'chatbot' 검색 결과

벵골어 검색과 AI 처리를 위한 문자 표현 통일, 단어 분리, 숫자 변환, 결합 문자를 보존하는 표시 방법을 정리합니다. 학습 데이터 정비와 텍스트 저장에도 활용할 수 있습니다.

• 벵골어 검색과 입력 기능을 구현합니다
• 벵골어 학습 데이터를 정리합니다
• 벵골어와 영어 대화를 지원합니다

LLaVA의 설치와 사용을 도와 사진 설명을 작성하고 이미지 내용에 답하도록 지원합니다. 같은 이미지를 두고 대화를 이어 가거나 이미지가 포함된 문서를 이해하는 데도 활용합니다.

• 사진 설명문 작성
• 이미지 속 사물과 장면에 관한 질문
• 이미지 대화 앱 시제품 제작

Assess the security of LLM applications and AI agents by tracing inputs, retrieved content, tool calls, and outputs. Covers prompt injection, where content carries unwanted instructions, along with permission misuse, memory poisoning, and supply-chain risks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Testing chatbot resistance to prompt injection
• Auditing agent tool permissions and approval steps
• Checking retrieval access controls and memory poisoning

Build AI applications that answer questions using retrieved documents. Covers vector databases, text embeddings that represent meaning as numbers, search strategies, and result reranking to connect language models with external knowledge.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building Q&A systems for internal documents
• Adding domain knowledge to chatbots
• Implementing natural language document search

Helps speed up LLM text generation by comparing methods that predict and verify multiple tokens at once. Covers draft model selection, Medusa prediction heads, Lookahead Decoding settings, and deployment examples for inference services.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reducing chatbot response latency
• Comparing methods for faster code generation
• Selecting a small draft model for a larger LLM

Develop applications with the Claude API using examples from Anthropic's official cookbooks. Explore document summarization, image analysis, document retrieval, external tool calls, and prompt caching through practical Python code and implementation guidance.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Learning basic Claude API integration
• Building an assistant that searches documents
• Extracting text and information from images

Helps build AI features in Go with Genkit, including text generation, structured data output, streaming, tool calls, and conversational agents. Guides HTTP serving and trace inspection to check model responses and tool execution.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding text generation or structured output to a Go app
• Building a chatbot that retains conversation state
• Connecting model responses to tool calls

Build AI applications in Python with Genkit, including conversational agents, generation workflows, streaming responses, and tool use. The skill also guides setup and debugging through traces, recorded details of model inputs, outputs, and actions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a chatbot that keeps conversation history
• Implement streaming responses and tool calls
• Investigate Genkit import and API errors

Configure OpenTelemetry to send AI application traces, records of execution steps, to Confident AI. Reuse existing exporters, choose the regional endpoint, and add AI-specific attributes without requiring the deepeval Python package.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Send existing AI application traces to Confident AI
• Configure tracing for a non-Python AI application
• Choose the US or EU endpoint for an API key

Add DeepEval tracing to Python AI applications so execution steps appear in Confident AI. Choose a supported integration or manual @observe instrumentation, then capture inputs, outputs, step types, tags, and metadata.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Trace execution steps in a Python AI application
• Select tracing integrations for an existing framework
• Add manual tracing with @observe

Reduce LLM generation delays with speculative decoding, which proposes tokens ahead of verification. This skill compares small draft models, Medusa, and Lookahead Decoding, with implementation examples, tuning guidance, and deployment using vLLM.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reducing response delays in chatbots
• Speeding up code generation
• Choosing a small model to draft candidate tokens

Build and deploy AI agents on Cloudflare Workers using the Agents SDK. Supports persistent conversation state, live WebSocket connections, scheduled tasks, and tool integration, with guidance for connecting browser or React chat interfaces.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a chatbot that preserves conversation history
• Connect a live chat interface through WebSockets
• Schedule reminders and recurring background tasks

Build chat, image generation, and speech transcription features on 0G Compute Network, a distributed GPU marketplace. This skill guides SDK integration, model fine-tuning, response processing for billing, and account funding through code patterns and CLI commands.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Integrating chat and image generation into an application
• Preparing model fine-tuning jobs
• Checking balances and funding provider accounts

Submit shopping questions to Amazon's Alexa/Rufus assistant and collect answers as JSON, a structured data format. Use product search results as context for category research, or run a series of general shopping questions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Collecting product recommendations for a specific category
• Gathering answers to a batch of shopping questions
• Researching deals and shopping trends

Add AI chat, text generation, and agents to applications using AI SDK. The skill checks documentation and source code to guide streaming replies, external tool calls, structured results, React integration, and fixes for outdated API usage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add AI chat to an application
• Build an agent that calls external tools
• Build answers using retrieved documents

Guide a bug bounty investigation from scope checks and asset discovery to vulnerability testing, impact validation, and report writing. Covers web applications, source code, and AI features, with an emphasis on reproducible evidence of real harm.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning an investigation for a new bug bounty target
• Reviewing source code for risky implementation patterns
• Testing web and AI features for security flaws

Guide bug bounty work from asset discovery to validation and reporting, while resolving local locations of security tools, wordlists, and cloned projects. It covers web and AI security testing with an emphasis on demonstrated impact.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Locate installed security tools and wordlists
• Plan reconnaissance within a program's scope
• Investigate related weaknesses and their combined impact

Implement Gemini API applications in Python or TypeScript for text, image, video, and speech generation. Covers ongoing conversations, external tool calls, structured responses, background research, managed agents, and migration from the older generateContent API.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a chatbot that retains conversation context
• Add image, video, or speech generation to an app
• Connect external tools and return structured data

Build Python agents with Agentica SDK using function decorators or agent instances. Examples cover conversation memory, external tools, MCP connections for tool access, multi-agent coordination, typed results, and logging to help implement and debug agent behavior.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add agent behavior to existing Python functions
• Build a chatbot that remembers conversation history
• Connect agents to external tools through MCP

Search this repository's awesome-ChatGPT-repositories list for open-source ChatGPT and LLM projects such as RAG frameworks, agents, chatbots, CLIs, prompts, and browser extensions. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, or AI development; not for editing or adding list entries.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Azure AI Voice Live SDK for JavaScript/TypeScript. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots in Node.js or browser environments. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession", "voice assistant TypeScript", "bidirectional audio", "speech-to-speech JavaScript".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build real-time voice AI applications using Azure AI Voice Live SDK (azure-ai-voicelive). Use this skill when creating Python applications that need real-time bidirectional audio communication with Azure AI, including voice assistants, voice-enabled chatbots, real-time speech-to-speech translation, voice-driven avatars, or any WebSocket-based audio streaming with AI models. Supports Server VAD (Voice Activity Detection), turn-based conversation, function calling, MCP tools, avatar integration, and transcription.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Azure AI Voice Live SDK for .NET. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession", "voice assistant .NET", "bidirectional audio", "speech-to-speech".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

AWS Startups reference content — Activate FAQ, credits guide, programs, partner offers, sample architectures, and hundreds of learn articles spanning generative AI, cloud architecture, cost optimization, security, fundraising, go-to-market, and real-world startup case studies. Use when the user asks factual questions about AWS Activate (eligibility, credits, programs, providers), wants a sample architecture or solution guide, or needs an AWS-curated learn article on a specific startup topic. For copy-paste AI prompts (RAG chatbot, MVP scaffold, security baseline, GPU quota, etc.), see the prompt-library-for-startups skill. Do not use for: account-specific lookups (credits balance, Activate membership status, application status), real-time event listings beyond the events stub, or content not present in the bundled `references/` tree.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.