1 files changed, 107 insertions, 0 deletions
diff --git a/g4f/Provider/needs_auth/GeminiPro.py b/g4f/Provider/needs_auth/GeminiPro.py
new file mode 100644
index 00000000..5c170ae5
--- /dev/null
+++ b/g4f/Provider/needs_auth/GeminiPro.py
@@ -0,0 +1,107 @@
+from __future__ import annotations
+
+import base64
+import json
+from aiohttp import ClientSession, BaseConnector
+
+from ...typing import AsyncResult, Messages, ImageType
+from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
+from ...image import to_bytes, is_accepted_format
+from ...errors import MissingAuthError
+from ..helper import get_connector
+
+class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin):
+    label = "Gemini API"
+    url = "https://ai.google.dev"
+    working = True
+    supports_message_history = True
+    needs_auth = True
+    default_model = "gemini-1.5-pro-latest"
+    default_vision_model = default_model
+    models = [default_model, "gemini-pro", "gemini-pro-vision", "gemini-1.5-flash"]
+
+    @classmethod
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        stream: bool = False,
+        proxy: str = None,
+        api_key: str = None,
+        api_base: str = "https://generativelanguage.googleapis.com/v1beta",
+        use_auth_header: bool = False,
+        image: ImageType = None,
+        connector: BaseConnector = None,
+        **kwargs
+    ) -> AsyncResult:
+        model = cls.get_model(model)
+
+        if not api_key:
+            raise MissingAuthError('Add a "api_key"')
+
+        headers = params = None
+        if use_auth_header:
+            headers = {"Authorization": f"Bearer {api_key}"}
+        else:
+            params = {"key": api_key}
+
+        method = "streamGenerateContent" if stream else "generateContent"
+        url = f"{api_base.rstrip('/')}/models/{model}:{method}"
+        async with ClientSession(headers=headers, connector=get_connector(connector, proxy)) as session:
+            contents = [
+                {
+                    "role": "model" if message["role"] == "assistant" else "user",
+                    "parts": [{"text": message["content"]}]
+                }
+                for message in messages
+                if message["role"] != "system"
+            ]
+            if image is not None:
+                image = to_bytes(image)
+                contents[-1]["parts"].append({
+                    "inline_data": {
+                        "mime_type": is_accepted_format(image),
+                        "data": base64.b64encode(image).decode()
+                    }
+                })
+            data = {
+                "contents": contents,
+                "generationConfig": {
+                    "stopSequences": kwargs.get("stop"),
+                    "temperature": kwargs.get("temperature"),
+                    "maxOutputTokens": kwargs.get("max_tokens"),
+                    "topP": kwargs.get("top_p"),
+                    "topK": kwargs.get("top_k"),
+                }
+            }
+            system_prompt = "\n".join(
+                message["content"]
+                for message in messages
+                if message["role"] == "system"
+            )
+            if system_prompt:
+                data["system_instruction"] = {"parts": {"text": system_prompt}}
+            async with session.post(url, params=params, json=data) as response:
+                if not response.ok:
+                    data = await response.json()
+                    data = data[0] if isinstance(data, list) else data
+                    raise RuntimeError(f"Response {response.status}: {data['error']['message']}")
+                if stream:
+                    lines = []
+                    async for chunk in response.content:
+                        if chunk == b"[{\n":
+                            lines = [b"{\n"]
+                        elif chunk == b",\r\n" or chunk == b"]":
+                            try:
+                                data = b"".join(lines)
+                                data = json.loads(data)
+                                yield data["candidates"][0]["content"]["parts"][0]["text"]
+                            except:
+                                data = data.decode(errors="ignore") if isinstance(data, bytes) else data
+                                raise RuntimeError(f"Read chunk failed: {data}")
+                            lines = []
+                        else:
+                            lines.append(chunk)
+                else:
+                    data = await response.json()
+                    yield data["candidates"][0]["content"]["parts"][0]["text"]