cookbook/liteLLM_Ollama.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install litellm # version 0.1.724 or higher "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Call Ollama - llama2 with Streaming"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<generator object get_ollama_response_stream at 0x109096c10>\n",
      "{'role': 'assistant', 'content': ' I'}\n",
      "{'role': 'assistant', 'content': \"'\"}\n",
      "{'role': 'assistant', 'content': 'm'}\n",
      "{'role': 'assistant', 'content': ' L'}\n",
      "{'role': 'assistant', 'content': 'La'}\n",
      "{'role': 'assistant', 'content': 'MA'}\n",
      "{'role': 'assistant', 'content': ','}\n",
      "{'role': 'assistant', 'content': ' an'}\n",
      "{'role': 'assistant', 'content': ' A'}\n",
      "{'role': 'assistant', 'content': 'I'}\n",
      "{'role': 'assistant', 'content': ' assistant'}\n",
      "{'role': 'assistant', 'content': ' developed'}\n",
      "{'role': 'assistant', 'content': ' by'}\n",
      "{'role': 'assistant', 'content': ' Meta'}\n",
      "{'role': 'assistant', 'content': ' A'}\n",
      "{'role': 'assistant', 'content': 'I'}\n",
      "{'role': 'assistant', 'content': ' that'}\n",
      "{'role': 'assistant', 'content': ' can'}\n",
      "{'role': 'assistant', 'content': ' understand'}\n",
      "{'role': 'assistant', 'content': ' and'}\n",
      "{'role': 'assistant', 'content': ' respond'}\n",
      "{'role': 'assistant', 'content': ' to'}\n",
      "{'role': 'assistant', 'content': ' human'}\n",
      "{'role': 'assistant', 'content': ' input'}\n",
      "{'role': 'assistant', 'content': ' in'}\n",
      "{'role': 'assistant', 'content': ' a'}\n",
      "{'role': 'assistant', 'content': ' convers'}\n",
      "{'role': 'assistant', 'content': 'ational'}\n",
      "{'role': 'assistant', 'content': ' manner'}\n",
      "{'role': 'assistant', 'content': '.'}\n"
     ]
    }
   ],
   "source": [
    "from litellm import completion\n",
    "\n",
    "response = completion(\n",
    "    model=\"ollama/llama2\", \n",
    "    messages=[{ \"content\": \"respond in 20 words. who are you?\",\"role\": \"user\"}], \n",
    "    api_base=\"http://localhost:11434\",\n",
    "    stream=True\n",
    ")\n",
    "print(response)\n",
    "for chunk in response:\n",
    "    print(chunk['choices'][0]['delta'])\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Call Ollama - Llama2 with Acompletion + Streaming"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: async_generator in /Users/ishaanjaffer/Library/Python/3.9/lib/python/site-packages (1.10)\n"
     ]
    }
   ],
   "source": [
    "# litellm uses async_generator for ollama async streaming, ensure it's installed\n",
    "!pip install async_generator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' I'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': \"'\"}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': 'm'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' just'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' an'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' A'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': 'I'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ','}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' I'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' don'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': \"'\"}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': 't'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' have'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' access'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' to'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' real'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': '-'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': 'time'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' weather'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' information'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' or'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' current'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' conditions'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' in'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' your'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' specific'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' location'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': '.'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' живело'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' can'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' provide'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' you'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' with'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' weather'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' forec'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': 'asts'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' and'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' information'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' for'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' your'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' location'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' if'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' you'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' would'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' like'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': '.'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' Please'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' let'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' me'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' know'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' where'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' you'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' are'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' located'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ','}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' and'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' I'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' will'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' do'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' my'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' best'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' to'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' assist'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': ' you'}}]}\n",
      "{'choices': [{'delta': {'role': 'assistant', 'content': '.'}}]}\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "import litellm\n",
    "\n",
    "async def async_ollama():\n",
    "    response = await litellm.acompletion(\n",
    "        model=\"ollama/llama2\", \n",
    "        messages=[{ \"content\": \"what's the weather\" ,\"role\": \"user\"}], \n",
    "        api_base=\"http://localhost:11434\", \n",
    "        stream=True\n",
    "    )\n",
    "    async for chunk in response:\n",
    "        print(chunk)\n",
    "\n",
    "result = await async_ollama()\n",
    "print(result)\n",
    "\n",
    "try:\n",
    "    async for chunk in result:\n",
    "        print(chunk)\n",
    "except TypeError: # the last chunk is None from Ollama, this raises an error with async streaming\n",
    "    pass"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Completion Call"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"object\": \"chat.completion\",\n",
      "  \"choices\": [\n",
      "    {\n",
      "      \"finish_reason\": \"stop\",\n",
      "      \"index\": 0,\n",
      "      \"message\": {\n",
      "        \"content\": \" I'm LLaMA, an AI assistant developed by Meta AI that can understand and respond to human input in a conversational manner.\",\n",
      "        \"role\": \"assistant\",\n",
      "        \"logprobs\": null\n",
      "      }\n",
      "    }\n",
      "  ],\n",
      "  \"id\": \"chatcmpl-ea7b8242-791f-4656-ba12-e098edeb960e\",\n",
      "  \"created\": 1695324686.6696231,\n",
      "  \"response_ms\": 4072.3050000000003,\n",
      "  \"model\": \"ollama/llama2\",\n",
      "  \"usage\": {\n",
      "    \"prompt_tokens\": 10,\n",
      "    \"completion_tokens\": 27,\n",
      "    \"total_tokens\": 37\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "from litellm import completion\n",
    "\n",
    "response = completion(\n",
    "    model=\"ollama/llama2\", \n",
    "    messages=[{ \"content\": \"respond in 20 words. who are you?\",\"role\": \"user\"}], \n",
    "    api_base=\"http://localhost:11434\"\n",
    ")\n",
    "print(response)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.9.6"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}