feat: Add native Google Gemini provider support

README.md

@@ -42,7 +42,7 @@ codewiki --version
 
 ### 2. Configure Your Environment
 
-CodeWiki supports multiple LLM providers: **OpenAI-compatible**, **Anthropic**, **AWS Bedrock**, and **Azure OpenAI**.
+CodeWiki supports multiple LLM providers: **OpenAI-compatible**, **Anthropic**, **AWS Bedrock**, **Azure OpenAI**, and **Google Gemini**.
 
 ```bash
 # Anthropic
@@ -68,6 +68,13 @@ codewiki config set \
   --aws-region us-east-1 \
   --main-model anthropic.claude-sonnet-4-v2:0 \
   --cluster-model anthropic.claude-sonnet-4-v2:0
+
+# Google Gemini
+codewiki config set \
+  --provider gemini \
+  --api-key YOUR_GEMINI_API_KEY \
+  --main-model gemini-2.5-pro \
+  --cluster-model gemini-2.5-pro
 ```
 
 ### 3. Generate Documentation
@@ -351,7 +358,7 @@ CodeWiki employs a three-stage process for comprehensive documentation generatio
 
 - **Python 3.12+**
 - **Node.js** (for Mermaid diagram validation)
-- **LLM API access** (Anthropic Claude, OpenAI, Azure OpenAI, AWS Bedrock)
+- **LLM API access** (Anthropic Claude, OpenAI, Azure OpenAI, AWS Bedrock, Google Gemini)
 - **Git** (for branch creation features)
 
 ---

codewiki/cli/commands/config.py

@@ -85,7 +85,7 @@ def config_group():
 )
 @click.option(
     "--provider",
-    type=click.Choice(['openai-compatible', 'anthropic', 'bedrock', 'azure-openai'], case_sensitive=False),
+    type=click.Choice(['openai-compatible', 'anthropic', 'bedrock', 'azure-openai', 'gemini'], case_sensitive=False),
     help="LLM provider type (default: openai-compatible)"
 )
 @click.option(
@@ -565,6 +565,11 @@ def config_validate(quick: bool, verbose: bool):
                         azure_endpoint=config.base_url,
                     )
                     client.models.list()
+                elif provider == "gemini":
+                    # Use Google Gemini SDK
+                    from google import genai
+                    gemini_client = genai.Client(api_key=api_key)
+                    list(gemini_client.models.list())
                 elif "api.anthropic.com" in base_url_lower:
                     # Use Anthropic SDK for native Anthropic endpoints
                     import anthropic

codewiki/src/be/llm_services.py

@@ -4,7 +4,7 @@
 Includes a compatibility layer for OpenAI-compatible API proxies that may
 return slightly non-standard responses (e.g. choices[].index = None).
 
-Supports multiple providers: openai-compatible, anthropic, bedrock, azure-openai.
+Supports multiple providers: openai-compatible, anthropic, bedrock, azure-openai, gemini.
 """
 import logging
 from openai.types import chat
@@ -57,13 +57,17 @@ def _get_litellm_model_name(model_name: str, provider: str) -> str:
 
     For Bedrock, prefixes the model name with 'bedrock/' if not already prefixed.
     For Anthropic, prefixes with 'anthropic/' if not already prefixed.
+    For Gemini, prefixes with 'gemini/' if not already prefixed.
     """
     if provider == "bedrock":
         if not model_name.startswith("bedrock/"):
             return f"bedrock/{model_name}"
     elif provider == "anthropic":
         if not model_name.startswith("anthropic/"):
             return f"anthropic/{model_name}"
+    elif provider == "gemini":
+        if not model_name.startswith("gemini/"):
+            return f"gemini/{model_name}"
     return model_name
 
 
@@ -154,8 +158,9 @@ def call_llm(
     """
     Call LLM with the given prompt.
 
-    Supports openai-compatible, anthropic, and bedrock providers.
+    Supports openai-compatible, anthropic, bedrock, azure-openai, and gemini providers.
     For bedrock/anthropic, uses litellm to translate the API call.
+    For gemini, uses the google-genai SDK directly.
 
     Args:
         prompt: The prompt to send
@@ -177,6 +182,9 @@ def call_llm(
     if provider == "azure-openai":
         return _call_llm_via_azure(prompt, config, model, temperature)
 
+    if provider == "gemini":
+        return _call_llm_via_gemini(prompt, config, model, temperature)
+
     # Default: OpenAI-compatible
     client = create_openai_client(config)
 
@@ -260,3 +268,39 @@ def _call_llm_via_azure(
         max_tokens=config.max_tokens,
     )
     return response.choices[0].message.content
+
+
+def _call_llm_via_gemini(
+    prompt: str,
+    config: Config,
+    model: str,
+    temperature: float = 0.0
+) -> str:
+    """
+    Call LLM via Google Gemini using the google-genai SDK.
+
+    Uses the google.genai client with the provided API key.
+    The model name may optionally include a 'gemini/' prefix, which is
+    stripped before passing to the SDK.
+    """
+    from google import genai
+    from google.genai import types as genai_types
+
+    api_key = config.llm_api_key
+    # Strip the 'gemini/' litellm prefix if present
+    sdk_model = model[len("gemini/"):] if model.startswith("gemini/") else model
+
+    logger.debug("Calling Gemini model %s via google-genai SDK", sdk_model)
+
+    client = genai.Client(api_key=api_key)
+    response = client.models.generate_content(
+        model=sdk_model,
+        contents=prompt,
+        config=genai_types.GenerateContentConfig(
+            temperature=temperature,
+            max_output_tokens=config.max_tokens,
+        ),
+    )
+    if response.text is None:
+        raise ValueError(f"Gemini model {sdk_model} returned an empty response")
+    return response.text

codewiki/src/config.py

@@ -58,7 +58,7 @@ class Config:
     cluster_model: str
     fallback_model: str = FALLBACK_MODEL_1
     # Provider configuration
-    provider: str = "openai-compatible"  # openai-compatible, anthropic, bedrock, azure-openai
+    provider: str = "openai-compatible"  # openai-compatible, anthropic, bedrock, azure-openai, gemini
     aws_region: str = "us-east-1"
     api_version: str = "2024-12-01-preview"  # Azure OpenAI API version
     azure_deployment: str = ""  # Azure OpenAI deployment name
@@ -181,7 +181,7 @@ def from_cli(
             main_model: Primary model
             cluster_model: Clustering model
             fallback_model: Fallback model
-            provider: LLM provider type (openai-compatible, anthropic, bedrock, azure-openai)
+            provider: LLM provider type (openai-compatible, anthropic, bedrock, azure-openai, gemini)
             aws_region: AWS region for Bedrock provider
             api_version: Azure OpenAI API version
             azure_deployment: Azure OpenAI deployment name