mirror of
https://github.com/BerriAI/litellm.git
synced 2025-12-06 11:33:26 +08:00
475 lines
74 KiB
Plaintext
Vendored
475 lines
74 KiB
Plaintext
Vendored
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "iFEmsVJI_2BR"
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},
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"source": [
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"# LiteLLM CometAPI Cookbook"
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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": 1,
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"metadata": {
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"id": "cBlUhCEP_xj4"
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},
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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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"Requirement already satisfied: litellm in /Users/xmx/.miniforge3/lib/python3.12/site-packages (1.78.2)\n",
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"Requirement already satisfied: aiohttp>=3.10 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (3.11.18)\n",
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"Requirement already satisfied: click in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (8.3.0)\n",
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"Requirement already satisfied: fastuuid>=0.13.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (0.13.3)\n",
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"Requirement already satisfied: httpx>=0.23.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (0.28.1)\n",
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"Requirement already satisfied: importlib-metadata>=6.8.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (8.6.1)\n",
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"Requirement already satisfied: jinja2<4.0.0,>=3.1.2 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (3.1.6)\n",
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"Requirement already satisfied: jsonschema<5.0.0,>=4.22.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (4.25.1)\n",
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"Requirement already satisfied: openai>=2.8.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (1.109.1)\n",
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"Requirement already satisfied: pydantic<3.0.0,>=2.5.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (2.11.10)\n",
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"Requirement already satisfied: python-dotenv>=0.2.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (1.1.1)\n",
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"Requirement already satisfied: tiktoken>=0.7.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (0.12.0)\n",
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"Requirement already satisfied: tokenizers in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (0.22.1)\n",
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"Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from aiohttp>=3.10->litellm) (2.6.1)\n",
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"Requirement already satisfied: aiosignal>=1.1.2 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from aiohttp>=3.10->litellm) (1.4.0)\n",
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"Requirement already satisfied: attrs>=17.3.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from aiohttp>=3.10->litellm) (25.3.0)\n",
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"Requirement already satisfied: frozenlist>=1.1.1 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from aiohttp>=3.10->litellm) (1.6.0)\n",
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"Requirement already satisfied: multidict<7.0,>=4.5 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from aiohttp>=3.10->litellm) (6.6.3)\n",
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"Requirement already satisfied: propcache>=0.2.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from aiohttp>=3.10->litellm) (0.3.1)\n",
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"Requirement already satisfied: yarl<2.0,>=1.17.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from aiohttp>=3.10->litellm) (1.20.0)\n",
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"Requirement already satisfied: anyio in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from httpx>=0.23.0->litellm) (4.11.0)\n",
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"Requirement already satisfied: certifi in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from httpx>=0.23.0->litellm) (2025.10.5)\n",
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"Requirement already satisfied: httpcore==1.* in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from httpx>=0.23.0->litellm) (1.0.9)\n",
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"Requirement already satisfied: idna in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from httpx>=0.23.0->litellm) (3.10)\n",
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"Requirement already satisfied: h11>=0.16 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from httpcore==1.*->httpx>=0.23.0->litellm) (0.16.0)\n",
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"Requirement already satisfied: zipp>=3.20 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from importlib-metadata>=6.8.0->litellm) (3.21.0)\n",
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"Requirement already satisfied: MarkupSafe>=2.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from jinja2<4.0.0,>=3.1.2->litellm) (3.0.3)\n",
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"Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from jsonschema<5.0.0,>=4.22.0->litellm) (2025.9.1)\n",
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"Requirement already satisfied: referencing>=0.28.4 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from jsonschema<5.0.0,>=4.22.0->litellm) (0.36.2)\n",
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"Requirement already satisfied: rpds-py>=0.7.1 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from jsonschema<5.0.0,>=4.22.0->litellm) (0.27.1)\n",
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"Requirement already satisfied: distro<2,>=1.7.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (1.9.0)\n",
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"Requirement already satisfied: jiter<1,>=0.4.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (0.11.0)\n",
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"Requirement already satisfied: sniffio in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (1.3.1)\n",
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"Requirement already satisfied: tqdm>4 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (4.67.1)\n",
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"Requirement already satisfied: typing-extensions<5,>=4.11 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (4.15.0)\n",
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"Requirement already satisfied: annotated-types>=0.6.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from pydantic<3.0.0,>=2.5.0->litellm) (0.7.0)\n",
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"Requirement already satisfied: pydantic-core==2.33.2 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from pydantic<3.0.0,>=2.5.0->litellm) (2.33.2)\n",
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"Requirement already satisfied: typing-inspection>=0.4.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from pydantic<3.0.0,>=2.5.0->litellm) (0.4.2)\n",
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"Requirement already satisfied: regex>=2022.1.18 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from tiktoken>=0.7.0->litellm) (2025.9.18)\n",
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"Requirement already satisfied: requests>=2.26.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from tiktoken>=0.7.0->litellm) (2.32.2)\n",
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"Requirement already satisfied: huggingface-hub<2.0,>=0.16.4 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from tokenizers->litellm) (0.25.2)\n",
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"Requirement already satisfied: filelock in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from huggingface-hub<2.0,>=0.16.4->tokenizers->litellm) (3.15.4)\n",
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"Requirement already satisfied: fsspec>=2023.5.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from huggingface-hub<2.0,>=0.16.4->tokenizers->litellm) (2025.9.0)\n",
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"Requirement already satisfied: packaging>=20.9 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from huggingface-hub<2.0,>=0.16.4->tokenizers->litellm) (25.0)\n",
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"Requirement already satisfied: pyyaml>=5.1 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from huggingface-hub<2.0,>=0.16.4->tokenizers->litellm) (6.0.3)\n",
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"Requirement already satisfied: charset-normalizer<4,>=2 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from requests>=2.26.0->tiktoken>=0.7.0->litellm) (3.4.0)\n",
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"Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from requests>=2.26.0->tiktoken>=0.7.0->litellm) (1.26.20)\n"
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]
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}
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],
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"source": [
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"!pip install litellm"
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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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"# Completion"
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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": null,
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"metadata": {
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"id": "p-MQqWOT_1a7"
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},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"os.environ['COMETAPI_KEY'] = \"Your_CometAPI_Key_Here\"\n",
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"api_key = os.getenv('COMETAPI_KEY')"
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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": 3,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "Ze8JqMqWAARO",
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"outputId": "64f3e836-69fa-4f8e-fb35-088a913bbe98"
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"ModelResponse(id='msg_017L3DDDit8AkEgHRe2DQBc9', created=1760589916, model='claude-sonnet-4-5-20250929', object='chat.completion', system_fingerprint=None, choices=[Choices(finish_reason='stop', index=0, message=Message(content='I\\'ll create a simple Python script that says hi.\\n\\n<write_to_file>\\n<path>hello.py</path>\\n<content>#!/usr/bin/env python3\\n\"\"\"\\nA simple script that says hi!\\n\"\"\"\\n\\ndef say_hi(name=None):\\n \"\"\"Say hi to someone, or just say hi generally.\"\"\"\\n if name:\\n print(f\"Hi, {name}!\")\\n else:\\n print(\"Hi!\")\\n\\nif __name__ == \"__main__\":\\n # Say hi generally\\n say_hi()\\n \\n # Say hi to someone specific\\n say_hi(\"World\")\\n</content>\\n</write_to_file>\\n\\nI\\'ve created a simple Python script called `hello.py` that:\\n\\n1. Defines a `say_hi()` function that can optionally take a name parameter\\n2. Prints \"Hi!\" if no name is provided\\n3. Prints \"Hi, [name]!\" if a name is provided\\n4. Demonstrates both usages when run\\n\\nYou can run it with:\\n```bash\\npython hello.py\\n```\\n\\nThis will output:\\n```\\nHi!\\nHi, World!\\n```\\n\\nWould you like me to create versions in other programming languages, or modify this in any way?', role='assistant', tool_calls=None, function_call=None, provider_specific_fields=None), provider_specific_fields={})], usage=Usage(completion_tokens=290, prompt_tokens=26, total_tokens=316, completion_tokens_details=None, prompt_tokens_details=PromptTokensDetailsWrapper(audio_tokens=None, cached_tokens=None, text_tokens=None, image_tokens=None, cached_tokens_details={})))"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from litellm import completion\n",
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"response = completion(\n",
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" model=\"cometapi/claude-sonnet-4-5-20250929\",\n",
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" messages=[{\"role\": \"user\", \"content\": \"write code for saying hi\"}]\n",
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")\n",
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"response"
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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": 4,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "-LnhELrnAM_J",
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"outputId": "d51c7ab7-d761-4bd1-f849-1534d9df4cd0"
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"ModelResponse(id='chatcmpl-CRA9Uo6nsQ9C7kMJv1J4kyNDFJym7', created=1760589916, model='gpt-5-chat-latest', object='chat.completion', system_fingerprint='fp_2da73a467a', choices=[Choices(finish_reason='stop', index=0, message=Message(content='Sure! I can help you write a simple code that prints out \"Hi\" in different programming languages. \\n\\nHere’s an example in **Python**:\\n\\n```python\\n# Simple Python program to say \"Hi\"\\nprint(\"Hi\")\\n```\\n\\nExample in **JavaScript**:\\n\\n```javascript\\n// Simple JavaScript program to say \"Hi\"\\nconsole.log(\"Hi\");\\n```\\n\\nExample in **C**:\\n\\n```c\\n#include <stdio.h>\\n\\nint main() {\\n printf(\"Hi\\\\n\");\\n return 0;\\n}\\n```\\n\\nExample in **Java**:\\n\\n```java\\npublic class SayHi {\\n public static void main(String[] args) {\\n System.out.println(\"Hi\");\\n }\\n}\\n```\\n\\nWhich language would you like me to focus on, or do you want me to make it interactive so the program greets the user by name?', role='assistant', tool_calls=None, function_call=None, provider_specific_fields={'refusal': None}, annotations=[]), provider_specific_fields={})], usage=Usage(completion_tokens=174, prompt_tokens=12, total_tokens=186, completion_tokens_details=CompletionTokensDetailsWrapper(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0, text_tokens=None), prompt_tokens_details=PromptTokensDetailsWrapper(audio_tokens=0, cached_tokens=0, text_tokens=None, image_tokens=None)))"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"response = completion(\n",
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" model=\"cometapi/gpt-5-chat-latest\",\n",
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" messages=[{\"role\": \"user\", \"content\": \"write code for saying hi\"}]\n",
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")\n",
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"response"
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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": 5,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "dJBOUYdwCEn1",
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"outputId": "ffa18679-ec15-4dad-fe2b-68665cdf36b0"
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},
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"outputs": [
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{
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||
"data": {
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||
"text/plain": [
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||
"ModelResponse(id='02176058998406949c23b3bf3d52941de23f13565a086747738f0', created=1760589991, model='deepseek-v3.2-exp', object='chat.completion', system_fingerprint=None, choices=[Choices(finish_reason='stop', index=0, message=Message(content='Here are several ways to say \"hi\" in different programming languages:\\n\\n## Python\\n```python\\nprint(\"Hi!\")\\n```\\n\\n## JavaScript (Browser)\\n```javascript\\nconsole.log(\"Hi!\");\\n// or\\nalert(\"Hi!\");\\n```\\n\\n## JavaScript (Node.js)\\n```javascript\\nconsole.log(\"Hi!\");\\n```\\n\\n## Java\\n```java\\npublic class Hello {\\n public static void main(String[] args) {\\n System.out.println(\"Hi!\");\\n }\\n}\\n```\\n\\n## C\\n```c\\n#include <stdio.h>\\n\\nint main() {\\n printf(\"Hi!\\\\n\");\\n return 0;\\n}\\n```\\n\\n## C++\\n```cpp\\n#include <iostream>\\n\\nint main() {\\n std::cout << \"Hi!\" << std::endl;\\n return 0;\\n}\\n```\\n\\n## C#\\n```csharp\\nusing System;\\n\\nclass Program {\\n static void Main() {\\n Console.WriteLine(\"Hi!\");\\n }\\n}\\n```\\n\\n## PHP\\n```php\\n<?php\\necho \"Hi!\";\\n?>\\n```\\n\\n## Ruby\\n```ruby\\nputs \"Hi!\"\\n```\\n\\n## Go\\n```go\\npackage main\\n\\nimport \"fmt\"\\n\\nfunc main() {\\n fmt.Println(\"Hi!\")\\n}\\n```\\n\\n## Rust\\n```rust\\nfn main() {\\n println!(\"Hi!\");\\n}\\n```\\n\\n## Swift\\n```swift\\nprint(\"Hi!\")\\n```\\n\\n## Kotlin\\n```kotlin\\nfun main() {\\n println(\"Hi!\")\\n}\\n```\\n\\n## HTML (webpage)\\n```html\\n<!DOCTYPE html>\\n<html>\\n<head>\\n <title>Hi Page</title>\\n</head>\\n<body>\\n <h1>Hi!</h1>\\n</body>\\n</html>\\n```\\n\\nThe Python version is probably the simplest if you\\'re just getting started!', role='assistant', tool_calls=None, function_call=None, provider_specific_fields={'refusal': None}), provider_specific_fields={})], usage=Usage(completion_tokens=347, prompt_tokens=10, total_tokens=357, completion_tokens_details=CompletionTokensDetailsWrapper(accepted_prediction_tokens=None, audio_tokens=None, reasoning_tokens=0, rejected_prediction_tokens=None, text_tokens=None), prompt_tokens_details=PromptTokensDetailsWrapper(audio_tokens=None, cached_tokens=0, text_tokens=None, image_tokens=None)), service_tier='default')"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"response = completion(\n",
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" model=\"cometapi/deepseek-v3.2-exp\",\n",
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" messages=[{\"role\": \"user\", \"content\": \"write code for saying hi\"}]\n",
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")\n",
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"response"
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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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"# Streaming"
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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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"## Streaming Responses"
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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": 6,
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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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"I'm\n",
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" doing\n",
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" well\n",
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" —\n",
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" thanks\n",
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" for\n",
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" asking\n",
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"!\n",
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" How\n",
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" can\n",
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" I\n",
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" help\n",
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" you\n",
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" today\n",
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"?\n",
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"\n"
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]
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}
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],
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"source": [
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"messages = [{\"role\": \"user\", \"content\": \"Hey, how's it going?\"}]\n",
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"response = completion(model=\"cometapi/gpt-5-mini\", messages=messages, stream=True)\n",
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"for part in response:\n",
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" print(part.choices[0].delta.content or \"\")"
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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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"# Async Completion"
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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": 7,
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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": [
|
||
"ModelResponse(id='chatcmpl-CRAAkmfczlmCEnCM55D9CKexbRenn', created=1760589994, model='gpt-5-mini-2025-08-07', object='chat.completion', system_fingerprint=None, choices=[Choices(finish_reason='stop', index=0, message=Message(content=\"I'm doing well, thanks — how are you? How can I help today?\", role='assistant', tool_calls=None, function_call=None, provider_specific_fields={'refusal': None}, annotations=[]), provider_specific_fields={'content_filter_results': {'hate': {'filtered': False, 'severity': 'safe'}, 'protected_material_code': {'filtered': False, 'detected': False}, 'protected_material_text': {'filtered': False, 'detected': False}, 'self_harm': {'filtered': False, 'severity': 'safe'}, 'sexual': {'filtered': False, 'severity': 'safe'}, 'violence': {'filtered': False, 'severity': 'safe'}}})], usage=Usage(completion_tokens=26, prompt_tokens=12, total_tokens=38, completion_tokens_details=CompletionTokensDetailsWrapper(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0, text_tokens=None), prompt_tokens_details=PromptTokensDetailsWrapper(audio_tokens=0, cached_tokens=0, text_tokens=None, image_tokens=None)), prompt_filter_results=[{'prompt_index': 0, 'content_filter_results': {'hate': {'filtered': False, 'severity': 'safe'}, 'jailbreak': {'filtered': False, 'detected': False}, 'self_harm': {'filtered': False, 'severity': 'safe'}, 'sexual': {'filtered': False, 'severity': 'safe'}, 'violence': {'filtered': False, 'severity': 'safe'}}}])\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from litellm import acompletion\n",
|
||
"import asyncio\n",
|
||
"\n",
|
||
"async def test_get_response():\n",
|
||
" user_message = \"Hello, how are you?\"\n",
|
||
" messages = [{\"content\": user_message, \"role\": \"user\"}]\n",
|
||
" response = await acompletion(model=\"cometapi/gpt-5-mini\", messages=messages)\n",
|
||
" return response\n",
|
||
"\n",
|
||
"response = await test_get_response()\n",
|
||
"print(response)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Async Streaming"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"test acompletion + streaming\n",
|
||
"response: <litellm.litellm_core_utils.streaming_handler.CustomStreamWrapper object at 0x11fa532f0>\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content='Hi', role='assistant', function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' —', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' I', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content='’m', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' doing', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' well', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=',', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' thanks', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content='!', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' How', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' are', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' you', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content='?', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' What', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' can', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' I', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' help', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' you', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' with', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content=' today', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(provider_specific_fields=None, content='?', role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None, citations=None)\n",
|
||
"ModelResponseStream(id='chatcmpl-CRAAl9VMDBB5skZt638Qx86K9h1Hb', created=1760589996, model='gpt-5-mini', object='chat.completion.chunk', system_fingerprint=None, choices=[StreamingChoices(finish_reason='stop', index=0, delta=Delta(provider_specific_fields=None, content=None, role=None, function_call=None, tool_calls=None, audio=None), logprobs=None)], provider_specific_fields=None)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from litellm import acompletion\n",
|
||
"import asyncio, os, traceback\n",
|
||
"\n",
|
||
"async def completion_call():\n",
|
||
" try:\n",
|
||
" print(\"test acompletion + streaming\")\n",
|
||
" response = await acompletion(\n",
|
||
" model=\"cometapi/gpt-5-mini\", \n",
|
||
" messages=[{\"content\": \"Hello, how are you?\", \"role\": \"user\"}], \n",
|
||
" stream=True\n",
|
||
" )\n",
|
||
" print(f\"response: {response}\")\n",
|
||
" async for chunk in response:\n",
|
||
" print(chunk)\n",
|
||
" except:\n",
|
||
" print(f\"error occurred: {traceback.format_exc()}\")\n",
|
||
" pass\n",
|
||
"\n",
|
||
"await completion_call()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Embedding"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"EmbeddingResponse(model='text-embedding-3-small', data=[{'object': 'embedding', 'index': 0, 'embedding': [-0.018048199, 0.0047550877, -0.013976435, -0.021936804, -0.038773336, -0.03708264, 0.03854791, -0.0007172257, 0.026473511, -0.0027438616, -0.019823432, -0.011947598, -0.013426959, -0.0059914105, 0.020485623, 0.04269012, -0.028276922, -0.015216281, -0.03325039, 0.045057096, 0.0037477135, 0.015793936, -0.005188329, -0.0071713766, 0.008446445, 0.0070938864, 0.0027632343, 0.025656339, 0.022091785, -0.026797561, -0.029840818, -0.0542714, 0.017907308, -0.03454659, -0.014582269, 0.0429719, 0.03575826, 0.007939235, -0.010123054, -0.029587213, 0.018921727, 0.022556728, 0.019598005, 0.008819807, 0.01655475, 0.043310042, -0.034321167, 0.004441604, 0.032686826, 0.047226828, -0.0043253684, 0.006681779, 0.008995921, 0.06593721, 0.0066078105, -0.023190739, -0.00777721, 0.049875587, -0.028023317, -0.019386668, -0.0013252605, 0.009214303, -0.0055828253, -0.007432026, -0.01199691, 0.0054384116, -0.024247425, 0.047255006, -0.013743965, 0.012799991, 0.009883538, -0.005579303, -0.012616833, -0.014709071, -0.004473305, -0.022204498, 0.010454148, -0.02202134, 0.034631126, 0.0097567355, 0.041478455, -0.010750021, -0.0005340668, -0.041450277, -0.04516981, 0.014709071, -0.06142869, 0.021640932, -0.0008752884, -0.0012671428, -0.045254346, -0.004216178, -0.028220564, -0.011074071, 0.010693664, -0.0029481545, -0.039590508, -0.030178957, -0.019062618, -0.03539194, 0.019978413, 0.019161243, -0.025924034, 0.0058329077, -0.029305428, 0.028840488, 0.02731886, -0.0008048426, -0.056582022, 0.003043256, -0.08459125, -0.012560476, 0.00081100664, 0.0015771041, 0.015188103, -0.0049206354, 0.046888687, -0.027107522, 0.019245777, -0.011412211, 0.039336905, -0.018611765, 0.0429719, -0.04302826, -0.018132735, -0.0074883825, -0.02035882, -0.073038146, -0.042380158, 0.04485985, 0.03361671, -0.033842135, -0.0017259207, -0.0017091898, -0.049199305, -0.024148801, -0.044803493, 0.040943068, -0.03093977, 0.045057096, -0.0186963, -0.014053926, -0.009848315, -0.0070480965, -0.0060054995, -0.02813603, -0.022105874, 0.010235767, -0.004476827, 0.027220234, -0.026290352, 0.0216832, -0.05559578, 0.042464696, 0.0253182, -0.0031594916, 0.02266944, -0.030798879, -0.02896729, -0.0005891025, 0.004061197, -0.042295624, -0.008383043, 0.017146494, -0.025797231, -0.046522368, 0.044127215, 0.021105545, -0.04302826, 0.024430584, -0.014934498, -0.01556851, -0.075743265, -0.022415835, -0.028586883, 0.032743182, 0.03539194, -0.0034483192, -0.04669144, 0.051932603, 0.021626843, 0.03127791, 0.015610777, -0.016470214, -0.0056744046, -0.012743635, 0.060132485, 0.017428277, -0.0039942735, -0.017118316, 0.025106862, 0.008974788, 0.018513141, 0.0016035212, -0.0049593803, 0.0017514573, 0.031221554, -0.034856554, -0.011461522, 0.04621241, 0.044239927, 0.034715664, -0.0121941585, -0.012053267, -0.08526753, -0.011813751, -0.025769053, 0.0125182085, -0.0046670306, 0.038266126, 0.1187997, 0.005787118, -0.030038064, -0.054553185, -0.041506633, -0.024078354, 0.0071854657, -0.013391736, 0.03192601, -0.059625275, 0.0023458432, 0.027924692, 0.09163582, 0.030967949, 0.017639615, 0.01489223, 0.029559033, 0.042943723, 0.0003306547, 0.0047198646, 0.029897174, 0.00012603184, 0.0046811197, -0.0427183, 0.01789322, 0.018175002, -0.0081857955, 0.02581132, 0.009890582, 0.03840702, -0.094453655, -0.01076411, 0.06858598, 0.041647524, 0.033532172, 0.007467249, -0.008235107, -0.030967949, 0.0151317455, 0.027361127, 0.011834885, 0.008707094, 0.008178751, -0.022458103, 0.02844599, 0.003605061, -0.02399382, 0.05212985, 0.06041427, -0.023317542, -0.013335379, -0.044099037, -0.040802173, -0.0047656544, -0.023909286, 0.017315563, 0.017428277, 0.00736158, -0.0016070436, -0.055454887, -0.038012523, -0.020626513, 0.018273626, 0.03260229, -0.016991513, 0.038463376, -0.022458103, -0.0109613575, -0.021810003, 0.04846667, -0.042521052, 0.008601425, -0.019259866, -0.0040048403, -0.03308132, -0.02499415, 0.026783472, 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-0.023303451, -0.025797231, -0.009524264]}], object='list', usage=Usage(completion_tokens=0, prompt_tokens=3, total_tokens=3, completion_tokens_details=None, prompt_tokens_details=None))\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import litellm\n",
|
||
"\n",
|
||
"\n",
|
||
"async def main():\n",
|
||
" response = await litellm.aembedding(\n",
|
||
" model=\"cometapi/text-embedding-3-small\", # The model name must include prefix \"openai\" + the model name from ai/ml api\n",
|
||
" api_key=api_key, # your aiml api-key\n",
|
||
" api_base=\"https://api.cometapi.com/v1\", # 👈 the URL has changed from v2 to v1\n",
|
||
" input=\"Your text string\",\n",
|
||
" )\n",
|
||
" print(response)\n",
|
||
"\n",
|
||
"await main()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"EmbeddingResponse(model='text-embedding-3-small', data=[{'object': 'embedding', 'index': 0, 'embedding': [-0.018048199, 0.0047550877, -0.013976435, -0.021936804, -0.038773336, -0.03708264, 0.03854791, -0.0007172257, 0.026473511, -0.0027438616, -0.019823432, -0.011947598, -0.013426959, -0.0059914105, 0.020485623, 0.04269012, -0.028276922, -0.015216281, -0.03325039, 0.045057096, 0.0037477135, 0.015793936, -0.005188329, -0.0071713766, 0.008446445, 0.0070938864, 0.0027632343, 0.025656339, 0.022091785, -0.026797561, -0.029840818, -0.0542714, 0.017907308, -0.03454659, -0.014582269, 0.0429719, 0.03575826, 0.007939235, -0.010123054, -0.029587213, 0.018921727, 0.022556728, 0.019598005, 0.008819807, 0.01655475, 0.043310042, -0.034321167, 0.004441604, 0.032686826, 0.047226828, -0.0043253684, 0.006681779, 0.008995921, 0.06593721, 0.0066078105, -0.023190739, -0.00777721, 0.049875587, -0.028023317, -0.019386668, -0.0013252605, 0.009214303, -0.0055828253, -0.007432026, -0.01199691, 0.0054384116, 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-0.023303451, -0.025797231, -0.009524264]}], object='list', usage=Usage(completion_tokens=0, prompt_tokens=3, total_tokens=3, completion_tokens_details=None, prompt_tokens_details=None))\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import litellm\n",
|
||
"\n",
|
||
"\n",
|
||
"async def main():\n",
|
||
" response = await litellm.aembedding(\n",
|
||
" model=\"cometapi/text-embedding-3-small\", # The model name must include prefix \"cometapi/\" + the model name from CometAPI\n",
|
||
" api_key=api_key, # your CometAPI api-key\n",
|
||
" api_base=\"https://api.cometapi.com/v1\",\n",
|
||
" input=\"Your text string\",\n",
|
||
" )\n",
|
||
" print(response)\n",
|
||
"\n",
|
||
"\n",
|
||
"await main()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Async Image Generation"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ImageResponse(created=1760591151, background=None, data=[ImageObject(b64_json=None, revised_prompt=\"Generate an image of an adorable baby sea otter. It should be floating on its back in a calm, clear ocean, playfully grasping a colorful shell in its small paws. The sun is setting in the background, casting a peaceful orange and purple hue across the sky and reflecting upon the ocean waves. The otter's fur is a deep, rich brown and appears silky and wet, with glints of sunlight catching on it. Its eyes are bright, expressing joy and curiosity as it examines its newfound treasure.\", url='https://oaidalleapiprodscus.blob.core.windows.net/private/org-OKnsK88id12jfvnKByup1O0l/user-3GxuMyEg9YMU8LFCPHi31prf/img-7PUEF8Wb6thGDAuZWLJjSnfP.png?st=2025-10-16T04%3A05%3A51Z&se=2025-10-16T06%3A05%3A51Z&sp=r&sv=2024-08-04&sr=b&rscd=inline&rsct=image/png&skoid=38e27a3b-6174-4d3e-90ac-d7d9ad49543f&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2025-10-16T02%3A51%3A01Z&ske=2025-10-17T02%3A51%3A01Z&sks=b&skv=2024-08-04&sig=IZKG2VE%2B6VdOe5Tq0Zk/5bVyGK/oK/yO8g%2BDX4krpug%3D')], output_format=None, quality=None, size=None, usage=Usage(completion_tokens=0, prompt_tokens=0, total_tokens=0, completion_tokens_details=None, prompt_tokens_details=None, input_tokens=0, input_tokens_details={'image_tokens': 0, 'text_tokens': 0}, output_tokens=0))\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import asyncio\n",
|
||
"\n",
|
||
"import litellm\n",
|
||
"\n",
|
||
"\n",
|
||
"async def main():\n",
|
||
" response = await litellm.aimage_generation(\n",
|
||
" model=\"cometapi/dall-e-3\", # The model name must include prefix \"cometapi/\" + the model name from CometAPI\n",
|
||
" api_key=api_key, # your cometapi api-key\n",
|
||
" api_base=\"https://api.cometapi.com/v1\",\n",
|
||
" prompt=\"A cute baby sea otter\",\n",
|
||
" )\n",
|
||
" print(response)\n",
|
||
"\n",
|
||
"\n",
|
||
"await main()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"provenance": []
|
||
},
|
||
"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": "3.12.8"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 0
|
||
}
|