Bump huggingface-hub from 0.31.1 to 0.32.2 in /requirements
Type: Pull Request
State: Open
Association: Contributor
Comments: 2
(6 months ago)
(6 months ago)
dependencies python
Bumps huggingface-hub from 0.31.1 to 0.32.2.
Release notes
Sourced from huggingface-hub's releases.
[v0.32.2]: Add endpoint support in Tiny-Agent + fix
snapshot_downloadon large reposFull Changelog: https://github.com/huggingface/huggingface_hub/compare/v0.32.1...v0.32.2
- [MCP] Add local/remote endpoint inference support huggingface/huggingface_hub#3121
- Fix snapshot_download on very large repo (>50k files) huggingface/huggingface_hub#3122
[v0.32.1]: hot-fix: Fix tiny agents on Windows
Patch release to fix #3116
Full Changelog: https://github.com/huggingface/huggingface_hub/compare/v0.32.0...v0.32.1
[v0.32.0]: MCP Client, Tiny Agents CLI and more!
🤖 Powering LLMs with Tools: MCP Client & Tiny Agents CLI
✨ The
huggingface_hublibrary now includes an MCP Client, designed to empower Large Language Models (LLMs) with the ability to interact with external Tools via Model Context Protocol (MCP). This client extends theInfrenceClientand provides a seamless way to connect LLMs to both local and remote tool servers!pip install -U huggingface_hub[mcp]In the following example, we use the Qwen/Qwen2.5-72B-Instruct model via the Nebius inference provider. We then add a remote MCP server, in this case, an SSE server which makes the Flux image generation tool available to the LLM:
import osfrom huggingface_hub import ChatCompletionInputMessage, ChatCompletionStreamOutput, MCPClient
async def main(): async with MCPClient( provider="nebius", model="Qwen/Qwen2.5-72B-Instruct", api_key=os.environ["HF_TOKEN"], ) as client: await client.add_mcp_server(type="sse", url="https://evalstate-flux1-schnell.hf.space/gradio_api/mcp/sse") messages = [ { "role": "user", "content": "Generate a picture of a cat on the moon", } ] async for chunk in client.process_single_turn_with_tools(messages): # Log messages if isinstance(chunk, ChatCompletionStreamOutput): delta = chunk.choices[0].delta if delta.content: print(delta.content, end="")
# Or tool calls elif isinstance(chunk, ChatCompletionInputMessage): print( f"\nCalled tool '{chunk.name}'. Result: '{chunk.content if len(chunk.content) < 1000 else chunk.content[:1000] + '...'}'" )</tr></table>
... (truncated)
Commits
6dd0164Release: v0.32.26f09ac7Fix snapshot_download on very large repo (>50k files) (#3122)b70c474[MCP] Add local/remote endpoint inference support (#3121)5add979Release: v0.32.17ea6e48[MCP] fix tiny-agents on Windows (#3116)a97424fRelease: v0.32.0e9177ebRelease: v0.32.0.rc10b9c9ee[MCP] better tiny-agents CLI help (#3105)3765848Release: v0.32.0.rc09f34fb8Release: v0.32.O.rc0- Additional commits viewable in compare view
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Pull Request Statistics
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Package Dependencies
huggingface-hub
pip
0.31.1 → 0.32.2
Minor
/requirements
Technical Details
| ID: | 701449 |
| UUID: | 3095701418 |
| Node ID: | PR_kwDOClTaK86X4Hhx |
| Host: | GitHub |
| Repository: | qubvel-org/segmentation_models.pytorch |