Langchain-Chatchat vs WeKnora
Short answer
Langchain-Chatchat: Chinese-first local knowledge-base Q&A and agent app built on LangChain, wired to local model servers. WeKnora: Tencent's open-source knowledge-base and agent platform with document parsing, RAG and team workspaces. Both are in our Knowledge base & RAG category.
Choose WeKnora if you want: an actively maintained project (Langchain-Chatchat is stale).
Langchain-Chatchat publishes no official RAM figure, so we cannot compare hosting cost directly.
Last updated · computed from each project's official docs and live GitHub data · sources
Langchain-Chatchat vs WeKnora side by side
| Langchain-Chatchat | WeKnora | |
|---|---|---|
| Category | Knowledge base & RAG | Knowledge base & RAG |
| What it is | Chinese-first local knowledge-base Q&A and agent app built on LangChain, wired to local model servers. | Tencent's open-source knowledge-base and agent platform with document parsing, RAG and team workspaces. |
| License | Apache-2.0 | MIT (with third-party components) |
| License type | Permissive | Permissive |
| License conditions | Permissive. Internal and commercial use allowed. Models keep their own licenses. | MIT for WeKnora itself; bundled third-party components keep their own licenses, listed in the LICENSE file. Internal and commercial use allowed. |
| Status | Stale (no commit in 180+ days) | Active |
| GitHub stars | 38.7k | 36.1k |
| Last commit | Nov 10, 2025 | Oct 30, 2026 |
| Latest release | v0.3.1 | v0.9.0 |
| Minimum hardware | Not published | Not published |
| Recommended hardware | Not published | 4 vCPU · 8 GB RAM |
| RAM measured by us | Not tested yet | Not tested yet |
| GPU | Not required by the app itself. Since 0.3.0 hardware depends on the model server you connect; the docs say it can run on CPU, GPU, NPU or MPS. The Docker Compose guide pairs it with Xinference and assumes the NVIDIA Container Toolkit. | Not required. Local models run through Ollama or another model service you configure. |
| Est. server cost | Not estimated | from €35.99/mo |
| Deploy method | pip (or Docker Compose with Xinference) | Docker Compose |
| Known gotchas | 5 listed | 4 listed |
| Telemetry | Not documented | Not documented |
| Calls home by default | Not documented | Not documented |
| SSO (OIDC / SAML / LDAP) | Not documented | Free (OIDC free) |
| Audit log | Not documented | Yes, free |
| RBAC | Not documented | Yes, free |
| Details | Full Langchain-Chatchat guide → | Full WeKnora guide → |
Key differences
- License: Langchain-Chatchat: Apache-2.0 (Permissive). WeKnora: MIT (with third-party components) (Permissive).
- Official hardware: Langchain-Chatchat: not published. WeKnora: recommended 4 vCPU · 8 GB RAM (no separate minimum published).
- Est. server cost: Langchain-Chatchat: not estimated (no official RAM figure). WeKnora: from €35.99/mo.
- Deploy: Langchain-Chatchat: pip (or Docker Compose with Xinference) · multi-container stack. WeKnora: Docker Compose · multi-container stack.
- Status: Langchain-Chatchat: Stale (no commit in 180+ days). WeKnora: Active.
- GitHub stars: Langchain-Chatchat: 38.7k. WeKnora: 36.1k.
- Last commit: Langchain-Chatchat: Nov 10, 2025. WeKnora: Oct 30, 2026.
- Latest release: Langchain-Chatchat: v0.3.1 (Jul 12, 2024). WeKnora: v0.9.0 (Oct 29, 2026).
Same for both: Category: Knowledge base & RAG; GPU: optional / see notes.
Langchain-Chatchat vs WeKnora: FAQ
Langchain-Chatchat or WeKnora: which should a small business choose?
Choose WeKnora if you want: an actively maintained project (Langchain-Chatchat is stale). Langchain-Chatchat publishes no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, Langchain-Chatchat or WeKnora?
Langchain-Chatchat: not estimated (no official RAM figure). WeKnora: from €35.99/mo. Our estimate is the cheapest Hetzner Cloud plan that meets each project's official RAM and vCPU figure; it covers the server only.
How much hardware do Langchain-Chatchat and WeKnora need?
Langchain-Chatchat: not published. WeKnora: recommended 4 vCPU · 8 GB RAM (no separate minimum published).
What is the license difference between Langchain-Chatchat and WeKnora?
Langchain-Chatchat: Apache-2.0 (Permissive). Permissive. Internal and commercial use allowed. Models keep their own licenses. WeKnora: MIT (with third-party components) (Permissive). MIT for WeKnora itself; bundled third-party components keep their own licenses, listed in the LICENSE file. Internal and commercial use allowed. This is a summary, not legal advice.
Is Langchain-Chatchat or WeKnora more actively maintained?
Langchain-Chatchat: Stale (no commit in 180+ days), last commit Nov 10, 2025. WeKnora: Active, last commit Oct 30, 2026. GitHub data refreshed Oct 31, 2026.
Which is easier to deploy, Langchain-Chatchat or WeKnora?
Langchain-Chatchat installs via pip (or Docker Compose with Xinference) (multi-container stack); WeKnora via Docker Compose (multi-container stack). Langchain-Chatchat lists 5 known gotchas and WeKnora lists 4; see each app page.
Related
- Langchain-Chatchat self-hosting guide · WeKnora self-hosting guide
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Sources
- Langchain-Chatchat GitHub repository: github.com/chatchat-space/Langchain-Chatchat
- Langchain-Chatchat documentation: github.com/chatchat-space/Langchain-Chatchat#readme
- Langchain-Chatchat license: github.com/chatchat-space/Langchain-Chatchat/blob/master/LICENSE
- Langchain-Chatchat hardware requirements: github.com/chatchat-space/Langchain-Chatchat#0-软硬件要求
- Langchain-Chatchat deploy instructions: github.com/chatchat-space/Langchain-Chatchat#pip-安装部署
- WeKnora GitHub repository: github.com/Tencent/WeKnora
- WeKnora documentation, WeKnora hardware requirements, WeKnora deploy instructions: weknora.weixin.qq.com/docs/01-getting-started/02-installation
- WeKnora license: github.com/Tencent/WeKnora/blob/main/LICENSE
- Hetzner Cloud pricing used for cost estimates (read 2026-10-25): www.hetzner.com/cloud/regular-performance
- GitHub REST API (stars, commits, releases): docs.github.com/en/rest
Every value is generated from the same verified data as the app pages. Spotted something wrong? Tell us.