updated docs link for modifying llms

Author: assafelovic

README-ko_KR.md

@@ -105,7 +105,7 @@ export TAVILY_API_KEY={Tavily API 키 입력}
 
 더 영구적인 설정을 원한다면, 현재의 `gpt-researcher` 디렉토리에 `.env` 파일을 생성하고 환경 변수를 입력하세요 (export 없이).
 
-- 기본 LLM은 [GPT](https://platform.openai.com/docs/guides/gpt)이지만, `claude`, `ollama3`, `gemini`, `mistral` 등 다른 LLM도 사용할 수 있습니다. LLM 제공자를 변경하는 방법은 [LLMs 문서](https://docs.gptr.dev/docs/gpt-researcher/llms/llms)를 참조하세요. 이 프로젝트는 OpenAI GPT 모델에 최적화되어 있습니다.
+- 기본 LLM은 [GPT](https://platform.openai.com/docs/guides/gpt)이지만, `claude`, `ollama3`, `gemini`, `mistral` 등 다른 LLM도 사용할 수 있습니다. LLM 제공자를 변경하는 방법은 [LLMs 문서](https://docs.gptr.dev/docs/gpt-researcher/llms)를 참조하세요. 이 프로젝트는 OpenAI GPT 모델에 최적화되어 있습니다.
 - 기본 검색기는 [Tavily](https://app.tavily.com)이지만, `duckduckgo`, `google`, `bing`, `searchapi`, `serper`, `searx`, `arxiv`, `exa` 등의 검색기를 사용할 수 있습니다. 검색 제공자를 변경하는 방법은 [검색기 문서](https://docs.gptr.dev/docs/gpt-researcher/retrievers)를 참조하세요.
 
 ### 빠른 시작

docs/docs/gpt-researcher/getting-started/getting-started.md

@@ -26,7 +26,7 @@ export OPENAI_BASE_URL={Your custom API base URL here}
 
 For a more permanent setup, create a `.env` file in the current `gpt-researcher` directory and input the env vars (without `export`).
 
-- For LLM provider, we recommend **[OpenAI GPT](https://platform.openai.com/docs/guides/gpt)**, but you can use any other LLM model (including open sources). To learn how to change the LLM model, please refer to the [documentation](https://docs.gptr.dev/docs/gpt-researcher/llms/llms) page. 
+- For LLM provider, we recommend **[OpenAI GPT](https://platform.openai.com/docs/guides/gpt)**, but you can use any other LLM model (including open sources). To learn how to change the LLM model, please refer to the [documentation](https://docs.gptr.dev/docs/gpt-researcher/llms) page. 
 - For web search API, we recommend **[Tavily Search API](https://app.tavily.com)**, but you can also refer to other search APIs of your choice by changing the search provider in config/config.py to `duckduckgo`, `google`, `bing`, `searchapi`, `serper`, `searx` and more. Then add the corresponding env API key.
 
 ## Quickstart

multi_agents/README.md

@@ -8,7 +8,7 @@ Inspired by the recent [STORM](https://arxiv.org/abs/2402.14207) paper, this exa
 
 An average run generates a 5-6 page research report in multiple formats such as PDF, Docx and Markdown.
 
-Please note: Multi-agents are utilizing the same configuration of models like GPT-Researcher does. However, only the SMART_LLM is used for the time being. Please refer to the [LLM config pages](https://docs.gptr.dev/docs/gpt-researcher/llms/llms).
+Please note: Multi-agents are utilizing the same configuration of models like GPT-Researcher does. However, only the SMART_LLM is used for the time being. Please refer to the [LLM config pages](https://docs.gptr.dev/docs/gpt-researcher/llms).
 
 ## The Multi Agent Team
 The research team is made up of 8 agents:
@@ -51,7 +51,7 @@ More specifically (as seen in the architecture diagram) the process is as follow
     ```bash
     pip install -r requirements.txt
     ```
-3. Update env variables, see the [GPT-Researcher docs](https://docs.gptr.dev/docs/gpt-researcher/llms/llms) for more details.
+3. Update env variables, see the [GPT-Researcher docs](https://docs.gptr.dev/docs/gpt-researcher/llms) for more details.
 
 2. Run the application:
     ```bash