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| title: ChatFed Re-Ranker Service | |
| emoji: 🤖 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: docker | |
| pinned: false | |
| license: mit | |
| # ReRanker Module | |
| This is an LLM-based generation service designed to be deployed as a modular component of a broader RAG system. The service runs on a docker container and exposes a gradio UI on port 7860 as well as an MCP endpoint. | |
| ## Configuration | |
| 1. The module requires an API key (set as an environment variable) for a model provider to run. Make sure to set the appropriate environment variables: | |
| - HuggingFace: `HF_TOKEN` | |
| 2. Inference provider and model settings are accessible via params.cfg | |
| ## MCP Endpoint | |
| ### Available Tools | |
| #### `rerank_context` | |
| Re-ranks a list of context dicts (each with 'page_content' & 'metadata') using a cross-encoder and returns the top_n sorted results. | |
| **Input Schema:** | |
| | Parameter | Type | Description | | |
| |-----------|------|-------------| | |
| | `query` | string | The search query to rank contexts against | | |
| | `contexts` | string | List of context dictionaries to be re-ranked | | |
| **Example Usage:** | |
| ```json | |
| { | |
| "query": "your search query here", | |
| "contexts": "your context data here" | |
| } | |
| ``` | |
| --- | |
| *This tool uses a cross-encoder model to improve the relevance ranking of retrieved contexts based on their similarity to the input query.* | |