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community: SamabanovaCloud tool calling and Structured output (#27967)
**Description:** Add tool calling and structured output support for SambaNovaCloud chat models, docs included --------- Co-authored-by: Erick Friis <erick@langchain.dev>
This commit is contained in:
Jorge Piedrahita Ortiz
committed by
GitHub
GitHub
parent
cb32bab69d
commit
abaea28417
@@ -19,7 +19,7 @@
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"source": [
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"# ChatSambaNovaCloud\n",
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"\n",
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"This will help you getting started with SambaNovaCloud [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatSambaNovaCloud features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.sambanova.ChatSambaNovaCloud.html).\n",
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"This will help you getting started with SambaNovaCloud [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatSambaNovaCloud features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.sambanova.ChatSambaNovaCloud.html).\n",
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"\n",
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"**[SambaNova](https://sambanova.ai/)'s** [SambaNova Cloud](https://cloud.sambanova.ai/) is a platform for performing inference with open-source models\n",
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"\n",
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@@ -28,13 +28,13 @@
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"\n",
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"| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n",
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"| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n",
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"| [ChatSambaNovaCloud](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.sambanova.ChatSambaNovaCloud.html) | [langchain-community](https://python.langchain.com/v0.2/api_reference/community/index.html) | ❌ | ❌ | ❌ |  |  |\n",
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"| [ChatSambaNovaCloud](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.sambanova.ChatSambaNovaCloud.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | ❌ | ❌ |  |  |\n",
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"\n",
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"### Model features\n",
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"\n",
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"| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\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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"## Setup\n",
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"\n",
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@@ -116,14 +116,18 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain_community.chat_models.sambanova import ChatSambaNovaCloud\n",
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"\n",
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"llm = ChatSambaNovaCloud(\n",
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" model=\"llama3-405b\", max_tokens=1024, temperature=0.7, top_k=1, top_p=0.01\n",
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" model=\"Meta-Llama-3.1-70B-Instruct\",\n",
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" max_tokens=1024,\n",
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" temperature=0.7,\n",
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" top_k=1,\n",
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" top_p=0.01,\n",
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")"
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]
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},
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@@ -142,7 +146,7 @@
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{
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"data": {
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"text/plain": [
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"AIMessage(content=\"J'adore la programmation.\", response_metadata={'finish_reason': 'stop', 'usage': {'acceptance_rate': 11, 'completion_tokens': 9, 'completion_tokens_after_first_per_sec': 97.07042823956884, 'completion_tokens_after_first_per_sec_first_ten': 276.3343994441849, 'completion_tokens_per_sec': 23.775192800224037, 'end_time': 1726158364.7954874, 'is_last_response': True, 'prompt_tokens': 56, 'start_time': 1726158364.3670964, 'time_to_first_token': 0.3459765911102295, 'total_latency': 0.3785458261316473, 'total_tokens': 65, 'total_tokens_per_sec': 171.70972577939582}, 'model_name': 'Meta-Llama-3.1-405B-Instruct', 'system_fingerprint': 'fastcoe', 'created': 1726158364}, id='7154b676-9d5a-4b1a-a425-73bbe69f28fc')"
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"AIMessage(content=\"J'adore la programmation.\", additional_kwargs={}, response_metadata={'finish_reason': 'stop', 'usage': {'acceptance_rate': 7, 'completion_tokens': 8, 'completion_tokens_after_first_per_sec': 195.0204119588971, 'completion_tokens_after_first_per_sec_first_ten': 618.3422770734173, 'completion_tokens_per_sec': 53.25837044790076, 'end_time': 1731535338.1864908, 'is_last_response': True, 'prompt_tokens': 55, 'start_time': 1731535338.0133238, 'time_to_first_token': 0.13727331161499023, 'total_latency': 0.15021112986973353, 'total_tokens': 63, 'total_tokens_per_sec': 419.4096672772185}, 'model_name': 'Meta-Llama-3.1-70B-Instruct', 'system_fingerprint': 'fastcoe', 'created': 1731535338}, id='f04b7c2c-bc46-47e0-9c6b-19a002e8f390')"
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]
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},
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"execution_count": 3,
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@@ -196,7 +200,7 @@
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{
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"data": {
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"text/plain": [
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"AIMessage(content='Ich liebe Programmieren.', response_metadata={'finish_reason': 'stop', 'usage': {'acceptance_rate': 11, 'completion_tokens': 6, 'completion_tokens_after_first_per_sec': 47.80258530102961, 'completion_tokens_after_first_per_sec_first_ten': 215.59002827036753, 'completion_tokens_per_sec': 5.263977583489829, 'end_time': 1726158506.3777263, 'is_last_response': True, 'prompt_tokens': 51, 'start_time': 1726158505.1611376, 'time_to_first_token': 1.1119918823242188, 'total_latency': 1.1398224830627441, 'total_tokens': 57, 'total_tokens_per_sec': 50.00778704315337}, 'model_name': 'Meta-Llama-3.1-405B-Instruct', 'system_fingerprint': 'fastcoe', 'created': 1726158505}, id='226471ac-8c52-44bb-baa7-f9d2f8c54477')"
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"AIMessage(content='Ich liebe das Programmieren.', additional_kwargs={}, response_metadata={'finish_reason': 'stop', 'usage': {'acceptance_rate': 2.3333333333333335, 'completion_tokens': 6, 'completion_tokens_after_first_per_sec': 106.06729752831038, 'completion_tokens_after_first_per_sec_first_ten': 204.92722183833433, 'completion_tokens_per_sec': 26.32497272023831, 'end_time': 1731535339.9997504, 'is_last_response': True, 'prompt_tokens': 50, 'start_time': 1731535339.7539687, 'time_to_first_token': 0.19864177703857422, 'total_latency': 0.22792046410696848, 'total_tokens': 56, 'total_tokens_per_sec': 245.6997453888909}, 'model_name': 'Meta-Llama-3.1-70B-Instruct', 'system_fingerprint': 'fastcoe', 'created': 1731535339}, id='dfe0bee6-b297-472e-ac9d-29906d162dcb')"
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]
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},
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"execution_count": 5,
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@@ -243,17 +247,24 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Yer lookin' fer some info on owls, eh? Alright then, matey, settle yerself down with a pint o' grog and listen close.\n",
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"Yer lookin' fer some knowledge about owls, eh? Alright then, matey, settle yerself down with a pint o' grog and listen close. \n",
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"\n",
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"Owls be nocturnal birds o' prey, meanin' they do most o' their huntin' at night. They got big, round eyes that be perfect fer seein' in the dark, like a trusty lantern on a dark sea. Their ears be sharp as a cutlass, too, helpin' 'em pinpoint the slightest sound o' a scurvy rodent scurryin' through the underbrush.\n",
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"Owls be a fascinatin' lot, with their big round eyes and silent wings. They be birds o' prey, which means they hunt other creatures fer food. There be over 220 species o' owls, rangin' in size from the tiny Elf Owl (which be smaller than a parrot) to the Great Grey Owl (which be as big as a small eagle).\n",
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"\n",
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"These birds be known fer their silent flight, like a ghost ship sailin' through the night. Their feathers be special, with a soft, fringed edge that helps 'em sneak up on their prey. And when they strike, it be swift and deadly, like a pirate's sword.\n",
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"One o' the most interestin' things about owls be their eyes. They be huge, with some species havin' eyes that be as big as their brains! This lets 'em see in the dark, which be perfect fer nocturnal huntin'. They also have special feathers on their faces that help 'em hear better, and their ears be specially designed to pinpoint sounds.\n",
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"\n",
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"Owls be found all over the world, from the frozen tundras o' the north to the scorching deserts o' the south. They come in all shapes and sizes, from the tiny elf owl to the great grey owl, which be as big as a small dog.\n",
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"Owls be known fer their silent flight, which be due to the special shape o' their wings. They be able to fly without makin' a sound, which be perfect fer sneakin' up on prey. They also be very agile, with some species able to fly through tight spaces and make sharp turns.\n",
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"\n",
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"Now, I know what ye be thinkin', \"Pirate, what about their hootin'?\" Aye, owls be famous fer their hoots, which be a form o' communication. They use different hoots to warn off predators, attract a mate, or even just to say, \"Shiver me timbers, I be happy to be alive!\"\n",
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"Some o' the most common species o' owls include:\n",
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"\n",
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"So there ye have it, me hearty. Owls be fascinatin' creatures, and I hope ye found this info as interestin' as a chest overflowin' with gold doubloons. Fair winds and following seas!"
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"* Barn Owl: A medium-sized owl with a heart-shaped face and a screechin' call.\n",
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"* Tawny Owl: A large owl with a distinctive hootin' call and a reddish-brown plumage.\n",
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"* Great Horned Owl: A big owl with ear tufts and a deep hootin' call.\n",
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"* Snowy Owl: A white owl with a round face and a soft, hootin' call.\n",
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"\n",
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"Owls be found all over the world, in a variety o' habitats, from forests to deserts. They be an important part o' many ecosystems, helpin' to keep populations o' small mammals and birds under control.\n",
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"\n",
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"So there ye have it, matey! Owls be amazin' creatures, with their big eyes, silent wings, and sharp talons. Now go forth and spread the word about these fascinatin' birds!"
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]
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}
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],
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@@ -283,7 +294,7 @@
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{
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"data": {
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"text/plain": [
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"AIMessage(content='The capital of France is Paris.', response_metadata={'finish_reason': 'stop', 'usage': {'acceptance_rate': 13, 'completion_tokens': 8, 'completion_tokens_after_first_per_sec': 86.00726488715989, 'completion_tokens_after_first_per_sec_first_ten': 326.92555640828857, 'completion_tokens_per_sec': 21.74539360394493, 'end_time': 1726159287.9987085, 'is_last_response': True, 'prompt_tokens': 43, 'start_time': 1726159287.5738964, 'time_to_first_token': 0.34342360496520996, 'total_latency': 0.36789400760944074, 'total_tokens': 51, 'total_tokens_per_sec': 138.62688422514893}, 'model_name': 'Meta-Llama-3.1-405B-Instruct', 'system_fingerprint': 'fastcoe', 'created': 1726159287}, id='9b4ef015-50a2-434b-b980-29f8aa90c3e8')"
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"AIMessage(content='The capital of France is Paris.', additional_kwargs={}, response_metadata={'finish_reason': 'stop', 'usage': {'acceptance_rate': 1, 'completion_tokens': 7, 'completion_tokens_after_first_per_sec': 442.126212227688, 'completion_tokens_after_first_per_sec_first_ten': 0, 'completion_tokens_per_sec': 46.28540439646366, 'end_time': 1731535343.0321083, 'is_last_response': True, 'prompt_tokens': 42, 'start_time': 1731535342.8808727, 'time_to_first_token': 0.137664794921875, 'total_latency': 0.15123558044433594, 'total_tokens': 49, 'total_tokens_per_sec': 323.99783077524563}, 'model_name': 'Meta-Llama-3.1-70B-Instruct', 'system_fingerprint': 'fastcoe', 'created': 1731535342}, id='c4b8c714-df38-4206-9aa8-fc8231f7275a')"
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]
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},
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"execution_count": 7,
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@@ -321,7 +332,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Quantum computers use quantum bits (qubits) to process vast amounts of data simultaneously, leveraging quantum mechanics to solve complex problems exponentially faster than classical computers."
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"Quantum computers use quantum bits (qubits) to process info, leveraging superposition and entanglement to perform calculations exponentially faster than classical computers for certain complex problems."
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]
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}
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],
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@@ -340,13 +351,202 @@
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" print(chunk.content, end=\"\", flush=True)"
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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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"## Tool calling"
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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": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"from datetime import datetime\n",
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"\n",
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"from langchain_core.messages import HumanMessage, ToolMessage\n",
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"from langchain_core.tools import tool\n",
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"\n",
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"\n",
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"@tool\n",
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"def get_time(kind: str = \"both\") -> str:\n",
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" \"\"\"Returns current date, current time or both.\n",
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" Args:\n",
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" kind(str): date, time or both\n",
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" Returns:\n",
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" str: current date, current time or both\n",
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" \"\"\"\n",
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" if kind == \"date\":\n",
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" date = datetime.now().strftime(\"%m/%d/%Y\")\n",
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" return f\"Current date: {date}\"\n",
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" elif kind == \"time\":\n",
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" time = datetime.now().strftime(\"%H:%M:%S\")\n",
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" return f\"Current time: {time}\"\n",
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" else:\n",
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" date = datetime.now().strftime(\"%m/%d/%Y\")\n",
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" time = datetime.now().strftime(\"%H:%M:%S\")\n",
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" return f\"Current date: {date}, Current time: {time}\"\n",
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"\n",
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"\n",
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"tools = [get_time]\n",
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"\n",
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"\n",
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"def invoke_tools(tool_calls, messages):\n",
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" available_functions = {tool.name: tool for tool in tools}\n",
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" for tool_call in tool_calls:\n",
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" selected_tool = available_functions[tool_call[\"name\"]]\n",
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" tool_output = selected_tool.invoke(tool_call[\"args\"])\n",
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" print(f\"Tool output: {tool_output}\")\n",
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" messages.append(ToolMessage(tool_output, tool_call_id=tool_call[\"id\"]))\n",
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" return messages"
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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": 10,
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"metadata": {},
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"outputs": [],
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"source": [
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"llm_with_tools = llm.bind_tools(tools=tools)\n",
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"messages = [\n",
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" HumanMessage(\n",
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" content=\"I need to schedule a meeting for two weeks from today. Can you tell me the exact date of the meeting?\"\n",
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" )\n",
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"]"
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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": 11,
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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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"Intermediate model response: [{'name': 'get_time', 'args': {'kind': 'date'}, 'id': 'call_7352ce7a18e24a7c9d', 'type': 'tool_call'}]\n",
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"Tool output: Current date: 11/13/2024\n",
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"final response: The meeting should be scheduled for two weeks from November 13th, 2024.\n"
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]
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}
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],
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"source": [
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"response = llm_with_tools.invoke(messages)\n",
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"while len(response.tool_calls) > 0:\n",
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" print(f\"Intermediate model response: {response.tool_calls}\")\n",
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" messages.append(response)\n",
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" messages = invoke_tools(response.tool_calls, messages)\n",
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" response = llm_with_tools.invoke(messages)\n",
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"\n",
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"print(f\"final response: {response.content}\")"
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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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"## Structured Outputs"
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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": 12,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Joke(setup='Why did the cat join a band?', punchline='Because it wanted to be the purr-cussionist!')"
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]
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},
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"execution_count": 12,
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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 pydantic import BaseModel, Field\n",
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"\n",
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"\n",
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"class Joke(BaseModel):\n",
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" \"\"\"Joke to tell user.\"\"\"\n",
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"\n",
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" setup: str = Field(description=\"The setup of the joke\")\n",
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" punchline: str = Field(description=\"The punchline to the joke\")\n",
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"\n",
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"\n",
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"structured_llm = llm.with_structured_output(Joke)\n",
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"\n",
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"structured_llm.invoke(\"Tell me a joke about cats\")"
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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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"## Input Image"
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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": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"multimodal_llm = ChatSambaNovaCloud(\n",
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" model=\"Llama-3.2-11B-Vision-Instruct\",\n",
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" max_tokens=1024,\n",
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" temperature=0.7,\n",
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" top_k=1,\n",
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" top_p=0.01,\n",
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")"
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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": 14,
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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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"The weather in this image is a serene and peaceful atmosphere, with a blue sky and white clouds, suggesting a pleasant day with mild temperatures and gentle breezes.\n"
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]
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}
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],
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"source": [
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"import base64\n",
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"\n",
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"import httpx\n",
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"\n",
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"image_url = (\n",
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" \"https://images.pexels.com/photos/147411/italy-mountains-dawn-daybreak-147411.jpeg\"\n",
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")\n",
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"image_data = base64.b64encode(httpx.get(image_url).content).decode(\"utf-8\")\n",
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"\n",
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"message = HumanMessage(\n",
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" content=[\n",
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" {\"type\": \"text\", \"text\": \"describe the weather in this image in 1 sentence\"},\n",
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" {\n",
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" \"type\": \"image_url\",\n",
|
||||
" \"image_url\": {\"url\": f\"data:image/jpeg;base64,{image_data}\"},\n",
|
||||
" },\n",
|
||||
" ],\n",
|
||||
")\n",
|
||||
"response = multimodal_llm.invoke([message])\n",
|
||||
"print(response.content)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## API reference\n",
|
||||
"\n",
|
||||
"For detailed documentation of all ChatSambaNovaCloud features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.sambanova.ChatSambaNovaCloud.html"
|
||||
"For detailed documentation of all ChatSambaNovaCloud features and configurations head to the API reference: https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.sambanova.ChatSambaNovaCloud.html"
|
||||
]
|
||||
}
|
||||
],
|
||||
@@ -366,7 +566,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.19"
|
||||
"version": "3.9.20"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
Reference in New Issue
Block a user