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community[minor]: DeepInfra support for chat models (#16380)
Add deepinfra chat models support. This is https://github.com/langchain-ai/langchain/pull/14234 re-opened from my branch (so maintainers can edit).
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@@ -0,0 +1,65 @@
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"""Test ChatDeepInfra wrapper."""
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from langchain_core.messages import BaseMessage, HumanMessage
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from langchain_core.outputs import ChatGeneration, LLMResult
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from langchain_community.chat_models.deepinfra import ChatDeepInfra
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from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
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def test_chat_deepinfra() -> None:
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"""Test valid call to DeepInfra."""
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chat = ChatDeepInfra(
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max_tokens=10,
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)
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response = chat.invoke([HumanMessage(content="Hello")])
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assert isinstance(response, BaseMessage)
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assert isinstance(response.content, str)
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def test_chat_deepinfra_streaming() -> None:
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callback_handler = FakeCallbackHandler()
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chat = ChatDeepInfra(
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callbacks=[callback_handler],
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streaming=True,
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max_tokens=10,
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)
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response = chat.invoke([HumanMessage(content="Hello")])
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assert callback_handler.llm_streams > 0
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assert isinstance(response, BaseMessage)
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async def test_async_chat_deepinfra() -> None:
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"""Test async generation."""
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chat = ChatDeepInfra(
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max_tokens=10,
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)
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message = HumanMessage(content="Hello")
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response = await chat.agenerate([[message]])
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assert isinstance(response, LLMResult)
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assert len(response.generations) == 1
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assert len(response.generations[0]) == 1
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generation = response.generations[0][0]
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assert isinstance(generation, ChatGeneration)
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assert isinstance(generation.text, str)
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assert generation.text == generation.message.content
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async def test_async_chat_deepinfra_streaming() -> None:
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callback_handler = FakeCallbackHandler()
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chat = ChatDeepInfra(
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# model="meta-llama/Llama-2-7b-chat-hf",
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callbacks=[callback_handler],
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max_tokens=10,
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streaming=True,
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timeout=5,
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)
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message = HumanMessage(content="Hello")
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response = await chat.agenerate([[message]])
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assert callback_handler.llm_streams > 0
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assert isinstance(response, LLMResult)
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assert len(response.generations) == 1
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assert len(response.generations[0]) == 1
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generation = response.generations[0][0]
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assert isinstance(generation, ChatGeneration)
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assert isinstance(generation.text, str)
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assert generation.text == generation.message.content
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@@ -5,7 +5,7 @@ from langchain_community.embeddings import DeepInfraEmbeddings
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def test_deepinfra_call() -> None:
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"""Test valid call to DeepInfra."""
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deepinfra_emb = DeepInfraEmbeddings(model_id="sentence-transformers/clip-ViT-B-32")
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deepinfra_emb = DeepInfraEmbeddings(model_id="BAAI/bge-base-en-v1.5")
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r1 = deepinfra_emb.embed_documents(
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[
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"Alpha is the first letter of Greek alphabet",
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@@ -13,7 +13,7 @@ def test_deepinfra_call() -> None:
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]
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)
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assert len(r1) == 2
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assert len(r1[0]) == 512
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assert len(r1[1]) == 512
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assert len(r1[0]) == 768
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assert len(r1[1]) == 768
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r2 = deepinfra_emb.embed_query("What is the third letter of Greek alphabet")
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assert len(r2) == 512
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assert len(r2) == 768
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@@ -5,13 +5,13 @@ from langchain_community.llms.deepinfra import DeepInfra
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def test_deepinfra_call() -> None:
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"""Test valid call to DeepInfra."""
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llm = DeepInfra(model_id="meta-llama/Llama-2-7b-chat-hf")
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output = llm("What is 2 + 2?")
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output = llm.invoke("What is 2 + 2?")
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assert isinstance(output, str)
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async def test_deepinfra_acall() -> None:
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llm = DeepInfra(model_id="meta-llama/Llama-2-7b-chat-hf")
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output = await llm.apredict("What is 2 + 2?")
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output = await llm.ainvoke("What is 2 + 2?")
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assert llm._llm_type == "deepinfra"
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assert isinstance(output, str)
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@@ -10,6 +10,7 @@ EXPECTED_ALL = [
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"ChatAnthropic",
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"ChatCohere",
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"ChatDatabricks",
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"ChatDeepInfra",
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"ChatGooglePalm",
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"ChatHuggingFace",
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"ChatMlflow",
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