The most widely used open-source framework for building LLM applications — chains, agents, RAG, and integrations.
LangChain — The most widely used open-source framework for building LLM applications — chains, agents, RAG, and integrations. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the llm frameworks segment with a focused feature set. Buyers researching llm frameworks options will find LangChain a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Llm Frameworks
⭐ 138,040 stars
python framework open-source rag
Data framework for LLM apps — connect, structure, and query private data with agentic RAG workflows.
LlamaIndex — Data framework for LLM apps — connect, structure, and query private data with agentic RAG workflows. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the llm frameworks segment with a focused feature set. Buyers researching llm frameworks options will find LlamaIndex a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Llm Frameworks
⭐ 49,775 stars
python rag data-indexing open-source
Unified API layer for 100+ LLMs — call any model with OpenAI-compatible syntax; load balancing and fallbacks.
LiteLLM — Unified API layer for 100+ LLMs — call any model with OpenAI-compatible syntax; load balancing and fallbacks. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the routing proxy segment with a focused feature set. Buyers researching routing proxy options will find LiteLLM a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Routing Proxy
⭐ 48,755 stars
proxy multi-model openai-compatible open-source
Stanford framework for programming LLMs — automated prompt optimization replaces hand-crafted prompt engineering.
DSPy — Stanford framework for programming LLMs — automated prompt optimization replaces hand-crafted prompt engineering. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the llm frameworks segment with a focused feature set. Buyers researching llm frameworks options will find DSPy a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Llm Frameworks
⭐ 34,733 stars
python stanford prompt-optimization open-source
Microsoft's guidance-ai library — constrain and control LLM generation with a programmatic templating language.
Guidance — Microsoft's guidance-ai library — constrain and control LLM generation with a programmatic templating language. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the llm frameworks segment with a focused feature set. Buyers researching llm frameworks options will find Guidance a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Llm Frameworks
⭐ 21,484 stars
python constrained-generation microsoft open-source
Structured text generation library — constrain LLM outputs to specific formats using regex and JSON schemas.
Outlines — Structured text generation library — constrain LLM outputs to specific formats using regex and JSON schemas. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the llm frameworks segment with a focused feature set. Buyers researching llm frameworks options will find Outlines a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Llm Frameworks
⭐ 13,905 stars
python structured-generation regex open-source
Python library for structured LLM outputs using Pydantic — turn LLM responses into type-safe objects reliably.
Instructor — Python library for structured LLM outputs using Pydantic — turn LLM responses into type-safe objects reliably. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the llm frameworks segment with a focused feature set. Buyers researching llm frameworks options will find Instructor a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Llm Frameworks
⭐ 13,069 stars
python structured-output pydantic open-source
ML experiment tracking and LLM observability — W&B Weave for LLM trace logging, evals, and dataset management.
Weights & Biases — ML experiment tracking and LLM observability — W&B Weave for LLM trace logging, evals, and dataset management. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the observability segment with a focused feature set. Buyers researching observability options will find Weights & Biases a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Observability
⭐ 11,093 stars
mlops experiment-tracking eval fine-tuning
Open-source LLM observability platform from Arize — traces, evals, and prompt playground in one tool.
Phoenix (Arize) — Open-source LLM observability platform from Arize — traces, evals, and prompt playground in one tool. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the observability segment with a focused feature set. Buyers researching observability options will find Phoenix (Arize) a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Observability
⭐ 9,918 stars
observability tracing evals open-source
Open-source framework for adding safety guardrails to LLM outputs — validate, structure, and correct AI responses.
Guardrails AI — Open-source framework for adding safety guardrails to LLM outputs — validate, structure, and correct AI responses. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the guardrails segment with a focused feature set. Buyers researching guardrails options will find Guardrails AI a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Guardrails
⭐ 6,944 stars
guardrails validation python open-source
LLM observability platform — one-line integration for logging, caching, rate limits, and cost tracking.
Helicone — LLM observability platform — one-line integration for logging, caching, rate limits, and cost tracking. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the observability segment with a focused feature set. Buyers researching observability options will find Helicone a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Observability
⭐ 5,755 stars
observability logging caching open-source
Enterprise AI evaluation and observability — run evals, trace LLM calls, and monitor production AI quality.
Braintrust — Enterprise AI evaluation and observability — run evals, trace LLM calls, and monitor production AI quality. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the observability segment with a focused feature set. Buyers researching observability options will find Braintrust a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Observability
eval observability tracing enterprise
Unified API for accessing 200+ AI models from a single endpoint — route to best model by price, speed, or quality.
OpenRouter — Unified API for accessing 200+ AI models from a single endpoint — route to best model by price, speed, or quality. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the routing proxy segment with a focused feature set. Buyers researching routing proxy options will find OpenRouter a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Routing Proxy
proxy multi-model api routing
AI gateway with routing, caching, observability, and guardrails — drop-in middleware for LLM API calls.
Portkey — AI gateway with routing, caching, observability, and guardrails — drop-in middleware for LLM API calls. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the routing proxy segment with a focused feature set. Buyers researching routing proxy options will find Portkey a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Routing Proxy
proxy multi-model observability caching
Prompt management and LLM request logging — version prompts, track costs, and replay LLM requests.
PromptLayer — Prompt management and LLM request logging — version prompts, track costs, and replay LLM requests. Built primarily for teams and organizations evaluating solutions in this market, the platform addresses common pain points in the prompt management segment with a focused feature set. Buyers researching prompt management options will find PromptLayer a relevant candidate to include in their evaluation, particularly when comparing capabilities, pricing models, and integration depth against competing platforms in the same category.
Prompt Management
prompt-management logging versioning collaboration