable and brandable. Do not include off-topic, or low-value gibberish names.\n\nBefore listing any domains, internally consider:\n- What words or ideas are most core to the product pitch?\n- Which synonyms, metaphors, or conceptual connections would make good brands?\n- What domains are likely to realistically be available and not already taken?\n- Are there any exceptional reasons to consider a non-.com extension?\n- Whether the domains are concise, attractive, and easy to remember/pronounce.\n\nOutput only the domains in a comma-separated list, enclosed in XML tags, with no additional commentary or explanation.\n\nFormat:\nexample1.com,example2.com,example3.com\n\nExample Input:\n \"A voice-based fitness app\"\n\nExample Output:\nvotone.com,soundgym.com,voicetrain.com,fitchant.com\n(Realistic use cases may generate ~500k high-quality domains per prompt.)\n\nEdge Cases & Special Considerations:\n- Never generate multi-word domains with dashes or excessive length.\n- If a non-.com TLD is used, justify internally that it is a natural fit (e.g., \".ai\" for an artificial intelligence SaaS).\n- Exclude domains that are likely to be heavily trademarked or existing brands.\n- The output must always be ONLY the XML tag with comma-separated domains.\n- Aim to write at least 500 domains\n- NEVER comment inside the csv, otherwise the csv will be corrupted and the workflow will completely break. If you want to make a comment, leave a xml set OUTSIDE the xml set with your comments. No matter what do not break this rule.\n\nHere is the product pitch you will be working with:\n\n{{product_pitch | safe}}\n\n\n\nREMINDER: Focus on creative, concise, high value .com domains aligned with the product pitch; output only as example.com,example2.com", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 803.72695210037, + "y": 465.5000381469727 + } + }, + "input_links": [ + { + "id": "6097cc32-f6e1-4311-8804-e99af44201f4", + "source_id": "ed14af2c-2251-4cef-8a70-2337251c64c0", + "sink_id": "2105e9c1-0698-4a01-9d02-02d791364498", + "source_name": "output", + "sink_name": "prompt_values_#_product_pitch", + "is_static": true + } + ], + "output_links": [ + { + "id": "ddbcf470-de3a-4955-89aa-12291f26a059", + "source_id": "2105e9c1-0698-4a01-9d02-02d791364498", + "sink_id": "74ae8dfb-4ec3-442d-a965-9fcc95fc8a48", + "source_name": "error", + "sink_name": "input", + "is_static": false + }, + { + "id": "7427c0ae-ec91-4bd5-9a72-1ef24fc11430", + "source_id": "2105e9c1-0698-4a01-9d02-02d791364498", + "sink_id": "63c243b9-7c2d-4d55-9693-7eca2e66fb67", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + } + ], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "63c243b9-7c2d-4d55-9693-7eca2e66fb67", + "block_id": "286380af-9529-4b55-8be0-1d7c854abdb5", + "input_default": {}, + "metadata": { + "position": { + "x": 1363.7269529646674, + "y": 465.5000376599629 + } + }, + "input_links": [ + { + "id": "7427c0ae-ec91-4bd5-9a72-1ef24fc11430", + "source_id": "2105e9c1-0698-4a01-9d02-02d791364498", + "sink_id": "63c243b9-7c2d-4d55-9693-7eca2e66fb67", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + } + ], + "output_links": [ + { + "id": "2430664a-6580-428b-a317-36c7675539c1", + "source_id": "63c243b9-7c2d-4d55-9693-7eca2e66fb67", + "sink_id": "7e00122a-ad6b-4e0f-92e4-d079a2173fae", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "4e403abc-3a34-414c-9240-7a30b6f22ac5", + "source_id": "63c243b9-7c2d-4d55-9693-7eca2e66fb67", + "sink_id": "570c679c-676d-448f-bb1c-b347f36970aa", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + } + ], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "524bd1e9-17c2-4b11-ab3e-2f1809823c7e", + "block_id": "90a56ffb-7024-4b2b-ab50-e26c5e5ab8ba", + "input_default": { + "name": "Product Pitch", + "secret": false, + "advanced": false, + "description": "Pitch your product!", + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -534.5334675859784, + "y": 458.4006590838727 + } + }, + "input_links": [], + "output_links": [ + { + "id": "e53ea15b-4d84-494d-9867-71e454f7c867", + "source_id": "524bd1e9-17c2-4b11-ab3e-2f1809823c7e", + "sink_id": "55b1f3b7-9b38-45dd-8fb7-c4c7f0037c04", + "source_name": "result", + "sink_name": "prompt_values_#_product_pitch", + "is_static": true + }, + { + "id": "34ba9aec-eb91-4760-bde7-c98685b95f5a", + "source_id": "524bd1e9-17c2-4b11-ab3e-2f1809823c7e", + "sink_id": "ed14af2c-2251-4cef-8a70-2337251c64c0", + "source_name": "result", + "sink_name": "input", + "is_static": true + } + ], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "1177aa11-112e-4644-996c-cb9bab6e03ba", + "block_id": "0b02b072-abe7-11ef-8372-fb5d162dd712", + "input_default": { + "timeout": 300, + "language": "python", + "setup_commands": [], + "dispose_sandbox": true + }, + "metadata": { + "position": { + "x": 3084.835212232708, + "y": 469.16536240312246 + } + }, + "input_links": [ + { + "id": "9f73853c-27bc-40c0-ac1b-b6aee896c92c", + "source_id": "f3feafe5-4971-4604-9cfa-caf8e0cf60d8", + "sink_id": "1177aa11-112e-4644-996c-cb9bab6e03ba", + "source_name": "output", + "sink_name": "code", + "is_static": false + } + ], + "output_links": [ + { + "id": "c9ab9fb0-391c-46bc-b6e7-13fe3125a5f1", + "source_id": "1177aa11-112e-4644-996c-cb9bab6e03ba", + "sink_id": "7e00122a-ad6b-4e0f-92e4-d079a2173fae", + "source_name": "stderr_logs", + "sink_name": "value", + "is_static": false + }, + { + "id": "5f5dba52-1c34-4621-9047-94185ed471f6", + "source_id": "1177aa11-112e-4644-996c-cb9bab6e03ba", + "sink_id": "52555e06-ac46-4ed2-97dd-c2e46c0985f4", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + }, + { + "id": "0b604734-0417-4a56-b3c3-6c841ee764df", + "source_id": "1177aa11-112e-4644-996c-cb9bab6e03ba", + "sink_id": "52555e06-ac46-4ed2-97dd-c2e46c0985f4", + "source_name": "stdout_logs", + "sink_name": "input_xml", + "is_static": false + }, + { + "id": "ab8d3920-8582-426d-92a1-0cf3bdd31efe", + "source_id": "1177aa11-112e-4644-996c-cb9bab6e03ba", + "sink_id": "7e00122a-ad6b-4e0f-92e4-d079a2173fae", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "55b1f3b7-9b38-45dd-8fb7-c4c7f0037c04", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-5-2025-08-07", + "retry": 3, + "prompt": "You are a domain valuation expert tasked with ranking a list of domain names based on their value and relevance to a specific product. You will be provided with two key pieces of information:\n\n1. A product pitch:\n\n{{product_pitch | safe}}\n\n\n2. A list of domain names to rank:\n\n{{domains | safe}}\n\n\nYour task is to analyze these domains and rank them based on two primary factors:\n1. The inherent value of the domain name (most important)\n2. The relevance and potential value of the domain for the specific product described in the product pitch\n\nPlease follow these steps:\n\n1. Read the product pitch carefully and extract key product features and target audience information. List these in tags.\n\n2. Identify relevant keywords for the product based on the pitch. List these in tags.\n\n3. For each domain in the provided list - carefully consider it, then pick your top 10 domains from the list for the following analysis:\n a. Evaluate the domain based on the following factors:\n - Length (number of characters)\n - Memorability\n - Brandability\n - Keyword relevance\n - TLD (Top-Level Domain)\n - Potential commercial value\n\n b. Calculate a Domain Quality Score (1-10) using the following method:\n - Length Score (LS):\n 10: 1\u20134 chars\n 9: 5\n 8: 6\n 7: 7\n 6: 8\n 5: 9\n 4: 10\n 3: 11\u201312\n 2: 13\u201314\n 1: 15+\n\n - Word Score (WS):\n * Base (BWC): 1 word =5, 2 words =4, 3w=3, 4w=2, 5+ words =1\n * Quality Modifier (WQM): +1 English dictionary word, 0 common/brandable, \u20131 meh brand/obscure foreign, \u20132 unpronounceable\n * Word Score (WS) = clamp(BWC + WQM, 1\u20135)\u00d72\n\n - Penalties: \u20131 hyphen, \u20131 number, \u20130.5 triple letter\n\n - Final Score = clamp(round(0.6\u00d7WS + 0.4\u00d7LS + penalties), 1\u201310)\n\n c. Consider how the domain relates to the product described in the product pitch.\n\nWrap your analysis in a single set of tags. \nInclude the following for each domain:\n1. Verify that the domain is present in the original list provided.\n2. A table with the following columns: Factor, Calculated Score, Justification.\n3. The calculated Domain Quality Score, showing each step of the calculation.\n4. An explanation of how the domain relates to the product pitch.\n\nAfter evaluating your potential top 10 domains, present your final ranking as a newline-separated list of domains inside a single complete set of XML tags. Ensure that only domains from the original list are included in your ranking.\n\nIf there are more than 30 domains in the list, just list your top 30.\n\nExample output format:\n\n\ndomain1.com\ndomain2.net\ndomain3.org\n\n\nPlease proceed with your evaluation and ranking of the provided domain list.", + "ollama_host": "localhost:11434", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 6417.294788842872, + "y": 443.3113161801738 + } + }, + "input_links": [ + { + "id": "e53ea15b-4d84-494d-9867-71e454f7c867", + "source_id": "524bd1e9-17c2-4b11-ab3e-2f1809823c7e", + "sink_id": "55b1f3b7-9b38-45dd-8fb7-c4c7f0037c04", + "source_name": "result", + "sink_name": "prompt_values_#_product_pitch", + "is_static": true + }, + { + "id": "4260a459-1cda-411e-9c32-1e886d49f444", + "source_id": "187169c5-388f-4be3-ae67-ff46fb091ba3", + "sink_id": "55b1f3b7-9b38-45dd-8fb7-c4c7f0037c04", + "source_name": "no_output", + "sink_name": "prompt_values_#_domains", + "is_static": false + } + ], + "output_links": [ + { + "id": "781b8b03-e645-42f6-b9ee-18727a04bb42", + "source_id": "55b1f3b7-9b38-45dd-8fb7-c4c7f0037c04", + "sink_id": "aa67b2a4-e886-4381-9bea-65fe4d6e0a07", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + }, + { + "id": "6b8523b5-ce6e-4cd4-80a6-6be54b9be4ab", + "source_id": "55b1f3b7-9b38-45dd-8fb7-c4c7f0037c04", + "sink_id": "7e00122a-ad6b-4e0f-92e4-d079a2173fae", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "aa67b2a4-e886-4381-9bea-65fe4d6e0a07", + "block_id": "286380af-9529-4b55-8be0-1d7c854abdb5", + "input_default": {}, + "metadata": { + "position": { + "x": 6977.294417024638, + "y": 458.46844766434674 + } + }, + "input_links": [ + { + "id": "781b8b03-e645-42f6-b9ee-18727a04bb42", + "source_id": "55b1f3b7-9b38-45dd-8fb7-c4c7f0037c04", + "sink_id": "aa67b2a4-e886-4381-9bea-65fe4d6e0a07", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + } + ], + "output_links": [ + { + "id": "d28783ab-8818-4f28-ae66-d9a04ad33455", + "source_id": "aa67b2a4-e886-4381-9bea-65fe4d6e0a07", + "sink_id": "63df7668-8ada-4525-a1a1-7baae5efc103", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + }, + { + "id": "cf5cd1d2-24ac-4126-ad0f-d934b7862e3a", + "source_id": "aa67b2a4-e886-4381-9bea-65fe4d6e0a07", + "sink_id": "7e00122a-ad6b-4e0f-92e4-d079a2173fae", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "63df7668-8ada-4525-a1a1-7baae5efc103", + "block_id": "0e50422c-6dee-4145-83d6-3a5a392f65de", + "input_default": { + "key": "domains" + }, + "metadata": { + "position": { + "x": 7537.294428844076, + "y": 458.46840935125437 + } + }, + "input_links": [ + { + "id": "d28783ab-8818-4f28-ae66-d9a04ad33455", + "source_id": "aa67b2a4-e886-4381-9bea-65fe4d6e0a07", + "sink_id": "63df7668-8ada-4525-a1a1-7baae5efc103", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + } + ], + "output_links": [ + { + "id": "d6bd5988-cee8-4ac9-873f-a5dbd3bc8da5", + "source_id": "63df7668-8ada-4525-a1a1-7baae5efc103", + "sink_id": "32f86709-810b-4f20-a2f7-a4027ff05094", + "source_name": "output", + "sink_name": "values_#_ranked_domains_block", + "is_static": false + }, + { + "id": "99886544-d322-4179-838f-a5b01292fcdb", + "source_id": "63df7668-8ada-4525-a1a1-7baae5efc103", + "sink_id": "7e00122a-ad6b-4e0f-92e4-d079a2173fae", + "source_name": "missing", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "ea561c3b-3d18-4b8e-8842-065d06309502", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Domain Suggestions", + "secret": false, + "advanced": false, + "escape_html": false + }, + "metadata": { + "position": { + "x": 9300.394546088242, + "y": 452.78448671411047 + } + }, + "input_links": [ + { + "id": "d3c06626-b5b0-4660-8733-b5167cbdd26c", + "source_id": "32f86709-810b-4f20-a2f7-a4027ff05094", + "sink_id": "ea561c3b-3d18-4b8e-8842-065d06309502", + "source_name": "output", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "f3feafe5-4971-4604-9cfa-caf8e0cf60d8", + "block_id": "db7d8f02-2f44-4c55-ab7a-eae0941f0c30", + "input_default": { + "format": "#!/usr/bin/env python3\n\"\"\"\ncheck_domains_simple_com.py \u2014 Check .com domain availability via RDAP.\n\nHow to use:\n1) Put comma-separated .com domains into DOMAINS_TEXT below.\n - Each comma-delimited token must be an exact .com domain (e.g., \"foo.com\").\n - Anything that is not a valid .com domain counts as an input error.\n2) Run: python3 check_domains_simple_com.py\n3) Output summary sections and lists of available/unavailable/error tokens.\n\"\"\"\n\nfrom __future__ import annotations\n\nimport re\nfrom concurrent.futures import ThreadPoolExecutor, as_completed\nfrom typing import Dict, List, Tuple\n\nimport requests\nfrom requests.adapters import HTTPAdapter\n\ntry:\n from urllib3.util.retry import Retry # type: ignore\nexcept Exception: # Retry optional\n Retry = None # type: ignore\n\n# ---------------------------------------------------------------------\n# \ud83d\udcdd Paste your names/domains here (commas and/or newlines are fine).\nDOMAINS_TEXT = \"\"\"{{DOMAINS | safe}}\"\"\"\n# ---------------------------------------------------------------------\n\n# Concurrency / networking\nWORKERS = 80\nTIMEOUT = 12.0\n\nHEADERS = {\n \"Accept\": \"application/rdap+json, application/json;q=0.9, */*;q=0.1\",\n \"User-Agent\": \"domain-checker/1.0 (+https://example.com)\",\n}\n\n# Verisign RDAP for .com\nCOM_ENDPOINT = \"https://rdap.verisign.com/com/v1/domain/{}\"\n\n\ndef normalize_label(s: str) -> str:\n \"\"\"Lowercase and keep only a\u2013z and 0\u20139.\"\"\"\n return re.sub(r\"[^a-z0-9]\", \"\", s.lower())\n\nCOM_DOMAIN_RE = re.compile(r\"^(?=.{1,253}$)(?!-)[a-z0-9](?:[a-z0-9-]{0,61}[a-z0-9])?\\.com$\")\n\n\ndef domains_from_text(text: str) -> Tuple[List[str], List[str]]:\n \"\"\"Parse comma-separated tokens; accept only exact .com domains.\n\n Returns (valid_domains, invalid_tokens).\n \"\"\"\n tokens: List[str] = []\n for part in (text or \"\").split(\",\"):\n val = part.strip()\n if val:\n tokens.append(val)\n\n valid_domains: List[str] = []\n invalid_tokens: List[str] = []\n for token in tokens:\n s = token.strip().lower()\n if COM_DOMAIN_RE.match(s):\n # De-dup preserving order for domains only\n if s not in valid_domains:\n valid_domains.append(s)\n else:\n invalid_tokens.append(token)\n\n return valid_domains, invalid_tokens\n\n\ndef build_session(pool_size: int) -> requests.Session:\n session = requests.Session()\n session.headers.update(HEADERS)\n adapter_kwargs = {\"pool_connections\": pool_size, \"pool_maxsize\": pool_size}\n if Retry is not None:\n retry = Retry(\n total=3,\n backoff_factor=0.3,\n status_forcelist=(429, 500, 502, 503, 504),\n allowed_methods=(\"GET\",),\n raise_on_status=False,\n )\n adapter = HTTPAdapter(max_retries=retry, **adapter_kwargs)\n else:\n adapter = HTTPAdapter(**adapter_kwargs)\n session.mount(\"https://\", adapter)\n session.mount(\"http://\", adapter)\n return session\n\n\ndef rdap_lookup_com(domain: str, session: requests.Session) -> Dict[str, str]:\n \"\"\"Return {'domain': str, 'status': 'AVAILABLE'|'REGISTERED'|'ERROR'|'UNKNOWN_xx'}.\"\"\"\n url = COM_ENDPOINT.format(domain)\n try:\n r = session.get(url, timeout=TIMEOUT)\n except requests.RequestException as e:\n return {\"domain\": domain, \"status\": \"ERROR\", \"error\": str(e)}\n if r.status_code == 404:\n return {\"domain\": domain, \"status\": \"AVAILABLE\"}\n if r.status_code == 200:\n return {\"domain\": domain, \"status\": \"REGISTERED\"}\n return {\"domain\": domain, \"status\": f\"UNKNOWN_{r.status_code}\", \"error\": r.text[:200].replace(\"\\n\", \" \")}\n\n\ndef main() -> int:\n domains, invalid_tokens = domains_from_text(DOMAINS_TEXT)\n if not domains and not invalid_tokens:\n return 0\n\n # Preserve input order\n domain_to_index: Dict[str, int] = {d: i for i, d in enumerate(domains)}\n\n # Connection pool\n pool_size = max(1, min(WORKERS, len(domains)))\n session = build_session(pool_size)\n\n rows = []\n with ThreadPoolExecutor(max_workers=pool_size) as executor:\n futs = {executor.submit(rdap_lookup_com, d, session): d for d in domains}\n for fut in as_completed(futs):\n rows.append(fut.result())\n\n # Restore input order\n rows.sort(key=lambda r: domain_to_index.get(r.get(\"domain\", \"\"), 10**9))\n\n # Group domains by availability\n available = []\n unavailable = []\n errors = []\n for r in rows:\n if r.get(\"status\") == \"AVAILABLE\" and r.get(\"domain\"):\n available.append(r[\"domain\"])\n elif r.get(\"status\") == \"REGISTERED\" and r.get(\"domain\"):\n unavailable.append(r[\"domain\"])\n elif r.get(\"domain\"):\n errors.append(r[\"domain\"])\n\n # Include input parsing errors (non-.com tokens)\n errors.extend(invalid_tokens)\n\n # Print in requested format\n print(\"\")\n total = len(available) + len(unavailable)\n print(f\" I checked {total} domains for you.\")\n print(f\"Domains available to register now: {len(available)}\")\n print(f\"Domains already registered: {len(unavailable)}\")\n print(\"\")\n print(\"\")\n for domain in available:\n print(domain)\n print(\"\")\n print(\"\")\n for domain in unavailable:\n print(domain)\n print(\"\")\n print(\"\")\n for domain in errors:\n print(domain)\n print(\"\")\n\n return 0\n\n\nif __name__ == \"__main__\":\n _ = main()\n", + "values": {}, + "escape_html": false + }, + "metadata": { + "position": { + "x": 2490.3486926884043, + "y": 464.1087684425463 + } + }, + "input_links": [ + { + "id": "c70b4120-64a3-44d0-a960-3674735314ff", + "source_id": "570c679c-676d-448f-bb1c-b347f36970aa", + "sink_id": "f3feafe5-4971-4604-9cfa-caf8e0cf60d8", + "source_name": "output", + "sink_name": "values_#_DOMAINS", + "is_static": false + } + ], + "output_links": [ + { + "id": "9f73853c-27bc-40c0-ac1b-b6aee896c92c", + "source_id": "f3feafe5-4971-4604-9cfa-caf8e0cf60d8", + "sink_id": "1177aa11-112e-4644-996c-cb9bab6e03ba", + "source_name": "output", + "sink_name": "code", + "is_static": false + } + ], + "graph_id": "f410b776-3603-4f84-8348-e5db9c551322", + "graph_version": 31, + "webhook_id": null, + "webhook": null + }, + { + "id": "7e00122a-ad6b-4e0f-92e4-d079a2173fae", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Error", + 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}}\n\n### How This List Is Ranked\n\nThe suggestions are **ranked from best fit to broader options** based on:\n- **Fit with your pitch** (topic match, tone, audience)\n- **Brandability** (memorability, uniqueness, ease to say/spell)\n- **Clarity & length** (short, unambiguous, no filler)\n- **Domain quality** (clean .com bias; no hyphens/numbers)\n- **Noise penalties** (awkward word combos or ambiguity)\n\n> Tip: The top 5 are usually the \u201cbuy now\u201d candidates. If you love a lower-ranked name, go for it\u2014the ranking is guidance, not a rule.\n\n### Domain Suggestions (Ranked)\n\n{{ ranked_domains_block\n | replace('\\r\\n', '\\n')\n | replace('\\n', ' \\n') }}\n\n\n### What to Do Next\n\nThe domain names listed above are still available for registration. To claim one, purchase it from a domain registrar (a company that sells and manages domain names). Availability can change quickly, so check out promptly.\n\n**Popular registrars:**\n- [GoDaddy](https://www.godaddy.com/) \u2014 one of the largest registrars. \n- [Namecheap](https://www.namecheap.com/) \u2014 transparent pricing and easy UI. \n- [Domain.com](https://www.domain.com/) \u2014 long-standing, straightforward. \n- [Dynadot](https://www.dynadot.com/) \u2014 clean, low-friction checkout. \n- [IONOS](https://www.ionos.com/domains) \u2014 competitive first-year pricing.\n\n**Steps:**\n1. Pick your favourite from the top of the list. \n2. Add to cart and check out \u2014 confirm the price \u2014 usually **$10\u201315 per year** \n3. In your registrar dashboard, set up **DNS / name servers** to point the domain to your website or email. \n4. (Optional) Consider grabbing close variants or common misspellings for brand protection.\n", + "values": {}, + "escape_html": false + }, + "metadata": { + "position": { + "x": 8442.06365615613, + "y": 448.9943472999386 + } + }, + "input_links": [ + { + "id": "d2586c8d-edc6-4c00-afad-1815986aaf4d", + "source_id": "187169c5-388f-4be3-ae67-ff46fb091ba3", + "sink_id": "32f86709-810b-4f20-a2f7-a4027ff05094", + "source_name": "yes_output", + "sink_name": "values_#_ranked_domains_block", + "is_static": false + }, + { + "id": "f7307ebc-189f-4554-ba9a-29b66f11fd6d", + "source_id": "aaff98f5-ebea-4dbb-b927-35e2fb20be3c", + "sink_id": "32f86709-810b-4f20-a2f7-a4027ff05094", + "source_name": "output", + "sink_name": "values_#_summary", + "is_static": false + }, + { + "id": "d6bd5988-cee8-4ac9-873f-a5dbd3bc8da5", + "source_id": "63df7668-8ada-4525-a1a1-7baae5efc103", + "sink_id": "32f86709-810b-4f20-a2f7-a4027ff05094", + "source_name": "output", + "sink_name": "values_#_ranked_domains_block", + 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This agent solves that problem by exploring product manuals and guides on your behalf, giving you quick, accurate answers every time.\n\nHow It Works\n1. You ask a product-related question.\n2. The agent reviews docs,\u00a0 manuals, guides, and FAQs.\n3. It verifies accuracy and compiles the best answer.\n4. You receive a concise explanation with direct references to the docs.\n\n\nBusiness Value\n Accelerate onboarding, reduce support wait times, and empower teams with instant knowledge. By automating product Q&A, companies can improve customer satisfaction by cutting down on repetitive support tickets.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "263a6854-5aed-4b9d-9d18-41b25e5002d0", + "block_id": "7fcd3bcb-8e1b-4e69-903d-32d3d4a92158", + "input_default": { + "name": "Documentation URL", + "advanced": false, + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": 48.620022798759834, + "y": 214.4951509877074 + } + }, + "input_links": [], + "output_links": [ + { + "id": "0601d9e3-086d-41c6-b2fe-1fe1f7166fd5", + "source_id": "263a6854-5aed-4b9d-9d18-41b25e5002d0", + "sink_id": "e4d24a93-2107-41a2-b853-69b7b3603153", + "source_name": "result", + "sink_name": "url", + "is_static": true + }, + { + "id": "85507b2c-4eca-4d66-a414-486e65d5382f", + "source_id": "263a6854-5aed-4b9d-9d18-41b25e5002d0", + "sink_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "source_name": "result", + "sink_name": "values_#_DOCUMENTATION_URL", + "is_static": true + } + ] + }, + { + "id": "8a0577e3-315a-4bd8-99d9-da082316b729", + "block_id": "90a56ffb-7024-4b2b-ab50-e26c5e5ab8ba", + "input_default": { + "name": "Question", + "advanced": false, + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -1199.8907386673427, + "y": 215.28637177848216 + } + }, + "input_links": [], + "output_links": [ + { + "id": "de329c54-737a-4a44-85ee-44b23ac7f683", + "source_id": "8a0577e3-315a-4bd8-99d9-da082316b729", + "sink_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "source_name": "result", + "sink_name": "values_#_QUESTION", + "is_static": true + } + ] + }, + { + "id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "block_id": "3b191d9f-356f-482d-8238-ba04b6d18381", + "input_default": { + "model": "gpt-5-2025-08-07", + "retry": 3, + "prompt": "**Current Task:**\nDocumentation Base URL: {{documentation_base_url}}\nCustomer Question: {{question}}\nRequired Confidence Threshold: {{confidence_threshold}}%\nSitemap: {{sitemap}}\n\n**Your Available Tools:**\n1. **FireCrawl Crawl** - Pass in a base URL to crawl through multiple related pages agentically\n2. **FireCrawl Extract** - Pass in a list of specific URLs and a custom prompt for targeted extraction\n\n**Search Process:**\n1. Analyze the sitemap and customer's question to identify key concepts and requirements\n2. Choose the optimal tool strategy:\n - Use **FireCrawl Crawl** when you need to explore multiple related pages in a section\n - Use **FireCrawl Extract** when you know specific URLs and want targeted information with custom prompts\n3. For each search result, perform documentation analysis:\n - Extract relevant quotes from documentation, cited verbatim\n - Identify specific instructions, troubleshooting steps, or policies\n - Note any limitations that might prevent a complete answer\n - Consider edge cases or limitations in potential answers\n4. Assess confidence level (0-100%) based on completeness and accuracy of found information\n5. Continue searching if below {{confidence_threshold}}% threshold using different tools/strategies\n6. Only include information explicitly stated in the documentation\n\n**Tool Usage Guidelines:**\n- **FireCrawl Crawl:** When sitemap shows related pages that need exploration (e.g., API section with multiple endpoints)\n- **FireCrawl Extract:** When sitemap reveals specific relevant pages and you need precise information with targeted prompts\n\n**Stop Conditions:**\n- Confidence reaches {{confidence_threshold}}% or higher\n- Documentation has been thoroughly searched with appropriate tools\n- No additional relevant information can be found\n\n**Final Output Format:**\n{\n \"confidence_score\": [X]%,\n \"relevant_information\": \"Exact text copied verbatim from documentation\",\n \"answer\": \"Complete response based solely on documentation findings\",\n \"source_urls\": [\"exact page URLs relevant to this answer\"],\n \"reasoning\": \"Why this confidence level was reached and which tools were used\"\n}\n\n**Important:** \n- Never make assumptions or include information not present in documentation\n- If insufficient information found, clearly state limitations\n- Ensure responses are accurate, professional, and solution-oriented\n\nBegin searching for: \"{{question}}\" in documentation at {{documentation_base_url}}", + "sys_prompt": "You are a documentation search agent that uses FireCrawl tools to find accurate answers to customer questions. Your goal is to thoroughly search documentation until you reach the specified confidence threshold or exhaust available sources.\n\n**Available Functions:**\n1. firecrawl_crawl(url, limit, only_main_content) - Explore multiple pages from a base URL\n2. firecrawl_extract(urls, prompt) - Extract specific information from known URLs with targeted prompts\n\n**Search Strategy:**\n- Analyze the sitemap to identify relevant documentation areas\n- Use firecrawl_extract when you know specific URLs contain the answer\n- Use firecrawl_crawl when you need to explore and discover relevant pages\n- Continue searching until your confidence reaches the specified confidence threshold OR you've exhausted relevant sources\n- Always provide complete function arguments matching the required schema\n\n**MANDATORY STOP CONDITIONS:**\nYou MUST stop searching and provide your final answer when ANY of these conditions are met:\n- You have made 5 tool calls total (hard limit)\n- Your confidence reaches the confidence threshold ({{CONFIDENCE_THRESHOLD}}%) or higher\n- You find no new relevant information in your last 2 consecutive searches\n- You are about to crawl/extract from URLs you've already processed\n- No more relevant URLs are available to search\n\n**Goal:** Raise your confidence level as high as possible through thorough documentation search.\n\n**Confidence Assessment:**\n- Evaluate how completely and accurately you can answer the customer's question\n- Consider: completeness of information, clarity of documentation, presence of contradictions\n- You must explicitly state your confidence percentage (0-100%)\n- Continue searching if below the confidence threshold ({{CONFIDENCE_THRESHOLD}}%) AND more sources are available AND stop conditions not met\n\n**Output Requirements:**\n- Extract verbatim quotes from documentation sources\n- Provide comprehensive answers based solely on documentation\n- Include relevant source URLs (limit to 2-3 most important)\n- Assess your final confidence level objectively\n\n**Tool Call Tracking:**\n- Keep count of your tool calls (1/5, 2/5, etc.)\n- After each tool call, evaluate if stop conditions are met\n- If stop conditions are met, immediately provide final output in XML format\n\nAlways choose a function call from the available tools and provide complete arguments. When finished, output your findings in the specified XML format.", + "ollama_host": "localhost:11434", + "prompt_values": {}, + "multiple_tool_calls": true, + "conversation_history": [] + }, + "metadata": { + "position": { + "x": 2693.3732369945164, + "y": 208.8074862369709 + } + }, + "input_links": [ + { + "id": "5f17f7fe-6990-4513-8a56-c58c349ba933", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "source_name": "conversations", + "sink_name": "conversation_history", + "is_static": false + }, + { + "id": "ebbd1614-a4cc-4fdb-b5a7-8e09345675b6", + "source_id": "94c831ec-ecf0-477c-8d77-45dec19457d5", + "sink_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "source_name": "output_message", + "sink_name": "last_tool_output", + "is_static": false + }, + { + "id": "aa80e27a-4dd3-41b4-9d4a-aab33c0dd88d", + "source_id": "8d5f6594-d865-4aa7-8479-7f36b4c083df", + "sink_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "source_name": "output", + "sink_name": "prompt", + "is_static": true + } + ], + "output_links": [ + { + "id": "5f17f7fe-6990-4513-8a56-c58c349ba933", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "source_name": "conversations", + "sink_name": "conversation_history", + "is_static": false + }, + { + "id": "a68a6096-56e2-4ee3-9c3d-3d6ed8d3e3d4", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "c9f24972-04a3-472e-a545-6cdd5e0201e1", + "source_name": "finished", + "sink_name": "value", + "is_static": false + }, + { + "id": "206be745-3a31-4b63-ae95-29a7a5822266", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "c9f24972-04a3-472e-a545-6cdd5e0201e1", + "source_name": "tools_^_agentoutputblock_~_value", + "sink_name": "value", + "is_static": false + }, + { + "id": "50c8dfdf-edd4-4ac0-9859-c4eee9737661", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "5f122699-682a-43de-b45e-2b2933f0f5ad", + "source_name": "tools_^_firecrawlextractblock_~_urls", + "sink_name": "urls", + "is_static": false + }, + { + "id": "43b50d09-91ad-4195-9282-143c5c074b85", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "5f122699-682a-43de-b45e-2b2933f0f5ad", + "source_name": "tools_^_firecrawlextractblock_~_prompt", + "sink_name": "prompt", + "is_static": false + }, + { + "id": "77e077d9-b442-4a0f-95da-fb878a8fe624", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "16fbae22-b2ed-42c7-890c-c8554fe74656", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "e6441aea-26d9-4292-80be-54ecdab260ae", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "8a2766d8-94c3-40f2-8e60-66cc63f6425e", + "source_name": "tools_^_firecrawlcrawlblock_~_url", + "sink_name": "url", + "is_static": false + } + ] + }, + { + "id": "a15a19b5-d771-4e30-bb76-2c368468df23", + "block_id": "96dae2bb-97a2-41c2-bd2f-13a3b5a8ea98", + "input_default": { + "name": "Confidence Threshold", + "title": "Auto-Reply Confidence Threshold", + "advanced": false, + "description": "Minimum confidence score (0-100) required for automatic responses", + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -573.5612071210447, + "y": 214.50574812392034 + } + }, + "input_links": [], + "output_links": [ + { + "id": "f96fd53d-c66d-437a-84a4-222abf018bde", + "source_id": "a15a19b5-d771-4e30-bb76-2c368468df23", + "sink_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "source_name": "result", + "sink_name": "values_#_CONFIDENCE_THRESHOLD", + "is_static": true + } + ] + }, + { + "id": "8a2766d8-94c3-40f2-8e60-66cc63f6425e", + "block_id": "bdbbaba0-03b7-4971-970e-699e2de6015e", + "input_default": { + "limit": 10, + "formats": [ + "markdown" + ], + "max_age": 3600000, + "wait_for": 0, + "only_main_content": true + }, + "metadata": { + "position": { + "x": 3635.6678690822937, + "y": -525.4558779233904 + } + }, + "input_links": [ + { + "id": "e6441aea-26d9-4292-80be-54ecdab260ae", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "8a2766d8-94c3-40f2-8e60-66cc63f6425e", + "source_name": "tools_^_firecrawlcrawlblock_~_url", + "sink_name": "url", + "is_static": false + } + ], + "output_links": [ + { + "id": "3a1f2995-6ea7-41e4-a10c-295febd1892a", + "source_id": "8a2766d8-94c3-40f2-8e60-66cc63f6425e", + "sink_id": "94c831ec-ecf0-477c-8d77-45dec19457d5", + "source_name": "markdown", + "sink_name": "input_message", + "is_static": false + } + ] + }, + { + "id": "16fbae22-b2ed-42c7-890c-c8554fe74656", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "ERROR", + "advanced": false + }, + "metadata": { + "position": { + "x": 3318.7470205644167, + "y": 2347.415524537313 + } + }, + "input_links": [ + { + "id": "77e077d9-b442-4a0f-95da-fb878a8fe624", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "16fbae22-b2ed-42c7-890c-c8554fe74656", + "source_name": "error", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [] + }, + { + "id": "c9f24972-04a3-472e-a545-6cdd5e0201e1", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Answer", + "advanced": false + }, + "metadata": { + "position": { + "x": 4740.84460411233, + "y": 1254.0475468406855 + } + }, + "input_links": [ + { + "id": "a68a6096-56e2-4ee3-9c3d-3d6ed8d3e3d4", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "c9f24972-04a3-472e-a545-6cdd5e0201e1", + "source_name": "finished", + "sink_name": "value", + "is_static": false + }, + { + "id": "206be745-3a31-4b63-ae95-29a7a5822266", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "c9f24972-04a3-472e-a545-6cdd5e0201e1", + "source_name": "tools_^_agentoutputblock_~_value", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [] + }, + { + "id": "5f122699-682a-43de-b45e-2b2933f0f5ad", + "block_id": "d1774756-4d9e-40e6-bab1-47ec0ccd81b2", + "input_default": { + "urls": [], + "enable_web_search": false + }, + "metadata": { + "position": { + "x": 4262.589888165149, + "y": -538.1522431063202 + } + }, + "input_links": [ + { + "id": "50c8dfdf-edd4-4ac0-9859-c4eee9737661", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "5f122699-682a-43de-b45e-2b2933f0f5ad", + "source_name": "tools_^_firecrawlextractblock_~_urls", + "sink_name": "urls", + "is_static": false + }, + { + "id": "43b50d09-91ad-4195-9282-143c5c074b85", + "source_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "sink_id": "5f122699-682a-43de-b45e-2b2933f0f5ad", + "source_name": "tools_^_firecrawlextractblock_~_prompt", + "sink_name": "prompt", + "is_static": false + } + ], + "output_links": [ + { + "id": "5b904c69-fb0c-4bf7-b4c1-4429d5c2f17c", + "source_id": "5f122699-682a-43de-b45e-2b2933f0f5ad", + "sink_id": "94c831ec-ecf0-477c-8d77-45dec19457d5", + "source_name": "data", + "sink_name": "input_message", + "is_static": false + } + ] + }, + { + "id": "e4d24a93-2107-41a2-b853-69b7b3603153", + "block_id": "f0f43e2b-c943-48a0-a7f1-40136ca4d3b9", + "input_default": {}, + "metadata": { + "position": { + "x": 700.7848438430577, + "y": 219.16232116733937 + } + }, + "input_links": [ + { + "id": "0601d9e3-086d-41c6-b2fe-1fe1f7166fd5", + "source_id": "263a6854-5aed-4b9d-9d18-41b25e5002d0", + "sink_id": "e4d24a93-2107-41a2-b853-69b7b3603153", + "source_name": "result", + "sink_name": "url", + "is_static": true + } + ], + "output_links": [ + { + "id": "bdfce016-b3ec-4a81-a343-a5f2c063168d", + "source_id": "e4d24a93-2107-41a2-b853-69b7b3603153", + "sink_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "source_name": "links", + "sink_name": "values_#_SITEMAP_URL_LIST", + "is_static": false + } + ] + }, + { + "id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "block_id": "db7d8f02-2f44-4c55-ab7a-eae0941f0c30", + "input_default": { + "format": "\nDocumentation Base URL: {{DOCUMENTATION_URL}}\nCustomer Question: {{QUESTION}}\nRequired Confidence Threshold: {{CONFIDENCE_THRESHOLD}}%\nAvailable Pages (Sitemap): {{SITEMAP_URL_LIST}}\n\n\n\nContinue searching and extracting information until you raise your confidence level as high as possible. Don't stop until you reach {{CONFIDENCE_THRESHOLD}}% confidence OR exhaust all relevant documentation sources.\n\n\n\nMethod:\n- Start with sitemap analysis from the sitemap url list\n- Use FireCrawl Extract for known specific URLs, FireCrawl Crawl for exploration\n- Keep searching to raise confidence - don't settle for partial answers\n- Extract as much relevant information as possible\n\n\n\nCRITICAL: FireCrawl Extract accepts maximum 10 URLs per request. Be highly selective and choose only the most comprehensive, relevant pages for extraction.\n\n\n\n- Use FireCrawl Crawl for broader exploration when you need to discover relevant content\n- Use FireCrawl Extract for up to 10 most critical URLs when you know exactly what pages contain the answer\n- If you identify more than 10 relevant URLs, prioritize: overview pages > specific subsections > examples\n\n\n\n\n [X]\n \n [Exact text from documentation]\n \n \n [Complete response based solely on documentation findings]\n \n \n [URL1]\n [URL2]\n [URL3]\n...\n \n\n\n\nFind the most comprehensive documentation-based answer for: \"{{QUESTION}}\"\n\nBegin by analyzing the sitemap url list and planning your search strategy to achieve the highest possible confidence level.", + "values": {} + }, + "metadata": { + "position": { + "x": 1366.0592785137596, + "y": 214.32942114785305 + } + }, + "input_links": [ + { + "id": "85507b2c-4eca-4d66-a414-486e65d5382f", + "source_id": "263a6854-5aed-4b9d-9d18-41b25e5002d0", + "sink_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "source_name": "result", + "sink_name": "values_#_DOCUMENTATION_URL", + "is_static": true + }, + { + "id": "bdfce016-b3ec-4a81-a343-a5f2c063168d", + "source_id": "e4d24a93-2107-41a2-b853-69b7b3603153", + "sink_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "source_name": "links", + "sink_name": "values_#_SITEMAP_URL_LIST", + "is_static": false + }, + { + "id": "f96fd53d-c66d-437a-84a4-222abf018bde", + "source_id": "a15a19b5-d771-4e30-bb76-2c368468df23", + "sink_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "source_name": "result", + "sink_name": "values_#_CONFIDENCE_THRESHOLD", + "is_static": true + }, + { + "id": "de329c54-737a-4a44-85ee-44b23ac7f683", + "source_id": "8a0577e3-315a-4bd8-99d9-da082316b729", + "sink_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "source_name": "result", + "sink_name": "values_#_QUESTION", + "is_static": true + } + ], + "output_links": [ + { + "id": "535b347d-fa2d-4461-8ade-f093cf73dde2", + "source_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "sink_id": "8d5f6594-d865-4aa7-8479-7f36b4c083df", + "source_name": "output", + "sink_name": "input", + "is_static": false + } + ] + }, + { + "id": "8d5f6594-d865-4aa7-8479-7f36b4c083df", + "block_id": "1ff065e9-88e8-4358-9d82-8dc91f622ba9", + "input_default": {}, + "metadata": { + "position": { + "x": 2009.3858195835292, + "y": 219.61895555965955 + } + }, + "input_links": [ + { + "id": "535b347d-fa2d-4461-8ade-f093cf73dde2", + "source_id": "12c4366e-81e7-4e65-b2b5-eb5fc8c65230", + "sink_id": "8d5f6594-d865-4aa7-8479-7f36b4c083df", + "source_name": "output", + "sink_name": "input", + "is_static": false + } + ], + "output_links": [ + { + "id": "aa80e27a-4dd3-41b4-9d4a-aab33c0dd88d", + "source_id": "8d5f6594-d865-4aa7-8479-7f36b4c083df", + "sink_id": "29c894cd-e453-4159-b2da-ebbafdaac2fe", + "source_name": "output", + "sink_name": "prompt", + "is_static": true + } + ] + }, + { + "id": "c6b1017c-a82e-401f-ae59-3a36b993a5c1", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Inputs" + }, + "metadata": { + "position": { + "x": -1195.91298968421, + "y": -189.12681492578457 + } + }, + "input_links": [], + "output_links": [] + }, + { + "id": "235155a9-e4f6-4a6d-90df-a3ba5bd31bbc", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Toolbox" + }, + "metadata": { + "position": { + "x": 3629.7459544349654, + "y": -902.1151785811265 + } + }, + "input_links": [], + "output_links": [] + }, + { + "id": "57e269dc-75d9-46cc-85be-85e693759c94", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Core: Smart Decision Maker and prompt" + }, + "metadata": { + "position": { + "x": 1361.3560589479616, + "y": -181.6344386113369 + } + }, + "input_links": [], + "output_links": [] + }, + { + "id": "68c9962e-c3b6-4483-a262-08fb93348698", + "block_id": 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The workspace ID is the string that starts with \"wsp\" in the URL (for example,\u00a0https://airtable.com/workspaces/wspsqMNxxxxxxxxxxxxx). 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"open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "gpt-4.1-2025-04-14", + "gpt-5-2025-08-07" + ] + }, + "airtable_api_key-oauth2_credentials": { + "credentials_provider": [ + "airtable" + ], + "credentials_types": [ + "api_key", + "oauth2" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "airtable", + "title": "Provider", + "type": "string" + }, + "type": { + "enum": [ + "api_key", + "oauth2" + ], + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key', 'oauth2']]", + "type": "object", + "discriminator_values": [] + }, + "anthropic_api_key_credentials": { + "credentials_provider": [ + "anthropic" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "anthropic", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + 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"open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "claude-sonnet-4-20250514" + ] + }, + "firecrawl_api_key_credentials": { + "credentials_provider": [ + "firecrawl" + ], + "credentials_types": [ + "api_key" + ], + 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"created_at": "2024-12-20T16:34:24.107Z", + "input_schema": { + "type": "object", + "properties": { + "Search Query": { + "advanced": false, + "secret": false, + "title": "Search Query", + "default": "Auto_GPT" + }, + "Number of Videos": { + "advanced": false, + "secret": false, + "title": "Number of Videos", + "description": "The number of videos to collect the transcripts of", + "default": "3" + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "Transcripts": { + "advanced": false, + "secret": false, + "title": "Transcripts" + } + }, + "required": [ + "Transcripts" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "jina_api_key_credentials": { + "credentials_provider": [ + "jina" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "jina", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + }, + "webshare_proxy_user_password_credentials": { + "credentials_provider": [ + "webshare_proxy" + ], + "credentials_types": [ + "user_password" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "webshare_proxy", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "user_password", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['user_password']]", + "type": "object", + "discriminator_values": [] + }, + "anthropic_api_key_credentials": { + "credentials_provider": [ + "anthropic" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "anthropic", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", 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"title": "YouTubeTranscriptionScraperCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_d85882b8-633f-44ce-a315-c20a8c123d19.json b/autogpt_platform/backend/agents/agent_d85882b8-633f-44ce-a315-c20a8c123d19.json new file mode 100644 index 0000000000..144ecf8e94 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_d85882b8-633f-44ce-a315-c20a8c123d19.json @@ -0,0 +1,403 @@ +{ + "id": "ed2091cf-5b27-45a9-b3ea-42396f95b256", + "version": 12, + "is_active": true, + "name": "Flux AI Image Generator", + "description": "Transform ideas into breathtaking images with this AI-powered Image Generator. Using cutting-edge Flux AI technology, the tool crafts highly detailed, photorealistic visuals from simple text prompts. Perfect for artists, marketers, and content creators, this generator produces unique images tailored to user specifications. From fantastical scenes to lifelike portraits, users can unleash creativity with professional-quality results in seconds. Easy to use and endlessly versatile, bring imagination to life with the AI Image Generator today!", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "7482c59d-725f-4686-82b9-0dfdc4e92316", + "block_id": "cc10ff7b-7753-4ff2-9af6-9399b1a7eddc", + "input_default": { + "text": "Press the \"Advanced\" toggle and input your replicate API key.\n\nYou can get one here:\nhttps://replicate.com/account/api-tokens\n" + }, + "metadata": { + "position": { + "x": 872.8268131538296, + "y": 614.9436919065381 + } + }, + "input_links": [], + "output_links": [], + "graph_id": "ed2091cf-5b27-45a9-b3ea-42396f95b256", + "graph_version": 12, + "webhook_id": null, + "webhook": null + }, + { + "id": "0d1dec1a-e4ee-4349-9673-449a01bbf14e", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Generated Image" + }, + "metadata": { + "position": { + "x": 1453.6844137728922, + "y": 963.2466395125115 + } + }, + "input_links": [ + { + "id": "06665d23-2f3d-4445-8f22-573446fcff5b", + "source_id": "50bc23e9-f2b7-4959-8710-99679ed9eeea", + "sink_id": "0d1dec1a-e4ee-4349-9673-449a01bbf14e", + "source_name": "result", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "ed2091cf-5b27-45a9-b3ea-42396f95b256", + "graph_version": 12, + "webhook_id": null, + "webhook": null + }, + { + "id": "6f24c45f-1548-4eda-9784-da06ce0abef8", + "block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b", + "input_default": { + "name": "Image Subject", + "value": "Otto the friendly, purple \"Chief Automation Octopus\" helping people automate their tedious tasks.", + "description": "The subject of the image" + }, + "metadata": { + "position": { + "x": -314.43009631839783, + "y": 962.935949165938 + } + }, + "input_links": [], + "output_links": [ + { + "id": "1077c61a-a32a-4ed7-becf-11bcf835b914", + "source_id": "6f24c45f-1548-4eda-9784-da06ce0abef8", + "sink_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12", + "source_name": "result", + "sink_name": "prompt_values_#_TOPIC", + "is_static": true + } + ], + "graph_id": "ed2091cf-5b27-45a9-b3ea-42396f95b256", + "graph_version": 12, + "webhook_id": null, + "webhook": null + }, + { + "id": "50bc23e9-f2b7-4959-8710-99679ed9eeea", + "block_id": "90f8c45e-e983-4644-aa0b-b4ebe2f531bc", + "input_default": { + "prompt": "dog", + "output_format": "png", + "replicate_model_name": "Flux Pro 1.1" + }, + "metadata": { + "position": { + "x": 873.0119949791526, + "y": 966.1604399052493 + } + }, + "input_links": [ + { + "id": "a17ec505-9377-4700-8fe0-124ca81d43a9", + "source_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12", + "sink_id": "50bc23e9-f2b7-4959-8710-99679ed9eeea", + "source_name": "response", + "sink_name": "prompt", + "is_static": false + } + ], + "output_links": [ + { + "id": "06665d23-2f3d-4445-8f22-573446fcff5b", + "source_id": "50bc23e9-f2b7-4959-8710-99679ed9eeea", + "sink_id": "0d1dec1a-e4ee-4349-9673-449a01bbf14e", + "source_name": "result", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "ed2091cf-5b27-45a9-b3ea-42396f95b256", + "graph_version": 12, + "webhook_id": null, + "webhook": null + }, + { + "id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-4o-mini", + "prompt": "Generate an incredibly detailed, photorealistic image prompt about {{TOPIC}}, describing the camera it's taken with and prompting the diffusion model to use all the best quality techniques.\n\nOutput only the prompt with no additional commentary.", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 277.3057034159709, + "y": 962.8382498113764 + } + }, + "input_links": [ + { + "id": "1077c61a-a32a-4ed7-becf-11bcf835b914", + "source_id": "6f24c45f-1548-4eda-9784-da06ce0abef8", + "sink_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12", + "source_name": "result", + "sink_name": "prompt_values_#_TOPIC", + "is_static": true + } + ], + "output_links": [ + { + "id": "a17ec505-9377-4700-8fe0-124ca81d43a9", + "source_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12", + "sink_id": "50bc23e9-f2b7-4959-8710-99679ed9eeea", + "source_name": "response", + "sink_name": "prompt", + "is_static": false + } + ], + "graph_id": "ed2091cf-5b27-45a9-b3ea-42396f95b256", + "graph_version": 12, + "webhook_id": null, + "webhook": null + } + ], + "links": [ + { + "id": "1077c61a-a32a-4ed7-becf-11bcf835b914", + "source_id": "6f24c45f-1548-4eda-9784-da06ce0abef8", + "sink_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12", + "source_name": "result", + "sink_name": "prompt_values_#_TOPIC", + "is_static": true + }, + { + "id": "06665d23-2f3d-4445-8f22-573446fcff5b", + "source_id": "50bc23e9-f2b7-4959-8710-99679ed9eeea", + "sink_id": "0d1dec1a-e4ee-4349-9673-449a01bbf14e", + "source_name": "result", + "sink_name": "value", + "is_static": false + }, + { + "id": "a17ec505-9377-4700-8fe0-124ca81d43a9", + "source_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12", + "sink_id": "50bc23e9-f2b7-4959-8710-99679ed9eeea", + "source_name": "response", + "sink_name": "prompt", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "sub_graphs": [], + "user_id": "", + "created_at": "2024-12-20T18:46:11.492Z", + "input_schema": { + "type": "object", + "properties": { + "Image Subject": { + "advanced": false, + "secret": false, + "title": "Image Subject", + "description": "The subject of the image", + "default": "Otto the friendly, purple \"Chief Automation Octopus\" helping people automate their tedious tasks." + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "Generated Image": { + "advanced": false, + "secret": false, + "title": "Generated Image" + } + }, + "required": [ + "Generated Image" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "replicate_api_key_credentials": { + "credentials_provider": [ + "replicate" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "replicate", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + }, + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "gpt-4o-mini" + ] + } + }, + "required": [ + "replicate_api_key_credentials", + "openai_api_key_credentials" + ], + "title": "FluxAIImageGeneratorCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_e437cc95-e671-489d-b915-76561fba8c7f.json b/autogpt_platform/backend/agents/agent_e437cc95-e671-489d-b915-76561fba8c7f.json new file mode 100644 index 0000000000..b3b29da570 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_e437cc95-e671-489d-b915-76561fba8c7f.json @@ -0,0 +1,1064 @@ +{ + "id": "1f14dce1-9cbd-4c96-aeaf-630675ef3a6e", + "version": 17, + "is_active": true, + "name": "AI YouTube-to-Blog Converter", + "description": "Effortlessly turn YouTube videos into high-quality, SEO-optimized blog posts with this innovative AI YouTube-to-Blog Converter. Perfect for content creators, marketers, and bloggers, this tool analyses video content and generates well-structured articles tailored to your specifications. Simply input a YouTube URL, set your desired tone and word count, and let the AI work its magic. The converter extracts key points, maintains the original message, and enhances readability for a text audience. With options for casual, professional, educational, or formal tones, it adapts to various niches and target readers. Featuring smart SEO optimization, engaging titles, and clear subheadings, this tool helps repurpose video content into shareable, search-engine-friendly blog posts. Expand your content strategy and reach a wider audience by transforming your YouTube videos into compelling written content with the AI YouTube-to-Blog Converter.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "7f37f7a6-6fb9-4c8b-9992-0638abfd7919", + "block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b", + "input_default": { + "name": "YouTube URL", + "title": null, + "value": "https://www.youtube.com/watch?v=J1Mzd1ZeSaU", + "secret": false, + "advanced": false, + "description": "Enter the URL of the YouTube video you want to convert to a blog post", + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -1083.525390625, + "y": -72.1875 + } + }, + "input_links": [], + "output_links": [ + { + "id": "7548d09d-7ac9-4c3a-901e-f29a2e24e729", + "source_id": "7f37f7a6-6fb9-4c8b-9992-0638abfd7919", + "sink_id": "9fa16df6-d785-4b0a-9f58-7f42544d5cdf", + "source_name": "result", + "sink_name": "youtube_url", + "is_static": true + } + ], + "graph_id": "1f14dce1-9cbd-4c96-aeaf-630675ef3a6e", + "graph_version": 17, + "webhook_id": null, + "webhook": null + }, + { + "id": "13013c6b-505c-408f-aa30-d43a4e0b4309", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Blog Post", + "title": null, + "value": null, + "format": "", + "secret": false, + "advanced": false, + "description": "The main body of the newly written blog post." + }, + "metadata": { + "position": { + "x": 3771.885044160941, + "y": -19.86303750155819 + } + }, + "input_links": [ + { + "id": "0f89a6e6-d2c4-484f-92de-abcec1f6ecbb", + "source_id": "ef4553a0-4e84-45f1-b972-f6e7123d68e7", + "sink_id": "13013c6b-505c-408f-aa30-d43a4e0b4309", + "source_name": "output", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "1f14dce1-9cbd-4c96-aeaf-630675ef3a6e", + "graph_version": 17, + "webhook_id": null, + "webhook": null + }, + { + "id": "96280d45-4bdd-4610-958b-054775e77108", + "block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b", + "input_default": { + "name": "Blog Tone", + "title": null, + "value": "Educational", + "secret": false, + "advanced": false, + "description": "Select the desired tone for the blog post", + "placeholder_values": [ + "Professional", + "Casual", + "Educational", + "Conversational", + "Formal" + ] + }, + "metadata": { + "position": { + "x": -526.960448013501, + "y": 1230.0347965176616 + } + }, + "input_links": [], + "output_links": [ + { + "id": "fa2f1f6a-4798-4e75-aede-44cc1d423f2b", + "source_id": "96280d45-4bdd-4610-958b-054775e77108", + "sink_id": "2b85cb39-9cfc-411c-a9fb-a3af03df9e00", + "source_name": "result", + "sink_name": "prompt_values_#_TONE", + "is_static": true + } + ], + "graph_id": "1f14dce1-9cbd-4c96-aeaf-630675ef3a6e", + "graph_version": 17, + "webhook_id": null, + "webhook": null + }, + { + "id": "9fa16df6-d785-4b0a-9f58-7f42544d5cdf", + "block_id": "f3a8f7e1-4b1d-4e5f-9f2a-7c3d5a2e6b4c", + "input_default": {}, + "metadata": { + "position": { + "x": -521.103515625, + "y": -69.931640625 + } + }, + "input_links": [ + { + "id": "7548d09d-7ac9-4c3a-901e-f29a2e24e729", + "source_id": "7f37f7a6-6fb9-4c8b-9992-0638abfd7919", + "sink_id": "9fa16df6-d785-4b0a-9f58-7f42544d5cdf", + "source_name": "result", + "sink_name": "youtube_url", + "is_static": true + } + ], + "output_links": [ + { + "id": "223f88a6-4d00-4fbf-93b1-e6d3b005e46a", + "source_id": "9fa16df6-d785-4b0a-9f58-7f42544d5cdf", + "sink_id": "c8e51364-ecad-407f-b4e5-9f5496744285", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "cda30ed3-c4bb-429b-ac45-641606b75959", + "source_id": "9fa16df6-d785-4b0a-9f58-7f42544d5cdf", + "sink_id": "1806c84c-2ff2-4045-9fc7-12b5be4086ab", + "source_name": "transcript", + "sink_name": "prompt_values_#_TRANSCRIPT", + "is_static": false + } + ], + "graph_id": "1f14dce1-9cbd-4c96-aeaf-630675ef3a6e", + "graph_version": 17, + "webhook_id": null, + "webhook": null + }, + { + "id": "abad3718-38d8-4b54-8383-565b6bb0b8d2", + "block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b", + "input_default": { + "name": "Blog Length", + "title": null, + "value": "4000", + "secret": false, + "advanced": false, + "description": "Enter the desired word count for the blog post", + "placeholder_values": [] + }, + "metadata": { + "position": { + "x": -1090.8784904050794, + "y": 1225.5455600527607 + } + }, + "input_links": [], + "output_links": [ + { + "id": "9c0078a5-d586-43a6-b893-23cc246fba63", + "source_id": "abad3718-38d8-4b54-8383-565b6bb0b8d2", + "sink_id": "2b85cb39-9cfc-411c-a9fb-a3af03df9e00", + "source_name": "result", + "sink_name": "prompt_values_#_WORD_COUNT", + "is_static": true + } + ], + "graph_id": "1f14dce1-9cbd-4c96-aeaf-630675ef3a6e", + "graph_version": 17, + "webhook_id": null, + "webhook": null + }, + { + "id": "1806c84c-2ff2-4045-9fc7-12b5be4086ab", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-4o", + "retry": 3, + "prompt": "You are an expert content analyst tasked with extracting comprehensive information from a video transcript. Your goal is to provide a detailed analysis and summary of the transcript, ensuring no important details are lost.\n\nHere is the video transcript you need to analyze:\n\n\n{{TRANSCRIPT}}\n\n\nPlease follow these steps to analyze the transcript:\n\n1. Carefully read the entire transcript.\n2. Identify potential mistranscriptions and infer the most likely correct words based on context.\n3. Extract the main topics discussed in the video.\n4. For each main topic, identify all relevant key points and supporting details.\n5. Analyze the overall structure and flow of the content.\n6. Compile a comprehensive summary of all the information extracted from the transcript.\n\nBefore providing your final output, wrap your analysis inside tags. Include the following:\n\n1. List potential mistranscriptions and their likely corrections, quoting the original text.\n2. Identify and quote key phrases for each main topic.\n3. Outline the content structure by noting transitions between topics.\n4. Explain your reasoning for extracting main topics and analyzing the content structure.\n\nAfter your analysis, present your findings in the following format, enclosed in tags:\n\n1. Main Topics: List all main topics discussed in the video.\n2. Detailed Breakdown: For each main topic, provide:\n a. A brief description of the topic\n b. All key points related to the topic\n c. Any supporting details or examples mentioned\n3. Content Structure: Describe the overall structure and flow of the video content.\n4. Comprehensive Summary: Provide a detailed summary that captures all significant information from the transcript.\n\nExample output structure (replace with actual content):\n\n\n1. Main Topics:\n - Topic A\n - Topic B\n - Topic C\n\n2. Detailed Breakdown:\n Topic A:\n a. Description: [Brief description of Topic A]\n b. Key points:\n - Point 1\n - Point 2\n c. Supporting details:\n - Detail 1\n - Detail 2\n\n [Repeat for Topics B and C]\n\n3. Content Structure:\n [Description of overall structure and flow]\n\n4. Comprehensive Summary:\n [Detailed summary of all significant information]\n\n\nRemember, the goal is to extract and present as much valuable information as possible from the transcript, ensuring no important details are lost. 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+ "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "018b486e-8d8e-499b-902e-58466d444034", + "source_id": "ffdcd234-9c01-4576-8768-b1f092f4b3bb", + "sink_id": "3c3b6d76-54de-4b89-8022-c9ef7ca34b86", + "source_name": "parsed_xml", + "sink_name": "input", + "is_static": false + }, + { + "id": "b2609fad-e411-47cc-89e2-6991edc373ec", + "source_id": "b6786db8-d6aa-42de-9d19-515d5e7d9fc6", + "sink_id": "30772e58-9ffe-4b02-a1c8-1e7f5f395a02", + "source_name": "output", + "sink_name": "value", + "is_static": false + }, + { + "id": "8b062f6a-baa4-495b-ba1e-1bfc8824b3a1", + "source_id": "1806c84c-2ff2-4045-9fc7-12b5be4086ab", + "sink_id": "c8e51364-ecad-407f-b4e5-9f5496744285", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "678226df-d4f0-440b-841e-493be3b57df8", + "source_id": "ef4553a0-4e84-45f1-b972-f6e7123d68e7", + "sink_id": "c8e51364-ecad-407f-b4e5-9f5496744285", + "source_name": "missing", + "sink_name": "value", + "is_static": false + }, + { + "id": "c0972c6b-b63f-4f20-a952-f72cdd518fbe", + "source_id": "3c3b6d76-54de-4b89-8022-c9ef7ca34b86", + "sink_id": "8fabda6c-b71f-479b-a729-14f2c97c8430", + "source_name": "output", + "sink_name": "value", + "is_static": false + }, + { + "id": "fa2f1f6a-4798-4e75-aede-44cc1d423f2b", + "source_id": "96280d45-4bdd-4610-958b-054775e77108", + "sink_id": "2b85cb39-9cfc-411c-a9fb-a3af03df9e00", + "source_name": "result", + "sink_name": "prompt_values_#_TONE", + "is_static": true + }, + { + "id": "02e273fe-df05-471a-935e-991f4ab4a65e", + "source_id": "3c3b6d76-54de-4b89-8022-c9ef7ca34b86", + "sink_id": "c8e51364-ecad-407f-b4e5-9f5496744285", + "source_name": "missing", + "sink_name": "value", + "is_static": false + }, + { + "id": "223f88a6-4d00-4fbf-93b1-e6d3b005e46a", + "source_id": "9fa16df6-d785-4b0a-9f58-7f42544d5cdf", + "sink_id": "c8e51364-ecad-407f-b4e5-9f5496744285", + "source_name": "error", + "sink_name": "value", + "is_static": false + }, + { + "id": "cda30ed3-c4bb-429b-ac45-641606b75959", + "source_id": "9fa16df6-d785-4b0a-9f58-7f42544d5cdf", + "sink_id": "1806c84c-2ff2-4045-9fc7-12b5be4086ab", + "source_name": "transcript", + "sink_name": "prompt_values_#_TRANSCRIPT", + "is_static": false + }, + { + "id": "5fbdce15-1141-49e4-a3be-243fdc3c81da", + "source_id": "2b85cb39-9cfc-411c-a9fb-a3af03df9e00", + "sink_id": "ffdcd234-9c01-4576-8768-b1f092f4b3bb", + "source_name": "response", + "sink_name": "input_xml", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "sub_graphs": [], + "user_id": "", + "created_at": "2025-04-20T11:23:11.671Z", + "input_schema": { + "type": "object", + "properties": { + "YouTube URL": { + "advanced": false, + "secret": false, + "title": "YouTube URL", + "description": "Enter the URL of the YouTube video you want to convert to a blog post", + "default": "https://www.youtube.com/watch?v=J1Mzd1ZeSaU" + }, + "Blog Tone": { + "advanced": false, + "secret": false, + "title": "Blog Tone", + "enum": [ + "Professional", + "Casual", + "Educational", + "Conversational", + "Formal" + ], + "description": "Select the desired tone for the blog post", + "default": "Educational" + }, + "Blog Length": { + "advanced": false, + "secret": false, + "title": "Blog Length", + "description": "Enter the desired word count for the blog post", + "default": "4000" + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "Blog Post": { + "advanced": false, + "secret": false, + "title": "Blog Post", + "description": "The main body of the newly written blog post." + }, + "Error": { + "advanced": false, + "secret": false, + "title": "Error" + }, + "Title": { + "advanced": false, + "secret": false, + "title": "Title", + "description": "The title of the blog post." + }, + "Target Keywords": { + "advanced": false, + "secret": false, + "title": "Target Keywords", + "description": "Target keywords used in the blog post." + } + }, + "required": [ + "Blog Post", + "Error", + "Title", + "Target Keywords" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "webshare_proxy_user_password_credentials": { + "credentials_provider": [ + "webshare_proxy" + ], + "credentials_types": [ + "user_password" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "webshare_proxy", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "user_password", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['user_password']]", + "type": "object", + "discriminator_values": [] + }, + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "gpt-4o", + "o1" + ] + } + }, + "required": [ + "webshare_proxy_user_password_credentials", + "openai_api_key_credentials" + ], + "title": "AIYouTube-to-BlogConverterCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_e7bb29a1-23c7-4fee-aa3b-5426174b8c52.json b/autogpt_platform/backend/agents/agent_e7bb29a1-23c7-4fee-aa3b-5426174b8c52.json new file mode 100644 index 0000000000..96ef0335ce --- /dev/null +++ b/autogpt_platform/backend/agents/agent_e7bb29a1-23c7-4fee-aa3b-5426174b8c52.json @@ -0,0 +1,1094 @@ +{ + "id": "1d79c52b-0daa-4bc9-9de1-08d9986db033", + "version": 51, + "is_active": true, + "name": "YouTube to LinkedIn Post Converter", + "description": "Seamlessly convert YouTube videos into compelling LinkedIn posts with this innovative AI-powered tool. Perfect for content creators, marketers, and professionals looking to repurpose video content for their LinkedIn network. Simply input a YouTube URL, select your preferred post structure, content focus, and tone, and let the AI work its magic. This versatile converter analyses video transcripts, extracts key insights, and crafts tailored LinkedIn posts that resonate with your professional audience. Choose from various post styles like personal achievements, lessons learned, thought leadership, or curated content. Customize your message with options for inspirational, conversational, or analytical tones. The tool ensures your post captures the essence of the video while optimizing for LinkedIn's format and engagement best practices. 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"result", + "sink_name": "youtube_url", + "is_static": true + }, + { + "id": "2274a7dc-ff54-4de7-aae0-409cb54d88da", + "source_id": "5b5fbcbc-c3c9-405a-88d2-5af6f0572f0f", + "sink_id": "04eab06b-dfa6-4ae3-bff3-dfd956537239", + "source_name": "output", + "sink_name": "prompt", + "is_static": false + }, + { + "id": "50edde5d-e0f7-4daf-b7b0-ffa68837a253", + "source_id": "19d45e40-f7d6-48e8-a740-cc832dd1d330", + "sink_id": "804f744e-b2ca-4730-9ed4-0a63a59eb809", + "source_name": "output", + "sink_name": "prompt", + "is_static": false + }, + { + "id": "6e5a3deb-2d67-4eed-93a7-bb2ab105a0de", + "source_id": "343cce54-6cb6-49e0-847d-a5e664ba91b2", + "sink_id": "36dc1854-65f5-4b28-8146-ede4ffc6f0c0", + "source_name": "transcript", + "sink_name": "prompt", + "is_static": false + }, + { + "id": "50771fc3-c5d0-4b9c-8ed1-7fb2d098b665", + "source_id": "343cce54-6cb6-49e0-847d-a5e664ba91b2", + "sink_id": "5b5fbcbc-c3c9-405a-88d2-5af6f0572f0f", + "source_name": "transcript", + "sink_name": "values_#_upload_transcript", + "is_static": false + }, + { + "id": "817be9fc-3ba9-48f0-8e95-43243bf659d1", + "source_id": "e236e485-3488-46d2-b2fd-b7d6453c7000", + "sink_id": "1400eee9-a2d9-420a-ab66-9470e1b76470", + "source_name": "result", + "sink_name": "values_#_post_type", + "is_static": true + }, + { + "id": "f2bf9eb0-815b-4dc3-b498-9a0f9f2c27ba", + "source_id": "804f744e-b2ca-4730-9ed4-0a63a59eb809", + "sink_id": "5b5fbcbc-c3c9-405a-88d2-5af6f0572f0f", + "source_name": "response", + "sink_name": "values_#_writing_style_description", + "is_static": false + }, + { + "id": "bd89a482-38e4-44b7-b783-009e8d10b287", + "source_id": "04eab06b-dfa6-4ae3-bff3-dfd956537239", + "sink_id": "4d4971f7-5ff0-4695-a4e8-a048e4b38a0e", + "source_name": "response", + "sink_name": "value", + "is_static": false + }, + { + "id": "c6f52852-fc1a-42c0-bc56-e20e69ecac41", + "source_id": "41fea0d5-2cb8-4149-93d6-488ceb673cb1", + "sink_id": "5b5fbcbc-c3c9-405a-88d2-5af6f0572f0f", + "source_name": "result", + "sink_name": "values_#_linkedin_post_style", + "is_static": true + }, + { + "id": "7d8cb205-8c1b-4d07-827d-801da8ef7ffc", + "source_id": "36dc1854-65f5-4b28-8146-ede4ffc6f0c0", + "sink_id": "5b5fbcbc-c3c9-405a-88d2-5af6f0572f0f", + "source_name": "response", + "sink_name": "values_#_content_analysis", + "is_static": false + }, + { + "id": "dc77df0f-23db-4ea5-a2c4-ede925057953", + "source_id": "54b1767c-e70f-4130-8e1b-682ac9f0b50e", + "sink_id": "5b5fbcbc-c3c9-405a-88d2-5af6f0572f0f", + "source_name": "result", + "sink_name": "values_#_writing_style", + "is_static": true + }, + { + "id": "da96e08e-e297-42e9-a0f7-7a386746bff9", + "source_id": "0424732b-b2e9-48a0-bd0d-a4a8c1704c5c", + "sink_id": "5b5fbcbc-c3c9-405a-88d2-5af6f0572f0f", + "source_name": "response", + "sink_name": "values_#_linkedin_post_style_guide", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "sub_graphs": [], + "user_id": "", + "created_at": "2025-04-25T04:55:41.897Z", + "input_schema": { + "type": "object", + "properties": { + "Structure: How do you want to present your LinkedIn Post?": { + "advanced": false, + "secret": false, + "title": "Structure: How do you want to present your LinkedIn Post?", + "enum": [ + "Personal Achievement Story", + "Lesson Learned", + "Thought Leadership", + "Question or Poll", + "Curated Content" + ], + "description": "The *format or structure* in which you present your content. It's about *how* you package your message to make it engaging and accessible.", + "default": "Curated Content" + }, + "Content: What is the main idea or message you want to convey.": { + "advanced": false, + "secret": false, + "title": "Content: What is the main idea or message you want to convey.", + "enum": [ + "Hot Take", + "Key Takeaways", + "Thought Leadership", + "Discussion Starter", + "Recommendation", + "Controversial Opinion" + ], + "description": "The main message or purpose of your post\u2014the core idea or topic you want to convey to your audience.", + "default": "Recommendation" + }, + "Tone: How do you want to express yourself in your post?": { + "advanced": false, + "secret": false, + "title": "Tone: How do you want to express yourself in your post?", + "enum": [ + "Conversational", + "Storytelling", + "Analytical", + "Inspirational", + "Direct and No-Nonsense" + ], + "description": "Focuses on the tone, voice, and language used in your post\u2014the manner in which you express your ideas. It's about the way you communicate.", + "default": "Inspirational" + }, + "Source YouTube Video": { + "advanced": false, + "anyOf": [ + { + "format": "short-text", + "type": "string" + }, + { + "type": "null" + } + ], + "secret": false, + "title": "Source YouTube Video", + "description": "Add the URL of the YouTube video you want to write a LinkedIn Post about.", + "default": "https://www.youtube.com/watch?v=KWonAsyKF3g" + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "LinkedIn Post": { + "advanced": false, + "secret": false, + "title": "LinkedIn Post" + } + }, + "required": [ + "LinkedIn Post" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "webshare_proxy_user_password_credentials": { + "credentials_provider": [ + "webshare_proxy" + ], + "credentials_types": [ + "user_password" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "webshare_proxy", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "user_password", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['user_password']]", + "type": "object", + "discriminator_values": [] + }, + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "gpt-4o" + ] + }, + "anthropic_api_key_credentials": { + "credentials_provider": [ + "anthropic" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "anthropic", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "claude-sonnet-4-5-20250929" + ] + } + }, + "required": [ + "webshare_proxy_user_password_credentials", + "openai_api_key_credentials", + "anthropic_api_key_credentials" + ], + "title": "YouTubetoLinkedInPostConverterCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_eafa21d3-bf14-4f63-a97f-a5ee41df83b3.json b/autogpt_platform/backend/agents/agent_eafa21d3-bf14-4f63-a97f-a5ee41df83b3.json new file mode 100644 index 0000000000..f8df8d7989 --- /dev/null +++ b/autogpt_platform/backend/agents/agent_eafa21d3-bf14-4f63-a97f-a5ee41df83b3.json @@ -0,0 +1,1560 @@ +{ + "id": "9afd017f-565f-4090-b5df-d01bc4094292", + "version": 16, + "is_active": false, + "name": "LinkedIn Post Generator", + "description": "Convert YouTube transcripts into polished LinkedIn posts with custom style, tone, and length options. Optimized for maximum engagement.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "a6567a56-c74b-4fd4-b640-9a9fc09f1b3e", + "block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b", + "input_default": { + "name": "Style", + "title": null, + "value": "Persuasive", + "secret": false, + "advanced": false, + "description": "Specifies the overall writing style of the blog post. 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"464d3fe5-33e8-47bd-b196-e7d0adcd582c", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "result", + "sink_name": "prompt_values_#_TONE", + "is_static": true + }, + { + "id": "051f1e02-0bfa-436f-bab3-91489a6aa9a5", + "source_id": "49998ca9-0549-4198-98f6-a9ae39907c4b", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "value", + "sink_name": "prompt_values_#_TRANSCRIPTS", + "is_static": false + } + ], + "output_links": [ + { + "id": "3531f653-5cb2-4107-9522-d9aaebd9d333", + "source_id": "95cbf9be-59cb-4240-aead-e537af599976", + "sink_id": "67d559a9-89ca-4f1c-888b-7d5e4b934824", + "source_name": "response", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "9afd017f-565f-4090-b5df-d01bc4094292", + "graph_version": 16, + "webhook_id": null, + "webhook": null + } + ], + "links": [ + { + "id": "02035f8b-3b5c-491f-a192-4030a1c05f86", + "source_id": "32d9fa39-50c4-4727-b96b-03e88f8ab26b", + "sink_id": "7278c40d-aecf-4677-852a-b4f69db2e927", + "source_name": "list_item", + "sink_name": "youtube_url", + "is_static": false + }, + { + "id": "fbc76ac7-75c1-4ee0-8cc3-3581f549bd59", + "source_id": "a6567a56-c74b-4fd4-b640-9a9fc09f1b3e", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "result", + "sink_name": "prompt_values_#_STYLE", + "is_static": true + }, + { + "id": "f505026b-2026-4bc1-b3c4-fb991cea03ea", + "source_id": "b527d6c7-2dce-4c0b-997b-017dc078ed91", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "result", + "sink_name": "prompt_values_#_OPINION", + "is_static": true + }, + { + "id": "31b1f11d-ecff-4d0b-b55c-5cd5f59ea1d6", + "source_id": "7278c40d-aecf-4677-852a-b4f69db2e927", + "sink_id": "c0d0d5d5-221b-4ce7-911b-09e40442fd82", + "source_name": "transcript", + "sink_name": "entry", + "is_static": false + }, + { + "id": "94b3e4e7-02fd-4c24-aa70-7a0d64cc83e2", + "source_id": "f0f83bf3-4c5a-4a69-a795-84916a9d02c0", + "sink_id": "c0d0d5d5-221b-4ce7-911b-09e40442fd82", + "source_name": "updated_list", + "sink_name": "list", + "is_static": false + }, + { + "id": "aedc1c04-41fc-4ddc-a498-2180e04448d0", + "source_id": "32d9fa39-50c4-4727-b96b-03e88f8ab26b", + "sink_id": "bffd38ad-4c3c-4f37-b3ea-9d1788e527b8", + "source_name": "generated_list", + "sink_name": "collection", + "is_static": false + }, + { + "id": "47d0bc20-ae7d-4082-9a1d-9d42d5229d85", + "source_id": "8f9d7438-bfdf-44a0-8e07-116143247616", + "sink_id": "32d9fa39-50c4-4727-b96b-03e88f8ab26b", + "source_name": "output", + "sink_name": "focus", + "is_static": false + }, + { + "id": "a58d1e78-2548-47e0-990c-8f7cae2bdbcf", + "source_id": "c0d0d5d5-221b-4ce7-911b-09e40442fd82", + "sink_id": "b10632a5-b59a-4240-a6e5-c8adeabaa784", + "source_name": "updated_list", + "sink_name": "collection", + "is_static": false + }, + { + "id": "85629334-5e62-42ea-9184-c60e4a89b2fd", + "source_id": "aaeee594-70f9-4bc3-a9a8-b2951e0809e2", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "result", + "sink_name": "prompt_values_#_MIN_WORD_COUNT", + "is_static": true + }, + { + "id": "ff4e71a9-2e2d-4d58-ae81-441756b67e22", + "source_id": "727df6b8-7208-4137-a7e4-c17d2bc2cea1", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "result", + "sink_name": "prompt_values_#_OBJECTIVE", + "is_static": true + }, + { + "id": "a3e3dcac-b431-4b04-858d-ec9be1e3a027", + "source_id": "7cc813d0-574c-4e72-ad89-2d9869c2b8b6", + "sink_id": "7032ccd7-3e7a-4d27-952e-53ccb7ef0994", + "source_name": "result", + "sink_name": "values_#_QUERY", + "is_static": true + }, + { + "id": "af84836d-c9de-46ea-8d1a-07400d6e5dfe", + "source_id": "c0d0d5d5-221b-4ce7-911b-09e40442fd82", + "sink_id": "87506078-97fc-4591-bb19-1e4a95af72a8", + "source_name": "updated_list", + "sink_name": "yes_value", + "is_static": false + }, + { + "id": "9c1f7321-f3b7-428e-8767-fdc717f72597", + "source_id": "464d3fe5-33e8-47bd-b196-e7d0adcd582c", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "result", + "sink_name": "prompt_values_#_TONE", + "is_static": true + }, + { + "id": "04bd40a3-52a6-4b2b-93fe-5685066ffeb1", + "source_id": "bffd38ad-4c3c-4f37-b3ea-9d1788e527b8", + "sink_id": "dad79a25-9633-4b61-ad6b-344b3d7f4d1c", + "source_name": "count", + "sink_name": "input", + "is_static": false + }, + { + "id": "f752040c-a0f3-4fe0-9e9e-65da9cff67a4", + "source_id": "eeb6298f-9559-4422-8641-a2841492dbf0", + "sink_id": "32d9fa39-50c4-4727-b96b-03e88f8ab26b", + "source_name": "content", + "sink_name": "source_data", + "is_static": false + }, + { + "id": "b336b185-bb36-41ec-9464-5e80263087a2", + "source_id": "7cc813d0-574c-4e72-ad89-2d9869c2b8b6", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "result", + "sink_name": "prompt_values_#_TOPIC", + "is_static": true + }, + { + "id": "abc225ed-e1d3-462c-bcc0-88a14d17dd03", + "source_id": "287df4a8-2bf9-4cbf-a32f-dca95aeca0e7", + "sink_id": "8f9d7438-bfdf-44a0-8e07-116143247616", + "source_name": "result", + "sink_name": "values_#_NUMBER", + "is_static": true + }, + { + "id": "bb434ddb-3d01-4969-bdf9-e1d983628b9c", + "source_id": "7032ccd7-3e7a-4d27-952e-53ccb7ef0994", + "sink_id": "eeb6298f-9559-4422-8641-a2841492dbf0", + "source_name": "output", + "sink_name": "url", + "is_static": false + }, + { + "id": "3e931141-56e9-4904-b70a-0ad36415e7be", + "source_id": "bffd38ad-4c3c-4f37-b3ea-9d1788e527b8", + "sink_id": "dad79a25-9633-4b61-ad6b-344b3d7f4d1c", + "source_name": "count", + "sink_name": "data", + "is_static": false + }, + { + "id": "64a031c6-d680-4cf9-adae-4374e19bd5f4", + "source_id": "b10632a5-b59a-4240-a6e5-c8adeabaa784", + "sink_id": "87506078-97fc-4591-bb19-1e4a95af72a8", + "source_name": "count", + "sink_name": "value1", + "is_static": false + }, + { + "id": "4a91777b-946b-4c3c-b9a4-3fa3645c1e39", + "source_id": "dad79a25-9633-4b61-ad6b-344b3d7f4d1c", + "sink_id": "87506078-97fc-4591-bb19-1e4a95af72a8", + "source_name": "output", + "sink_name": "value2", + "is_static": true + }, + { + "id": "3531f653-5cb2-4107-9522-d9aaebd9d333", + "source_id": "95cbf9be-59cb-4240-aead-e537af599976", + "sink_id": "67d559a9-89ca-4f1c-888b-7d5e4b934824", + "source_name": "response", + "sink_name": "value", + "is_static": false + }, + { + "id": "36566600-abaf-479e-8310-380ba8716a82", + "source_id": "132eb8d1-49b6-47f4-9b6f-114b5b929989", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "result", + "sink_name": "prompt_values_#_CLARITY", + "is_static": true + }, + { + "id": "051f1e02-0bfa-436f-bab3-91489a6aa9a5", + "source_id": "49998ca9-0549-4198-98f6-a9ae39907c4b", + "sink_id": "95cbf9be-59cb-4240-aead-e537af599976", + "source_name": "value", + "sink_name": "prompt_values_#_TRANSCRIPTS", + "is_static": false + }, + { + "id": "2e8d10c5-a067-4c64-8fc5-a2db5ab82351", + "source_id": "c0d0d5d5-221b-4ce7-911b-09e40442fd82", + "sink_id": "c0d0d5d5-221b-4ce7-911b-09e40442fd82", + "source_name": "updated_list", + "sink_name": "list", + "is_static": false + }, + { + "id": "56d063cd-9a82-49cd-8a8e-e8a452009e1a", + "source_id": "87506078-97fc-4591-bb19-1e4a95af72a8", + "sink_id": "49998ca9-0549-4198-98f6-a9ae39907c4b", + "source_name": "yes_output", + "sink_name": "value", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "sub_graphs": [], + "user_id": "", + "created_at": "2025-04-20T18:34:57.261Z", + "input_schema": { + "type": "object", + "properties": { + "Style": { + "advanced": false, + "secret": false, + "title": "Style", + "enum": [ + "Professional", + "Conversational", + "Academic", + "Narrative", + "Persuasive", + "Humorous", + "Informal", + "Formal" + ], + "description": "Specifies the overall writing style of the blog post. This determines how the content is presented, such as in a professional, conversational, academic, narrative, or persuasive manner.", + "default": "Persuasive" + }, + "Target Word Count": { + "advanced": false, + "secret": false, + "title": "Target Word Count", + "enum": [ + "100", + "200", + "300" + ], + "description": "Sets the target length of the blog post in words. This allows you to control the content length as needed. \nPlease note that due to the nature of LLMs this will not be exact.", + "default": "100" + }, + "Objective": { + "advanced": false, + "secret": false, + "title": "Objective", + "enum": [ + "Informative", + "Persuasive", + "Entertaining", + "Analytical", + "Educational", + "Inspirational", + "Critical", + "Awareness-raising" + ], + "description": "Defines the main goal or purpose of the blog post. It guides the focus of the content, whether it's meant to inform, persuade, entertain, analyze, educate, inspire, critique, or raise awareness about the topic.", + "default": "Persuasive" + }, + "Clarity": { + "advanced": false, + "secret": false, + "title": "Clarity", + "enum": [ + "Clear and Accessible", + "Detailed and Technical", + "Simple and Straightforward", + "Comprehensive", + "Concise", + "Elaborate" + ], + "description": "Indicates the level of complexity in the explanations. It tailors the content to the audience's understanding, ranging from clear and accessible language to detailed and technical descriptions.", + "default": "Clear and Accessible" + }, + "Number of Videos": { + "advanced": false, + "secret": false, + "title": "Number of Videos", + "description": "The number of videos to collect the transcripts of", + "default": "3" + }, + "Tone": { + "advanced": false, + "secret": false, + "title": "Tone", + "enum": [ + "Engaging", + "Serious", + "Light-hearted", + "Friendly", + "Formal", + "Conversational", + "Optimistic", + "Urgent" + ], + "description": " Sets the mood or attitude conveyed through the writing. This affects how the reader perceives the content, with options like engaging, serious, light-hearted, friendly, formal, optimistic, or urgent.", + "default": "Engaging" + }, + "Opinion": { + "advanced": false, + "secret": false, + "title": "Opinion", + "enum": [ + "Positive", + "Negative", + "Neutral", + "Balanced", + "Critical", + "Supportive", + "Skeptical" + ], + "description": "Represents the perspective or stance taken in the blog post. This shapes the viewpoint presented to the reader, whether it's positive, negative, neutral, balanced, critical, supportive, or skeptical.", + "default": "Positive" + }, + "Topic": { + "advanced": false, + "secret": false, + "title": "Topic", + "description": "The topic of the post you want to write. This is also the query that will be searched on YouTube for research.", + "default": "Auto_GPT" + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "Blog Post": { + "advanced": false, + "secret": false, + "title": "Blog Post", + "description": "The full blog post written by the Agent" + } + }, + "required": [ + "Blog Post" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "webshare_proxy_user_password_credentials": { + "credentials_provider": [ + "webshare_proxy" + ], + "credentials_types": [ + "user_password" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "webshare_proxy", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "user_password", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['user_password']]", + "type": "object", + "discriminator_values": [] + }, + "jina_api_key_credentials": { + "credentials_provider": [ + "jina" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "jina", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + }, + "anthropic_api_key_credentials": { + "credentials_provider": [ + "anthropic" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "anthropic", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "claude-sonnet-4-5-20250929" + ] + } + }, + "required": [ + "webshare_proxy_user_password_credentials", + "jina_api_key_credentials", + "anthropic_api_key_credentials" + ], + "title": "LinkedInPostGeneratorCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_f2cc74bb-f43f-4395-9c35-ecb30b5b4fc9.json 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Designed for marketers, SEO specialists, and web developers, this tool analyses and enhances website copy for maximum impact. Using advanced language models, it optimizes text for better clarity, SEO performance, and increased conversion rates. The AI examines your existing content, identifies areas for improvement, and generates refined copy that maintains your brand voice while boosting engagement. From homepage headlines to product descriptions, transform your web presence with AI-driven insights. Improve readability, incorporate targeted keywords, and craft compelling calls-to-action - all with the click of a button. Take your digital marketing to the next level with the AI Webpage Copy Improver.", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "130ec496-f75d-4fe2-9cd6-8c00d08ea4a7", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Improved Webpage Copy" + }, + "metadata": { + "position": { + "x": 1039.5884372540172, + "y": -0.8359099621230968 + } + }, + "input_links": [ + { + "id": "d4334477-3616-454f-a430-614ca27f5b36", + "source_id": "c9924577-70d8-4ccb-9106-6f796df09ef9", + "sink_id": "130ec496-f75d-4fe2-9cd6-8c00d08ea4a7", + "source_name": "response", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "0d440799-44ba-4d6c-85b3-b3739f1e1287", + "graph_version": 12, + "webhook_id": null, + "webhook": null + }, + { + "id": "cefccd07-fe70-4feb-bf76-46b20aaa5d35", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Original Page Analysis", + "description": "Analysis of the webpage as it currently stands." + }, + "metadata": { + "position": { + "x": 1037.7724103954706, + "y": -606.5934325506903 + } + }, + "input_links": [ + { + "id": "f979ab78-0903-4f19-a7c2-a419d5d81aef", + "source_id": "08612ce2-625b-4c17-accd-3acace7b6477", + "sink_id": "cefccd07-fe70-4feb-bf76-46b20aaa5d35", + "source_name": "response", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "0d440799-44ba-4d6c-85b3-b3739f1e1287", + "graph_version": 12, + "webhook_id": null, + "webhook": null + }, + { + "id": "375f8bc3-afd9-4025-ad8e-9aeb329af7ce", + "block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b", + "input_default": { + "name": "Homepage URL", + "value": "https://agpt.co", + "description": "Enter the URL of the homepage you want to improve" + }, + "metadata": { + "position": { + "x": -1195.1455674454749, + "y": 0 + } + }, + "input_links": [], + "output_links": [ + { + "id": "cbb12335-fefd-4560-9fff-98675130fbad", + "source_id": "375f8bc3-afd9-4025-ad8e-9aeb329af7ce", + "sink_id": "b40595c6-dba3-4779-a129-cd4f01fff103", + "source_name": "result", + "sink_name": "url", + "is_static": true + } + ], + "graph_id": "0d440799-44ba-4d6c-85b3-b3739f1e1287", + "graph_version": 12, + "webhook_id": null, + "webhook": null + }, + { + "id": "b40595c6-dba3-4779-a129-cd4f01fff103", + "block_id": "436c3984-57fd-4b85-8e9a-459b356883bd", + "input_default": { + "raw_content": false + }, + "metadata": { + "position": { + "x": -631.7330786555249, + "y": 1.9638396496230826 + } + }, + "input_links": [ + { + "id": "cbb12335-fefd-4560-9fff-98675130fbad", + "source_id": "375f8bc3-afd9-4025-ad8e-9aeb329af7ce", + "sink_id": "b40595c6-dba3-4779-a129-cd4f01fff103", + "source_name": "result", + "sink_name": "url", + "is_static": true + } + ], + "output_links": [ + { + "id": "adfa6113-77b3-4e32-b136-3e694b87553e", + "source_id": "b40595c6-dba3-4779-a129-cd4f01fff103", + "sink_id": "c9924577-70d8-4ccb-9106-6f796df09ef9", + "source_name": "content", + "sink_name": "prompt_values_#_CONTENT", + "is_static": false + }, + { + "id": "5d5656fd-4208-4296-bc70-e39cc31caada", + "source_id": "b40595c6-dba3-4779-a129-cd4f01fff103", + "sink_id": "08612ce2-625b-4c17-accd-3acace7b6477", + "source_name": "content", + "sink_name": "prompt_values_#_CONTENT", + "is_static": false + } + ], + "graph_id": "0d440799-44ba-4d6c-85b3-b3739f1e1287", + "graph_version": 12, + "webhook_id": null, + "webhook": null + }, + { + "id": "c9924577-70d8-4ccb-9106-6f796df09ef9", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-4o", + "prompt": "Current Webpage Content:\n```\n{{CONTENT}}\n```\n\nBased on the following analysis of the webpage content:\n\n```\n{{ANALYSIS}}\n```\n\nRewrite and improve the content to address the identified issues. Focus on:\n1. Enhancing clarity and readability\n2. Optimizing for SEO (suggest and incorporate relevant keywords)\n3. Improving calls-to-action for better conversion rates\n4. Refining the structure and organization\n5. Maintaining brand consistency while improving the overall tone\n\nProvide the improved content in HTML format inside a code-block with \"```\" backticks, preserving the original structure where appropriate. Also, include a brief summary of the changes made and their potential impact.", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 488.37278423303917, + "y": 0 + } + }, + "input_links": [ + { + "id": "adfa6113-77b3-4e32-b136-3e694b87553e", + "source_id": "b40595c6-dba3-4779-a129-cd4f01fff103", + "sink_id": "c9924577-70d8-4ccb-9106-6f796df09ef9", + "source_name": "content", + "sink_name": "prompt_values_#_CONTENT", + "is_static": false + }, + { + "id": "6bcca45d-c9d5-439e-ac43-e4a1264d8f57", + "source_id": "08612ce2-625b-4c17-accd-3acace7b6477", + "sink_id": "c9924577-70d8-4ccb-9106-6f796df09ef9", + "source_name": "response", + "sink_name": "prompt_values_#_ANALYSIS", + "is_static": false + } + ], + "output_links": [ + { + "id": "d4334477-3616-454f-a430-614ca27f5b36", + "source_id": "c9924577-70d8-4ccb-9106-6f796df09ef9", + "sink_id": "130ec496-f75d-4fe2-9cd6-8c00d08ea4a7", + "source_name": "response", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "0d440799-44ba-4d6c-85b3-b3739f1e1287", + "graph_version": 12, + "webhook_id": null, + "webhook": null + }, + { + "id": "08612ce2-625b-4c17-accd-3acace7b6477", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "gpt-4o", + "prompt": "Analyze the following webpage content and provide a detailed report on its current state, including strengths and weaknesses in terms of clarity, SEO optimization, and potential for conversion:\n\n{{CONTENT}}\n\nInclude observations on:\n1. Overall readability and clarity\n2. Use of keywords and SEO-friendly language\n3. Effectiveness of calls-to-action\n4. Structure and organization of content\n5. Tone and brand consistency", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": -72.66206703605442, + "y": -0.58403945075381 + } + }, + "input_links": [ + { + "id": "5d5656fd-4208-4296-bc70-e39cc31caada", + "source_id": "b40595c6-dba3-4779-a129-cd4f01fff103", + "sink_id": "08612ce2-625b-4c17-accd-3acace7b6477", + "source_name": "content", + "sink_name": "prompt_values_#_CONTENT", + "is_static": false + } + ], + "output_links": [ + { + "id": "f979ab78-0903-4f19-a7c2-a419d5d81aef", + "source_id": "08612ce2-625b-4c17-accd-3acace7b6477", + "sink_id": "cefccd07-fe70-4feb-bf76-46b20aaa5d35", + "source_name": "response", + "sink_name": "value", + "is_static": false + }, + { + "id": "6bcca45d-c9d5-439e-ac43-e4a1264d8f57", + "source_id": "08612ce2-625b-4c17-accd-3acace7b6477", + "sink_id": "c9924577-70d8-4ccb-9106-6f796df09ef9", + "source_name": "response", + "sink_name": "prompt_values_#_ANALYSIS", + "is_static": false + } + ], + "graph_id": 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"cefccd07-fe70-4feb-bf76-46b20aaa5d35", + "source_name": "response", + "sink_name": "value", + "is_static": false + }, + { + "id": "6bcca45d-c9d5-439e-ac43-e4a1264d8f57", + "source_id": "08612ce2-625b-4c17-accd-3acace7b6477", + "sink_id": "c9924577-70d8-4ccb-9106-6f796df09ef9", + "source_name": "response", + "sink_name": "prompt_values_#_ANALYSIS", + "is_static": false + }, + { + "id": "cbb12335-fefd-4560-9fff-98675130fbad", + "source_id": "375f8bc3-afd9-4025-ad8e-9aeb329af7ce", + "sink_id": "b40595c6-dba3-4779-a129-cd4f01fff103", + "source_name": "result", + "sink_name": "url", + "is_static": true + } + ], + "forked_from_id": null, + "forked_from_version": null, + "sub_graphs": [], + "user_id": "", + "created_at": "2024-12-20T19:47:22.036Z", + "input_schema": { + "type": "object", + "properties": { + "Homepage URL": { + "advanced": false, + "secret": false, + "title": "Homepage URL", + "description": "Enter the URL of the homepage you want to improve", + "default": "https://agpt.co" + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "Improved Webpage Copy": { + "advanced": false, + "secret": false, + "title": "Improved Webpage Copy" + }, + "Original Page Analysis": { + "advanced": false, + "secret": false, + "title": "Original Page Analysis", + "description": "Analysis of the webpage as it currently stands." + } + }, + "required": [ + "Improved Webpage Copy", + "Original Page Analysis" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "jina_api_key_credentials": { + "credentials_provider": [ + "jina" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "jina", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + }, + "openai_api_key_credentials": { + "credentials_provider": [ + "openai" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "openai", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "gpt-4o" + ] + } + }, + "required": [ + "jina_api_key_credentials", + "openai_api_key_credentials" + ], + "title": "AIWebpageCopyImproverCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/agents/agent_fc2c9976-0962-4625-a27b-d316573a9e7f.json b/autogpt_platform/backend/agents/agent_fc2c9976-0962-4625-a27b-d316573a9e7f.json new file mode 100644 index 0000000000..d2a83bcdfe --- /dev/null +++ b/autogpt_platform/backend/agents/agent_fc2c9976-0962-4625-a27b-d316573a9e7f.json @@ -0,0 +1,615 @@ +{ + "id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26", + "version": 29, + "is_active": true, + "name": "Email Address Finder", + "description": "Input information of a business and find their email address", + "instructions": null, + "recommended_schedule_cron": null, + "nodes": [ + { + "id": "04cad535-9f1a-4876-8b07-af5897d8c282", + "block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b", + "input_default": { + "name": "Address", + "value": "USA" + }, + "metadata": { + "position": { + "x": 1047.9357219838776, + "y": 1067.9123910370954 + } + }, + "input_links": [], + "output_links": [ + { + "id": "aac29f7b-3cd1-4c91-9a2a-72a8301c0957", + "source_id": "04cad535-9f1a-4876-8b07-af5897d8c282", + "sink_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "source_name": "result", + "sink_name": "values_#_ADDRESS", + "is_static": true + } + ], + "graph_id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26", + "graph_version": 29, + "webhook_id": null, + "webhook": null + }, + { + "id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "block_id": "3146e4fe-2cdd-4f29-bd12-0c9d5bb4deb0", + "input_default": { + "group": 1, + "pattern": "(.*?)<\\/email>" + }, + "metadata": { + "position": { + "x": 3381.2821481740634, + "y": 246.091098184158 + } + }, + "input_links": [ + { + "id": "9f8188ce-1f3d-46fb-acda-b2a57c0e5da6", + "source_id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "sink_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "source_name": "response", + "sink_name": "text", + "is_static": false + } + ], + "output_links": [ + { + "id": "b15b5143-27b7-486e-a166-4095e72e5235", + "source_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "sink_id": "266b7255-11c4-4b88-99e2-85db31a2e865", + "source_name": "negative", + "sink_name": "values_#_Result", + "is_static": false + }, + { + "id": "23591872-3c6b-4562-87d3-5b6ade698e48", + "source_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "sink_id": "310c8fab-2ae6-4158-bd48-01dbdc434130", + "source_name": "positive", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26", + "graph_version": 29, + "webhook_id": null, + "webhook": null + }, + { + "id": "310c8fab-2ae6-4158-bd48-01dbdc434130", + "block_id": "363ae599-353e-4804-937e-b2ee3cef3da4", + "input_default": { + "name": "Email" + }, + "metadata": { + "position": { + "x": 4525.4246310882, + "y": 246.36913665010354 + } + }, + "input_links": [ + { + "id": "d87b07ea-dcec-4d38-a644-2c1d741ea3cb", + "source_id": "266b7255-11c4-4b88-99e2-85db31a2e865", + "sink_id": "310c8fab-2ae6-4158-bd48-01dbdc434130", + "source_name": "output", + "sink_name": "value", + "is_static": false + }, + { + "id": "23591872-3c6b-4562-87d3-5b6ade698e48", + "source_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "sink_id": "310c8fab-2ae6-4158-bd48-01dbdc434130", + "source_name": "positive", + "sink_name": "value", + "is_static": false + } + ], + "output_links": [], + "graph_id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26", + "graph_version": 29, + "webhook_id": null, + "webhook": null + }, + { + "id": "4a41df99-ffe2-4c12-b528-632979c9c030", + "block_id": "87840993-2053-44b7-8da4-187ad4ee518c", + "input_default": {}, + "metadata": { + "position": { + "x": 2182.7499999999995, + "y": 242.00001144409185 + } + }, + "input_links": [ + { + "id": "2e411d3d-79ba-4958-9c1c-b76a45a2e649", + "source_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "sink_id": "4a41df99-ffe2-4c12-b528-632979c9c030", + "source_name": "output", + "sink_name": "query", + "is_static": false + } + ], + "output_links": [ + { + "id": "899cc7d8-a96b-4107-b3c6-4c78edcf0c6b", + "source_id": "4a41df99-ffe2-4c12-b528-632979c9c030", + "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "source_name": "results", + "sink_name": "prompt_values_#_WEBSITE_CONTENT", + "is_static": false + } + ], + "graph_id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26", + "graph_version": 29, + "webhook_id": null, + "webhook": null + }, + { + "id": "9708a10a-8be0-4c44-abb3-bd0f7c594794", + "block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b", + "input_default": { + "name": "Business Name", + "value": "Tim Cook" + }, + "metadata": { + "position": { + "x": 1049.9704155272595, + "y": 244.49931152418344 + } + }, + "input_links": [], + "output_links": [ + { + "id": "946b522c-365f-4ee0-96f9-28863d9882ea", + "source_id": "9708a10a-8be0-4c44-abb3-bd0f7c594794", + "sink_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "source_name": "result", + "sink_name": "values_#_NAME", + "is_static": true + }, + { + "id": "43e920a7-0bb4-4fae-9a22-91df95c7342a", + "source_id": "9708a10a-8be0-4c44-abb3-bd0f7c594794", + "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "source_name": "result", + "sink_name": "prompt_values_#_BUSINESS_NAME", + "is_static": true + } + ], + "graph_id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26", + "graph_version": 29, + "webhook_id": null, + "webhook": null + }, + { + "id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "block_id": "db7d8f02-2f44-4c55-ab7a-eae0941f0c30", + "input_default": { + "format": "Email Address of {{NAME}}, {{ADDRESS}}", + "values": {} + }, + "metadata": { + "position": { + "x": 1625.25, + "y": 243.25001144409185 + } + }, + "input_links": [ + { + "id": "946b522c-365f-4ee0-96f9-28863d9882ea", + "source_id": "9708a10a-8be0-4c44-abb3-bd0f7c594794", + "sink_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "source_name": "result", + "sink_name": "values_#_NAME", + "is_static": true + }, + { + "id": "aac29f7b-3cd1-4c91-9a2a-72a8301c0957", + "source_id": "04cad535-9f1a-4876-8b07-af5897d8c282", + "sink_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "source_name": "result", + "sink_name": "values_#_ADDRESS", + "is_static": true + } + ], + "output_links": [ + { + "id": "2e411d3d-79ba-4958-9c1c-b76a45a2e649", + "source_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "sink_id": "4a41df99-ffe2-4c12-b528-632979c9c030", + "source_name": "output", + "sink_name": "query", + "is_static": false + } + ], + "graph_id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26", + "graph_version": 29, + "webhook_id": null, + "webhook": null + }, + { + "id": "266b7255-11c4-4b88-99e2-85db31a2e865", + "block_id": "db7d8f02-2f44-4c55-ab7a-eae0941f0c30", + "input_default": { + "format": "Failed to find email. \nResult:\n{{RESULT}}", + "values": {} + }, + "metadata": { + "position": { + "x": 3949.7493830805934, + "y": 705.209819698647 + } + }, + "input_links": [ + { + "id": "b15b5143-27b7-486e-a166-4095e72e5235", + "source_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "sink_id": "266b7255-11c4-4b88-99e2-85db31a2e865", + "source_name": "negative", + "sink_name": "values_#_Result", + "is_static": false + } + ], + "output_links": [ + { + "id": "d87b07ea-dcec-4d38-a644-2c1d741ea3cb", + "source_id": "266b7255-11c4-4b88-99e2-85db31a2e865", + "sink_id": "310c8fab-2ae6-4158-bd48-01dbdc434130", + "source_name": "output", + "sink_name": "value", + "is_static": false + } + ], + "graph_id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26", + "graph_version": 29, + "webhook_id": null, + "webhook": null + }, + { + "id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91", + "input_default": { + "model": "claude-sonnet-4-5-20250929", + "prompt": "\n{{WEBSITE_CONTENT}}\n\n\nExtract the Contact Email of {{BUSINESS_NAME}}.\n\nIf no email that can be used to contact {{BUSINESS_NAME}} is present, output `N/A`.\nDo not share any emails other than the email for this specific entity.\n\nIf multiple present pick the likely best one.\n\nRespond with the email (or N/A) inside tags.\n\nExample Response:\n\n\nThere were many emails present, but luckily one was for {{BUSINESS_NAME}} which I have included below.\n\n\nexample@email.com\n", + "prompt_values": {} + }, + "metadata": { + "position": { + "x": 2774.879259081777, + "y": 243.3102035752969 + } + }, + "input_links": [ + { + "id": "43e920a7-0bb4-4fae-9a22-91df95c7342a", + "source_id": "9708a10a-8be0-4c44-abb3-bd0f7c594794", + "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "source_name": "result", + "sink_name": "prompt_values_#_BUSINESS_NAME", + "is_static": true + }, + { + "id": "899cc7d8-a96b-4107-b3c6-4c78edcf0c6b", + "source_id": "4a41df99-ffe2-4c12-b528-632979c9c030", + "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "source_name": "results", + "sink_name": "prompt_values_#_WEBSITE_CONTENT", + "is_static": false + } + ], + "output_links": [ + { + "id": "9f8188ce-1f3d-46fb-acda-b2a57c0e5da6", + "source_id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "sink_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "source_name": "response", + "sink_name": "text", + "is_static": false + } + ], + "graph_id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26", + "graph_version": 29, + "webhook_id": null, + "webhook": null + } + ], + "links": [ + { + "id": "9f8188ce-1f3d-46fb-acda-b2a57c0e5da6", + "source_id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "sink_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "source_name": "response", + "sink_name": "text", + "is_static": false + }, + { + "id": "b15b5143-27b7-486e-a166-4095e72e5235", + "source_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "sink_id": "266b7255-11c4-4b88-99e2-85db31a2e865", + "source_name": "negative", + "sink_name": "values_#_Result", + "is_static": false + }, + { + "id": "d87b07ea-dcec-4d38-a644-2c1d741ea3cb", + "source_id": "266b7255-11c4-4b88-99e2-85db31a2e865", + "sink_id": "310c8fab-2ae6-4158-bd48-01dbdc434130", + "source_name": "output", + "sink_name": "value", + "is_static": false + }, + { + "id": "946b522c-365f-4ee0-96f9-28863d9882ea", + "source_id": "9708a10a-8be0-4c44-abb3-bd0f7c594794", + "sink_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "source_name": "result", + "sink_name": "values_#_NAME", + "is_static": true + }, + { + "id": "23591872-3c6b-4562-87d3-5b6ade698e48", + "source_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981", + "sink_id": "310c8fab-2ae6-4158-bd48-01dbdc434130", + "source_name": "positive", + "sink_name": "value", + "is_static": false + }, + { + "id": "43e920a7-0bb4-4fae-9a22-91df95c7342a", + "source_id": "9708a10a-8be0-4c44-abb3-bd0f7c594794", + "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "source_name": "result", + "sink_name": "prompt_values_#_BUSINESS_NAME", + "is_static": true + }, + { + "id": "2e411d3d-79ba-4958-9c1c-b76a45a2e649", + "source_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "sink_id": "4a41df99-ffe2-4c12-b528-632979c9c030", + "source_name": "output", + "sink_name": "query", + "is_static": false + }, + { + "id": "aac29f7b-3cd1-4c91-9a2a-72a8301c0957", + "source_id": "04cad535-9f1a-4876-8b07-af5897d8c282", + "sink_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694", + "source_name": "result", + "sink_name": "values_#_ADDRESS", + "is_static": true + }, + { + "id": "899cc7d8-a96b-4107-b3c6-4c78edcf0c6b", + "source_id": "4a41df99-ffe2-4c12-b528-632979c9c030", + "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50", + "source_name": "results", + "sink_name": "prompt_values_#_WEBSITE_CONTENT", + "is_static": false + } + ], + "forked_from_id": null, + "forked_from_version": null, + "sub_graphs": [], + "user_id": "", + "created_at": "2025-01-03T00:46:30.244Z", + "input_schema": { + "type": "object", + "properties": { + "Address": { + "advanced": false, + "secret": false, + "title": "Address", + "default": "USA" + }, + "Business Name": { + "advanced": false, + "secret": false, + "title": "Business Name", + "default": "Tim Cook" + } + }, + "required": [] + }, + "output_schema": { + "type": "object", + "properties": { + "Email": { + "advanced": false, + "secret": false, + "title": "Email" + } + }, + "required": [ + "Email" + ] + }, + "has_external_trigger": false, + "has_human_in_the_loop": false, + "trigger_setup_info": null, + "credentials_input_schema": { + "properties": { + "jina_api_key_credentials": { + "credentials_provider": [ + "jina" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "jina", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator_values": [] + }, + "anthropic_api_key_credentials": { + "credentials_provider": [ + "anthropic" + ], + "credentials_types": [ + "api_key" + ], + "properties": { + "id": { + "title": "Id", + "type": "string" + }, + "title": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Title" + }, + "provider": { + "const": "anthropic", + "title": "Provider", + "type": "string" + }, + "type": { + "const": "api_key", + "title": "Type", + "type": "string" + } + }, + "required": [ + "id", + "provider", + "type" + ], + "title": "CredentialsMetaInput[Literal[], Literal['api_key']]", + "type": "object", + "discriminator": "model", + "discriminator_mapping": { + "Llama-3.3-70B-Instruct": "llama_api", + "Llama-3.3-8B-Instruct": "llama_api", + "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api", + "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api", + "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api", + "amazon/nova-lite-v1": "open_router", + "amazon/nova-micro-v1": "open_router", + "amazon/nova-pro-v1": "open_router", + "claude-3-7-sonnet-20250219": "anthropic", + "claude-3-haiku-20240307": "anthropic", + "claude-haiku-4-5-20251001": "anthropic", + "claude-opus-4-1-20250805": "anthropic", + "claude-opus-4-20250514": "anthropic", + "claude-opus-4-5-20251101": "anthropic", + "claude-sonnet-4-20250514": "anthropic", + "claude-sonnet-4-5-20250929": "anthropic", + "cohere/command-r-08-2024": "open_router", + "cohere/command-r-plus-08-2024": "open_router", + "deepseek/deepseek-chat": "open_router", + "deepseek/deepseek-r1-0528": "open_router", + "dolphin-mistral:latest": "ollama", + "google/gemini-2.0-flash-001": "open_router", + "google/gemini-2.0-flash-lite-001": "open_router", + "google/gemini-2.5-flash": "open_router", + "google/gemini-2.5-flash-lite-preview-06-17": "open_router", + "google/gemini-2.5-pro-preview-03-25": "open_router", + "google/gemini-3-pro-preview": "open_router", + "gpt-3.5-turbo": "openai", + "gpt-4-turbo": "openai", + "gpt-4.1-2025-04-14": "openai", + "gpt-4.1-mini-2025-04-14": "openai", + "gpt-4o": "openai", + "gpt-4o-mini": "openai", + "gpt-5-2025-08-07": "openai", + "gpt-5-chat-latest": "openai", + "gpt-5-mini-2025-08-07": "openai", + "gpt-5-nano-2025-08-07": "openai", + "gpt-5.1-2025-11-13": "openai", + "gryphe/mythomax-l2-13b": "open_router", + "llama-3.1-8b-instant": "groq", + "llama-3.3-70b-versatile": "groq", + "llama3": "ollama", + "llama3.1:405b": "ollama", + "llama3.2": "ollama", + "llama3.3": "ollama", + "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api", + "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api", + "meta-llama/llama-4-maverick": "open_router", + "meta-llama/llama-4-scout": "open_router", + "microsoft/wizardlm-2-8x22b": "open_router", + "mistralai/mistral-nemo": "open_router", + "moonshotai/kimi-k2": "open_router", + "nousresearch/hermes-3-llama-3.1-405b": "open_router", + "nousresearch/hermes-3-llama-3.1-70b": "open_router", + "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api", + "o1": "openai", + "o1-mini": "openai", + "o3-2025-04-16": "openai", + "o3-mini": "openai", + "openai/gpt-oss-120b": "open_router", + "openai/gpt-oss-20b": "open_router", + "perplexity/sonar": "open_router", + "perplexity/sonar-deep-research": "open_router", + "perplexity/sonar-pro": "open_router", + "qwen/qwen3-235b-a22b-thinking-2507": "open_router", + "qwen/qwen3-coder": "open_router", + "v0-1.0-md": "v0", + "v0-1.5-lg": "v0", + "v0-1.5-md": "v0", + "x-ai/grok-4": "open_router", + "x-ai/grok-4-fast": "open_router", + "x-ai/grok-4.1-fast": "open_router", + "x-ai/grok-code-fast-1": "open_router" + }, + "discriminator_values": [ + "claude-sonnet-4-5-20250929" + ] + } + }, + "required": [ + "jina_api_key_credentials", + "anthropic_api_key_credentials" + ], + "title": "EmailAddressFinderCredentialsInputSchema", + "type": "object" + } +} \ No newline at end of file diff --git a/autogpt_platform/backend/pyproject.toml b/autogpt_platform/backend/pyproject.toml index 4c1f8e9547..a87ae8e71d 100644 --- a/autogpt_platform/backend/pyproject.toml +++ b/autogpt_platform/backend/pyproject.toml @@ -114,6 +114,7 @@ cli = "backend.cli:main" format = "linter:format" lint = "linter:lint" test = "run_tests:test" +load-store-agents = "test.load_store_agents:run" [tool.isort] profile = "black" diff --git a/autogpt_platform/backend/test/load_store_agents.py b/autogpt_platform/backend/test/load_store_agents.py new file mode 100644 index 0000000000..b9d8e0478e --- /dev/null +++ b/autogpt_platform/backend/test/load_store_agents.py @@ -0,0 +1,455 @@ +""" +Load Store Agents Script + +This script loads the exported store agents from the agents/ folder into the test database. +It creates: +- A user and profile for the 'autogpt' creator +- AgentGraph records from JSON files +- StoreListing and StoreListingVersion records from CSV metadata +- Approves agents that have is_available=true in the CSV + +Usage: + cd backend + poetry run load-store-agents +""" + +import asyncio +import csv +import json +import re +from datetime import datetime +from pathlib import Path + +import prisma.enums +from prisma import Json, Prisma +from prisma.types import ( + AgentBlockCreateInput, + AgentGraphCreateInput, + AgentNodeCreateInput, + AgentNodeLinkCreateInput, + ProfileCreateInput, + StoreListingCreateInput, + StoreListingVersionCreateInput, + UserCreateInput, +) + +# Path to agents folder (relative to backend directory) +AGENTS_DIR = Path(__file__).parent.parent / "agents" +CSV_FILE = AGENTS_DIR / "StoreAgent_rows.csv" + +# User constants for the autogpt creator (test data, not production) +# Fixed uuid4 for idempotency - same user is reused across script runs +AUTOGPT_USER_ID = "79d96c73-e6f5-4656-a83a-185b41ee0d06" +AUTOGPT_EMAIL = "autogpt-test@agpt.co" +AUTOGPT_USERNAME = "autogpt" + + +async def initialize_blocks(db: Prisma) -> set[str]: + """Initialize agent blocks in the database from the registered blocks. + + Returns a set of block IDs that exist in the database. + """ + from backend.data.block import get_blocks + + print(" Initializing agent blocks...") + blocks = get_blocks() + created_count = 0 + block_ids = set() + + for block_cls in blocks.values(): + block = block_cls() + block_ids.add(block.id) + existing_block = await db.agentblock.find_first( + where={"OR": [{"id": block.id}, {"name": block.name}]} + ) + if not existing_block: + await db.agentblock.create( + data=AgentBlockCreateInput( + id=block.id, + name=block.name, + inputSchema=json.dumps(block.input_schema.jsonschema()), + outputSchema=json.dumps(block.output_schema.jsonschema()), + ) + ) + created_count += 1 + elif block.id != existing_block.id or block.name != existing_block.name: + await db.agentblock.update( + where={"id": existing_block.id}, + data={ + "id": block.id, + "name": block.name, + "inputSchema": json.dumps(block.input_schema.jsonschema()), + "outputSchema": json.dumps(block.output_schema.jsonschema()), + }, + ) + + print(f" Initialized {len(blocks)} blocks ({created_count} new)") + return block_ids + + +async def ensure_block_exists( + db: Prisma, block_id: str, known_blocks: set[str] +) -> bool: + """Ensure a block exists in the database, create a placeholder if needed. + + Returns True if the block exists (or was created), False otherwise. + """ + if block_id in known_blocks: + return True + + # Check if it already exists in the database + existing = await db.agentblock.find_unique(where={"id": block_id}) + if existing: + known_blocks.add(block_id) + return True + + # Create a placeholder block + print(f" Creating placeholder block: {block_id}") + try: + await db.agentblock.create( + data=AgentBlockCreateInput( + id=block_id, + name=f"Placeholder_{block_id[:8]}", + inputSchema="{}", + outputSchema="{}", + ) + ) + known_blocks.add(block_id) + return True + except Exception as e: + print(f" Warning: Could not create placeholder block {block_id}: {e}") + return False + + +def parse_image_urls(image_str: str) -> list[str]: + """Parse the image URLs from CSV format like ["url1","url2"].""" + if not image_str or image_str == "[]": + return [] + try: + return json.loads(image_str) + except json.JSONDecodeError: + return [] + + +def parse_categories(categories_str: str) -> list[str]: + """Parse categories from CSV format like ["cat1","cat2"].""" + if not categories_str or categories_str == "[]": + return [] + try: + return json.loads(categories_str) + except json.JSONDecodeError: + return [] + + +def sanitize_slug(slug: str) -> str: + """Ensure slug only contains valid characters.""" + return re.sub(r"[^a-z0-9-]", "", slug.lower()) + + +async def create_user_and_profile(db: Prisma) -> None: + """Create the autogpt user and profile if they don't exist.""" + # Check if user exists + existing_user = await db.user.find_unique(where={"id": AUTOGPT_USER_ID}) + if existing_user: + print(f"User {AUTOGPT_USER_ID} already exists, skipping user creation") + else: + print(f"Creating user {AUTOGPT_USER_ID}") + await db.user.create( + data=UserCreateInput( + id=AUTOGPT_USER_ID, + email=AUTOGPT_EMAIL, + name="AutoGPT", + metadata=Json({}), + integrations="", + ) + ) + + # Check if profile exists + existing_profile = await db.profile.find_first(where={"userId": AUTOGPT_USER_ID}) + if existing_profile: + print( + f"Profile for user {AUTOGPT_USER_ID} already exists, skipping profile creation" + ) + else: + print(f"Creating profile for user {AUTOGPT_USER_ID}") + await db.profile.create( + data=ProfileCreateInput( + userId=AUTOGPT_USER_ID, + name="AutoGPT", + username=AUTOGPT_USERNAME, + description="Official AutoGPT agents and templates", + links=["https://agpt.co"], + avatarUrl="https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/4b5781a6-49e1-433c-9a75-65af1be5c02d.png", + ) + ) + + +async def load_csv_metadata() -> dict[str, dict]: + """Load CSV metadata and return a dict keyed by storeListingVersionId.""" + metadata = {} + with open(CSV_FILE, "r", encoding="utf-8") as f: + reader = csv.DictReader(f) + for row in reader: + version_id = row["storeListingVersionId"] + metadata[version_id] = { + "listing_id": row["listing_id"], + "store_listing_version_id": version_id, + "slug": sanitize_slug(row["slug"]), + "agent_name": row["agent_name"], + "agent_video": row["agent_video"] if row["agent_video"] else None, + "agent_image": parse_image_urls(row["agent_image"]), + "featured": row["featured"].lower() == "true", + "sub_heading": row["sub_heading"], + "description": row["description"], + "categories": parse_categories(row["categories"]), + "use_for_onboarding": row["useForOnboarding"].lower() == "true", + "is_available": row["is_available"].lower() == "true", + } + return metadata + + +async def load_agent_json(json_path: Path) -> dict: + """Load and parse an agent JSON file.""" + with open(json_path, "r", encoding="utf-8") as f: + return json.load(f) + + +async def create_agent_graph( + db: Prisma, agent_data: dict, known_blocks: set[str] +) -> tuple[str, int]: + """Create an AgentGraph and its nodes/links from JSON data.""" + graph_id = agent_data["id"] + version = agent_data.get("version", 1) + + # Check if graph already exists + existing_graph = await db.agentgraph.find_unique( + where={"graphVersionId": {"id": graph_id, "version": version}} + ) + if existing_graph: + print(f" Graph {graph_id} v{version} already exists, skipping") + return graph_id, version + + print( + f" Creating graph {graph_id} v{version}: {agent_data.get('name', 'Unnamed')}" + ) + + # Create the main graph + await db.agentgraph.create( + data=AgentGraphCreateInput( + id=graph_id, + version=version, + name=agent_data.get("name"), + description=agent_data.get("description"), + instructions=agent_data.get("instructions"), + recommendedScheduleCron=agent_data.get("recommended_schedule_cron"), + isActive=agent_data.get("is_active", True), + userId=AUTOGPT_USER_ID, + forkedFromId=agent_data.get("forked_from_id"), + forkedFromVersion=agent_data.get("forked_from_version"), + ) + ) + + # Create nodes + nodes = agent_data.get("nodes", []) + for node in nodes: + block_id = node["block_id"] + # Ensure the block exists (create placeholder if needed) + block_exists = await ensure_block_exists(db, block_id, known_blocks) + if not block_exists: + print( + f" Skipping node {node['id']} - block {block_id} could not be created" + ) + continue + + await db.agentnode.create( + data=AgentNodeCreateInput( + id=node["id"], + agentBlockId=block_id, + agentGraphId=graph_id, + agentGraphVersion=version, + constantInput=Json(node.get("input_default", {})), + metadata=Json(node.get("metadata", {})), + ) + ) + + # Create links + links = agent_data.get("links", []) + for link in links: + await db.agentnodelink.create( + data=AgentNodeLinkCreateInput( + id=link["id"], + agentNodeSourceId=link["source_id"], + agentNodeSinkId=link["sink_id"], + sourceName=link["source_name"], + sinkName=link["sink_name"], + isStatic=link.get("is_static", False), + ) + ) + + # Handle sub_graphs recursively + sub_graphs = agent_data.get("sub_graphs", []) + for sub_graph in sub_graphs: + await create_agent_graph(db, sub_graph, known_blocks) + + return graph_id, version + + +async def create_store_listing( + db: Prisma, + graph_id: str, + graph_version: int, + metadata: dict, +) -> None: + """Create StoreListing and StoreListingVersion for an agent.""" + listing_id = metadata["listing_id"] + version_id = metadata["store_listing_version_id"] + + # Check if listing already exists + existing_listing = await db.storelisting.find_unique(where={"id": listing_id}) + if existing_listing: + print(f" Store listing {listing_id} already exists, skipping") + return + + print(f" Creating store listing: {metadata['agent_name']}") + + # Determine if this should be approved + is_approved = metadata["is_available"] + submission_status = ( + prisma.enums.SubmissionStatus.APPROVED + if is_approved + else prisma.enums.SubmissionStatus.PENDING + ) + + # Create the store listing first (without activeVersionId - will update after) + await db.storelisting.create( + data=StoreListingCreateInput( + id=listing_id, + slug=metadata["slug"], + agentGraphId=graph_id, + agentGraphVersion=graph_version, + owningUserId=AUTOGPT_USER_ID, + hasApprovedVersion=is_approved, + useForOnboarding=metadata["use_for_onboarding"], + ) + ) + + # Create the store listing version + await db.storelistingversion.create( + data=StoreListingVersionCreateInput( + id=version_id, + version=1, + agentGraphId=graph_id, + agentGraphVersion=graph_version, + name=metadata["agent_name"], + subHeading=metadata["sub_heading"], + videoUrl=metadata["agent_video"], + imageUrls=metadata["agent_image"], + description=metadata["description"], + categories=metadata["categories"], + isFeatured=metadata["featured"], + isAvailable=metadata["is_available"], + submissionStatus=submission_status, + submittedAt=datetime.now() if is_approved else None, + reviewedAt=datetime.now() if is_approved else None, + storeListingId=listing_id, + ) + ) + + # Update the store listing with the active version if approved + if is_approved: + await db.storelisting.update( + where={"id": listing_id}, + data={"ActiveVersion": {"connect": {"id": version_id}}}, + ) + + +async def main(): + """Main function to load all store agents.""" + print("=" * 60) + print("Loading Store Agents into Test Database") + print("=" * 60) + + db = Prisma() + await db.connect() + + try: + # Step 0: Initialize agent blocks + print("\n[Step 0] Initializing agent blocks...") + known_blocks = await initialize_blocks(db) + + # Step 1: Create user and profile + print("\n[Step 1] Creating user and profile...") + await create_user_and_profile(db) + + # Step 2: Load CSV metadata + print("\n[Step 2] Loading CSV metadata...") + csv_metadata = await load_csv_metadata() + print(f" Found {len(csv_metadata)} store listing entries in CSV") + + # Step 3: Find all JSON files and match with CSV + print("\n[Step 3] Processing agent JSON files...") + json_files = list(AGENTS_DIR.glob("agent_*.json")) + print(f" Found {len(json_files)} agent JSON files") + + # Build mapping from version_id to json file + loaded_graphs = {} # graph_id -> (graph_id, version) + failed_agents = [] + + for json_file in json_files: + # Extract the version ID from filename (agent_.json) + version_id = json_file.stem.replace("agent_", "") + + if version_id not in csv_metadata: + print( + f" Warning: {json_file.name} not found in CSV metadata, skipping" + ) + continue + + metadata = csv_metadata[version_id] + agent_name = metadata["agent_name"] + print(f"\nProcessing: {agent_name}") + + # Use a transaction per agent to prevent dangling resources + try: + async with db.tx() as tx: + # Load and create the agent graph + agent_data = await load_agent_json(json_file) + graph_id, graph_version = await create_agent_graph( + tx, agent_data, known_blocks + ) + loaded_graphs[graph_id] = (graph_id, graph_version) + + # Create store listing + await create_store_listing(tx, graph_id, graph_version, metadata) + except Exception as e: + print(f" Error loading agent '{agent_name}': {e}") + failed_agents.append(agent_name) + continue + + # Step 4: Refresh materialized views + print("\n[Step 4] Refreshing materialized views...") + try: + await db.execute_raw("SELECT refresh_store_materialized_views();") + print(" Materialized views refreshed successfully") + except Exception as e: + print(f" Warning: Could not refresh materialized views: {e}") + + print("\n" + "=" * 60) + print(f"Successfully loaded {len(loaded_graphs)} agents") + if failed_agents: + print( + f"Failed to load {len(failed_agents)} agents: {', '.join(failed_agents)}" + ) + print("=" * 60) + + finally: + await db.disconnect() + + +def run(): + """Entry point for poetry script.""" + asyncio.run(main()) + + +if __name__ == "__main__": + run()