feat(provider) add gemini provider

console/src/components/MarkdownCopy/MarkdownCopy.tsx

@@ -77,8 +77,8 @@ export function MarkdownCopy({
       localShowMarkdown && !(editable && !textareaProps.disabled)
         ? content
         : editable
-        ? editContent
-        : content;
+          ? editContent
+          : content;
 
     if (!contentToCopy) return;
 

console/src/layouts/Sidebar.tsx

@@ -255,8 +255,8 @@ export default function Sidebar({ selectedKey }: SidebarProps) {
     const lang = i18n.language?.startsWith("zh")
       ? "zh"
       : i18n.language?.startsWith("ru")
-      ? "ru"
-      : "en";
+        ? "ru"
+        : "en";
     const faqLang = lang === "zh" ? "zh" : "en";
     const url = `https://copaw.agentscope.io/docs/faq.${faqLang}.md`;
     fetch(url, { cache: "no-cache" })
@@ -268,7 +268,7 @@ export default function Sidebar({ selectedKey }: SidebarProps) {
         setUpdateMarkdown(
           match && lang !== "ru"
             ? match[0].trim()
-            : UPDATE_MD[lang] ?? UPDATE_MD.en,
+            : (UPDATE_MD[lang] ?? UPDATE_MD.en),
         );
       })
       .catch(() => {

console/src/pages/Control/Sessions/index.tsx

@@ -56,9 +56,8 @@ function SessionsPage() {
     let filtered: Session[] = sessions;
 
     if (filterUserId) {
-      filtered = filtered.filter(
-        (session: Session) =>
-          session.user_id?.toLowerCase().includes(filterUserId.toLowerCase()),
+      filtered = filtered.filter((session: Session) =>
+        session.user_id?.toLowerCase().includes(filterUserId.toLowerCase()),
       );
     }
 

console/src/pages/Settings/Models/components/cards/RemoteProviderCard.tsx

@@ -87,23 +87,23 @@ export function RemoteProviderCard({
   const statusLabel = isAvailable
     ? t("models.providerAvailable")
     : isConfigured
-    ? t("models.providerNoModels")
-    : t("models.providerNotConfigured");
+      ? t("models.providerNoModels")
+      : t("models.providerNotConfigured");
   const statusType = isAvailable
     ? "enabled"
     : isConfigured
-    ? "partial"
-    : "disabled";
+      ? "partial"
+      : "disabled";
   const statusDotColor = isAvailable
     ? "#52c41a"
     : isConfigured
-    ? "#faad14"
-    : "#d9d9d9";
+      ? "#faad14"
+      : "#d9d9d9";
   const statusDotShadow = isAvailable
     ? "0 0 0 2px rgba(82, 196, 26, 0.2)"
     : isConfigured
-    ? "0 0 0 2px rgba(250, 173, 20, 0.2)"
-    : "none";
+      ? "0 0 0 2px rgba(250, 173, 20, 0.2)"
+      : "none";
 
   return (
     <Card
@@ -135,8 +135,8 @@ export function RemoteProviderCard({
                 statusType === "enabled"
                   ? styles.enabled
                   : statusType === "partial"
-                  ? styles.partial
-                  : styles.disabled
+                    ? styles.partial
+                    : styles.disabled
               }`}
             >
               {statusLabel}

console/src/pages/Settings/Models/components/modals/ProviderConfigModal.tsx

@@ -14,8 +14,10 @@ import api from "../../../../../api";
 import { useTranslation } from "react-i18next";
 import styles from "../../index.module.less";
 
-interface ProviderConfigFormValues
-  extends Omit<ProviderConfigRequest, "generate_kwargs"> {
+interface ProviderConfigFormValues extends Omit<
+  ProviderConfigRequest,
+  "generate_kwargs"
+> {
   generate_kwargs_text?: string;
 }
 

pyproject.toml

@@ -27,6 +27,7 @@ dependencies = [
     "aiofiles>=24.1.0",
     "paho-mqtt>=2.0.0",
     "matrix-nio>=0.24.0",
+    "google-genai>=1.67.0",
 ]
 
 [tool.setuptools.dynamic]

src/copaw/agents/model_factory.py

@@ -26,6 +26,13 @@
     AnthropicChatFormatter = None
     AnthropicChatModel = None
 
+try:
+    from agentscope.formatter import GeminiChatFormatter
+    from agentscope.model import GeminiChatModel
+except ImportError:  # pragma: no cover - compatibility fallback
+    GeminiChatFormatter = None
+    GeminiChatModel = None
+
 from .utils.tool_message_utils import _sanitize_tool_messages
 from ..providers import ProviderManager
 from ..providers.retry_chat_model import RetryChatModel
@@ -82,6 +89,8 @@ async def wrapper(
 }
 if AnthropicChatModel is not None and AnthropicChatFormatter is not None:
     _CHAT_MODEL_FORMATTER_MAP[AnthropicChatModel] = AnthropicChatFormatter
+if GeminiChatModel is not None and GeminiChatFormatter is not None:
+    _CHAT_MODEL_FORMATTER_MAP[GeminiChatModel] = GeminiChatFormatter
 
 
 def _get_formatter_for_chat_model(

src/copaw/providers/gemini_provider.py

@@ -0,0 +1,113 @@
+# -*- coding: utf-8 -*-
+"""A Google Gemini provider implementation using AgentScope's native
+GeminiChatModel."""
+
+from __future__ import annotations
+
+from typing import Any, List
+
+from agentscope.model import ChatModelBase
+from google import genai
+
+from copaw.providers.provider import ModelInfo, Provider
+
+
+class GeminiProvider(Provider):
+    """Provider implementation for Google Gemini API."""
+
+    def _client(self, timeout: float = 5) -> Any:  # noqa: W0613
+        _ = timeout  # Gemini SDK does not support per-client timeout
+        return genai.Client(api_key=self.api_key)
+
+    @staticmethod
+    def _normalize_models_payload(payload: Any) -> List[ModelInfo]:
+        models: List[ModelInfo] = []
+        for row in payload or []:
+            model_id = str(getattr(row, "name", "") or "").strip()
+            display_name = str(
+                getattr(row, "display_name", "") or model_id,
+            ).strip()
+
+            if not model_id:
+                continue
+
+            # Gemini API returns model names like "models/gemini-2.5-flash"
+            # Strip the "models/" prefix for cleaner IDs
+            if model_id.startswith("models/"):
+                model_id = model_id[len("models/") :]
+
+            if not display_name or display_name.startswith("models/"):
+                display_name = model_id
+
+            models.append(ModelInfo(id=model_id, name=display_name))
+
+        deduped: List[ModelInfo] = []
+        seen: set[str] = set()
+        for model in models:
+            if model.id in seen:
+                continue
+            seen.add(model.id)
+            deduped.append(model)
+        return deduped
+
+    async def check_connection(self, timeout: float = 5) -> tuple[bool, str]:
+        """Check if Google Gemini provider is reachable."""
+        try:
+            client = self._client(timeout=timeout)
+            # Use the async list models endpoint to verify connectivity
+            async for _ in await client.aio.models.list():
+                break
+            return True, ""
+        except Exception:
+            return (
+                False,
+                "Failed to connect to Google Gemini API. "
+                "Check your API key.",
+            )
+
+    async def fetch_models(self, timeout: float = 5) -> List[ModelInfo]:
+        """Fetch available models from Gemini API."""
+        try:
+            client = self._client(timeout=timeout)
+            payload = []
+            async for model in await client.aio.models.list():
+                payload.append(model)
+            models = self._normalize_models_payload(payload)
+            return models
+        except Exception:
+            return []
+
+    async def check_model_connection(
+        self,
+        model_id: str,
+        timeout: float = 5,
+    ) -> tuple[bool, str]:
+        """Check if a specific Gemini model is reachable/usable."""
+        target = (model_id or "").strip()
+        if not target:
+            return False, "Empty model ID"
+
+        try:
+            client = self._client(timeout=timeout)
+            response = client.aio.models.generate_content_stream(
+                model=target,
+                contents="ping",
+            )
+            async for _ in response:
+                break
+            return True, ""
+        except Exception:
+            return (
+                False,
+                f"Model '{model_id}' is not reachable or usable",
+            )
+
+    def get_chat_model_instance(self, model_id: str) -> ChatModelBase:
+        from agentscope.model import GeminiChatModel
+
+        return GeminiChatModel(
+            model_name=model_id,
+            stream=True,
+            api_key=self.api_key,
+            generate_kwargs=self.generate_kwargs,
+        )

src/copaw/providers/provider_manager.py

@@ -21,6 +21,7 @@
 )
 from copaw.providers.openai_provider import OpenAIProvider
 from copaw.providers.anthropic_provider import AnthropicProvider
+from copaw.providers.gemini_provider import GeminiProvider
 from copaw.providers.ollama_provider import OllamaProvider
 from copaw.constant import SECRET_DIR
 from copaw.local_models import create_local_chat_model
@@ -92,6 +93,16 @@
 
 ANTHROPIC_MODELS: List[ModelInfo] = []
 
+GEMINI_MODELS: List[ModelInfo] = [
+    ModelInfo(id="gemini-3.1-pro", name="Gemini 3.1 Pro"),
+    ModelInfo(id="gemini-3-flash", name="Gemini 3 Flash"),
+    ModelInfo(id="gemini-3.1-flash-lite", name="Gemini 3.1 Flash Lite"),
+    ModelInfo(id="gemini-2.5-pro", name="Gemini 2.5 Pro"),
+    ModelInfo(id="gemini-2.5-flash", name="Gemini 2.5 Flash"),
+    ModelInfo(id="gemini-2.5-flash-lite", name="Gemini 2.5 Flash Lite"),
+    ModelInfo(id="gemini-2.0-flash", name="Gemini 2.0 Flash"),
+]
+
 PROVIDER_MODELSCOPE = OpenAIProvider(
     id="modelscope",
     name="ModelScope",
@@ -169,6 +180,17 @@
     freeze_url=True,
 )
 
+PROVIDER_GEMINI = GeminiProvider(
+    id="gemini",
+    name="Google Gemini",
+    base_url="https://generativelanguage.googleapis.com",
+    api_key_prefix="",
+    models=GEMINI_MODELS,
+    chat_model="GeminiChatModel",
+    freeze_url=True,
+    support_model_discovery=True,
+)
+
 PROVIDER_OLLAMA = OllamaProvider(
     id="ollama",
     name="Ollama",
@@ -244,6 +266,7 @@ def _init_builtins(self):
         self._add_builtin(PROVIDER_AZURE_OPENAI)
         self._add_builtin(PROVIDER_MINIMAX)
         self._add_builtin(PROVIDER_ANTHROPIC)
+        self._add_builtin(PROVIDER_GEMINI)
         self._add_builtin(PROVIDER_OLLAMA)
         self._add_builtin(PROVIDER_LMSTUDIO)
         self._add_builtin(PROVIDER_LLAMACPP)
@@ -454,6 +477,8 @@ def _provider_from_data(self, data: Dict) -> Provider:
 
         if provider_id == "anthropic" or chat_model == "AnthropicChatModel":
             return AnthropicProvider.model_validate(data)
+        if provider_id == "gemini" or chat_model == "GeminiChatModel":
+            return GeminiProvider.model_validate(data)
         if provider_id == "ollama":
             return OllamaProvider.model_validate(data)
         if data.get("is_local", False):

website/public/docs/models.en.md

@@ -4,13 +4,13 @@ You need to configure a model before chatting with CoPaw. You can do this under
 
 ![Console models](https://img.alicdn.com/imgextra/i1/O1CN01zHAE1Z26w6jXl2xbr_!!6000000007725-2-tps-3802-1968.png)
 
-CoPaw supports multiple LLM providers: **cloud providers** (require API Key), **local providers** (llama.cpp / MLX), **Ollama provider**, **LM Studio provider**, and you can add **custom providers**. This page explains how to configure each type.
+CoPaw supports multiple LLM providers: **cloud providers** (require API Key, including Google Gemini), **local providers** (llama.cpp / MLX), **Ollama provider**, **LM Studio provider**, and you can add **custom providers**. This page explains how to configure each type.
 
 ---
 
 ## Configure cloud providers
 
-Cloud providers (including ModelScope, DashScope, Aliyun Coding Plan, OpenAI, and Azure OpenAI) call remote models via API and require an **API Key**.
+Cloud providers (including ModelScope, DashScope, Aliyun Coding Plan, OpenAI, Azure OpenAI, Google Gemini, and MiniMax) call remote models via API and require an **API Key**.
 
 **In the console:**
 
@@ -35,6 +35,33 @@ Cloud providers (including ModelScope, DashScope, Aliyun Coding Plan, OpenAI, an
 >
 > ![cancel](https://img.alicdn.com/imgextra/i2/O1CN01A8j1IR1n8fHGnio0q_!!6000000005045-2-tps-3802-1968.png)
 
+## Google Gemini provider
+
+The Google Gemini provider uses Google's native Gemini API (via the `google-genai` SDK) to access Gemini models. Pre-configured models include Gemini 3.1 Pro, Gemini 3 Flash, Gemini 3.1 Flash Lite, Gemini 2.5 Pro, Gemini 2.5 Flash, Gemini 2.5 Flash Lite, and Gemini 2.0 Flash. Additional models can be auto-discovered from the API.
+
+**Prerequisites:**
+
+- Obtain a Gemini API key from [Google AI Studio](https://aistudio.google.com/apikey).
+
+**In the console:**
+
+1. Open the console and go to **Settings → Models**.
+2. Find the **Google Gemini** provider card and click **Settings**. Enter your **API key** and click **Save**.
+3. After saving, the card status becomes **Available**. The provider supports **model discovery** — click **Models** to auto-discover available Gemini models from the API.
+4. In the **LLM Configuration** section at the top, select **Google Gemini** in the **Provider** dropdown and choose a model (e.g. `gemini-2.5-flash`), then click **Save**.
+
+**Using the CLI:**
+
+```bash
+# Configure the API key
+copaw models config-key gemini
+
+# Set Gemini as the active LLM
+copaw models set-llm
+```
+
+> **Tip:** Gemini models with thinking capabilities (e.g. Gemini 3.1 Pro, Gemini 2.5 Pro, Gemini 2.5 Flash) support extended reasoning. CoPaw automatically handles thinking blocks and thought signatures from these models.
+
 ## Local providers (llama.cpp / MLX)
 
 Local providers run models on your machine with **no API Key**; data stays on-device.