update notebook for easier comparison
This commit is contained in:
Yingbei
parent
eaec0b8748
commit
711fda99c6
1 changed files with 180 additions and 143 deletions
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@ -2,14 +2,69 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 69,
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"execution_count": 21,
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"metadata": {},
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"outputs": [],
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"source": [
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"def run_completion(chat_method, user_query):\n",
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" print(chat_method)\n",
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"import json\n",
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"import uuid\n",
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"from functools import partial\n",
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"\n",
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"def get_oai_response(model, functions, msgs, api_key, base_url):\n",
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" import openai\n",
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" openai.api_key = api_key ## Add your API key here\n",
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" openai.base_url = base_url\n",
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" print(f\"Pointing to URL: {base_url}\")\n",
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" \n",
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" try:\n",
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" completion = openai.chat.completions.create(\n",
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" model=model,\n",
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" temperature=0.1,\n",
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" messages=msgs,\n",
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" tools=functions,\n",
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" tool_choice=\"auto\",\n",
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" # functions=functions,\n",
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" # function_call=\"auto\",\n",
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" stream=False,\n",
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" )\n",
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" return completion.choices[0]\n",
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" except Exception as e:\n",
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" print(e)\n",
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"\n",
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"\n",
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"def insert_tool_response(res, msgs):\n",
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" # for tool_call in res.message.tool_calls:\n",
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" # print(f\"Tool Call: {tool_call.id}, {tool_call.function}\")\n",
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" assistant_message = res.message\n",
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" tool_calls = []\n",
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" for tool_call in assistant_message.tool_calls:\n",
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" tool_calls.append( {\n",
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" \"id\": tool_call.id,\n",
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" \"function\": {\"name\": tool_call.function.name,\n",
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" \"arguments\": tool_call.function.arguments},\n",
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" \"type\": \"function\",\n",
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" })\n",
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" msgs.append({\"role\": \"assistant\", \"tool_calls\": tool_calls})\n",
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" \n",
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" for i, tool_call in enumerate(assistant_message.tool_calls):\n",
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" if tool_call.function.name == \"getCurrentWeather\":\n",
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" print()\n",
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" l = len((json.loads(assistant_message.tool_calls[i].function.arguments))[\"location\"])\n",
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" msgs.append({\"role\": \"tool\", \"tool_call_id\": str(assistant_message.tool_calls[i].id), \"name\": assistant_message.tool_calls[i].function.name, \"content\": f\"temprature is {(i+1) * 50 + l } degree\"})\n",
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" elif tool_call.function.name == \"calculate_distance\":\n",
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" msgs.append({\"role\": \"tool\", \"tool_call_id\": str(assistant_message.tool_calls[i].id), \"name\": assistant_message.tool_calls[i].function.name, \"content\": f\"Distance is {(i+1) * 1700} miles.\"})\n",
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" elif tool_call.function.name == \"generate_password\":\n",
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" msgs.append({\"role\": \"tool\", \"tool_call_id\": str(assistant_message.tool_calls[i].id), \"name\": assistant_message.tool_calls[i].function.name, \"content\": f\"Password generated: {uuid.uuid4().hex[:8]}\"})\n",
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" else:\n",
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" msgs.append({\"role\": \"tool\", \"tool_call_id\": str(assistant_message.tool_calls[i].id), \"name\": assistant_message.tool_calls[i].function.name, \"content\": f\"Order placed. the price is {(i+1) * 10} dollars.\"})\n",
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" \n",
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" return msgs\n",
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"\n",
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"def run_completion(chat_method, user_query, msgs=[]):\n",
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" system_prompt = \"You are a helpful assistant.\"\n",
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" functions = [\n",
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" # {\"type\": \"function\",\"function\":{\"name\":\"calculate_distance\",\"description\":\"Calculate the distance between two locations\",\"parameters\":{\"type\":\"object\",\"properties\":{\"origin\":{\"type\":\"string\",\"description\":\"The starting location\"},\"destination\":{\"type\":\"string\",\"description\":\"The destination location\"},\"mode\":{\"type\":\"string\",\"description\":\"The mode of transportation\"}},\"required\":[\"origin\",\"destination\",\"mode\"]}}},{\"type\": \"function\",\"function\":{\"name\":\"generate_password\",\"description\":\"Generate a random password\",\"parameters\":{\"type\":\"object\",\"properties\":{\"length\":{\"type\":\"integer\",\"description\":\"The length of the password\"}},\"required\":[\"length\"]}}},\n",
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" \n",
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" {\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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@ -43,102 +98,36 @@
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" ]\n",
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" }\n",
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" }},\n",
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" ]\n",
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" {\"type\": \"function\",\"function\":{\"name\":\"calculate_distance\",\"description\":\"Calculate the distance between two locations\",\"parameters\":{\"type\":\"object\",\"properties\":{\"origin\":{\"type\":\"string\",\"description\":\"The starting location\"},\"destination\":{\"type\":\"string\",\"description\":\"The destination location\"},\"mode\":{\"type\":\"string\",\"description\":\"The mode of transportation\"}},\"required\":[\"origin\",\"destination\",\"mode\"]}}},{\"type\": \"function\",\"function\":{\"name\":\"generate_password\",\"description\":\"Generate a random password\",\"parameters\":{\"type\":\"object\",\"properties\":{\"length\":{\"type\":\"integer\",\"description\":\"The length of the password\"}},\"required\":[\"length\"]}}}\n",
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" ]\n",
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" # functions = [{\"type\": \"function\",\"function\":{\"name\":\"calculate_distance\",\"description\":\"Calculate the distance between two locations\",\"parameters\":{\"type\":\"object\",\"properties\":{\"origin\":{\"type\":\"string\",\"description\":\"The starting location\"},\"destination\":{\"type\":\"string\",\"description\":\"The destination location\"},\"mode\":{\"type\":\"string\",\"description\":\"The mode of transportation\"}},\"required\":[\"origin\",\"destination\",\"mode\"]}}},{\"type\": \"function\",\"function\":{\"name\":\"generate_password\",\"description\":\"Generate a random password\",\"parameters\":{\"type\":\"object\",\"properties\":{\"length\":{\"type\":\"integer\",\"description\":\"The length of the password\"}},\"required\":[\"length\"]}}}]\n",
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"\n",
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" msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}]\n",
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" if not msgs or len(msgs) == 0:\n",
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" msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}]\n",
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" else:\n",
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" msgs.append({\"role\": \"user\", \"content\": user_query})\n",
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"\n",
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" res = chat_method(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
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" print(f\"First Response:\")\n",
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" for tool_call in res.message.tool_calls:\n",
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" print(f\"Tool Call: {tool_call.id}, {tool_call.function}\")\n",
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" assistant_message = res.message\n",
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" tool_calls = []\n",
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" for tool_call in assistant_message.tool_calls:\n",
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" tool_calls.append( {\n",
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" \"id\": tool_call.id,\n",
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" \"function\": {\"name\": tool_call.function.name,\n",
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" \"arguments\": tool_call.function.arguments},\n",
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" \"type\": \"function\",\n",
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" })\n",
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" msgs.append({\"role\": \"assistant\", \"tool_calls\": tool_calls})\n",
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" \n",
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" for i, tool_call in enumerate(assistant_message.tool_calls):\n",
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" if tool_call.function.name == \"getCurrentWeather\":\n",
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" msgs.append({\"role\": \"tool\", \"tool_call_id\": str(assistant_message.tool_calls[i].id), \"name\": assistant_message.tool_calls[i].function.name, \"content\": f\"temprature is {i * 50} degree\"})\n",
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" res = chat_method(model=\"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
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" res_next = res\n",
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" if res_next.message.content and len(res_next.message.content) > 0:\n",
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" print(\"\\n[AI response]:\\n\", res_next.message.content)\n",
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" else:\n",
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" print(\"\\n[AI calling functions]:\")\n",
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" for tool_call in res_next.message.tool_calls:\n",
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" print(f\"Tool Call: {tool_call.function}\")\n",
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" while res_next.message.tool_calls and len(res_next.message.tool_calls) > 0:\n",
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" msgs = insert_tool_response(res_next, msgs)\n",
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"\n",
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" res_next = chat_method(model=\"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
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" # for m in msgs:\n",
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" # print(m)\n",
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" if res_next.message.content and len(res_next.message.content) > 0:\n",
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" print(\"\\n[AI response]:\\n\", res_next.message.content)\n",
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" else:\n",
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" msgs.append({\"role\": \"tool\", \"tool_call_id\": str(assistant_message.tool_calls[i].id), \"name\": assistant_message.tool_calls[i].function.name, \"content\": f\"Order placed.\"})\n",
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" \n",
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"\n",
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" print(\"Print before second response...\")\n",
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" res_next = chat_method(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
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" for m in msgs:\n",
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" print(m)\n",
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" print(f\"Second Response: {res_next.message}\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## OpenAI"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 70,
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"metadata": {},
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"outputs": [],
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"source": [
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"import openai\n",
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"\n",
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"\n",
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"def get_oai_response(prompt, model, functions, msgs):\n",
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" openai.api_key = \"sk-\" ## Add your API key here\n",
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" openai.base_url = \"https://api.openai.com/v1/\"\n",
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" \n",
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" try:\n",
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" completion = openai.chat.completions.create(\n",
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" model=model,\n",
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" temperature=0.1,\n",
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" messages=msgs,\n",
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" tools=functions,\n",
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" tool_choice=\"auto\",\n",
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" # functions=functions,\n",
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" # function_call=\"auto\",\n",
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" stream=False,\n",
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" )\n",
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" return completion.choices[0]\n",
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" except Exception as e:\n",
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" print(e, model, prompt)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 71,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"<function get_oai_response at 0x10b9c93f0>\n",
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"First Response:\n",
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"Tool Call: call_FYLEpX5CVo2dqSyNupcgtFak, Function(arguments='{\"number_to_buy\":2}', name='orderUmbrella')\n",
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"Print before second response...\n",
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"{'role': 'system', 'content': 'You are a helpful assistant.'}\n",
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"{'role': 'user', 'content': 'order 2 umbrellas'}\n",
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"{'role': 'assistant', 'tool_calls': [{'id': 'call_FYLEpX5CVo2dqSyNupcgtFak', 'function': {'name': 'orderUmbrella', 'arguments': '{\"number_to_buy\":2}'}, 'type': 'function'}]}\n",
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"{'role': 'tool', 'tool_call_id': 'call_FYLEpX5CVo2dqSyNupcgtFak', 'name': 'orderUmbrella', 'content': 'Order placed.'}\n",
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"Second Response: ChatCompletionMessage(content=\"I've placed the order for 2 umbrellas for you. Is there anything else I can help with?\", role='assistant', function_call=None, tool_calls=None)\n"
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]
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}
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],
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"source": [
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"# user_query = \"What is the distance between San Francisco and Cupertino by car and by air\"\n",
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"# user_query = \"weather in boston as well as cupertino?\"\n",
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"user_query = \"order 2 umbrellas\"\n",
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"run_completion(get_oai_response, user_query)"
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" print(\"\\n[AI calling functions]:\")\n",
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" for tool_call in res_next.message.tool_calls:\n",
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" print(f\"Tool Call: {tool_call.function}\")\n",
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" "
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]
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},
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{
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@ -150,58 +139,102 @@
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},
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{
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"cell_type": "code",
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"execution_count": 72,
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"metadata": {},
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"outputs": [],
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"source": [
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"import openai\n",
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"\n",
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"\n",
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"def get_mistral_rubra_response(prompt, model, functions, msgs):\n",
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" openai.api_key = \"sk-\"\n",
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" openai.base_url = \"http://localhost:8019/v1/\"\n",
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" \n",
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" try:\n",
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" completion = openai.chat.completions.create(\n",
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" model=model,\n",
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" temperature=0.1,\n",
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" messages=msgs,\n",
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" tools=functions,\n",
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" tool_choice=\"auto\",\n",
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" stream=False,\n",
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" )\n",
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" return completion.choices[0]\n",
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" except Exception as e:\n",
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" print(e, model, prompt)\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 73,
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"execution_count": 22,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"<function get_mistral_rubra_response at 0x10b9cac20>\n",
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"First Response:\n",
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"Tool Call: 0, Function(arguments='{\"number_to_buy\":\"2\"}', name='orderUmbrella')\n",
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"Print before second response...\n",
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"{'role': 'system', 'content': 'You are a helpful assistant.'}\n",
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"{'role': 'user', 'content': 'order 2 umbrellas'}\n",
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"{'role': 'assistant', 'tool_calls': [{'id': '0', 'function': {'name': 'orderUmbrella', 'arguments': '{\"number_to_buy\":\"2\"}'}, 'type': 'function'}]}\n",
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"{'role': 'tool', 'tool_call_id': '0', 'name': 'orderUmbrella', 'content': 'Order placed.'}\n",
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"Second Response: ChatCompletionMessage(content=' Your order for 2 umbrellas has been placed.', role='assistant', function_call=None, tool_calls=None)\n"
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"Pointing to URL: http://localhost:8019/v1/\n",
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"\n",
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"[AI calling functions]:\n",
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"Tool Call: Function(arguments='{\"location\":\"Boston, MA\"}', name='getCurrentWeather')\n",
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"\n",
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"Pointing to URL: http://localhost:8019/v1/\n",
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"\n",
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"[AI calling functions]:\n",
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"Tool Call: Function(arguments='{\"location\":\"Cupertino, CA\"}', name='getCurrentWeather')\n",
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"\n",
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"Pointing to URL: http://localhost:8019/v1/\n",
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"\n",
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"[AI calling functions]:\n",
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"Tool Call: Function(arguments='{\"location\":\"Los Angeles, CA\"}', name='getCurrentWeather')\n",
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"\n",
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"Pointing to URL: http://localhost:8019/v1/\n",
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"\n",
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"[AI calling functions]:\n",
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"Tool Call: Function(arguments='{\"location\":\"New York City, NY\"}', name='getCurrentWeather')\n",
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"\n",
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"Pointing to URL: http://localhost:8019/v1/\n",
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"\n",
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"[AI response]:\n",
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" The distance from Boston, MA to Cupertino, CA is approximately 2,800 miles. The distance from Los Angeles, CA to New York City, NY is approximately 2,800 miles as well.\n"
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]
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}
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],
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"source": [
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"# user_query = \"generate a password of length 10 and another of length 20\" \n",
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"# user_query = \"what's the weather in Boston and Cupertino?\"\n",
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"user_query = \"order 2 umbrellas\"\n",
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"run_completion(get_mistral_rubra_response, user_query)"
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"import openai\n",
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"\n",
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"\n",
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"local_api_key = \"sk-\"\n",
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"local_base_url = \"http://localhost:8019/v1/\"\n",
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"get_mistral_rubra_response = partial(get_oai_response, api_key=local_api_key, base_url=local_base_url)\n",
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"\n",
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"user_query = \"calculate the distance from boston to cupertino? and distance from LA to NYC\"\n",
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"msgs = run_completion(get_mistral_rubra_response, user_query)\n",
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"# user_query = \"what's the weather in Boston and Cupertino and Chicago?\"\n",
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"# # user_query = \"order 2 umbrellas\"\n",
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"# msgs = run_completion(get_mistral_rubra_response, user_query)\n",
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"# user_query2 = \"now order 3 umbrellas for me\"\n",
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"# msgs = run_completion(get_mistral_rubra_response, user_query2, msgs)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## OpenAI"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Pointing to URL: https://api.openai.com/v1/\n",
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"\n",
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"[AI calling functions]:\n",
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"Tool Call: Function(arguments='{\"location\": \"Boston, MA\", \"unit\": \"f\"}', name='getCurrentWeather')\n",
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"Tool Call: Function(arguments='{\"location\": \"Cupertino, CA\", \"unit\": \"f\"}', name='getCurrentWeather')\n",
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"Tool Call: Function(arguments='{\"origin\": \"Boston, MA\", \"destination\": \"Cupertino, CA\", \"mode\": \"driving\"}', name='calculate_distance')\n",
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"\n",
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"\n",
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"Pointing to URL: https://api.openai.com/v1/\n",
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"\n",
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"[AI response]:\n",
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" The current weather in Boston, MA is 60°F, and in Cupertino, CA, it is 113°F. The distance from Boston, MA to Cupertino, CA is approximately 5100 miles when traveling by driving.\n"
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]
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}
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],
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"source": [
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"import openai\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"openai_api_key = \"sk-\"\n",
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"openai_base_url = \"https://api.openai.com/v1/\"\n",
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"get_openai_response = partial(get_oai_response, api_key=openai_api_key, base_url=openai_base_url)\n",
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"\n",
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"# oai_user_query = \"What is the distance between San Francisco and Cupertino by car and by air\"\n",
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"oai_user_query = \"weather in boston as well as cupertino? and calculate the distance from boston to cupertino\"\n",
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"# user_query = \"order 2 umbrellas\"\n",
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"run_completion(get_openai_response, oai_user_query)"
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]
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||||
},
|
||||
{
|
||||
|
|
@ -213,14 +246,18 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 46,
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"None\n"
|
||||
"ename": "TypeError",
|
||||
"evalue": "get_oai_response() got multiple values for argument 'functions'",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"Cell \u001b[0;32mIn[4], line 48\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[38;5;66;03m# \u001b[39;00m\n\u001b[1;32m 46\u001b[0m \u001b[38;5;66;03m# msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}, {\"role\": \"function\", \"content\": '<<functions>>[get_stock_price(symbol=\"TSLA\")], <<functions>>[get_stock_price(symbol=\"GOOG\")]'}, {\"role\": \"observation\", \"content\": \"{'symbol': 'TSLA', 'company_name': 'Tesla, Inc.', 'sector': 'Consumer Cyclical', 'industry': 'Auto Manufacturers', 'market_cap': 611384164352, 'pe_ratio': 49.604652, 'pb_ratio': 9.762013, 'dividend_yield': None, 'eps': 4.3, 'beta': 2.427, '52_week_high': 299.29, '52_week_low': 152.37}}\"}]\u001b[39;00m\n\u001b[1;32m 47\u001b[0m msgs \u001b[38;5;241m=\u001b[39m [{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrole\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msystem\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcontent\u001b[39m\u001b[38;5;124m\"\u001b[39m:system_prompt} ,{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrole\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muser\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcontent\u001b[39m\u001b[38;5;124m\"\u001b[39m: user_query},]\n\u001b[0;32m---> 48\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[43mget_mistral_rubra_response\u001b[49m\u001b[43m(\u001b[49m\u001b[43muser_query\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmistral_rubra\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunctions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfunctions\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmsgs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmsgs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 49\u001b[0m \u001b[38;5;28mprint\u001b[39m(res\u001b[38;5;241m.\u001b[39mmessage\u001b[38;5;241m.\u001b[39mcontent)\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: get_oai_response() got multiple values for argument 'functions'"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -278,7 +315,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 47,
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue