🗂️ move actual prompts out of chains

codeinterpreterapi/chains/modifications_check.py

@@ -1,51 +1,11 @@
 import json
-from json import JSONDecodeError
 from typing import List
 
 from langchain.base_language import BaseLanguageModel
 from langchain.chat_models.openai import ChatOpenAI
-from langchain.prompts.chat import (
-    ChatPromptTemplate,
-    HumanMessagePromptTemplate,
-)
-from langchain.schema import (
-    AIMessage,
-    OutputParserException,
-    SystemMessage,
-)
-
-
-prompt = ChatPromptTemplate(
-    input_variables=["code"],
-    messages=[
-        SystemMessage(
-            content="The user will input some code and you will need to determine if the code makes any changes to the file system. \n"
-            "With changes it means creating new files or modifying exsisting ones.\n"
-            "Answer with a function call `determine_modifications` and list them inside.\n"
-            "If the code does not make any changes to the file system, still answer with the function call but return an empty list.\n",
-        ),
-        HumanMessagePromptTemplate.from_template("{code}"),
-    ],
-)
-
-functions = [
-    {
-        "name": "determine_modifications",
-        "description": "Based on code of the user determine if the code makes any changes to the file system. \n"
-        "With changes it means creating new files or modifying exsisting ones.\n",
-        "parameters": {
-            "type": "object",
-            "properties": {
-                "modifications": {
-                    "type": "array",
-                    "items": {"type": "string"},
-                    "description": "The filenames that are modified by the code.",
-                },
-            },
-            "required": ["modifications"],
-        },
-    }
-]
+from langchain.schema import AIMessage, OutputParserException
+
+from codeinterpreterapi.prompts import determine_modifications_function, determine_modifications_prompt
 
 
 async def get_file_modifications(
@@ -55,8 +15,8 @@ async def get_file_modifications(
 ) -> List[str] | None:
     if retry < 1:
         return None
-    messages = prompt.format_prompt(code=code).to_messages()
-    message = await llm.apredict_messages(messages, functions=functions)
+    messages = determine_modifications_prompt.format_prompt(code=code).to_messages()
+    message = await llm.apredict_messages(messages, functions=[determine_modifications_function])
 
     if not isinstance(message, AIMessage):
         raise OutputParserException("Expected an AIMessage")
@@ -71,7 +31,7 @@ async def get_file_modifications(
 
 
 async def test():
-    llm = ChatOpenAI(model="gpt-3.5-turbo-0613")  # type: ignore
+    llm = ChatOpenAI(model="gpt-3.5")  # type: ignore
 
     code = """
     import matplotlib.pyplot as plt
@@ -87,17 +47,12 @@ async def test():
     plt.show()
     """
 
-    code2 = "import pandas as pd\n\n# Read the Excel file\ndata = pd.read_excel('Iris.xlsx')\n\n# Convert the data to CSV\ndata.to_csv('Iris.csv', index=False)"
-
-    modifications = await get_file_modifications(code2, llm)
-
-    print(modifications)
+    print(await get_file_modifications(code, llm))
 
 
 if __name__ == "__main__":
     import asyncio
     from dotenv import load_dotenv
-
     load_dotenv()
 
     asyncio.run(test())

codeinterpreterapi/chains/remove_download_link.py

@@ -1,39 +1,15 @@
 from langchain.base_language import BaseLanguageModel
 from langchain.chat_models.openai import ChatOpenAI
-from langchain.prompts.chat import (
-    ChatPromptTemplate,
-    HumanMessagePromptTemplate,
-)
-from langchain.schema import (
-    AIMessage,
-    OutputParserException,
-    SystemMessage,
-    HumanMessage,
-)
-
-
-prompt = ChatPromptTemplate(
-    input_variables=["input_response"],
-    messages=[
-        SystemMessage(
-            content="The user will send you a response and you need to remove the download link from it.\n"
-            "Reformat the remaining message so no whitespace or half sentences are still there.\n"
-            "If the response does not contain a download link, return the response as is.\n"
-        ),
-        HumanMessage(
-            content="The dataset has been successfully converted to CSV format. You can download the converted file [here](sandbox:/Iris.csv)."
-        ),
-        AIMessage(content="The dataset has been successfully converted to CSV format."),
-        HumanMessagePromptTemplate.from_template("{input_response}"),
-    ],
-)
+from langchain.schema import AIMessage, OutputParserException
+
+from codeinterpreterapi.prompts import remove_dl_link_prompt
 
 
 async def remove_download_link(
     input_response: str,
     llm: BaseLanguageModel,
 ) -> str:
-    messages = prompt.format_prompt(input_response=input_response).to_messages()
+    messages = remove_dl_link_prompt.format_prompt(input_response=input_response).to_messages()
     message = await llm.apredict_messages(messages)
 
     if not isinstance(message, AIMessage):
@@ -47,15 +23,12 @@ async def test():
 
     example = "I have created the plot to your dataset.\n\nLink to the file [here](sandbox:/plot.png)."
 
-    modifications = await remove_download_link(example, llm)
-
-    print(modifications)
+    print(await remove_download_link(example, llm))
 
 
 if __name__ == "__main__":
     import asyncio
-    import dotenv
-
-    dotenv.load_dotenv()
+    from dotenv import load_dotenv
+    load_dotenv()
 
     asyncio.run(test())

codeinterpreterapi/prompts/__init__.py

@@ -1 +1,3 @@
 from .system_message import system_message as code_interpreter_system_message
+from .modifications_check import determine_modifications_function, determine_modifications_prompt
+from .remove_dl_link import remove_dl_link_prompt

codeinterpreterapi/prompts/modifications_check.py

@@ -0,0 +1,35 @@
+
+from langchain.schema import SystemMessage
+from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
+
+
+determine_modifications_prompt = ChatPromptTemplate(
+    input_variables=["code"],
+    messages=[
+        SystemMessage(
+            content="The user will input some code and you will need to determine if the code makes any changes to the file system. \n"
+            "With changes it means creating new files or modifying exsisting ones.\n"
+            "Answer with a function call `determine_modifications` and list them inside.\n"
+            "If the code does not make any changes to the file system, still answer with the function call but return an empty list.\n",
+        ),
+        HumanMessagePromptTemplate.from_template("{code}"),
+    ],
+)
+
+
+determine_modifications_function = {
+    "name": "determine_modifications",
+    "description": "Based on code of the user determine if the code makes any changes to the file system. \n"
+    "With changes it means creating new files or modifying exsisting ones.\n",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "modifications": {
+                "type": "array",
+                "items": {"type": "string"},
+                "description": "The filenames that are modified by the code.",
+            },
+        },
+        "required": ["modifications"],
+    },
+}

codeinterpreterapi/prompts/remove_dl_link.py

@@ -0,0 +1,26 @@
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    HumanMessagePromptTemplate,
+)
+from langchain.schema import (
+    AIMessage,
+    SystemMessage,
+    HumanMessage,
+)
+
+
+remove_dl_link_prompt = ChatPromptTemplate(
+    input_variables=["input_response"],
+    messages=[
+        SystemMessage(
+            content="The user will send you a response and you need to remove the download link from it.\n"
+            "Reformat the remaining message so no whitespace or half sentences are still there.\n"
+            "If the response does not contain a download link, return the response as is.\n"
+        ),
+        HumanMessage(
+            content="The dataset has been successfully converted to CSV format. You can download the converted file [here](sandbox:/Iris.csv)."
+        ),
+        AIMessage(content="The dataset has been successfully converted to CSV format."),
+        HumanMessagePromptTemplate.from_template("{input_response}"),
+    ],
+)