Consolidate explain and diff-converse functions

src/cwhy/__main__.py

@@ -113,13 +113,11 @@ def main() -> None:
         "subcommand",
         nargs="?",
         default="explain",
-        choices=["explain", "diff", "converse", "diff-converse"],
+        choices=["explain", "diff-converse"],
         metavar="subcommand",
         help=textwrap.dedent(
             r"""
                 explain:       explain the diagnostic (default)
-                diff:          \[experimental] generate a diff to fix the diagnostic
-                converse:      \[experimental] interactively converse with CWhy
                 diff-converse: \[experimental] interactively fix errors with CWhy
             """
         ).strip(),
@@ -129,7 +127,7 @@ def main() -> None:
         "--llm",
         type=str,
         default="openai/gpt-4o-mini",
-        help="the language model to use"
+        help="the language model to use",
     )
     parser.add_argument(
         "--timeout",

src/cwhy/conversation/__init__.py

@@ -1,64 +1,13 @@
 import json
 import textwrap
 
-import llm_utils
-import openai
+import openai  # type: ignore
 
 from . import utils
 from .diff_functions import DiffFunctions
-from .explain_functions import ExplainFunctions
 from ..print_debug import dprint
 
 
-def converse(client: openai.OpenAI, args, diagnostic):
-    fns = ExplainFunctions(args)
-    available_functions_names = [fn["function"]["name"] for fn in fns.as_tools()]
-    system_message = textwrap.dedent(
-        f"""
-            You are an assistant debugger. The user is having an issue with their code, and you are trying to help them.
-            A few functions exist to help with this process, namely: {", ".join(available_functions_names)}.
-            Don't hesitate to call as many functions as needed to give the best possible answer.
-            Once you have identified the problem, explain the diagnostic and provide a way to fix the issue if you can.
-        """
-    ).strip()
-    user_message = f"Here is my error message:\n\n```\n{utils.get_truncated_error_message(args, diagnostic)}\n```\n\nWhat's the problem?"
-    conversation = [
-        {"role": "system", "content": system_message},
-        {"role": "user", "content": user_message},
-    ]
-
-    while True:
-        completion = client.chat.completions.create(
-            model=args.llm,
-            messages=conversation,
-            tools=fns.as_tools(),
-            timeout=args.timeout,
-        )
-
-        choice = completion.choices[0]
-        if choice.finish_reason == "tool_calls":
-            responses = []
-            for tool_call in choice.message.tool_calls:
-                function_response = fns.dispatch(tool_call.function)
-                if function_response:
-                    responses.append(
-                        {
-                            "tool_call_id": tool_call.id,
-                            "role": "tool",
-                            "name": tool_call.function.name,
-                            "content": function_response,
-                        }
-                    )
-            conversation.append(choice.message)
-            conversation.extend(responses)
-            dprint()
-        elif choice.finish_reason == "stop":
-            text = completion.choices[0].message.content
-            return llm_utils.word_wrap_except_code_blocks(text)
-        else:
-            dprint(f"Not found: {choice.finish_reason}.")
-
-
 def diff_converse(client: openai.OpenAI, args, diagnostic):
     fns = DiffFunctions(args)
     tools = fns.as_tools()
@@ -76,41 +25,43 @@ def diff_converse(client: openai.OpenAI, args, diagnostic):
         {"role": "user", "content": user_message},
     ]
 
-    pick_action_schema = {
-        "name": "pick_action",
-        "description": "Picks an action to take to get more information about or fix the code.",
-        "parameters": {
-            "type": "object",
-            "properties": {
-                "action": {
-                    "type": "string",
-                    "enum": tool_names,
-                },
-            },
-            "required": ["action"],
-        },
-    }
-
     while True:
         # 1. Pick an action.
-        completion = client.chat.completions.create(
+        completion = client.chat.completions.create(  # type: ignore
             model=args.llm,
             messages=conversation,
-            tools=[{"type": "function", "function": pick_action_schema}],
-            tool_choice={
-                "type": "function",
-                "function": {"name": "pick_action"},
-            },
+            tools=[
+                {
+                    "type": "function",
+                    "function": {
+                        "name": "pick_action",
+                        "description": "Picks an action to get more information about the code or fix it.",
+                        "parameters": {
+                            "type": "object",
+                            "properties": {
+                                "action": {
+                                    "type": "string",
+                                    "enum": tool_names,
+                                },
+                            },
+                            "required": ["action"],
+                        },
+                    },
+                }
+            ],
+            tool_choice={"type": "function", "function": {"name": "pick_action"}},
             timeout=args.timeout,
         )
 
-        print(completion)
-        fn = completion.choices[0].message.tool_calls[0].function
+        assert completion.choices and len(completion.choices) == 1
+        choice = completion.choices[0]
+        assert choice.message.tool_calls and len(choice.message.tool_calls) == 1
+        fn = choice.message.tool_calls[0].function
         arguments = json.loads(fn.arguments)
         action = arguments["action"]
 
         tool = [t for t in tools if t["function"]["name"] == action][0]
-        completion = client.chat.completions.create(
+        completion = client.chat.completions.create(  # type: ignore
             model=args.llm,
             messages=conversation,
             tools=[tool],
@@ -121,7 +72,9 @@ def diff_converse(client: openai.OpenAI, args, diagnostic):
             timeout=args.timeout,
         )
 
+        assert completion.choices and len(completion.choices) == 1
         choice = completion.choices[0]
+        assert choice.message.tool_calls and len(choice.message.tool_calls) == 1
         tool_call = choice.message.tool_calls[0]
         function_response = fns.dispatch(tool_call.function)
         if function_response:
@@ -130,7 +83,6 @@ def diff_converse(client: openai.OpenAI, args, diagnostic):
                 {
                     "tool_call_id": tool_call.id,
                     "role": "tool",
-                    "name": tool_call.function.name,
                     "content": function_response,
                 }
             )

src/cwhy/cwhy.py

@@ -92,8 +92,6 @@ def evaluate(client: openai.OpenAI, args, stdin):
         tool_calls = completion.choices[0].message.tool_calls
         assert len(tool_calls) == 1
         return tool_calls[0].function.arguments
-    elif args.subcommand == "converse":
-        return conversation.converse(client, args, stdin)
     elif args.subcommand == "diff-converse":
         return conversation.diff_converse(client, args, stdin)
     else:

src/cwhy/print_debug.py

@@ -6,7 +6,7 @@
 
 
 def dprint(
-    *objects, sep: str = " ", end: str = "\n", file=None, flush: bool = False
+    *objects: object, sep: str = " ", end: str = "\n", file=None, flush: bool = False
 ) -> None:
     global _debug
     if not _debug: