| Name | llama-index-packs-fuzzy-citation JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | |
| Summary | llama-index packs fuzzy_citation integration |
| upload_time | 2024-02-10 23:14:43 |
| maintainer | |
| docs_url | None |
| author | Your Name |
| requires_python | >=3.8.1,<3.12 |
| license | MIT |
| keywords |
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| VCS |
|
| bugtrack_url |
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| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
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# Fuzzy Citation Query Engine Pack
Creates and runs a `CustomQueryEngine` -- `FuzzCitationQueryEngine` -- which post-processes response objects to identify source sentences using fuzzy matching.
The identified sentences are available in the `response.metadata` dictionary, containing a mapping of `(response_sentence, source_chunk)` -> `{"start_char_idx": idx, "end_char_idx": idx, "node" node}`. The start/end idxs represent the character indexes in the node text that the source chunk comes from.
The fuzzy matching uses `fuzz.ratio()` to compare sentences. The default threshold score is 50.
## CLI Usage
You can download llamapacks directly using `llamaindex-cli`, which comes installed with the `llama-index` python package:
```bash
llamaindex-cli download-llamapack FuzzyCitationEnginePack --download-dir ./fuzzy_citation_pack
```
You can then inspect the files at `./fuzzy_citation_pack` and use them as a template for your own project!
## Code Usage
You can download the pack to a the `./fuzzy_citation_pack` directory:
```python
from llama_index import Document, VectorStoreIndex
from llama_index.core.llama_pack import download_llama_pack
# download and install dependencies
FuzzyCitationEnginePack = download_llama_pack(
"FuzzyCitationEnginePack", "./fuzzy_citation_pack"
)
index = VectorStoreIndex.from_documents([Document.example()])
query_engine = index.as_query_engine()
fuzzy_engine = FuzzyCitationEnginePack(query_engine, threshold=50)
```
The `run()` function is a light wrapper around `query_engine.query()`. The response will have metadata attached to it indicating the fuzzy citations.
```python
response = fuzzy_engine.run("What can you tell me about LLMs?")
# print source sentences
print(response.metadata.keys())
# print full source sentence info
print(response.metadata)
```
See the [notebook on llama-hub](https://github.com/run-llama/llama-hub/blob/main/llama_hub/llama_packs/fuzzy_citation/fuzzy_citation_example.ipynb) for a full example.
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"description": "# Fuzzy Citation Query Engine Pack\n\nCreates and runs a `CustomQueryEngine` -- `FuzzCitationQueryEngine` -- which post-processes response objects to identify source sentences using fuzzy matching.\n\nThe identified sentences are available in the `response.metadata` dictionary, containing a mapping of `(response_sentence, source_chunk)` -> `{\"start_char_idx\": idx, \"end_char_idx\": idx, \"node\" node}`. The start/end idxs represent the character indexes in the node text that the source chunk comes from.\n\nThe fuzzy matching uses `fuzz.ratio()` to compare sentences. The default threshold score is 50.\n\n## CLI Usage\n\nYou can download llamapacks directly using `llamaindex-cli`, which comes installed with the `llama-index` python package:\n\n```bash\nllamaindex-cli download-llamapack FuzzyCitationEnginePack --download-dir ./fuzzy_citation_pack\n```\n\nYou can then inspect the files at `./fuzzy_citation_pack` and use them as a template for your own project!\n\n## Code Usage\n\nYou can download the pack to a the `./fuzzy_citation_pack` directory:\n\n```python\nfrom llama_index import Document, VectorStoreIndex\nfrom llama_index.core.llama_pack import download_llama_pack\n\n# download and install dependencies\nFuzzyCitationEnginePack = download_llama_pack(\n \"FuzzyCitationEnginePack\", \"./fuzzy_citation_pack\"\n)\n\nindex = VectorStoreIndex.from_documents([Document.example()])\nquery_engine = index.as_query_engine()\n\nfuzzy_engine = FuzzyCitationEnginePack(query_engine, threshold=50)\n```\n\nThe `run()` function is a light wrapper around `query_engine.query()`. The response will have metadata attached to it indicating the fuzzy citations.\n\n```python\nresponse = fuzzy_engine.run(\"What can you tell me about LLMs?\")\n\n# print source sentences\nprint(response.metadata.keys())\n\n# print full source sentence info\nprint(response.metadata)\n```\n\nSee the [notebook on llama-hub](https://github.com/run-llama/llama-hub/blob/main/llama_hub/llama_packs/fuzzy_citation/fuzzy_citation_example.ipynb) for a full example.\n",
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