feat: Neo4j vector index method support (#1111)

* feat: Neo4j vector index method support

This commit introduces support for specifying vector index methods (HNSW)
for Neo4j targets.

- Modified `src/base/spec.rs` to derive `Eq` for `VectorIndexMethod`.
- Modified `src/ops/targets/neo4j.rs` to:
    - Allow `VectorIndexMethod` to be passed to `IndexDef::from_vector_index_def`.
    - Store `VectorIndexMethod` in `IndexDef::VectorIndex`.
    - Implement error handling for unsupported `VectorIndexMethod` (IVFFlat).
    - Update `SetupComponentOperator::describe_state` to display the method.
    - Update `SetupComponentOperator::create` to include HNSW parameters in the Cypher query.

* feat: integrate Ollama for LLM tasks to enable on-premises testing

- Updated docs_to_knowledge_graph example to use Ollama instead of OpenAI
- Added alternative configuration comments for OpenAI usage
- Enables end-to-end testing without requiring OpenAI API key
- Supports the Neo4j vector index method implementation

* Simplify Neo4j vector index

* Fix: Refactor LLM usage and update Neo4j vector index

This commit addresses feedback on the docs-to-knowledge-graph example and Neo4j vector index implementation.

- Refactors the docs-to-knowledge-graph example to use Ollama by default, removing the explicit address parameter.
- Updates the corresponding README to reflect the change to Ollama.
- Removes the unused `_method` parameter from the `from_vector_index_def` function in the Neo4j target.

Author: belloibrahv

examples/docs_to_knowledge_graph/README.md

@@ -16,7 +16,7 @@ Please drop [Cocoindex on Github](https://github.com/cocoindex-io/cocoindex) a s
 *   [Install Postgres](https://cocoindex.io/docs/getting_started/installation#-install-postgres) if you don't have one.
 *   Install [Neo4j](https://cocoindex.io/docs/ops/targets#neo4j-dev-instance) or [Kuzu](https://cocoindex.io/docs/ops/targets#kuzu-dev-instance) if you don't have one.
     *   The example uses Neo4j by default for now. If you want to use Kuzu, find out the "SELECT ONE GRAPH DATABASE TO USE" section and switch the active branch.
-*   [Configure your OpenAI API key](https://cocoindex.io/docs/ai/llm#openai).
+*   Install / configure LLM API. In this example we use Ollama, which runs LLM model locally. You need to get it ready following [this guide](https://cocoindex.io/docs/ai/llm#ollama). Alternatively, you can also follow the comments in source code to switch to OpenAI, and [configure OpenAI API key](https://cocoindex.io/docs/ai/llm#openai) before running the example.
 
 ## Documentation
 You can read the official CocoIndex Documentation for Property Graph Targets [here](https://cocoindex.io/docs/ops/targets#property-graph-targets).

examples/docs_to_knowledge_graph/main.py

@@ -82,9 +82,14 @@ def docs_to_kg_flow(
             cocoindex.functions.ExtractByLlm(
                 llm_spec=cocoindex.LlmSpec(
                     # Supported LLM: https://cocoindex.io/docs/ai/llm
-                    api_type=cocoindex.LlmApiType.OPENAI,
-                    model="gpt-4o",
+                    api_type=cocoindex.LlmApiType.OLLAMA,
+                    model="llama3.2",
                 ),
+                # Alternative: Use OpenAI API model instead of Ollama
+                # llm_spec=cocoindex.LlmSpec(
+                #     api_type=cocoindex.LlmApiType.OPENAI,
+                #     model="gpt-4o",
+                # ),
                 output_type=DocumentSummary,
                 instruction="Please summarize the content of the document.",
             )
@@ -100,9 +105,14 @@ def docs_to_kg_flow(
             cocoindex.functions.ExtractByLlm(
                 llm_spec=cocoindex.LlmSpec(
                     # Supported LLM: https://cocoindex.io/docs/ai/llm
-                    api_type=cocoindex.LlmApiType.OPENAI,
-                    model="gpt-4o",
+                    api_type=cocoindex.LlmApiType.OLLAMA,
+                    model="llama3.2",
                 ),
+                # Alternative: Use OpenAI API model instead of Ollama
+                # llm_spec=cocoindex.LlmSpec(
+                #     api_type=cocoindex.LlmApiType.OPENAI,
+                #     model="gpt-4o",
+                # ),
                 output_type=list[Relationship],
                 instruction=(
                     "Please extract relationships from CocoIndex documents. "

src/base/spec.rs

@@ -384,7 +384,7 @@ impl fmt::Display for VectorSimilarityMetric {
     }
 }
 
-#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
+#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq)]
 #[serde(tag = "kind")]
 pub enum VectorIndexMethod {
     Hnsw {

src/ops/targets/neo4j.rs

@@ -568,9 +568,6 @@ impl SetupState {
             .map(|f| (f.name.as_str(), &f.value_type.typ))
             .collect::<HashMap<_, _>>();
         for index_def in index_options.vector_indexes.iter() {
-            if index_def.method.is_some() {
-                api_bail!("Vector index method is not configurable for Neo4j yet");
-            }
             sub_components.push(ComponentState {
                 object_label: schema.elem_type.clone(),
                 index_def: IndexDef::from_vector_index_def(
@@ -644,6 +641,7 @@ enum IndexDef {
         field_name: String,
         metric: spec::VectorSimilarityMetric,
         vector_size: usize,
+        method: Option<spec::VectorIndexMethod>,
     },
 }
 
@@ -652,6 +650,10 @@ impl IndexDef {
         index_def: &spec::VectorIndexDef,
         field_typ: &schema::ValueType,
     ) -> Result<Self> {
+        let method = index_def.method.clone();
+        if let Some(spec::VectorIndexMethod::IvfFlat { .. }) = method {
+            api_bail!("IVFFlat vector index method is not supported for Neo4j");
+        }
         Ok(Self::VectorIndex {
             field_name: index_def.field_name.clone(),
             vector_size: (match field_typ {
@@ -664,6 +666,7 @@ impl IndexDef {
                 api_error!("Vector index field must be a vector with fixed dimension")
             })?,
             metric: index_def.metric,
+            method,
         })
     }
 }
@@ -723,9 +726,14 @@ impl components::SetupOperator for SetupComponentOperator {
                 field_name,
                 metric,
                 vector_size,
+                method,
             } => {
+                let method_str = method
+                    .as_ref()
+                    .map(|m| format!(", method: {}", m))
+                    .unwrap_or_default();
                 format!(
-                    "{key_desc} ON {label} (field_name: {field_name}, vector_size: {vector_size}, metric: {metric})",
+                    "{key_desc} ON {label} (field_name: {field_name}, vector_size: {vector_size}, metric: {metric}{method_str})",
                 )
             }
         }
@@ -752,17 +760,32 @@ impl components::SetupOperator for SetupComponentOperator {
                 field_name,
                 metric,
                 vector_size,
+                method,
             } => {
+                let mut parts = vec![];
+
+                parts.push(format!("`vector.dimensions`: {}", vector_size));
+                parts.push(format!("`vector.similarity_function`: '{}'", metric));
+
+                if let Some(spec::VectorIndexMethod::Hnsw { m, ef_construction }) = method {
+                    if let Some(m_val) = m {
+                        parts.push(format!("`vector.hnsw.m`: {}", m_val));
+                    }
+                    if let Some(ef_val) = ef_construction {
+                        parts.push(format!("`vector.hnsw.ef_construction`: {}", ef_val));
+                    }
+                }
+
                 formatdoc! {"
                     CREATE VECTOR INDEX {name} IF NOT EXISTS
                     FOR {matcher} ON {qualifier}.{field_name}
                     OPTIONS {{
                         indexConfig: {{
-                            `vector.dimensions`: {vector_size},
-                            `vector.similarity_function`: '{metric}'
+                            {config}
                         }}
                     }}",
                     name = key.name,
+                    config = parts.join(", ")
                 }
             }
         });