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app.py

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+# + tags=["hide_inp"]
+
+desc = """
+### Agent
+
+Chain that executes different tools based on model decisions. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/srush/MiniChain/blob/master/examples/bash.ipynb)
+
+(Adapted from LangChain )
+"""
+# -
+
+# $
+
+from minichain import Id, prompt, OpenAI, show, transform, Mock, Break
+from gradio_tools.tools import StableDiffusionTool, ImageCaptioningTool, ImageToMusicTool
+
+
+# class ImageCaptioningTool:
+#     def run(self, inp):
+#         return "This is a picture of a smiling huggingface logo."
+
+#     description = "Image Captioning"
+
+tools = [StableDiffusionTool(), ImageCaptioningTool(), ImageToMusicTool()]
+
+
+@prompt(OpenAI(stop=["Observation:"]),
+        template_file="agent.pmpt.tpl")
+def agent(model, query, history):
+    return model(dict(tools=[(str(tool.__class__.__name__), tool.description)
+                             for tool in tools],
+                      input=query,
+                      agent_scratchpad=history
+                      ))
+@transform()
+def tool_parse(out):
+    lines = out.split("\n")
+    if lines[0].split("?")[-1].strip() == "Yes":
+        tool = lines[1].split(":", 1)[-1].strip()
+        command = lines[2].split(":", 1)[-1].strip()
+        return tool, command
+    else:
+        return Break()
+
+@prompt(tools)
+def tool_use(model, usage):
+    selector, command = usage
+    for i, tool in enumerate(tools):
+        if selector == tool.__class__.__name__:
+            return model(command, tool_num=i)
+    return ("",)
+
+@transform()
+def append(history, new, observation):
+    return history + "\n" + new + "Observation: " + observation
+
+def run(query):
+    history = ""
+    observations = []
+    for i in range(3):
+        select_input = agent(query, history)
+        observations.append(tool_use(tool_parse(select_input)))
+        history = append(history, select_input, observations[i])
+
+    return observations[-1]
+
+# $
+
+gradio = show(run,
+              subprompts=[agent, tool_use] * 3,
+              examples=[
+                  "I would please like a photo of a dog riding a skateboard. "
+                  "Please caption this image and create a song for it.",
+                  'Use an image generator tool to draw a cat.',
+                  'Caption the image https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo.png from the internet'],
+              out_type="markdown",
+              description=desc,
+              show_advanced=False
+              )
+if __name__ == "__main__":
+    gradio.queue().launch()
+