sigoden/aichat
All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI Tools & Agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
Repository profile
A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS
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Latest capture 2026-07-02 03:10
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Scanned 2026-07-02 03:10
package.json
javascript ecosystem,
48 dependencies
pyproject.toml
python ecosystem,
29 dependencies
package-lock.json
javascript ecosystem,
742 dependencies
lib/shared/file-import-batch-job/requirements.txt
python ecosystem,
19 dependencies
lib/shared/web-crawler-batch-job/requirements.txt
python ecosystem,
20 dependencies
lib/user-interface/react-app/package.json
javascript ecosystem,
42 dependencies
lib/user-interface/react-app/package-lock.json
javascript ecosystem,
0 dependencies
lib/rag-engines/sagemaker-rag-models/model/requirements.txt
python ecosystem,
0 dependencies
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All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI Tools & Agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
One delightful Ruby framework for every major AI provider. Build AI agents, chatbots, RAG apps, and multimodal workflows in beautiful, expressive code.
The collaborative spreadsheet for AI. Chain cells into powerful pipelines, experiment with prompts and models, and evaluate LLM responses in real-time. Work together seamlessly to build and iterate on AI applications.
OpenAI-Compatible RESTful APIs for Amazon Bedrock
A Solution Accelerator for the RAG pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. This includes most common requirements and best practices.
Deploy any AI model, agent, database, RAG, and pipeline locally or remotely in minutes