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32 dépôts

Awesome GitHub RepositoriesLanguage Model Interaction Patterns

Standardized methods and structural patterns for communicating with and executing tasks via language models.

Explore 32 awesome GitHub repositories matching artificial intelligence & ml · Language Model Interaction Patterns. Refine with filters or upvote what's useful.

Awesome Language Model Interaction Patterns GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • anomalyco/opencodeAvatar de anomalyco

    anomalyco/opencode

    175,152Voir sur GitHub↗

    OpenCode is a framework for orchestrating autonomous AI agents within development environments. It provides a multi-tiered architecture where primary assistants manage user interaction while specialized subagents handle specific tasks like planning, research, and code generation. The system includes a comprehensive command-line interface for managing these workflows, configuring agent behavior, and defining custom tools or commands through metadata-rich files. The platform features a modular plugin system and extensive integration support, including standardized protocols for connecting local

    Selects the optimal model for a task by evaluating a hierarchy of command-line flags, configuration files, and historical usage.

    TypeScript
    Voir sur GitHub↗175,152
  • langchain-ai/langchainAvatar de langchain-ai

    langchain-ai/langchain

    139,458Voir sur GitHub↗

    LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows that manage state, memory, and tool execution. The project distinguishes itself through a durable execution runtime that maintains persistent state across long-running processes by checkpointing progress to external storage. It models agent workflows as directed graphs, allowing

    Exposes unified interfaces for initializing and interacting with various chat-based language models.

    Pythonagentsaiai-agents
    Voir sur GitHub↗139,458
  • chatgptnextweb/nextchatAvatar de ChatGPTNextWeb

    ChatGPTNextWeb/NextChat

    88,256Voir sur GitHub↗

    NextChat is a self-hosted web application that provides a unified interface for interacting with multiple large language models. It functions as a conversational platform where users can manage and switch between diverse AI providers through configurable API backends, maintaining full control over their data and infrastructure. The platform features a persistent session layer designed to handle long-running dialogues by managing message history and context. It distinguishes itself through a structured prompt engineering environment that allows for the development and application of templates

    Standardizes communication by routing requests through a single interface capable of switching between diverse language model backends.

    TypeScriptcalclaudechatgptclaude
    Voir sur GitHub↗88,256
  • openhands/openhandsAvatar de OpenHands

    OpenHands/OpenHands

    77,330Voir sur GitHub↗

    OpenHands is an autonomous agent framework designed for software engineering workflows. It provides a modular platform for orchestrating AI agents that reason, plan, and execute tasks within isolated, containerized development environments. By integrating with standard version control and development tools, the system enables agents to autonomously navigate codebases, implement features, and resolve issues through iterative reasoning and tool execution. The platform distinguishes itself through a model-agnostic orchestrator that connects diverse language models to a unified tool registry. It

    Standardizes communication with various language model APIs through unified interfaces that include built-in authentication and retry logic.

    Pythonagentartificial-intelligencechatgpt
    Voir sur GitHub↗77,330
  • xtekky/gpt4freeAvatar de xtekky

    xtekky/gpt4free

    66,335Voir sur GitHub↗

    This project provides a unified interface for interacting with a wide range of artificial intelligence services, acting as a central orchestration layer for text and image generation. It standardizes access to diverse AI backends, allowing developers to integrate multiple language and vision models through a single, consistent programming interface. By abstracting provider-specific protocols and authentication requirements, the tool simplifies the development of applications that rely on external AI services. The platform distinguishes itself through a resilient request routing architecture d

    Enables non-blocking message processing and streaming responses from various artificial intelligence models through a unified interface.

    Pythonchatbotchatbotschatgpt
    Voir sur GitHub↗66,335
  • openinterpreter/open-interpreterAvatar de openinterpreter

    openinterpreter/open-interpreter

    63,998Voir sur GitHub↗

    Open Interpreter is an autonomous agent runtime that translates natural language instructions into executable code to interact with local software and operating systems. It functions as an orchestration framework that connects language models to a secure execution environment, enabling the development of agents capable of managing system resources and performing complex tasks. To ensure safety, the system mandates explicit user verification before executing any generated code and provides robust isolation through containerized sandboxing. The project distinguishes itself through its deep inte

    Orchestrates complex tasks by linking language model outputs to local execution engines for seamless system-level integration.

    Rustchatgptgpt-4interpreter
    Voir sur GitHub↗63,998
  • mintplex-labs/anything-llmAvatar de Mintplex-Labs

    Mintplex-Labs/anything-llm

    61,663Voir sur GitHub↗

    This platform serves as a comprehensive environment for managing private language models, document knowledge bases, and automated agent workflows within secure local infrastructure. It functions as a document-aware workspace that enables users to ingest diverse file formats into searchable repositories, ensuring that all data processing and model inference remain within private, local environments to maintain data sovereignty. The system distinguishes itself through a modular agentic engine that allows for the definition of custom skills and external tool execution. By utilizing a multi-model

    Standardizes communication patterns between diverse language model backends through a unified internal API.

    JavaScriptai-agentscustom-ai-agentsdeepseek
    Voir sur GitHub↗61,663
  • openai/openai-agents-pythonAvatar de openai

    openai/openai-agents-python

    27,191Voir sur GitHub↗

    This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services

    Provides a unified interface for interacting with LLMs, managing tool execution, and handling structured outputs.

    Pythonagentsaiframework
    Voir sur GitHub↗27,191
  • cinnamon/kotaemonAvatar de Cinnamon

    Cinnamon/kotaemon

    25,139Voir sur GitHub↗

    Kotaemon is an orchestration framework designed for building modular, agentic workflows that integrate document processing, retrieval-augmented generation, and multi-step reasoning. It provides a comprehensive platform for developing document-based question answering systems, allowing users to chain language models, prompt templates, and external tools into complex, automated pipelines. The system distinguishes itself through a highly modular architecture that emphasizes component-based composition and schema-driven data exchange. It supports autonomous agents capable of decomposing complex q

    Manages administrative credentials for external data sources and language model providers.

    Pythonchatbotllmsopen-source
    Voir sur GitHub↗25,139
  • vercel/aiAvatar de vercel

    vercel/ai

    21,885Voir sur GitHub↗

    This project is a comprehensive framework for building AI-powered applications, providing a unified toolkit for orchestrating language models, autonomous agents, and interactive user interfaces. It serves as a central library for managing the entire lifecycle of AI interactions, from initial prompt generation and model provider abstraction to complex, multi-step reasoning and tool execution. The framework distinguishes itself through its deep integration with frontend development, specifically by enabling generative user interfaces that render dynamic components directly from model outputs. I

    Create and configure chat, completion, and response-based language models to process text, manage conversations, and enforce structured output schemas.

    TypeScriptanthropicartificial-intelligencegemini
    Voir sur GitHub↗21,885
  • guidance-ai/guidanceAvatar de guidance-ai

    guidance-ai/guidance

    21,502Voir sur GitHub↗

    Guidance is a generative AI orchestration framework designed to manage complex interactions with language models by embedding programmatic control directly into the prompt generation process. It functions as a prompt programming environment that allows developers to interleave raw text with executable logic, enabling the construction of sophisticated, multi-step agentic workflows. The framework distinguishes itself through grammar-constrained token sampling and stateful stream interception, which restrict the model's output distribution based on formal language rules. By enforcing these const

    Embeds logical flow and structured templates into prompt generation to ensure predictable model behavior.

    Jupyter Notebook
    Voir sur GitHub↗21,502
  • github/docsAvatar de github

    github/docs

    18,951Voir sur GitHub↗

    GitHub Copilot is an AI-powered development platform designed to integrate large language models directly into coding environments. It functions as an interactive assistant and an agentic workflow orchestrator, enabling developers to automate code generation, perform automated code reviews, and execute complex, multi-step development tasks through natural language prompts. The platform distinguishes itself through its autonomous agent capabilities, which allow for repository-level research, implementation planning, and code modifications across multiple files. It supports a modular architectu

    Matches specific development needs like coding or reasoning to the most appropriate language model.

    TypeScriptdocsworks-with-codespaces
    Voir sur GitHub↗18,951
  • onyx-dot-app/onyxAvatar de onyx-dot-app

    onyx-dot-app/onyx

    17,491Voir sur GitHub↗

    Onyx is an enterprise-grade AI platform designed for knowledge management, search, and autonomous agent orchestration. It functions as a centralized system that aggregates unstructured organizational data, enabling secure, context-aware retrieval and interaction across internal documents and communication history. By integrating retrieval-augmented generation with multi-model orchestration, the platform provides a unified interface for teams to query internal knowledge bases and execute complex, multi-step business processes. The platform distinguishes itself through a focus on private infras

    Implements standardized interaction patterns for communicating with diverse language models to facilitate collaborative analysis.

    Pythonaiai-chatchatgpt
    Voir sur GitHub↗17,491
  • kvcache-ai/ktransformersAvatar de kvcache-ai

    kvcache-ai/ktransformers

    17,288Voir sur GitHub↗

    Ktransformers is a comprehensive framework designed for the operation, fine-tuning, and serving of large language models. It functions as a heterogeneous inference engine and quantized execution runtime, enabling the deployment of massive models by distributing computational workloads across both CPU and GPU resources. This architecture allows users to bypass local memory constraints, making it possible to run and train models that exceed the capacity of a single device. The project distinguishes itself through specialized support for sparse architectures, particularly mixture-of-experts mode

    Offers an interactive command-line interface for direct chat-based testing and validation of loaded models.

    Python
    Voir sur GitHub↗17,288
  • stackblitz/bolt.newAvatar de stackblitz

    stackblitz/bolt.new

    16,419Voir sur GitHub↗

    bolt.new is an AI-powered full-stack web builder and browser-based IDE that generates, edits, and deploys web applications using natural language prompts. It functions as an AI-driven application orchestrator, managing the entire development lifecycle through a chat interface. The platform distinguishes itself by integrating a WebAssembly-based runtime and virtual terminal emulation directly in the browser. This allows an AI agent to execute tool calls, manage a virtual filesystem, install packages, and run servers without requiring a local development environment. The system covers a compre

    Provides a secure way to store authentication tokens for external language model provider APIs.

    TypeScript
    Voir sur GitHub↗16,419
  • kilo-org/kilocodeAvatar de Kilo-Org

    Kilo-Org/kilocode

    15,616Voir sur GitHub↗

    Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development tasks. It functions as a comprehensive system for automating coding, testing, and repository management by integrating directly with your codebase and terminal. The platform provides a unified gateway for model orchestration, allowing for the management of agentic workflows, event-driven automation, and persistent session state across distributed development environments. The platform distinguishes itself through its federated task management and policy-based access control, which

    Provides options to choose from a variety of local or cloud-based language models to power coding tasks.

    TypeScriptaiai-ageai-coding
    Voir sur GitHub↗15,616
  • libretranslate/libretranslateAvatar de LibreTranslate

    LibreTranslate/LibreTranslate

    15,201Voir sur GitHub↗

    LibreTranslate is an open-source, self-hosted machine translation engine that provides a private alternative to proprietary cloud-based translation services. It functions as a portable translation server, allowing users to process text and document translations locally or within their own infrastructure without relying on external providers. The platform distinguishes itself through its focus on privacy and flexible deployment, supporting anonymous network routing to bypass restrictive firewalls and protect user data. It is designed for integration into broader software ecosystems, offering a

    Manages the loading and availability of specific translation models.

    Pythonapimachinetranslate
    Voir sur GitHub↗15,201
  • chiphuyen/aie-bookAvatar de chiphuyen

    chiphuyen/aie-book

    13,779Voir sur GitHub↗

    This project serves as a comprehensive educational resource and technical handbook for engineers building applications powered by large language models. It provides a structured framework for mastering the principles of artificial intelligence engineering, covering the full lifecycle of model development from initial design to production deployment. The repository distinguishes itself by offering a deep dive into the practical implementation of advanced design patterns, including retrieval-augmented generation, agentic tool orchestration, and parameter-efficient model adaptation. It emphasize

    Implements standardized methods and structural patterns for communicating with and executing tasks via language models.

    Jupyter Notebook
    Voir sur GitHub↗13,779
  • mistralai/mistral-inferenceAvatar de mistralai

    mistralai/mistral-inference

    10,819Voir sur GitHub↗

    Mistral Inference is a library for running Mistral large language models on a GPU, generating text from prompts with token streaming. It loads pretrained model weights from local disk or a remote registry into GPU memory, then produces output tokens one by one for real-time display in interactive applications. The library supports multimodal prompts that accept image URLs alongside text, enabling visual description and reasoning. It includes content safety guardrails that scan generated text against predefined policies to block or flag policy violations. For structured interactions, it provid

    Provides a command-line session that accepts user prompts and streams model responses.

    Jupyter Notebookllmllm-inferencemistralai
    Voir sur GitHub↗10,819
  • facebookresearch/parlaiAvatar de facebookresearch

    facebookresearch/ParlAI

    10,625Voir sur GitHub↗

    ParlAI is a conversational AI research framework designed for training, evaluating, and sharing dialogue models using a unified interface for datasets and agents. It functions as a PyTorch-based training platform and a dialogue data collection system, providing a centralized model zoo for the distribution of versioned pretrained agents. The project distinguishes itself through a knowledge-grounded retrieval system that combines dense and sparse indexing to ground responses in external information. It also provides a comprehensive infrastructure for gathering human-AI interaction data via inte

    Defines interaction loops and environments to manage how multiple agents exchange messages in sequences or batches.

    Python
    Voir sur GitHub↗10,625
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  1. Home
  2. Artificial Intelligence & ML
  3. Language Model Orchestration
  4. Language Model Interaction Patterns

Explorer les sous-tags

  • Asynchronous Chat CompletionsNon-blocking interfaces for streaming or batch processing of conversational model responses.
  • Chat Model Interfaces1 sous-tagUnified abstractions for interacting with chat-based LLMs.
  • Deterministic Interaction Patterns1 sous-tagStructural patterns for enforcing consistency and minimizing hallucinations in model outputs. **Distinct from Language Model Interaction Patterns:** Focuses on architectural consistency in LLM interactions, distinct from general interaction patterns.
  • LLM Provider AdaptersStandardized interfaces for communicating with different language model APIs including authentication and retry logic.
  • Language Model Tooling3 sous-tagsUtilities and management tools required to configure and secure access to language model services.