[integration]: ChatLinkrra (langchain-linkrra)
Maintainers usually reply within 1 day
Nobody has claimed this yet.
Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 68/100
- Issue type
- Documentation
- Clarity
- Mostly clear
- Activity status
- Active
- Tech stack
- python
- Domain
- documentation
Research direction
Read the integration contribution guidance in the LangChain docs repository and follow the docs structure for chat model integrations. The issue provides the provider details and links to the package README as source material; use those to determine the documentation entry point. Done means adding accurate integration documentation for ChatLinkrra and its listed capabilities.
Written by the indexing model from the issue text.
Description
Display or class name
ChatLinkrra
Language
Python
Component type
chat
PyPI package name
langchain-linkrra
npm package name
No response
Docs URL
https://github.com/weare-linkrra/linkrra-synap/tree/main/langchain-linkrra#readme
Source repository
weare-linkrra/linkrra-synap
Short provider description
Chat model for Linkrra Synap, an OpenAI-compatible API serving open-weight models such as Qwen3 Coder, gpt-oss-20b and Gemma 4.
Capability flags (optional)
stream: true
tool_calling: true
structured_output: true
token_usage: true
async: true
Confirmations
- The package is already published on PyPI and/or npm.
Checked against the live API on 2026-11-11 with langchain-linkrra 0.1.0, langchain-openai 1.7.4 and langchain-core 1.8.0: invoke, stream, ainvoke, bind_tools (tool call returned) and with_structured_output on qwen3-coder-30b and gpt-oss-20b. Note: this is unrelated to the separate "Synap" memory product that already has LangChain docs, which is why the package uses the linkrra name. Disclosure: I work on Linkrra.
- Dominant language
- MDX
- Stars
- 444
- Forks
- 2.8k
- Avg merge
- 23h 53m
- Merged PRs (30d)
- 671
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
More from langchain-ai/docs
-
external
Difficulty 2/5 1-3 hours Newbie friendliness 65/100
langchain-ai/docs#7652 ·
Maintainers usually reply within 1 day
-
external
Difficulty 2/5 1-3 hours Newbie friendliness 68/100
langchain-ai/docs#7651 ·
Maintainers usually reply within 1 day
-
external
Difficulty 2/5 1-3 hours Newbie friendliness 64/100
langchain-ai/docs#7643 ·
Maintainers usually reply within 1 day
-
external integration integration-submission
Difficulty 2/5 1-3 hours Newbie friendliness 70/100
langchain-ai/docs#7633 ·
Maintainers usually reply within 1 day
-
Outdated models in LangSmith onboarding snippetsPossibly taken A pull request linked to this issue is open or already merged. Open
Difficulty 1/5 1-3 hours Newbie friendliness 88/100
langchain-ai/docs#7532 ·
Maintainers usually reply within 1 day
All issues in langchain-ai/docs
Similar issues
-
Difficulty 1/5 1-3 hours Newbie friendliness 76/100
theforeman/foreman-documentation#5687 ·
Maintainers usually reply within 2 days
-
Difficulty 2/5 1-3 hours Newbie friendliness 66/100
SasanLabs/VulnerableApp#912 ·
Maintainers usually reply within 1 day
-
docs: qualify copied and custom kubectl debug policy notesPossibly taken @nym01 claimed this today. Open
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
kubescape/cel-admission-library#166 · 1 comment ·
Maintainers usually reply within 1 day
-
sync-en
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
Maintainers usually reply within 1 day
-
[Sync EN] Formatting improvements to "Large Objects (LOBs)" docs (#6056)Possibly taken A pull request linked to this issue is open or already merged. Opensync-en
Difficulty 1/5 Under an hour Newbie friendliness 74/100
Maintainers usually reply within 1 day