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BotSmith.pro's answer:
BotSmith is not just a chatbot builder โ itโs an AI infrastructure designed specifically for agencies operating in a B2B2C model. What makes it different: Agency-first architecture โ Built for agencies managing multiple clients, not individual founders. True multi-tenant system โ Each client is isolated, secure, and independently manageable. White-label ready โ Agencies can deploy AI solutions under their own brand. Usage-based control & plan enforcement โ Real SaaS-grade subscription and resource management. Multi-LLM support โ GPT, Claude, and Gemini in one unified system. RAG-powered intelligence โ Structured knowledge ingestion from files, websites, and text. Most competitors sell chatbots. BotSmith enables agencies to sell AI as a service.
BotSmith.pro's answer:
Because BotSmith is built for scale โ not experimentation. Designed for agencies managing clients Built-in usage limits & monetization logic Optimized RAG pipeline for speed and cost control Multi-model flexibility (avoid vendor lock-in) Infrastructure-level thinking โ not surface-level automation If you're an agency that wants to move from manual service provider to AI-powered infrastructure provider, BotSmith gives you the backend muscle to do it. Itโs not just a tool. Itโs a leverage system.
BotSmith.pro's answer:
BotSmith is built for: Digital marketing agencies Web development agencies Automation consultants SaaS resellers AI-native service providers Specifically, those who: Serve multiple clients Want recurring AI revenue Need white-label capabilities Want operational control over AI deployments Itโs not optimized for hobbyists. Itโs optimized for operators.
BotSmith.pro's answer:
BotSmith was created from a simple observation: Agencies are being asked to deliver AI solutions โ but they lack scalable infrastructure. Instead of building one-off chatbots manually for every client, BotSmith was designed to: Centralize AI deployment Standardize knowledge ingestion Control costs Enable recurring monetization Provide multi-client AI control from a single dashboard BotSmith exists to turn agencies into AI-native service providers โ not just resellers of tools.
BotSmith.pro's answer:
BotSmith is built using modern, scalable infrastructure: FastAPI (Python) โ High-performance backend API MongoDB โ Multi-tenant data isolation Async processing architecture โ Non-blocking background tasks Custom RAG pipeline โ Chunking + retrieval logic Vector storage layer โ Context management system Multi-LLM integration โ OpenAI, Anthropic, Google Gemini Secure authentication & RBAC system Usage-based subscription enforcement system The focus is on reliability, modularity, and long-term scalability.
Based on our record, GitHub seems to be more popular. It has been mentiond 2476 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
"""Clones a single branch of a GitHub repository into a temporary directory for local scanning.""" Import logging Import shutil Import subprocess Import tempfile Logger = logging.getLogger(__name__) Class RepoFetchError(RuntimeError): """Raised when the target repository/branch cannot be cloned.""" Class RepoFetcher: """Shallow-clones a single branch of a repository so its tests can be scanned... - Source: dev.to / 3 days ago
# video-meta.yml Topic: > Walking through how we cut cold-start time on a Lambda-backed GraphQL API from 2.4s to under 400ms, including the two things that didn't work. Target_keyword: lambda cold start optimization Audience: backend devs who already ship serverless, not beginners Model_channels: - the three channels currently ranking for this keyword Links: repo: https://github.com/... slides:... - Source: dev.to / 4 days ago
Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 9 days ago
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 16 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 17 days ago
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Botsonic - Train ChatGPT on your own data and build an AI Chatbot in minutes. No coding skills required.