revert: google_gemini.py and google-gemini-integration.md

Author: owndev

docs/google-gemini-integration.md

@@ -2,11 +2,11 @@
 
 This integration enables **Open WebUI** to interact with **Google Gemini** models via the official Google Generative AI API (using API Keys) or through Google Cloud Vertex AI (leveraging Google Cloud's infrastructure and authentication). It provides a robust and customizable pipeline to access text and multimodal generation capabilities from Google’s latest AI models.
 
-🔗 [Learn More About Google AI](https://ai.google.dev/)
+🔗 [Learn More About Google AI](https://own.dev/ai-google-dev)
 
 ## Pipeline
 
-- 🧩 [Google Gemini Pipeline](../pipelines/google/google_gemini.py)
+- 🧩 [Google Gemini Pipeline](https://own.dev/github-owndev-open-webui-functions-google-gemini)
 
 ## Features
 
@@ -111,7 +111,7 @@ GOOGLE_API_KEY="your-google-api-key"
 ```
 
 > [!TIP]
-> You can obtain your API key from the [Google AI Studio](https://aistudio.google.com/) dashboard after signing up.
+> You can obtain your API key from the [Google AI Studio](https://own.dev/aistudio-google-com) dashboard after signing up.
 
 ### Connection Method: Google Cloud Vertex AI
 
@@ -153,4 +153,4 @@ When enabled, sources and google queries used by Gemini will be displayed with t
 
 ## Native tool calling support
 
-Native tool calling is enabled/disabled via the standard 'Function calling' Open Web UI toggle.
+Native tool calling is enabled/disabled via the standard 'Function calling' Open Web UI toggle.

pipelines/google/google_gemini.py

@@ -4,7 +4,7 @@
 author_url: https://github.com/owndev/
 project_url: https://github.com/owndev/Open-WebUI-Functions
 funding_url: https://github.com/sponsors/owndev
-version: 1.5.2
+version: 1.5.1
 license: Apache License 2.0
 description: Highly optimized Google Gemini pipeline with advanced image generation capabilities, intelligent compression, and streamlined processing workflows.
 features:
@@ -1329,18 +1329,9 @@ async def _handle_streaming_response(
                 duration_s = int(
                     max(0, time.time() - (thinking_started_at or time.time()))
                 )
-                # Format each line with > for blockquote while preserving formatting
-                thought_content = ''.join(thought_chunks).strip()
-                quoted_lines = []
-                for line in thought_content.split('\n'):
-                    quoted_lines.append(f"> {line}")
-                quoted_content = '\n'.join(quoted_lines)
-                
                 details_block = f"""<details>
-<summary>Thought ({duration_s}s)</summary>
-
-{quoted_content}
-
+<summary>Thinking ({duration_s}s)</summary>
+{''.join(thought_chunks)}
 </details>""".strip()
 
                 # Combine thoughts and answer (images not processed in streaming mode)
@@ -1720,18 +1711,9 @@ async def get_response():
                     # If we have thoughts, wrap them using <details>
                     if thought_segments:
                         duration_s = int(max(0, time.time() - start_ts))
-                        # Format each line with > for blockquote while preserving formatting
-                        thought_content = ''.join(thought_segments).strip()
-                        quoted_lines = []
-                        for line in thought_content.split('\n'):
-                            quoted_lines.append(f"> {line}")
-                        quoted_content = '\n'.join(quoted_lines)
-                        
                         details_block = f"""<details>
-<summary>Thought ({duration_s}s)</summary>
-
-{quoted_content}
-
+<summary>Thinking ({duration_s}s)</summary>
+{''.join(thought_segments)}
 </details>""".strip()
                         full_response += details_block