demo

cookbook/demo.ipynb

@@ -2,28 +2,9 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
+   "outputs": [],
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "No relevant file found: the question has no relevant file because while some files discuss startups, none specifically address how to find or generate startup ideas\n",
-      "No question asked\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "'default'"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
    "source": [
     "# Example App for text summarization & QA using minillmflow\n",
     "from minillmflow import Node, BatchNode, Flow, BatchFlow, AsyncNode, AsyncFlow, BatchAsyncFlow\n",
@@ -37,8 +18,15 @@
     "        model=\"gpt-4\",\n",
     "        messages=[{\"role\": \"user\", \"content\": prompt}]\n",
     "    )\n",
-    "    return r.choices[0].message.content\n",
+    "    return r.choices[0].message.content"
-    "\n",
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "# 2) Create a shared store (dict) for Node/Flow data exchange.\n",
     "#    This can be replaced with a DB or other storage.\n",
     "#    Design the structure / schema based on the app requirements.\n",
@@ -60,8 +48,15 @@
     "\n",
     "load_data = LoadData()\n",
     "# Run the data-loading node once\n",
-    "load_data.run(shared)\n",
+    "load_data.run(shared)"
-    "\n",
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "# 4) Create a Node that summarizes a single file using the LLM.\n",
     "class SummarizeFile(Node):\n",
     "    def prep(self, shared):\n",
@@ -81,8 +76,15 @@
     "# For testing, we set params directly on the node.\n",
     "# In real usage, you'd set them in a Flow or BatchFlow.\n",
     "summarize_file.set_params({\"filename\":\"addiction.txt\"})\n",
-    "summarize_file.run(shared)\n",
+    "summarize_file.run(shared)"
-    "\n",
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "# 5) If data is large, we can apply a map-reduce pattern:\n",
     "#    - MapSummaries(BatchNode) => chunk the file and summarize each chunk\n",
     "#    - ReduceSummaries(Node)   => combine those chunk-level summaries\n",
@@ -135,8 +137,15 @@
     "file_summary_flow = Flow(start=map_summaries)\n",
     "# When a flow params is set, it will recursively set its params to all nodes in the flow\n",
     "file_summary_flow.set_params({\"filename\":\"before.txt\"})\n",
-    "file_summary_flow.run(shared)\n",
+    "file_summary_flow.run(shared)"
-    "\n",
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "# 7) Summarize all files using a BatchFlow that reruns file_summary_flow for each file\n",
     "class SummarizeAllFiles(BatchFlow):\n",
     "    def prep(self, shared):\n",
@@ -147,9 +156,15 @@
     "        return [{\"filename\":filename} for filename in shared['data']]\n",
     "\n",
     "summarize_all_files = SummarizeAllFiles(start=file_summary_flow)\n",
-    "summarize_all_files.run(shared)\n",
+    "summarize_all_files.run(shared)"
-    "\n",
+   ]
-    "\n",
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "# 8) QA Agent: Find the most relevant file based on summary with actions\n",
     "#    if no question is asked:\n",
     "#       (a) end: terminate the flow \n",