Better UX for interactive model

promptware · Nov 12, 2024 · dfbf8e1 · dfbf8e1
1 parent ab591c7
commit dfbf8e1
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Showing 3 changed files with 12 additions and 5 deletions.
diff --git a/python/src/eval.py b/python/src/eval.py
@@ -91,16 +91,16 @@ async def eval_ast(ast, runtime):
         retries = 0
         prompt = IF_PROMPT + condition
         while prompt_result != "true" and prompt_result != "false":
-            prompt_result = await runtime.invoke(prompt)
-            prompt_result = prompt_result.strip()
-            retries += 1
             if retries >= MAX_RETRIES:
                 raise ValueError(
                     "Failed to answer :if prompt: "
                     + prompt
                     + "\nOutput: "
                     + prompt_result
                 )
+            prompt_result = await runtime.invoke(prompt)
+            prompt_result = prompt_result.strip()
+            retries += 1
         if prompt_result == "true":
             async for chunk in eval_ast(ast["then"], runtime):
                 yield chunk

diff --git a/python/src/main.py b/python/src/main.py
@@ -33,6 +33,13 @@ def parse_arguments():
         "INPUT_FILES", nargs="*", help="A list of metaprompt files."
     )
 
+    parser.add_argument(
+        "--model",
+        type=str,
+        help="LLM id to use",
+        default="interactive" # TODO: use dynamic model selection
+    )
+
     parser.add_argument(
         "--set",
         action=ParseSetAction,
@@ -55,7 +62,7 @@ async def main():
                 content = file.read()
                 metaprompt = parse_metaprompt(content)
                 env = Env(env=config.parameters)
-                config.model = "gpt-3.5-turbo"
+                config.model = args.model or "interactive"
                 runtime = Runtime(config, env)
                 runtime.cwd = os.path.dirname(file_path)
                 async for chunk in eval_ast(metaprompt, runtime):

diff --git a/python/src/providers/interactive.py b/python/src/providers/interactive.py
@@ -29,5 +29,5 @@ async def ainvoke(self, prompt: str) -> AsyncGenerator[str, None]:
         Yields:
             str: Chunks of the response as they're received.
         """
-        output = input("[interactive]: " + prompt)
+        output = input("[Q]: " + prompt + "\n[A]: ")
         yield output