Implement Inference API (#67)

## Problem
The `2024-07` release of the Pinecone API included [Inference
operations](https://docs.pinecone.io/reference/api/2024-07/inference/generate-embeddings).
Currently `pinecone-ts-client`, `pinecone-python-client`, and
`pinecone-rust-client` support Inference.

We'd like to expose the `Embed` operation in the Go SDK.

## Solution
I followed a similar approach to how we've addressed adding inference in
other SDKs. Specifically, after discussing things internally I've opted
to add an `Inference` namespace to the `Client` struct to add separation
between existing index management operations, and inference-related
operations such as `Embed`. This approach is similar to the
implementation in Python and TypeScript.

- Add new structs: `EmbedRequest`, `EmbedParameters`, and
`InferenceService`. Add a new `Inference` field to `Client` which holds
an `*InferenceService` value allowing users to interact with the
Inference API.
- Attach new `Embed` method to `InferenceService` which wraps the
underlying `Embed` call on `*control.Client`, and handles massaging the
input and output to match the generated types.
- Add new integration tests to cover `Embed` in `client_test.go`.
- Add doc comments to new code, update README to include an Inference
section.

## Type of Change
- [ ] Bug fix (non-breaking change which fixes an issue)
- [X] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to not work as expected)
- [ ] This change requires a documentation update
- [ ] Infrastructure change (CI configs, etc)
- [ ] Non-code change (docs, etc)
- [ ] None of the above: (explain here)

## Test Plan
Added integration tests to validate calling the new
`client.Inference.Embed()` function.

In order to test yourself you'll need to consume this branch as a
dependency locally, and then call the `Embed` operation:

`go get` the branch for this PR:
```bash
go get github.com/pinecone-io/go-pinecone@adenoble/implement-inference
```
In your Go code:
```go
ctx := context.Background()

pc, err := pinecone.NewClient(pinecone.NewClientParams{
    ApiKey: "YOUR_API_KEY",
})
if err !=  nil {
    log.Fatalf("Failed to create Client: %v", err)
}

embeddingModel := "multilingual-e5-large"
documents := []string{
    "Turkey is a classic meat to eat at American Thanksgiving."
    "Many people enjoy the beautiful mosques in Turkey."
}
docParameters := pinecone.EmbedParameters{
    InputType: "passage",
    Truncate: "END",
}

docEmbeddingsResponse, err := pc.Inference.Embed(ctx, &pinecone.EmbedRequest{
    Model: embeddingModel,
    TextInputs: documents,
    Parameters: docParameters,
})
if err != nil {
    log.Fatalf("Failed to embed documents: %v", err)
}
fmt.Printf("docs embedding response: %+v", docEmbeddingsResponse)
```

README.md

@@ -403,7 +403,7 @@ func main() {
 
 The following examlpe describes the statistics of an index by name.
 
-```Go
+```go
 package main
 
 import (
@@ -781,7 +781,7 @@ func main() {
 The following example deletes a vector by its ID value from `example-index` and `example-namespace`. You can pass a
 slice of vector IDs to `DeleteVectorsById`.
 
-```Go
+```go
 package main
 
 import (
@@ -829,7 +829,7 @@ func main() {
 
 The following example deletes vectors from `example-index` using a metadata filter.
 
-```Go
+```go
 package main
 
 import (
@@ -884,7 +884,7 @@ func main() {
 
 The following example deletes all vectors from `example-index` and `example-namespace`.
 
-```Go
+```go
 package main
 
 import (
@@ -1012,7 +1012,7 @@ func main() {
 
 The following example updates vectors by ID in `example-index` and `example-namespace`.
 
-```Go
+```go
 package main
 
 import (
@@ -1145,7 +1145,7 @@ Collections are only available for pod-based indexes.
 
 The following example creates a collection from a source index.
 
-```Go
+```go
 package main
 
 import (
@@ -1186,7 +1186,7 @@ func main() {
 
 The following example lists all collections in your Pinecone project.
 
-```Go
+```go
 package main
 
 import (
@@ -1231,7 +1231,7 @@ func main() {
 
 The following example describes a collection by name.
 
-```Go
+```go
 package main
 
 import (
@@ -1269,7 +1269,7 @@ func main() {
 
 The following example deletes a collection by name.
 
-```Go
+```go
 package main
 
 import (
@@ -1305,6 +1305,73 @@ func main() {
 }
 ```
 
+## Inference
+
+The `Client` object has an `Inference` namespace which allows interacting with Pinecone's [Inference API](https://docs.pinecone.io/reference/api/2024-07/inference/generate-embeddings). The Inference API is a service that gives you access to embedding models hosted on Pinecone's infrastructure. Read more at [Understanding Pinecone Inference](https://docs.pinecone.io/guides/inference/understanding-inference).
+
+**Notes:**
+
+Models currently supported:
+
+- [multilingual-e5-large](https://docs.pinecone.io/guides/inference/understanding-inference#embedding-models)
+
+### Create Embeddings
+
+Send text to Pinecone's inference API to generate embeddings for documents and queries.
+
+```go
+	ctx := context.Background()
+
+	pc, err := pinecone.NewClient(pinecone.NewClientParams{
+		ApiKey: "YOUR_API_KEY",
+	})
+	if err !=  nil {
+		log.Fatalf("Failed to create Client: %v", err)
+	}
+
+	embeddingModel := "multilingual-e5-large"
+	documents := []string{
+		"Turkey is a classic meat to eat at American Thanksgiving."
+		"Many people enjoy the beautiful mosques in Turkey."
+	}
+	docParameters := pinecone.EmbedParameters{
+		InputType: "passage",
+		Truncate: "END",
+	}
+
+	docEmbeddingsResponse, err := pc.Inference.Embed(ctx, &pinecone.EmbedRequest{
+		Model: embeddingModel,
+		TextInputs: documents,
+		Parameters: docParameters,
+	})
+	if err != nil {
+		log.Fatalf("Failed to embed documents: %v", err)
+	}
+	fmt.Printf("docs embedding response: %+v", docEmbeddingsResponse)
+
+	// << Upsert documents into Pinecone >>
+
+	userQuery := []string{
+		"How should I prepare my turkey?"
+	}
+	queryParameters := pinecone.EmbedParameters{
+		InputType: "query",
+		Truncate: "END",
+	}
+	queryEmbeddingsResponse, err := pc.Inference.Embed(ctx, &pinecone.EmbedRequest{
+		Model: embeddingModel,
+		TextInputs: userQuery,
+		Parameters: queryParameters
+	})
+	if err != nil {
+		log.Fatalf("Failed to embed query: %v", err)
+	}
+	fmt.Printf("query embedding response: %+v", queryEmbeddingsResponse)
+
+	// << Send query to Pinecone to retrieve similar documents >>
+
+```
+
 ## Support
 
 To get help using go-pinecone you can file an issue on [GitHub](https://github.com/pinecone-io/go-pinecone/issues), visit the [community forum](https://community.pinecone.io/),