siliconflow/silicondata

siliconflow/silicondata

Description: baseon langfuse: 🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with LlamaIndex, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

Language: TypeScript

License: NOASSERTION

Stars: 0

Forks: 1

Open issues: 0

Created: 2024-12-12T11:01:28Z

Pushed: 2025-01-06T11:02:52Z

Default branch: main

Fork: yes

Parent repository: langfuse/langfuse

Archived: no

README: !Langfuse GitHub Banner

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Langfuse uses Github Discussions for Support and Feature Requests.

We're hiring. Join us in Product Engineering and Developer Relations.

Langfuse Overview

_Unmute video for voice-over_

https://github.com/langfuse/langfuse/assets/2834609/a94062e9-c782-4ee9-af59-dee6370149a8

Develop

• LLM Observability: Instrument your app and start ingesting traces to Langfuse (Quickstart, Integrations Tracing)
• Langfuse UI: Inspect and debug complex logs (Demo, Tracing)
• Prompt Management: Manage, version and deploy prompts from within Langfuse (Prompt Management)
• Prompt Engineering: Test and iterate on your prompts with the LLM Playground

Monitor

• LLM Analytics: Track metrics (cost, latency, quality) and gain insights from dashboards & data exports (Analytics)
• LLM Evaluations: Collect and calculate scores for your LLM completions (Scores & Evaluations)
• Run (Model-based evaluations) and LLM-as-a-Judge within Langfuse
• Collect user feedback (User Feedback)
• Manually score LLM outputs in Langfuse (Manual Scores)

Test

• Experiments: Track and test app behaviour before deploying a new version
• Datasets let you test expected in and output pairs and benchmark performance before deploying (Datasets)
• Track versions and releases in your application (Experimentation, Prompt Management)

Get started

Langfuse Cloud

Managed deployment by the Langfuse team, generous free-tier (hobby plan), no credit card required.

[» Langfuse Cloud](https://cloud.langfuse.com)

Self-Hosting Open Source LLM Observability with Langfuse

Localhost (docker)

# Clone repository
git clone https://github.com/langfuse/langfuse.git
cd langfuse

# Run server and database
docker compose up -d

→ Learn more about deploying locally

Self-host (docker)

Langfuse is simple to self-host and keep updated. It currently requires only a single docker container and a postgres database. → Self Hosting Instructions

Templated deployments: Railway, GCP, AWS, Azure, Kubernetes and others

Get Started

API Keys

You need a Langfuse public and secret key to get started. Sign up here and find them in your project settings.

Ingesting Data · Instrumenting Your Application · LLM Observability with Langfuse

Note: We recommend using our fully async, typed SDKs that allow you to instrument any LLM application with any underlying model. They are available in Python (Decorators) & JS/TS. The SDKs will always be the most fully featured and stable way to ingest data into Langfuse.

See the → Quickstart to integrate Langfuse.

LLM Observability Integrations

| Integration | Supports | Description | | ---------------------------------------------------------------------------- | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | | SDK | Python, JS/TS | Manual instrumentation using the SDKs for full flexibility. | | OpenAI | Python, JS/TS | Automated instrumentation using drop-in replacement of OpenAI SDK. | | Langchain | Python, JS/TS | Automated instrumentation by passing callback handler to Langchain application. | | LlamaIndex | Python | Automated instrumentation via LlamaIndex callback system. | | Haystack | Python | Automated instrumentation via Haystack content tracing system. | | LiteLLM | Python, JS/TS (proxy only) | Use any LLM as a drop in replacement for GPT. Use Azure, OpenAI, Cohere, Anthropic, Ollama, VLLM, Sagemaker, HuggingFace, Replicate (100+ LLMs). | | Vercel AI SDK | JS/TS | TypeScript toolkit designed to help developers build AI-powered applications with React, Next.js, Vue, Svelte, Node.js. | | API | | Directly call the public API. OpenAPI spec available. |

Packages integrated with Langfuse:

| Name | Description | | --------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------- | | Instructor | Library to get structured LLM outputs (JSON, Pydantic) | | Dify | Open source LLM app development platform with no-code builder. | | Ollama | Easily run open source LLMs on your own machine. | |…