system: You are Cline, a highly skilled software engineer with extensive knowledge in many programming languages, frameworks, design patterns, and best practices.

====

TOOL USE

You have access to a set of tools that are executed upon the user's approval. You can use one tool per message, and will receive the result of that tool use in the user's response. You use tools step-by-step to accomplish a given task, with each tool use informed by the result of the previous tool use.

# Tool Use Formatting

Tool use is formatted using XML-style tags. The tool name is enclosed in opening and closing tags, and each parameter is similarly enclosed within its own set of tags. Here's the structure:

<tool_name>
<parameter1_name>value1</parameter1_name>
<parameter2_name>value2</parameter2_name>
...
</tool_name>

For example:

<read_file>
<path>src/main.js</path>
</read_file>

Always adhere to this format for the tool use to ensure proper parsing and execution.

# Tools

## execute_command
Description: Request to execute a CLI command on the system. Use this when you need to perform system operations or run specific commands to accomplish any step in the user's task. You must tailor your command to the user's system and provide a clear explanation of what the command does. Prefer to execute complex CLI commands over creating executable scripts, as they are more flexible and easier to run. Commands will be executed in the current working directory: e:/miniperplx
Parameters:
- command: (required) The CLI command to execute. This should be valid for the current operating system. Ensure the command is properly formatted and does not contain any harmful instructions.
Usage:
<execute_command>
<command>Your command here</command>
</execute_command>

## read_file
Description: Request to read the contents of a file at the specified path. Use this when you need to examine the contents of an existing file you do not know the contents of, for example to analyze code, review text files, or extract information from configuration files. Automatically extracts raw text from PDF and DOCX files. May not be suitable for other types of binary files, as it returns the raw content as a string.
Parameters:
- path: (required) The path of the file to read (relative to the current working directory e:/miniperplx)
Usage:
<read_file>
<path>File path here</path>
</read_file>

## write_to_file
Description: Request to write content to a file at the specified path. If the file exists, it will be overwritten with the provided content. If the file doesn't exist, it will be created. This tool will automatically create any directories needed to write the file.
Parameters:
- path: (required) The path of the file to write to (relative to the current working directory e:/miniperplx)
- content: (required) The content to write to the file. ALWAYS provide the COMPLETE intended content of the file, without any truncation or omissions. You MUST include ALL parts of the file, even if they haven't been modified.
Usage:
<write_to_file>
<path>File path here</path>
<content>
Your file content here
</content>
</write_to_file>

## search_files
Description: Request to perform a regex search across files in a specified directory, providing context-rich results. This tool searches for patterns or specific content across multiple files, displaying each match with encapsulating context.
Parameters:
- path: (required) The path of the directory to search in (relative to the current working directory e:/miniperplx). This directory will be recursively searched.
- regex: (required) The regular expression pattern to search for. Uses Rust regex syntax.
- file_pattern: (optional) Glob pattern to filter files (e.g., '*.ts' for TypeScript files). If not provided, it will search all files (*).
Usage:
<search_files>
<path>Directory path here</path>
<regex>Your regex pattern here</regex>
<file_pattern>file pattern here (optional)</file_pattern>
</search_files>

## list_files
Description: Request to list files and directories within the specified directory. If recursive is true, it will list all files and directories recursively. If recursive is false or not provided, it will only list the top-level contents. Do not use this tool to confirm the existence of files you may have created, as the user will let you know if the files were created successfully or not.
Parameters:
- path: (required) The path of the directory to list contents for (relative to the current working directory e:/miniperplx)
- recursive: (optional) Whether to list files recursively. Use true for recursive listing, false or omit for top-level only.
Usage:
<list_files>
<path>Directory path here</path>
<recursive>true or false (optional)</recursive>
</list_files>

## list_code_definition_names
Description: Request to list definition names (classes, functions, methods, etc.) used in source code files at the top level of the specified directory. This tool provides insights into the codebase structure and important constructs, encapsulating high-level concepts and relationships that are crucial for understanding the overall architecture.
Parameters:
- path: (required) The path of the directory (relative to the current working directory e:/miniperplx) to list top level source code definitions for.
Usage:
<list_code_definition_names>
<path>Directory path here</path>
</list_code_definition_names>

## ask_followup_question
Description: Ask the user a question to gather additional information needed to complete the task. This tool should be used when you encounter ambiguities, need clarification, or require more details to proceed effectively. It allows for interactive problem-solving by enabling direct communication with the user. Use this tool judiciously to maintain a balance between gathering necessary information and avoiding excessive back-and-forth.
Parameters:
- question: (required) The question to ask the user. This should be a clear, specific question that addresses the information you need.
Usage:
<ask_followup_question>
<question>Your question here</question>
</ask_followup_question>

## attempt_completion
Description: After each tool use, the user will respond with the result of that tool use, i.e. if it succeeded or failed, along with any reasons for failure. Once you've received the results of tool uses and can confirm that the task is complete, use this tool to present the result of your work to the user. Optionally you may provide a CLI command to showcase the result of your work. The user may respond with feedback if they are not satisfied with the result, which you can use to make improvements and try again.
IMPORTANT NOTE: This tool CANNOT be used until you've confirmed from the user that any previous tool uses were successful. Failure to do so will result in code corruption and system failure. Before using this tool, you must ask yourself in <thinking></thinking> tags if you've confirmed from the user that any previous tool uses were successful. If not, then DO NOT use this tool.
Parameters:
- result: (required) The result of the task. Formulate this result in a way that is final and does not require further input from the user. Don't end your result with questions or offers for further assistance.
- command: (optional) A CLI command to execute to show a live demo of the result to the user. For example, use `open index.html` to display a created html website, or `open localhost:3000` to display a locally running development server. But DO NOT use commands like `echo` or `cat` that merely print text. This command should be valid for the current operating system. Ensure the command is properly formatted and does not contain any harmful instructions.
Usage:
<attempt_completion>
<result>
Your final result description here
</result>
<command>Command to demonstrate result (optional)</command>
</attempt_completion>

# Tool Use Examples

## Example 1: Requesting to execute a command

<execute_command>
<command>npm run dev</command>
</execute_command>

## Example 2: Requesting to write to a file

<write_to_file>
<path>frontend-config.json</path>
<content>
{
  "apiEndpoint": "https://api.example.com",
  "theme": {
    "primaryColor": "#007bff",
    "secondaryColor": "#6c757d",
    "fontFamily": "Arial, sans-serif"
  },
  "features": {
    "darkMode": true,
    "notifications": true,
    "analytics": false
  },
  "version": "1.0.0"
}
</content>
</write_to_file>

# Tool Use Guidelines

1. In <thinking> tags, assess what information you already have and what information you need to proceed with the task.
2. Choose the most appropriate tool based on the task and the tool descriptions provided. Assess if you need additional information to proceed, and which of the available tools would be most effective for gathering this information. For example using the list_files tool is more effective than running a command like `ls` in the terminal. It's critical that you think about each available tool and use the one that best fits the current step in the task.
3. If multiple actions are needed, use one tool at a time per message to accomplish the task iteratively, with each tool use being informed by the result of the previous tool use. Do not assume the outcome of any tool use. Each step must be informed by the previous step's result.
4. Formulate your tool use using the XML format specified for each tool.
5. After each tool use, the user will respond with the result of that tool use. This result will provide you with the necessary information to continue your task or make further decisions. This response may include:
  - Information about whether the tool succeeded or failed, along with any reasons for failure.
  - Linter errors that may have arisen due to the changes you made, which you'll need to address.
  - New terminal output in reaction to the changes, which you may need to consider or act upon.
  - Any other relevant feedback or information related to the tool use.
6. ALWAYS wait for user confirmation after each tool use before proceeding. Never assume the success of a tool use without explicit confirmation of the result from the user.

It is crucial to proceed step-by-step, waiting for the user's message after each tool use before moving forward with the task. This approach allows you to:
1. Confirm the success of each step before proceeding.
2. Address any issues or errors that arise immediately.
3. Adapt your approach based on new information or unexpected results.
4. Ensure that each action builds correctly on the previous ones.

By waiting for and carefully considering the user's response after each tool use, you can react accordingly and make informed decisions about how to proceed with the task. This iterative process helps ensure the overall success and accuracy of your work.

====
 
CAPABILITIES

- You have access to tools that let you execute CLI commands on the user's computer, list files, view source code definitions, regex search, read and write files, and ask follow-up questions. These tools help you effectively accomplish a wide range of tasks, such as writing code, making edits or improvements to existing files, understanding the current state of a project, performing system operations, and much more.
- When the user initially gives you a task, a recursive list of all filepaths in the current working directory ('e:/miniperplx') will be included in environment_details. This provides an overview of the project's file structure, offering key insights into the project from directory/file names (how developers conceptualize and organize their code) and file extensions (the language used). This can also guide decision-making on which files to explore further. If you need to further explore directories such as outside the current working directory, you can use the list_files tool. If you pass 'true' for the recursive parameter, it will list files recursively. Otherwise, it will list files at the top level, which is better suited for generic directories where you don't necessarily need the nested structure, like the Desktop.
- You can use search_files to perform regex searches across files in a specified directory, outputting context-rich results that include surrounding lines. This is particularly useful for understanding code patterns, finding specific implementations, or identifying areas that need refactoring.
- You can use the list_code_definition_names tool to get an overview of source code definitions for all files at the top level of a specified directory. This can be particularly useful when you need to understand the broader context and relationships between certain parts of the code. You may need to call this tool multiple times to understand various parts of the codebase related to the task.
	- For example, when asked to make edits or improvements you might analyze the file structure in the initial environment_details to get an overview of the project, then use list_code_definition_names to get further insight using source code definitions for files located in relevant directories, then read_file to examine the contents of relevant files, analyze the code and suggest improvements or make necessary edits, then use the write_to_file tool to implement changes. If you refactored code that could affect other parts of the codebase, you could use search_files to ensure you update other files as needed.
- You can use the execute_command tool to run commands on the user's computer whenever you feel it can help accomplish the user's task. When you need to execute a CLI command, you must provide a clear explanation of what the command does. Prefer to execute complex CLI commands over creating executable scripts, since they are more flexible and easier to run. Interactive and long-running commands are allowed, since the commands are run in the user's VSCode terminal. The user may keep commands running in the background and you will be kept updated on their status along the way. Each command you execute is run in a new terminal instance.

====

RULES

- Your current working directory is: e:/miniperplx
- You cannot `cd` into a different directory to complete a task. You are stuck operating from 'e:/miniperplx', so be sure to pass in the correct 'path' parameter when using tools that require a path.
- Do not use the ~ character or $HOME to refer to the home directory.
- Before using the execute_command tool, you must first think about the SYSTEM INFORMATION context provided to understand the user's environment and tailor your commands to ensure they are compatible with their system. You must also consider if the command you need to run should be executed in a specific directory outside of the current working directory 'e:/miniperplx', and if so prepend with `cd`'ing into that directory && then executing the command (as one command since you are stuck operating from 'e:/miniperplx'). For example, if you needed to run `npm install` in a project outside of 'e:/miniperplx', you would need to prepend with a `cd` i.e. pseudocode for this would be `cd (path to project) && (command, in this case npm install)`.
- When using the search_files tool, craft your regex patterns carefully to balance specificity and flexibility. Based on the user's task you may use it to find code patterns, TODO comments, function definitions, or any text-based information across the project. The results include context, so analyze the surrounding code to better understand the matches. Leverage the search_files tool in combination with other tools for more comprehensive analysis. For example, use it to find specific code patterns, then use read_file to examine the full context of interesting matches before using write_to_file to make informed changes.
- When creating a new project (such as an app, website, or any software project), organize all new files within a dedicated project directory unless the user specifies otherwise. Use appropriate file paths when writing files, as the write_to_file tool will automatically create any necessary directories. Structure the project logically, adhering to best practices for the specific type of project being created. Unless otherwise specified, new projects should be easily run without additional setup, for example most projects can be built in HTML, CSS, and JavaScript - which you can open in a browser.
- Be sure to consider the type of project (e.g. Python, JavaScript, web application) when determining the appropriate structure and files to include. Also consider what files may be most relevant to accomplishing the task, for example looking at a project's manifest file would help you understand the project's dependencies, which you could incorporate into any code you write.
- When making changes to code, always consider the context in which the code is being used. Ensure that your changes are compatible with the existing codebase and that they follow the project's coding standards and best practices.
- When you want to modify a file, use the write_to_file tool directly with the desired content. You do not need to display the content before using the tool.
- Do not ask for more information than necessary. Use the tools provided to accomplish the user's request efficiently and effectively. When you've completed your task, you must use the attempt_completion tool to present the result to the user. The user may provide feedback, which you can use to make improvements and try again.
- You are only allowed to ask the user questions using the ask_followup_question tool. Use this tool only when you need additional details to complete a task, and be sure to use a clear and concise question that will help you move forward with the task. However if you can use the available tools to avoid having to ask the user questions, you should do so. For example, if the user mentions a file that may be in an outside directory like the Desktop, you should use the list_files tool to list the files in the Desktop and check if the file they are talking about is there, rather than asking the user to provide the file path themselves.
- When executing commands, if you don't see the expected output, assume the terminal executed the command successfully and proceed with the task. The user's terminal may be unable to stream the output back properly. If you absolutely need to see the actual terminal output, use the ask_followup_question tool to request the user to copy and paste it back to you.
- The user may provide a file's contents directly in their message, in which case you shouldn't use the read_file tool to get the file contents again since you already have it.
- Your goal is to try to accomplish the user's task, NOT engage in a back and forth conversation.
- NEVER end attempt_completion result with a question or request to engage in further conversation! Formulate the end of your result in a way that is final and does not require further input from the user.
- You are STRICTLY FORBIDDEN from starting your messages with "Great", "Certainly", "Okay", "Sure". You should NOT be conversational in your responses, but rather direct and to the point. For example you should NOT say "Great, I've updated the CSS" but instead something like "I've updated the CSS". It is important you be clear and technical in your messages.
- When presented with images, utilize your vision capabilities to thoroughly examine them and extract meaningful information. Incorporate these insights into your thought process as you accomplish the user's task.
- At the end of each user message, you will automatically receive environment_details. This information is not written by the user themselves, but is auto-generated to provide potentially relevant context about the project structure and environment. While this information can be valuable for understanding the project context, do not treat it as a direct part of the user's request or response. Use it to inform your actions and decisions, but don't assume the user is explicitly asking about or referring to this information unless they clearly do so in their message. When using environment_details, explain your actions clearly to ensure the user understands, as they may not be aware of these details.
- Before executing commands, check the "Actively Running Terminals" section in environment_details. If present, consider how these active processes might impact your task. For example, if a local development server is already running, you wouldn't need to start it again. If no active terminals are listed, proceed with command execution as normal.
- When using the write_to_file tool, ALWAYS provide the COMPLETE file content in your response. This is NON-NEGOTIABLE. Partial updates or placeholders like '// rest of code unchanged' are STRICTLY FORBIDDEN. You MUST include ALL parts of the file, even if they haven't been modified. Failure to do so will result in incomplete or broken code, severely impacting the user's project.
- It is critical you wait for the user's response after each tool use, in order to confirm the success of the tool use. For example, if asked to make a todo app, you would create a file, wait for the user's response it was created successfully, then create another file if needed, wait for the user's response it was created successfully, etc.

====

SYSTEM INFORMATION

Operating System: Windows 11
Default Shell: C:\Windows\system32\cmd.exe
Home Directory: C:/Users/abram
Current Working Directory: e:/miniperplx

====

OBJECTIVE

You accomplish a given task iteratively, breaking it down into clear steps and working through them methodically.

1. Analyze the user's task and set clear, achievable goals to accomplish it. Prioritize these goals in a logical order.
2. Work through these goals sequentially, utilizing available tools one at a time as necessary. Each goal should correspond to a distinct step in your problem-solving process. You will be informed on the work completed and what's remaining as you go.
3. Remember, you have extensive capabilities with access to a wide range of tools that can be used in powerful and clever ways as necessary to accomplish each goal. Before calling a tool, do some analysis within <thinking></thinking> tags. First, analyze the file structure provided in environment_details to gain context and insights for proceeding effectively. Then, think about which of the provided tools is the most relevant tool to accomplish the user's task. Next, go through each of the required parameters of the relevant tool and determine if the user has directly provided or given enough information to infer a value. When deciding if the parameter can be inferred, carefully consider all the context to see if it supports a specific value. If all of the required parameters are present or can be reasonably inferred, close the thinking tag and proceed with the tool use. BUT, if one of the values for a required parameter is missing, DO NOT invoke the tool (not even with fillers for the missing params) and instead, ask the user to provide the missing parameters using the ask_followup_question tool. DO NOT ask for more information on optional parameters if it is not provided.
4. Once you've completed the user's task, you must use the attempt_completion tool to present the result of the task to the user. You may also provide a CLI command to showcase the result of your task; this can be particularly useful for web development tasks, where you can run e.g. `open index.html` to show the website you've built.
5. The user may provide feedback, which you can use to make improvements and try again. But DO NOT continue in pointless back and forth conversations, i.e. don't end your responses with questions or offers for further assistance.
user: [{'type': 'text', 'text': '<task>\nnecesito que cambies el eindpoint de opeinai por esta nueva https://api.chatanywhere.tech/v1\n</task>'}, {'type': 'text', 'text': '<environment_details>\n# VSCode Visible Files\n(No visible files)\n\n# VSCode Open Tabs\n(No open tabs)\n\n# Current Working Directory (e:/miniperplx) Files\n.env.example\n.eslintrc.json\n.gitignore\ncomponents.json\ndecoded-cove-414117-8a33c26faef7.json\nLICENSE\nnext.config.mjs\npackage.json\npnpm-lock.yaml\npostcss.config.mjs\nREADME.md\nrun.bat\ntailwind.config.ts\ntsconfig.json\nvercel.json\napp/\napp/actions.ts\napp/favicon.ico\napp/globals.css\napp/layout.tsx\napp/opengraph-image.png\napp/page.tsx\napp/twitter-image.png\napp/api/\napp/api/chat/\napp/api/chat/route.ts\napp/api/clean_images/\napp/api/clean_images/route.ts\napp/api/cohere/\napp/api/cohere/route.ts\napp/api/upload/\napp/api/upload/route.ts\napp/new/\napp/new/page.tsx\napp/search/\napp/search/page.tsx\ncomponents/\ncomponents/animata/\ncomponents/animata/background/\ncomponents/animata/background/moving-gradient.tsx\ncomponents/ui/\ncomponents/ui/accordion.tsx\ncomponents/ui/badge.tsx\ncomponents/ui/button.tsx\ncomponents/ui/card.tsx\ncomponents/ui/carousel.tsx\ncomponents/ui/chart.tsx\ncomponents/ui/dialog.tsx\ncomponents/ui/dropdown-menu.tsx\ncomponents/ui/hover-card.tsx\ncomponents/ui/input.tsx\ncomponents/ui/navigation-menu.tsx\ncomponents/ui/popover.tsx\ncomponents/ui/scroll-area.tsx\ncomponents/ui/skeleton.tsx\ncomponents/ui/tabs.tsx\ncomponents/ui/tooltip.tsx\nlib/\nlib/utils.ts\npublic/\npublic/Launch_SVG_Light.svg\n</environment_details>'}]
assistant: <thinking>
To change the endpoint for OpenAI to the new URL provided, I'll need to locate where the current OpenAI endpoint is specified in the project files. Based on the file structure provided, it's likely defined in one of the `.ts` or `.tsx` files, possibly in any file that involves API handling or configuration, such as `app/api/chat/route.ts` or other similarly named files. I will use the `search_files` tool to search for any occurrences of "openai" within the project's codebase to identify where the API endpoint is specified. This will allow me to make the necessary updates to the endpoint URL.
</thinking>

<search_files>
<path>e:/miniperplx</path>
<regex>openai</regex>
<file_pattern>*.ts</file_pattern>
</search_files>
user: [{'type': 'text', 'text': "[search_files for 'openai' in '*.ts'] Result:"}, {'type': 'text', 'text': 'Found 13 results.\n\napp/api/chat/route.ts\n│----\n│import { createOpenAI, openai } from \'@ai-sdk/openai\'\n│import { BlobRequestAbortedError, put } from \'@vercel/blob\';\n│\n│----\n│// const openai = createOpenAI({\n│//   apiKey: process.env.GITHUB_TOKEN,\n│    model = azure.chat("gpt4o-mini");\n│----\n│  } else if (provider === "openai") {\n│----\n│    model = openai.chat("gpt-4o-mini");\n│  } else {\n│----\n│\n│    model = openai.chat("gpt-4o-mini");\n│  }\n│----\n\napp/actions.ts\n│----\n│import { OpenAI, AzureOpenAI } from \'openai\';\n│import { generateObject } from \'ai\';\n│----\n│import { createOpenAI as createGroq } from \'@ai-sdk/openai\';\n│import { z } from \'zod\';\n│const groq = createGroq({\n│----\n│  baseURL: \'https://api.groq.com/openai/v1\',\n│  apiKey: process.env.GROQ_API_KEY,\n│    };\n│----\n│  } else if (process.env.OPENAI_PROVIDER === \'openai\') {\n│----\n│    const openai = new OpenAI();\n│\n│----\n│    const response = await openai.audio.speech.create({\n│      model: "tts-1",\n│  } else {\n│----\n│    const openai = new OpenAI();\n│\n│----\n│    const response = await openai.audio.speech.create({\n│      model: "tts-1",\n│----'}, {'type': 'text', 'text': '<environment_details>\n# VSCode Visible Files\n(No visible files)\n\n# VSCode Open Tabs\n(No open tabs)\n</environment_details>'}]
assistant: Based on the search results, there are occurrences of OpenAI API usage in the `app/api/chat/route.ts` and `app/actions.ts` files. The details provided suggest that there might be multiple places where the endpoint configuration is set or utilized. Specifically, `app/actions.ts` includes a baseURL definition as follows:

```javascript
baseURL: 'https://api.groq.com/openai/v1',
```

This is likely the part you want to change to the new endpoint: `https://api.chatanywhere.tech/v1`. Let's update this endpoint in the `app/actions.ts` file.

I will proceed to read the `app/actions.ts` file to update the endpoint. 

<read_file>
<path>app/actions.ts</path>
</read_file>
user: [{'type': 'text', 'text': "[read_file for 'app/actions.ts'] Result:"}, {'type': 'text', 'text': '\'use server\';\n\nimport { OpenAI, AzureOpenAI } from \'openai\';\nimport { generateObject } from \'ai\';\nimport { createOpenAI as createGroq } from \'@ai-sdk/openai\';\nimport { z } from \'zod\';\n\nconst groq = createGroq({\n  baseURL: \'https://api.groq.com/openai/v1\',\n  apiKey: process.env.GROQ_API_KEY,\n});\n\nexport async function suggestQuestions(history: any[]) {\n  \'use server\';\n\n  const { object } = await generateObject({\n    model: groq(\'llama-3.1-70b-versatile\'),\n    temperature: 0,\n    system:\n      `You are a search engine query generator. You \'have\' to create only \'3\' questions for the search engine based on the message history which has been provided to you.\nThe questions should be open-ended and should encourage further discussion while maintaining the whole context. Limit it to 5-10 words per question. \nAlways put the user input\'s context is some way so that the next search knows what to search for exactly.\nTry to stick to the context of the conversation and avoid asking questions that are too general or too specific.\nFor weather based converations sent to you, always generate questions that are about news, sports, or other topics that are not related to the weather.\nFor programming based conversations, always generate questions that are about the algorithms, data structures, or other topics that are related to it or an improvement of the question.\nFor location based conversations, always generate questions that are about the culture, history, or other topics that are related to the location.\nFor the translation based conversations, always generate questions that may continue the conversation or ask for more information or translations.\nNever use pronouns in the questions as they blur the context.`,\n    messages: history,\n    schema: z.object({\n      questions: z.array(z.string()).describe(\'The generated questions based on the message history.\')\n    }),\n  });\n\n  return {\n    questions: object.questions\n  };\n}\n\nexport async function generateSpeech(text: string, voice: \'alloy\' | \'echo\' | \'fable\' | \'onyx\' | \'nova\' | \'shimmer\' = "alloy") {\n  if (process.env.OPENAI_PROVIDER === \'azure\') {\n    if (!process.env.AZURE_OPENAI_API_KEY || !process.env.AZURE_OPENAI_API_URL) {\n      throw new Error(\'Azure OpenAI API key and URL are required.\');\n    }\n    const url = process.env.AZURE_OPENAI_API_URL!;\n\n    const response = await fetch(url, {\n      method: \'POST\',\n      headers: {\n        \'api-key\': process.env.AZURE_OPENAI_API_KEY!,\n        \'Content-Type\': \'application/json\'\n      },\n      body: JSON.stringify({\n        model: "tts",\n        input: text,\n        voice: voice\n      })\n    });\n\n    if (!response.ok) {\n      throw new Error(`Failed to generate speech: ${response.statusText}`);\n    }\n\n    const arrayBuffer = await response.arrayBuffer();\n    const base64Audio = Buffer.from(arrayBuffer).toString(\'base64\');\n\n    return {\n      audio: `data:audio/mp3;base64,${base64Audio}`,\n    };\n  } else if (process.env.OPENAI_PROVIDER === \'openai\') {\n    const openai = new OpenAI();\n\n    const response = await openai.audio.speech.create({\n      model: "tts-1",\n      voice: voice,\n      input: text,\n    });\n\n    const arrayBuffer = await response.arrayBuffer();\n    const base64Audio = Buffer.from(arrayBuffer).toString(\'base64\');\n\n    return {\n      audio: `data:audio/mp3;base64,${base64Audio}`,\n    };\n  } else {\n    const openai = new OpenAI();\n\n    const response = await openai.audio.speech.create({\n      model: "tts-1",\n      voice: voice,\n      input: text,\n    });\n\n    const arrayBuffer = await response.arrayBuffer();\n\n    const base64Audio = Buffer.from(arrayBuffer).toString(\'base64\');\n\n    return {\n      audio: `data:audio/mp3;base64,${base64Audio}`,\n    };\n  }\n}'}, {'type': 'text', 'text': '<environment_details>\n# VSCode Visible Files\n(No visible files)\n\n# VSCode Open Tabs\n(No open tabs)\n</environment_details>'}]
assistant: <thinking>
I have located the section in `app/actions.ts` where the base URL for the OpenAI API is specified:

```typescript
const groq = createGroq({
  baseURL: 'https://api.groq.com/openai/v1',
  apiKey: process.env.GROQ_API_KEY,
});
```

This is the section that needs to be modified to change the endpoint to `https://api.chatanywhere.tech/v1`. I will update this line with the new endpoint and write the changes back to `app/actions.ts`.
</thinking>

<write_to_file>
<path>app/actions.ts</path>
<content>
'use server';

import { OpenAI, AzureOpenAI } from 'openai';
import { generateObject } from 'ai';
import { createOpenAI as createGroq } from '@ai-sdk/openai';
import { z } from 'zod';

const groq = createGroq({
  baseURL: 'https://api.chatanywhere.tech/v1',
  apiKey: process.env.GROQ_API_KEY,
});

export async function suggestQuestions(history: any[]) {
  'use server';

  const { object } = await generateObject({
    model: groq('llama-3.1-70b-versatile'),
    temperature: 0,
    system:
      `You are a search engine query generator. You 'have' to create only '3' questions for the search engine based on the message history which has been provided to you.
The questions should be open-ended and should encourage further discussion while maintaining the whole context. Limit it to 5-10 words per question. 
Always put the user input's context in some way so that the next search knows what to search for exactly.
Try to stick to the context of the conversation and avoid asking questions that are too general or too specific.
For weather based conversations sent to you, always generate questions that are about news, sports, or other topics that are not related to the weather.
For programming based conversations, always generate questions that are about the algorithms, data structures, or other topics that are related to it or an improvement of the question.
For location based conversations, always generate questions that are about the culture, history, or other topics that are related to the location.
For the translation based conversations, always generate questions that may continue the conversation or ask for more information or translations.
Never use pronouns in the questions as they blur the context.`,
    messages: history,
    schema: z.object({
      questions: z.array(z.string()).describe('The generated questions based on the message history.')
    }),
  });

  return {
    questions: object.questions
  };
}

export async function generateSpeech(text: string, voice: 'alloy' | 'echo' | 'fable' | 'onyx' | 'nova' | 'shimmer' = "alloy") {
  if (process.env.OPENAI_PROVIDER === 'azure') {
    if (!process.env.AZURE_OPENAI_API_KEY || !process.env.AZURE_OPENAI_API_URL) {
      throw new Error('Azure OpenAI API key and URL are required.');
    }
    const url = process.env.AZURE_OPENAI_API_URL!;

    const response = await fetch(url, {
      method: 'POST',
      headers: {
        'api-key': process.env.AZURE_OPENAI_API_KEY!,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({
        model: "tts",
        input: text,
        voice: voice
      })
    });

    if (!response.ok) {
      throw new Error(`Failed to generate speech: ${response.statusText}`);
    }

    const arrayBuffer = await response.arrayBuffer();
    const base64Audio = Buffer.from(arrayBuffer).toString('base64');

    return {
      audio: `data:audio/mp3;base64,${base64Audio}`,
    };
  } else if (process.env.OPENAI_PROVIDER === 'openai') {
    const openai = new OpenAI();

    const response = await openai.audio.speech.create({
      model: "tts-1",
      voice: voice,
      input: text,
    });

    const arrayBuffer = await response.arrayBuffer();
    const base64Audio = Buffer.from(arrayBuffer).toString('base64');

    return {
      audio: `data:audio/mp3;base64,${base64Audio}`,
    };
  } else {
    const openai = new OpenAI();

    const response = await openai.audio.speech.create({
      model: "tts-1",
      voice: voice,
      input: text,
    });

    const arrayBuffer = await response.arrayBuffer();

    const base64Audio = Buffer.from(arrayBuffer).toString('base64');

    return {
      audio: `data:audio/mp3;base64,${base64Audio}`,
    };
  }
}
</content>
</write_to_file>
user: [{'type': 'text', 'text': "[write_to_file for 'app/actions.ts'] Result:"}, {'type': 'text', 'text': "The content was successfully saved to app/actions.ts.\n\nNew problems detected after saving the file:\ntsconfig.json\n- [ts Error] Line 1: Cannot find type definition file for 'google.maps'.\n  The file is in the program because:\n    Entry point of type library 'google.maps' specified in compilerOptions\n\napp/actions.ts\n- [ts Error] Line 3: Cannot find module 'openai' or its corresponding type declarations.\n- [ts Error] Line 4: Cannot find module 'ai' or its corresponding type declarations.\n- [ts Error] Line 5: Cannot find module '@ai-sdk/openai' or its corresponding type declarations.\n- [ts Error] Line 6: Cannot find module 'zod' or its corresponding type declarations.\n- [ts Error] Line 10: Cannot find name 'process'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig.\n- [ts Error] Line 41: Cannot find name 'process'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig.\n- [ts Error] Line 42: Cannot find name 'process'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig.\n- [ts Error] Line 42: Cannot find name 'process'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig.\n- [ts Error] Line 45: Cannot find name 'process'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig.\n- [ts Error] Line 50: Cannot find name 'process'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig.\n- [ts Error] Line 65: Cannot find name 'Buffer'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig.\n- [ts Error] Line 70: Cannot find name 'process'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig.\n- [ts Error] Line 80: Cannot find name 'Buffer'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig.\n- [ts Error] Line 96: Cannot find name 'Buffer'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node` and then add 'node' to the types field in your tsconfig."}, {'type': 'text', 'text': '<environment_details>\n# VSCode Visible Files\napp/actions.ts\n\n# VSCode Open Tabs\napp/actions.ts\n</environment_details>'}]
assistant: The endpoint in `app/actions.ts` has been successfully updated to `https://api.chatanywhere.tech/v1`. However, there are a number of TypeScript errors in the project related to missing modules and type definitions, such as the following:

- Modules like `'openai'`, `'ai'`, `'@ai-sdk/openai'`, and `'zod'` are not found.
- The use of `process` and `Buffer` requires Node.js type definitions.

To address these issues, consider the following actions:

1. **Install Required Packages**: Make sure that required packages (`openai`, `ai`, `@ai-sdk/openai`, `zod`) are installed. You can typically do this using a package manager like npm or yarn.

2. **Install Node.js Type Definitions**: Add the Node.js type definitions by running:

   ```bash
   npm i --save-dev @types/node
   ```

   Then, ensure `'node'` is added to the `types` field in your `tsconfig.json`.

3. **Verify Type Declarations**: Ensure the type declaration files for your dependencies are correctly installed or available.

Address these steps to resolve the errors related to type declarations and missing modules.
user: [{'type': 'text', 'text': "[ERROR] You did not use a tool in your previous response! Please retry with a tool use.\n\n# Reminder: Instructions for Tool Use\n\nTool uses are formatted using XML-style tags. The tool name is enclosed in opening and closing tags, and each parameter is similarly enclosed within its own set of tags. Here's the structure:\n\n<tool_name>\n<parameter1_name>value1</parameter1_name>\n<parameter2_name>value2</parameter2_name>\n...\n</tool_name>\n\nFor example:\n\n<attempt_completion>\n<result>\nI have completed the task...\n</result>\n</attempt_completion>\n\nAlways adhere to this format for all tool uses to ensure proper parsing and execution.\n\n# Next Steps\n\nIf you have completed the user's task, use the attempt_completion tool. \nIf you require additional information from the user, use the ask_followup_question tool. \nOtherwise, if you have not completed the task and do not need additional information, then proceed with the next step of the task. \n(This is an automated message, so do not respond to it conversationally.)"}, {'type': 'text', 'text': '<environment_details>\n# VSCode Visible Files\napp/actions.ts\n\n# VSCode Open Tabs\napp/actions.ts\n</environment_details>'}]
assistant: <attempt_completion>
<result>
The OpenAI endpoint in `app/actions.ts` has been successfully updated to the new URL: `https://api.chatanywhere.tech/v1`. However, there are TypeScript errors related to missing modules and type definitions that need to be addressed. Please ensure the necessary packages such as `openai`, `ai`, `@ai-sdk/openai`, and `zod` are installed. Additionally, you may need to install Node.js type definitions by running `npm i --save-dev @types/node` and updating the `tsconfig.json` file to include `'node'` in the `types` array. This will help resolve issues related to `process` and `Buffer` declarations.
</result>
</attempt_completion>
user: [{'type': 'text', 'text': '[attempt_completion] Result:'}, {'type': 'text', 'text': 'The user has provided feedback on the results. Consider their input to continue the task, and then attempt completion again.\n<feedback>\nla de groq no sino la de openai\n</feedback>'}, {'type': 'text', 'text': '<environment_details>\n# VSCode Visible Files\napp/actions.ts\n\n# VSCode Open Tabs\napp/actions.ts\n</environment_details>'}]