Convo-UI vs Langfuse

Langfuse focuses on observability for LLM apps, not UI rendering.

Side by side

What it is: Convo-UI:Convo-UI is an open-source chatbot UI template that supports multiple chats, auth, theming, markdown tables, custom backends and streaming.; Langfuse:Langfuse is an open-source platform for tracing, evaluating and monitoring LLM applications and AI agents.
Best for: Convo-UI:Multi-chat UI with backend streaming; Langfuse:LLM observability & analytics
Who it’s for: Convo-UI:Frontend developers building chat interfaces with OpenAI or custom models.; Langfuse:Developers building, debugging and scaling LLM-based apps and agents.
Pricing: Convo-UI:Open source; Langfuse:Freemium
Plans: Convo-UI:—; Langfuse:Hobby Free · Core $29 per month · Pro $199 per month · Enterprise $2499 per month
Open source: Convo-UI:Yes, 20 GitHub stars; Langfuse:Yes, 35,097 GitHub stars
Works with: Convo-UI:OpenAI API, Flask, Langserve; Langfuse:Python, TypeScript, Go, Java, .NET, Ruby, PHP, Swift
DevHunt upvotes: Convo-UI:3; Langfuse:89
Launched on DevHunt: Convo-UI:Aug 2025; Langfuse:Jan 2023

Multiple Conversations. Stores several chats locally via localStorage and links them to authentication keys.
OpenAI API Key Auth. Integrates authentication using OpenAI API keys without persisting them on the server.
Dark/Light Mode. Automatically follows system theme or can be toggled manually.
Markdown Table Rendering. Parses and displays markdown tables cleanly, matching OpenAI's UI.
Custom Backend Integration. Provides examples for calling Flask or Langserve backends and selecting them in the UI.
Streaming Outputs. Supports streaming responses from both foundation and custom backend models.

Hierarchical Traces. Capture every LLM call, tool invocation and retrieval step with filters for user, session, cost and latency.
Prompt Management. Version, fetch, release and cache prompts separately from code with one-click deployments.
Evaluation Engine. Run LLM-as-judge, heuristic or human-review evaluations on production data or experiments.
Experiments & Datasets. Define test cases, run experiments and create golden datasets for continuous improvement.
Dashboards & Alerts. Monitor cost, latency and quality via custom dashboards and automated alerts.
Human Annotation. Collaborative human-in-the-loop workflows with annotation queues.
Extensive Integrations. Supports Python, TypeScript, Go, Java, .NET, Ruby, PHP, Swift and 100+ agent frameworks and model providers.
Self-hosted & Cloud Options. Available as hosted SaaS or self-hosted under MIT license.

Based on each tool's website and DevHunt data. Details may change; check the official sites.