[Feature] Add support for Together AI API (#1058)

configs/together.yaml

@@ -0,0 +1,6 @@
+llm:
+  provider: together
+  config:
+    model: mistralai/Mixtral-8x7B-Instruct-v0.1
+    temperature: 0.5
+    max_tokens: 1000

docs/components/data-sources/docs-site.mdx

@@ -10,5 +10,5 @@ from embedchain import Pipeline as App
 app = App()
 app.add("https://docs.embedchain.ai/", data_type="docs_site")
 app.query("What is Embedchain?")
-# Answer: Embedchain is a platform that utilizes various components, including paid/proprietary ones, to provide what is believed to be the best configuration available. It uses LLM (Language Model) providers such as OpenAI, Anthpropic, Vertex_AI, GPT4ALL, Azure_OpenAI, LLAMA2, JINA, Ollama and COHERE. Embedchain allows users to import and utilize these LLM providers for their applications.'
+# Answer: Embedchain is a platform that utilizes various components, including paid/proprietary ones, to provide what is believed to be the best configuration available. It uses LLM (Language Model) providers such as OpenAI, Anthpropic, Vertex_AI, GPT4ALL, Azure_OpenAI, LLAMA2, JINA, Ollama, Together and COHERE. Embedchain allows users to import and utilize these LLM providers for their applications.'
 ```

docs/components/llms.mdx

@@ -12,7 +12,8 @@ Embedchain comes with built-in support for various popular large language models
   <Card title="Azure OpenAI" href="#azure-openai"></Card>
   <Card title="Anthropic" href="#anthropic"></Card>
   <Card title="Cohere" href="#cohere"></Card>
-  <Card title="Ollama" href="#Ollama"></Card>
+  <Card title="Together" href="#together"></Card>
+  <Card title="Ollama" href="#ollama"></Card>
   <Card title="GPT4All" href="#gpt4all"></Card>
   <Card title="JinaChat" href="#jinachat"></Card>
   <Card title="Hugging Face" href="#hugging-face"></Card>
@@ -330,6 +331,42 @@ llm:
 
 </CodeGroup>
 
+## Together
+
+Install related dependencies using the following command:
+
+```bash
+pip install --upgrade 'embedchain[together]'
+```
+
+Set the `TOGETHER_API_KEY` as environment variable which you can find on their [Account settings page](https://api.together.xyz/settings/api-keys).
+
+Once you have the API key, you are all set to use it with Embedchain.
+
+<CodeGroup>
+
+```python main.py
+import os
+from embedchain import Pipeline as App
+
+os.environ["TOGETHER_API_KEY"] = "xxx"
+
+# load llm configuration from config.yaml file
+app = App.from_config(config_path="config.yaml")
+```
+
+```yaml config.yaml
+llm:
+  provider: together
+  config:
+    model: togethercomputer/RedPajama-INCITE-7B-Base
+    temperature: 0.5
+    max_tokens: 1000
+    top_p: 1
+```
+
+</CodeGroup>
+
 ## Ollama
 
 Setup Ollama using https://github.com/jmorganca/ollama

docs/examples/notebooks-and-replits.mdx

@@ -44,6 +44,10 @@ Get started with Embedchain by trying out the examples below. You can run the ex
       <td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/cohere.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
       <td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/cohere#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&amp;variant=small" noZoom alt="Try with Replit Badge"/></a></td>
     </tr>
+    <tr>
+      <td className="align-middle">Together</td>
+      <td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/together.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
+    </tr>
     <tr>
       <td className="align-middle">Ollama</td>
       <td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/ollama.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>

docs/examples/rest-api/create.mdx

@@ -81,6 +81,7 @@ curl --request POST \
 | `OPENAI_API_BASE`          | Azure OpenAI                   |
 | `OPENAI_API_VERSION`       | Azure OpenAI                   |
 | `COHERE_API_KEY`           | Cohere                         |
+| `TOGETHER_API_KEY`         | Together                       |
 | `ANTHROPIC_API_KEY`        | Anthropic                      |
 | `JINACHAT_API_KEY`         | Jina                           |
 | `HUGGINGFACE_ACCESS_TOKEN` | Huggingface                    |

embedchain/factory.py

@@ -12,6 +12,7 @@ class LlmFactory:
         "anthropic": "embedchain.llm.anthropic.AnthropicLlm",
         "azure_openai": "embedchain.llm.azure_openai.AzureOpenAILlm",
         "cohere": "embedchain.llm.cohere.CohereLlm",
+        "together": "embedchain.llm.together.TogetherLlm",
         "gpt4all": "embedchain.llm.gpt4all.GPT4ALLLlm",
         "ollama": "embedchain.llm.ollama.OllamaLlm",
         "huggingface": "embedchain.llm.huggingface.HuggingFaceLlm",

embedchain/llm/together.py

@@ -0,0 +1,43 @@
+import importlib
+import os
+from typing import Optional
+
+from langchain.llms import Together
+
+from embedchain.config import BaseLlmConfig
+from embedchain.helpers.json_serializable import register_deserializable
+from embedchain.llm.base import BaseLlm
+
+
+@register_deserializable
+class TogetherLlm(BaseLlm):
+    def __init__(self, config: Optional[BaseLlmConfig] = None):
+        if "TOGETHER_API_KEY" not in os.environ:
+            raise ValueError("Please set the TOGETHER_API_KEY environment variable.")
+
+        try:
+            importlib.import_module("together")
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "The required dependencies for Together are not installed."
+                'Please install with `pip install --upgrade "embedchain[together]"`'
+            ) from None
+
+        super().__init__(config=config)
+
+    def get_llm_model_answer(self, prompt):
+        if self.config.system_prompt:
+            raise ValueError("TogetherLlm does not support `system_prompt`")
+        return TogetherLlm._get_answer(prompt=prompt, config=self.config)
+
+    @staticmethod
+    def _get_answer(prompt: str, config: BaseLlmConfig) -> str:
+        llm = Together(
+            together_api_key=os.environ["TOGETHER_API_KEY"],
+            model=config.model,
+            max_tokens=config.max_tokens,
+            temperature=config.temperature,
+            top_p=config.top_p,
+        )
+
+        return llm(prompt)

embedchain/utils.py

@@ -384,6 +384,7 @@ def validate_config(config_data):
                     "anthropic",
                     "huggingface",
                     "cohere",
+                    "together",
                     "gpt4all",
                     "ollama",
                     "jina",

examples/rest-api/requirements.txt

@@ -1,6 +1,6 @@
 fastapi==0.104.0
 uvicorn==0.23.2
 embedchain==0.1.3
-embedchain[streamlit, community, opensource, elasticsearch, opensearch, poe, discord, slack, whatsapp, weaviate, pinecone, qdrant, images, huggingface_hub, cohere, milvus, dataloaders, vertexai, llama2, gmail, json]==0.1.3
+embedchain[streamlit, community, opensource, elasticsearch, opensearch, poe, discord, slack, whatsapp, weaviate, pinecone, qdrant, images, huggingface_hub, cohere, together, milvus, dataloaders, vertexai, llama2, gmail, json]==0.1.3
 sqlalchemy==2.0.22
 python-multipart==0.0.6

examples/rest-api/utils.py

@@ -5,6 +5,7 @@ def generate_error_message_for_api_keys(error: ValueError) -> str:
         "OPENAI_API_BASE": "OPENAI_API_BASE",
         "OPENAI_API_VERSION": "OPENAI_API_VERSION",
         "COHERE_API_KEY": "COHERE_API_KEY",
+        "TOGETHER_API_KEY": "TOGETHER_API_KEY",
         "ANTHROPIC_API_KEY": "ANTHROPIC_API_KEY",
         "JINACHAT_API_KEY": "JINACHAT_API_KEY",
         "HUGGINGFACE_ACCESS_TOKEN": "HUGGINGFACE_ACCESS_TOKEN",

notebooks/together.ipynb

@@ -0,0 +1,235 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "b02n_zJ_hl3d"
+      },
+      "source": [
+        "## Cookbook for using Cohere with Embedchain"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "gyJ6ui2vhtMY"
+      },
+      "source": [
+        "### Step-1: Install embedchain package"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "-NbXjAdlh0vJ",
+        "outputId": "fae77912-4e6a-4c78-fcb7-fbbe46f7a9c7"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install embedchain[dataloaders,together]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "nGnpSYAAh2bQ"
+      },
+      "source": [
+        "### Step-2: Set Cohere related environment variables\n",
+        "\n",
+        "You can find `OPENAI_API_KEY` on your [OpenAI dashboard](https://platform.openai.com/account/api-keys) and `TOGETHER_API_KEY` key on your [Together dashboard](https://api.together.xyz/settings/api-keys)."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "0fBdQ9GAiRvK"
+      },
+      "outputs": [],
+      "source": [
+        "import os\n",
+        "from embedchain import Pipeline as App\n",
+        "\n",
+        "os.environ[\"OPENAI_API_KEY\"] = \"\"\n",
+        "os.environ[\"TOGETHER_API_KEY\"] = \"\""
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Ns6RhPfbiitr"
+      },
+      "source": [
+        "### Step-3: Define your llm and embedding model config"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "S9CkxVjriotB"
+      },
+      "outputs": [],
+      "source": [
+        "config = \"\"\"\n",
+        "llm:\n",
+        "  provider: together\n",
+        "  config:\n",
+        "    model: mistralai/Mixtral-8x7B-Instruct-v0.1\n",
+        "    temperature: 0.5\n",
+        "    max_tokens: 1000\n",
+        "\"\"\"\n",
+        "\n",
+        "# Write the multi-line string to a YAML file\n",
+        "with open('together.yaml', 'w') as file:\n",
+        "    file.write(config)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "PGt6uPLIi1CS"
+      },
+      "source": [
+        "### Step-4 Create embedchain app based on the config"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 321
+        },
+        "id": "Amzxk3m-i3tD",
+        "outputId": "afe8afde-5cb8-46bc-c541-3ad26cc3fa6e"
+      },
+      "outputs": [],
+      "source": [
+        "app = App.from_config(config_path=\"together.yaml\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "XNXv4yZwi7ef"
+      },
+      "source": [
+        "### Step-5: Add data sources to your app"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 176
+        },
+        "id": "Sn_0rx9QjIY9",
+        "outputId": "2f2718a4-3b7e-4844-fd46-3e0857653ca0"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Inserting batches in chromadb: 100%|██████████| 1/1 [00:01<00:00,  1.16s/it]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Successfully saved https://www.forbes.com/profile/elon-musk (DataType.WEB_PAGE). New chunks count: 4\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "\n"
+          ]
+        },
+        {
+          "data": {
+            "text/plain": [
+              "'8cf46026cabf9b05394a2658bd1fe890'"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "app.add(\"https://www.forbes.com/profile/elon-musk\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_7W6fDeAjMAP"
+      },
+      "source": [
+        "### Step-6: All set. Now start asking questions related to your data"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "cvIK7dWRjN_f",
+        "outputId": "79e873c8-9594-45da-f5a3-0a893511267f"
+      },
+      "outputs": [],
+      "source": [
+        "while(True):\n",
+        "    question = input(\"Enter question: \")\n",
+        "    if question in ['q', 'exit', 'quit']:\n",
+        "        break\n",
+        "    answer = app.query(question)\n",
+        "    print(answer)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "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": "3.11.4"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
 
 [[package]]
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 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
-greenlet = {version = "!=0.4.17", optional = true, markers = "platform_machine == \"win32\" or platform_machine == \"WIN32\" or platform_machine == \"AMD64\" or platform_machine == \"amd64\" or platform_machine == \"x86_64\" or platform_machine == \"ppc64le\" or platform_machine == \"aarch64\" or extra == \"asyncio\""}
+greenlet = {version = "!=0.4.17", optional = true, markers = "platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\" or extra == \"asyncio\""}
 typing-extensions = ">=4.2.0"
 
 [package.extras]
@@ -6514,6 +6596,17 @@ files = [
 [package.dependencies]
 starlette = "*"
 
+[[package]]
+name = "sseclient-py"
+version = "1.8.0"
+description = "SSE client for Python"
+optional = true
+python-versions = "*"
+files = [
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+]
+
 [[package]]
 name = "starlette"
 version = "0.27.0"
@@ -6702,6 +6795,25 @@ requests-file = ">=1.4"
 [package.extras]
 testing = ["black", "mypy", "pytest", "pytest-gitignore", "pytest-mock", "responses", "ruff", "tox", "types-filelock", "types-requests"]
 
+[[package]]
+name = "together"
+version = "0.2.10"
+description = "Python client for Together's Cloud Platform!"
+optional = true
+python-versions = ">=3.7,<4.0"
+files = [
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+]
+
+[package.dependencies]
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+requests = ">=2.31.0,<3.0.0"
+sseclient-py = ">=1.7.2,<2.0.0"
+tabulate = ">=0.9.0,<0.10.0"
+tqdm = ">=4.66.1,<5.0.0"
+typer = ">=0.9.0,<0.10.0"
+
 [[package]]
 name = "tokenizers"
 version = "0.14.1"
@@ -8023,6 +8135,7 @@ qdrant = ["qdrant-client"]
 rss-feed = ["feedparser", "listparser", "newspaper3k"]
 slack = ["flask", "slack-sdk"]
 streamlit = []
+together = ["together"]
 vertexai = ["google-cloud-aiplatform"]
 weaviate = ["weaviate-client"]
 whatsapp = ["flask", "twilio"]
@@ -8031,4 +8144,4 @@ youtube = ["youtube-transcript-api", "yt_dlp"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.12"
-content-hash = "5237dfb5f5c38ecfbf7bc3a2832c1aeff51a24429641d6175bb55e3e1d90e70e"
+content-hash = "bc763595ae5e903a5a819a2d3f31f045fac52555f72e44ead9df0e5e191955aa"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "embedchain"
-version = "0.1.43"
+version = "0.1.44"
 description = "Data platform for LLMs - Load, index, retrieve and sync any unstructured data"
 authors = [
     "Taranjeet Singh <taranjeet@embedchain.ai>",
@@ -120,6 +120,7 @@ fastapi-poe = { version = "0.0.16", optional = true }
 discord = { version = "^2.3.2", optional = true }
 slack-sdk = { version = "3.21.3", optional = true }
 cohere = { version = "^4.27", optional = true }
+together = { version = "^0.2.8", optional = true }
 weaviate-client = { version = "^3.24.1", optional = true }
 docx2txt = { version = "^0.8", optional = true }
 pinecone-client = { version = "^2.2.4", optional = true }
@@ -177,6 +178,7 @@ qdrant = ["qdrant-client"]
 images = ["torch", "ftfy", "regex", "pillow", "torchvision"]
 huggingface_hub=["huggingface_hub"]
 cohere = ["cohere"]
+together = ["together"]
 milvus = ["pymilvus"]
 dataloaders=[
     "youtube-transcript-api",

tests/llm/test_together.py

@@ -0,0 +1,56 @@
+import os
+
+import pytest
+
+from embedchain.config import BaseLlmConfig
+from embedchain.llm.together import TogetherLlm
+
+
+@pytest.fixture
+def together_llm_config():
+    os.environ["TOGETHER_API_KEY"] = "test_api_key"
+    config = BaseLlmConfig(model="togethercomputer/RedPajama-INCITE-7B-Base", max_tokens=50, temperature=0.7, top_p=0.8)
+    yield config
+    os.environ.pop("TOGETHER_API_KEY")
+
+
+def test_init_raises_value_error_without_api_key(mocker):
+    mocker.patch.dict(os.environ, clear=True)
+    with pytest.raises(ValueError):
+        TogetherLlm()
+
+
+def test_get_llm_model_answer_raises_value_error_for_system_prompt(together_llm_config):
+    llm = TogetherLlm(together_llm_config)
+    llm.config.system_prompt = "system_prompt"
+    with pytest.raises(ValueError):
+        llm.get_llm_model_answer("prompt")
+
+
+def test_get_llm_model_answer(together_llm_config, mocker):
+    mocker.patch("embedchain.llm.together.TogetherLlm._get_answer", return_value="Test answer")
+
+    llm = TogetherLlm(together_llm_config)
+    answer = llm.get_llm_model_answer("Test query")
+
+    assert answer == "Test answer"
+
+
+def test_get_answer_mocked_together(together_llm_config, mocker):
+    mocked_together = mocker.patch("embedchain.llm.together.Together")
+    mock_instance = mocked_together.return_value
+    mock_instance.return_value = "Mocked answer"
+
+    llm = TogetherLlm(together_llm_config)
+    prompt = "Test query"
+    answer = llm.get_llm_model_answer(prompt)
+
+    assert answer == "Mocked answer"
+    mocked_together.assert_called_once_with(
+        together_api_key="test_api_key",
+        model="togethercomputer/RedPajama-INCITE-7B-Base",
+        max_tokens=50,
+        temperature=0.7,
+        top_p=0.8,
+    )
+    mock_instance.assert_called_once_with(prompt)

tests/test_utils.py

@@ -8,6 +8,7 @@ CONFIG_YAMLS = [
     "configs/chroma.yaml",
     "configs/chunker.yaml",
     "configs/cohere.yaml",
+    "configs/together.yaml",
     "configs/ollama.yaml",
     "configs/full-stack.yaml",
     "configs/gpt4.yaml",