adb track usage

README.md

@@ -41,4 +41,8 @@ pip3 install --upgrade langchain
 查看安装列表及版本：
 pip3 list
 
+TODO:
+1.看一下ONNXruntime
+2.详细看一下gptcache
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

llms_cache_gpt_similarity.py

@@ -13,8 +13,8 @@ from gptcache.similarity_evaluation.distance import SearchDistanceEvaluation
 llm = OpenAI(model_name="text-davinci-003")
 
 # Avoid multiple caches using the same file, causing different llm model caches to affect each other
-i = 0
-file_prefix = "data_map_similarity"
+i = 1
+file_prefix = "data_onnx"
 llm_cache = Cache()
 
 
@@ -33,10 +33,8 @@ def init_gptcache_map(cache_obj: gptcache.Cache):
     )
     i += 1
 
-langchain.llm_cache = GPTCache(init_gptcache_map)
-
-%%time
-for i in range(20):
+for i in range(50):
+    langchain.llm_cache = GPTCache(init_gptcache_map)
     start = time.perf_counter()
     prompt = "男生有2人，女生有{:d}人，一共多少人？".format(i)
     print("男生有2人，女生有{:d}人, {:s}。 suspend: {:0.4f}".format(i, llm(prompt), time.perf_counter() - start))

openai_agent.py

@@ -2,6 +2,7 @@ from langchain.agents import load_tools
 from langchain.agents import initialize_agent
 from langchain.agents import AgentType
 from langchain.llms import OpenAI
+from langchain.callbacks import get_openai_callback
 
 # First, let's load the language model we're going to use to control the agent.
 llm = OpenAI(temperature=0)
@@ -14,4 +15,11 @@ tools = load_tools(["serpapi", "llm-math"], llm=llm)
 agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)
 
 # Now let's test it out!
-agent.run("昨天北京气温如何?")
+agent.run("昨天北京气温如何?")
+
+with get_openai_callback() as cb:
+    response = agent.run("Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?")
+    print(f"Total Tokens: {cb.total_tokens}")
+    print(f"Prompt Tokens: {cb.prompt_tokens}")
+    print(f"Completion Tokens: {cb.completion_tokens}")
+    print(f"Total Cost (USD): ${cb.total_cost}")

openai_track_usage.ipynb

@@ -0,0 +1,69 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.llms import OpenAI\n",
+    "from langchain.callbacks import get_openai_callback"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "llm = OpenAI(model_name=\"text-davinci-002\", temperature=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tokens Used: 56\n",
+      "\tPrompt Tokens: 44\n",
+      "\tCompletion Tokens: 12\n",
+      "Successful Requests: 2\n",
+      "Total Cost (USD): $0.0011200000000000001\n"
+     ]
+    }
+   ],
+   "source": [
+    "with get_openai_callback() as suspend:\n",
+    "    llm(\"男生3人，女生2人，老师有1人，一共多少人？\")\n",
+    "    llm(\"33*2=？\")\n",
+    "    print(suspend)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.10"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}