server : add docs

common/arg.cpp

@@ -1093,7 +1093,7 @@ gpt_params_context gpt_params_parser_init(gpt_params & params, llama_example ex,
         }
     ).set_sparam());
     add_opt(llama_arg(
-        {"--pooling"}, "{none,mean,cls,last, rank}",
+        {"--pooling"}, "{none,mean,cls,last,rank}",
         "pooling type for embeddings, use model default if unspecified",
         [](gpt_params & params, const std::string & value) {
             /**/ if (value == "none") { params.pooling_type = LLAMA_POOLING_TYPE_NONE; }

examples/server/README.md

@@ -7,6 +7,7 @@ Set of LLM REST APIs and a simple web front end to interact with llama.cpp.
 **Features:**
  * LLM inference of F16 and quantized models on GPU and CPU
  * [OpenAI API](https://github.com/openai/openai-openapi) compatible chat completions and embeddings routes
+ * Reranking endoint (WIP: https://github.com/ggerganov/llama.cpp/pull/9510)
  * Parallel decoding with multi-user support
  * Continuous batching
  * Multimodal (wip)
@@ -130,7 +131,7 @@ The project is under active development, and we are [looking for feedback and co
 | `--no-context-shift` | disables context shift on inifinite text generation (default: disabled)<br/>(env: LLAMA_ARG_NO_CONTEXT_SHIFT) |
 | `-sp, --special` | special tokens output enabled (default: false) |
 | `--spm-infill` | use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this. (default: disabled) |
-| `--pooling {none,mean,cls,last}` | pooling type for embeddings, use model default if unspecified<br/>(env: LLAMA_ARG_POOLING) |
+| `--pooling {none,mean,cls,last,rank}` | pooling type for embeddings, use model default if unspecified<br/>(env: LLAMA_ARG_POOLING) |
 | `-cb, --cont-batching` | enable continuous batching (a.k.a dynamic batching) (default: enabled)<br/>(env: LLAMA_ARG_CONT_BATCHING) |
 | `-nocb, --no-cont-batching` | disable continuous batching<br/>(env: LLAMA_ARG_NO_CONT_BATCHING) |
 | `-a, --alias STRING` | set alias for model name (to be used by REST API)<br/>(env: LLAMA_ARG_ALIAS) |
@@ -478,6 +479,39 @@ The same as [the embedding example](../embedding) does.
 
     `image_data`: An array of objects to hold base64-encoded image `data` and its `id`s to be reference in `content`. You can determine the place of the image in the content as in the following: `Image: [img-21].\nCaption: This is a picture of a house`. In this case, `[img-21]` will be replaced by the embeddings of the image with id `21` in the following `image_data` array: `{..., "image_data": [{"data": "<BASE64_STRING>", "id": 21}]}`. Use `image_data` only with multimodal models, e.g., LLaVA.
 
+### POST `/reranking`: Rerank documents according to a given query
+
+Similar to https://jina.ai/reranker/ but might change in the future.
+Requires a reranker model (such as [bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3)) and the `--embedding --pooling rank` options.
+
+    *Options:*
+
+    `query`: The query against which the documents will be ranked.
+
+    `documents`: An array strings representing the documents to be ranked.
+
+    *Aliases:*
+      - `/rerank`
+      - `/v1/rerank`
+      - `/v1/reranking`
+
+    *Examples:*
+
+    ```shell
+    curl http://127.0.0.1:8012/v1/rerank \
+        -H "Content-Type: application/json" \
+        -d '{
+            "model": "some-model",
+                "query": "What is panda?",
+                "top_n": 3,
+                "documents": [
+                    "hi",
+                "it is a bear",
+                "The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China."
+                ]
+        }' | jq
+    ```
+
 ### POST `/infill`: For code infilling.
 
 Takes a prefix and a suffix and returns the predicted completion as stream.

examples/server/server.cpp

@@ -3297,7 +3297,9 @@ int main(int argc, char ** argv) {
     svr->Post("/embeddings",          handle_embeddings);
     svr->Post("/v1/embeddings",       handle_embeddings);
     svr->Post("/rerank",              handle_rerank);
+    svr->Post("/reranking",           handle_rerank);
     svr->Post("/v1/rerank",           handle_rerank);
+    svr->Post("/v1/reranking",        handle_rerank);
     svr->Post("/tokenize",            handle_tokenize);
     svr->Post("/detokenize",          handle_detokenize);
     // LoRA adapters hotswap