feat: add docs for gemini

Author: par4m

docs/docs/ai/llm.mdx

@@ -21,7 +21,7 @@ It has the following fields:
 *   `address` (optional): The address of the LLM API.
 
 
-## LLM API integrations
+## LLM API Integrations
 
 CocoIndex integrates with various LLM APIs for these functions.
 
@@ -77,3 +77,24 @@ cocoindex.LlmSpec(
 </TabItem>
 </Tabs>
 
+### Google Gemini
+
+To use the Gemini LLM API, you need to set the environment variable `GEMINI_API_KEY`.
+You can generate the API key from [Google AI Studio](https://aistudio.google.com/apikey).
+
+A spec for Gemini looks like this:
+
+<Tabs>
+<TabItem value="python" label="Python" default>
+
+```python
+cocoindex.LlmSpec(
+    api_type=cocoindex.LlmApiType.GEMINI,
+    model="gemini-2.0-flash",
+)
+```
+
+</TabItem>
+</Tabs>
+
+You can find the full list of models supported by Gemini [here](https://ai.google.dev/gemini-api/docs/models).

src/llm/gemini.rs

@@ -3,7 +3,7 @@ use crate::llm::{LlmGenerationClient, LlmSpec, LlmGenerateRequest, LlmGenerateRe
 use anyhow::{Result, anyhow};
 use serde_json;
 use reqwest::Client as HttpClient;
-use serde_json::{json, Value};
+use serde_json::Value;
 
 pub struct Client {
     model: String,
@@ -45,7 +45,7 @@ impl LlmGenerationClient for Client {
         request: LlmGenerateRequest<'req>,
     ) -> Result<LlmGenerateResponse> {
         // Compose the prompt/messages
-        let mut contents = vec![serde_json::json!({
+        let contents = vec![serde_json::json!({
             "role": "user",
             "parts": [{ "text": request.user_prompt }]
         })];
@@ -90,10 +90,6 @@ impl LlmGenerationClient for Client {
 
         let resp_json: Value = resp.json().await.map_err(|e| anyhow!("Invalid JSON: {e}"))?;
 
-        // Debug log Gemini response
-        println!("Gemini request payload: {:#}", payload);
-        println!("Gemini response JSON: {:#}", resp_json);
-
         if let Some(error) = resp_json.get("error") {
             return Err(anyhow!("Gemini API error: {:?}", error));
         }