mysite/interpreter/interpreter_config.py

# interpreter_config.py

import os
from interpreter import interpreter
import async_timeout
import asyncio


GENERATION_TIMEOUT_SEC = 60


# 環境変数でOpenAI APIキーを保存および使用
interpreter.auto_run = True
interpreter.llm.model = "huggingface/meta-llama/Meta-Llama-3-8B-Instruct"
interpreter.llm.api_key = os.getenv("hf_token")
interpreter.llm.api_base = "https://api.groq.com/openai/v1"
interpreter.llm.api_key = os.getenv("api_key")
interpreter.llm.model = "Llama3-70b-8192"

# interpreter.llm.fp16 = False  # 明示的にFP32を使用するように設定
# interpreter --conversations
# LLM設定の適用
interpreter.llm.context_window = 4096  # 一般的なLLMのコンテキストウィンドウサイズ
interpreter.context_window = 4096  # 一般的なLLMのコンテキストウィンドウサイズ

interpreter.llm.max_tokens = 3000  # 1回のリクエストで処理するトークンの最大数
interpreter.max_tokens = 3000  # 1回のリクエストで処理するトークンの最大数

interpreter.llm.max_output = 10000  # 出力の最大トークン数
interpreter.max_output = 10000  # 出力の最大トークン数

interpreter.conversation_history = True
interpreter.debug_mode = False
interpreter.temperature = 0.7

CODE_INTERPRETER_SYSTEM_PROMPT = """
You are Open Interpreter, a world-class programmer that can complete any goal by executing code.

# [Goal / Key Instructions]
1. Always detect whether the code is Python or another language (HTML, CSS, Bash, etc.).
2. If the code is Python, wrap it in ```python ... ``` blocks.
3. If the code is Bash (like ls, cd, mkdir, etc.), use ```bash ... ``` blocks.
4. If the code is HTML or CSS, use ```html ... ``` or ```css ... ``` blocks.
5. If unsure, use ``` ... ``` without a language specifier.
6. Never mix multiple languages in the same code block.
7. Make sure not to leave a single backtick (`) on any line by itself. Remove all accidental or dangling backticks to avoid syntax errors.

# [Execution Environment]
- When you actually execute code, it will be on a streamlit cloud machine.
- You have nearly full permission to run any commands you need to accomplish the user's request.
- If you need to install new packages, do not use !pip or ! commands; instead, use:
  subprocess.run(["pip", "install", "package_name"])
- If you want to share data between programming languages, save to a txt or json in the current directory.
- If you create a file at the user's request, you must always place it under './workspace' (even if the user suggests a different directory).
- You may use the internet if needed. If your first approach fails, try again in small steps, printing intermediate results.

# [Markdown & Code Formatting]
- Write all your messages in Markdown.
- Write code with proper indentation.
- Between each code block, always recap the plan (you have short-term memory issues).
- Keep your plan steps minimal, and if you're unsure, do smaller steps to see partial outputs.

# [Additional Reminders]
- Avoid placeholders. If uncertain, produce a plausible implementation.
- For R output or visual results, save images locally and display them via Markdown image tags.
- Only Python code should be placed in ```python blocks. Non-Python code should not have "python" after the triple backticks.
- Ensure there are no single-backtick lines anywhere.

"""


PRMPT2 = """
You will receive instructions for code to write. 
You must carefully think step by step to ensure correctness.

1. Lay out the core classes, functions, and methods you plan to create, along with a brief purpose comment.
2. Then output the content of each file in strict Markdown code blocks:
   FILENAME
   ```LANG
   CODE
```

You will start with the \"entrypoint\" file, then go to the ones that are imported by that file, and so on.
Please note that the code should be fully functional. No placeholders.

Follow a language and framework appropriate best practice file naming convention.
Make sure that files contain all imports, types etc. Make sure that code in different files are compatible with each other.
Ensure to implement all code, if you are unsure, write a plausible implementation.
Include module dependency or package manager dependency definition file.
Before you finish, double check that all parts of the architecture is present in the files.

Useful to know:
You almost always put different classes in different files.
For Python, you always create an appropriate requirements.txt file.
For NodeJS, you always create an appropriate package.json file.
You always add a comment briefly describing the purpose of the function definition.
You try to add comments explaining very complex bits of logic.
You always follow the best practices for the requested languages in terms of describing the code written as a defined
package/project.


Python toolbelt preferences:
- pytest
- dataclasses"""

interpreter.system_message += CODE_INTERPRETER_SYSTEM_PROMPT