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app.py

@@ -1,6 +1,15 @@
-# Information extraction from a typed data specification.
 
-import minichain
+desc = """
+### Typed Extraction
+
+Information extraction that is automatically generated from a typed specification. [[Code](https://github.com/srush/MiniChain/blob/main/examples/stats.py)]
+
+(Novel to MiniChain)
+"""
+
+# $
+
+from minichain import prompt, show, type_to_prompt, OpenAI
 from dataclasses import dataclass
 from typing import List
 from enum import Enum
@@ -25,22 +34,28 @@ class Player:
 # -
 
 
-# Code
+@prompt(OpenAI(), template_file="stats.pmpt.tpl", parser="json")
+def stats(model, passage):
+    out = model(dict(passage=passage, typ=type_to_prompt(Player)))
+    return [Player(**j) for j in out]  
 
-class ExtractionPrompt(minichain.TypedTemplatePrompt):
-    template_file = "stats.pmpt.tpl"
-    Out = Player
+# $
 
+article = open("sixers.txt").read()
+gradio = show(lambda passage: stats(passage),
+              examples=[article],
+              subprompts=[stats],
+              out_type="json",
+              description=desc,
+              code=open("stats.py", "r").read().split("$")[1].strip().strip("#").strip(),
+)
+if __name__ == "__main__":
+    gradio.launch()
 
-with minichain.start_chain("stats") as backend:
-    p = ExtractionPrompt(backend.OpenAI(max_tokens=512))
-    article = open("sixers.txt").read()
-    for player in p({"passage": article}):
-        print(player)
 
-ExtractionPrompt().show({"passage": "Harden had 10 rebounds."},
-                        '[{"player": "Harden", "stats": {"value": 10, "stat": 2}}]')
+# ExtractionPrompt().show({"passage": "Harden had 10 rebounds."},
+#                         '[{"player": "Harden", "stats": {"value": 10, "stat": 2}}]')
 
-# View the run log.
+# # View the run log.
 
-minichain.show_log("bash.log")
+# minichain.show_log("bash.log")

requirements.txt

@@ -1,3 +1,4 @@
-gradio
+gradio==3.21.0
 git+https://github.com/srush/minichain@gradio
 manifest-ml
+faiss-cpu