From 5a8bc88147ecd53c7566d4a643e584b434183f44 Mon Sep 17 00:00:00 2001
From: writinwaters <93570324+writinwaters@users.noreply.github.com>
Date: Wed, 17 Sep 2025 13:48:29 +0800
Subject: [PATCH] Docs: Removed `/v1` from Ollama base URLs (#10067)

### What problem does this PR solve?


### Type of change

- [x] Documentation Update
---
 docs/guides/chat/start_chat.md          | 2 +-
 docs/guides/models/deploy_local_llm.mdx | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/guides/chat/start_chat.md b/docs/guides/chat/start_chat.md
index c56b0ff6b..abe7f8a8f 100644
--- a/docs/guides/chat/start_chat.md
+++ b/docs/guides/chat/start_chat.md
@@ -106,7 +106,7 @@ RAGFlow offers HTTP and Python APIs for you to integrate RAGFlow's capabilities
 
 You can use iframe to embed the created chat assistant into a third-party webpage:
 
-1. Before proceeding, you must [acquire an API key](../models/llm_api_key_setup.md); otherwise, an error message would appear.
+1. Before proceeding, you must [acquire an API key](../../develop/acquire_ragflow_api_key.md); otherwise, an error message would appear.
 2. Hover over an intended chat assistant **>** **Edit** to show the **iframe** window:
 
    ![chat-embed](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/embed_chat_into_webpage.jpg)
diff --git a/docs/guides/models/deploy_local_llm.mdx b/docs/guides/models/deploy_local_llm.mdx
index af75a1324..918e9503c 100644
--- a/docs/guides/models/deploy_local_llm.mdx
+++ b/docs/guides/models/deploy_local_llm.mdx
@@ -91,7 +91,7 @@ In RAGFlow, click on your logo on the top right of the page **>** **Model provid
 In the popup window, complete basic settings for Ollama:
 
 1. Ensure that your model name and type match those been pulled at step 1 (Deploy Ollama using Docker). For example, (`llama3.2` and `chat`) or (`bge-m3` and `embedding`).
-2. In Ollama base URL, put the URL you found in step 2 followed by `/v1`, i.e. `http://host.docker.internal:11434/v1`, `http://localhost:11434/v1` or `http://${IP_OF_OLLAMA_MACHINE}:11434/v1`.
+2. Put in the Ollama base URL, i.e. `http://host.docker.internal:11434`, `http://localhost:11434` or `http://${IP_OF_OLLAMA_MACHINE}:11434`.
 3. OPTIONAL: Switch on the toggle under **Does it support Vision?** if your model includes an image-to-text model.