Add OpenAI API key parameter and refactor file handling

gpt_engineer/ai.py

@@ -37,7 +37,9 @@ class TokenUsage:
 
 
 class AI:
-    def __init__(self, model_name="gpt-4", temperature=0.1, azure_endpoint=""):
+    def __init__(
+        self, model_name="gpt-4", temperature=0.1, azure_endpoint="", openai_api_key=""
+    ):
         """
         Initialize the AI class.
 
@@ -53,7 +55,9 @@ def __init__(self, model_name="gpt-4", temperature=0.1, azure_endpoint=""):
         self.model_name = (
             fallback_model(model_name) if azure_endpoint == "" else model_name
         )
-        self.llm = create_chat_model(self, self.model_name, self.temperature)
+        self.llm = create_chat_model(
+            self, self.model_name, self.temperature, openai_api_key
+        )
         self.tokenizer = get_tokenizer(self.model_name)
         logger.debug(f"Using model {self.model_name} with llm {self.llm}")
 
@@ -339,7 +343,7 @@ def fallback_model(model: str) -> str:
         return "gpt-3.5-turbo"
 
 
-def create_chat_model(self, model: str, temperature) -> BaseChatModel:
+def create_chat_model(self, model: str, temperature, openai_api_key="") -> BaseChatModel:
     """
     Create a chat model with the specified model name and temperature.
 
@@ -349,6 +353,8 @@ def create_chat_model(self, model: str, temperature) -> BaseChatModel:
         The name of the model to create.
     temperature : float
         The temperature to use for the model.
+    openai_api_key : str
+        OpenAI API key
 
     Returns
     -------
@@ -362,6 +368,7 @@ def create_chat_model(self, model: str, temperature) -> BaseChatModel:
             deployment_name=model,
             openai_api_type="azure",
             streaming=True,
+            openai_api_key=openai_api_key,
         )
     # Fetch available models from OpenAI API
     supported = [model["id"] for model in openai.Model.list()["data"]]
@@ -374,6 +381,7 @@ def create_chat_model(self, model: str, temperature) -> BaseChatModel:
         temperature=temperature,
         streaming=True,
         client=openai.ChatCompletion,
+        openai_api_key=openai_api_key,
     )
 
 

gpt_engineer/chat_to_files.py

@@ -45,7 +45,7 @@ def parse_chat(chat) -> List[Tuple[str, str]]:
 
     # Get all the text before the first ``` block
     readme = chat.split("```")[0]
-    files.append(("README.md", readme))
+    files.append(("LAST_MODIFICATION_README.md", readme))
 
     # Return the files
     return files
@@ -69,6 +69,24 @@ def to_files(chat, workspace):
         workspace[file_name] = file_content
 
 
+def to_files_(chat, dbs):
+    """
+    Parse the chat and add all extracted files to the workspace.
+
+    Parameters
+    ----------
+    chat : str
+        The chat to parse.
+    workspace : dict
+        The workspace to add the files to.
+    """
+    dbs.project_metadata["all_output.txt"] = chat
+
+    files = parse_chat(chat)
+    for file_name, file_content in files:
+        dbs.workspace[file_name] = file_content
+
+
 def overwrite_files(chat, dbs):
     """
     Replace the AI files with the older local files.
@@ -82,12 +100,14 @@ def overwrite_files(chat, dbs):
     replace_files : dict
         A dictionary mapping file names to file paths of the local files.
     """
-    dbs.workspace["all_output.txt"] = chat
+    dbs.project_metadata[
+        "all_output.txt"
+    ] = chat  # files_info = get_code_strings(dbs.project_metadata)
 
     files = parse_chat(chat)
     for file_name, file_content in files:
-        if file_name == "README.md":
-            dbs.workspace["LAST_MODIFICATION_README.md"] = file_content
+        if file_name == "LAST_MODIFICATION_README.md":
+            dbs.project_metadata["LAST_MODIFICATION_README.md"] = file_content
         else:
             dbs.workspace[file_name] = file_content
 

gpt_engineer/db.py

@@ -124,6 +124,7 @@ class DBs:
     input: DB
     workspace: DB
     archive: DB
+    project_metadata: DB
 
 
 def archive(dbs: DBs) -> None:

gpt_engineer/main.py

@@ -77,6 +77,7 @@ def main(
             Path(__file__).parent / "preprompts"
         ),  # Loads preprompts from the preprompts directory
         archive=DB(archive_path),
+        project_metadata=DB(base_metadata_path),
     )
 
     if steps_config not in [

gpt_engineer/steps.py

@@ -1,4 +1,5 @@
 import inspect
+import os
 import re
 import subprocess
 
@@ -14,6 +15,7 @@
     get_code_strings,
     overwrite_files,
     to_files,
+    to_files_,
 )
 from gpt_engineer.db import DBs
 from gpt_engineer.file_selector import FILE_LIST_NAME, ask_for_files
@@ -81,7 +83,14 @@ def curr_fn() -> str:
 def simple_gen(ai: AI, dbs: DBs) -> List[Message]:
     """Run the AI on the main prompt and save the results"""
     messages = ai.start(setup_sys_prompt(dbs), get_prompt(dbs), step_name=curr_fn())
-    to_files(messages[-1].content.strip(), dbs.workspace)
+
+    SERVICE_MODE = os.environ.get("SERVICE_MODE", False)
+
+    if SERVICE_MODE:
+        to_files_(messages[-1].content.strip(), dbs)
+    else:
+        to_files(messages[-1].content.strip(), dbs.workspace)
+
     return messages
 
 
@@ -273,7 +282,8 @@ def gen_entrypoint(ai: AI, dbs: DBs) -> List[dict]:
             "Do not use placeholders, use example values (like . for a folder argument) "
             "if necessary.\n"
         ),
-        user="Information about the codebase:\n\n" + dbs.workspace["all_output.txt"],
+        user="Information about the codebase:\n\n"
+        + dbs.project_metadata["all_output.txt"],
         step_name=curr_fn(),
     )
     print()
@@ -357,7 +367,7 @@ def improve_existing_code(ai: AI, dbs: DBs):
     to sent the formatted prompt to the LLM.
     """
 
-    files_info = get_code_strings(dbs.input)  # this only has file names not paths
+    files_info = get_code_strings(dbs.input)
 
     messages = [
         ai.fsystem(setup_sys_prompt_existing_code(dbs)),
@@ -441,7 +451,7 @@ class Config(str, Enum):
     Config.SIMPLE: [
         simple_gen,
         gen_entrypoint,
-        execute_entrypoint,
+        # execute_entrypoint,
     ],
     Config.TDD: [
         gen_spec,