diff --git a/configs/clarifai.yaml b/configs/clarifai.yaml
new file mode 100644
index 00000000..0c52ba00
--- /dev/null
+++ b/configs/clarifai.yaml
@@ -0,0 +1,12 @@
+llm:
+ provider: clarifai
+ config:
+ model: "https://clarifai.com/mistralai/completion/models/mistral-7B-Instruct"
+ model_kwargs:
+ temperature: 0.5
+ max_tokens: 1000
+
+embedder:
+ provider: clarifai
+ config:
+ model: "https://clarifai.com/clarifai/main/models/BAAI-bge-base-en-v15"
diff --git a/docs/components/embedding-models.mdx b/docs/components/embedding-models.mdx
index af24b89c..96ee815a 100644
--- a/docs/components/embedding-models.mdx
+++ b/docs/components/embedding-models.mdx
@@ -16,6 +16,7 @@ Embedchain supports several embedding models from the following providers:
+
## OpenAI
@@ -385,4 +386,51 @@ embedder:
model: 'all-minilm:latest'
```
+
+
+## Clarifai
+
+Install related dependencies using the following command:
+
+```bash
+pip install --upgrade 'embedchain[clarifai]'
+```
+
+set the `CLARIFAI_PAT` as environment variable which you can find in the [security page](https://clarifai.com/settings/security). Optionally you can also pass the PAT key as parameters in LLM/Embedder class.
+
+Now you are all set with exploring Embedchain.
+
+
+
+```python main.py
+import os
+from embedchain import App
+
+os.environ["CLARIFAI_PAT"] = "XXX"
+
+# load llm and embedder configuration from config.yaml file
+app = App.from_config(config_path="config.yaml")
+
+#Now let's add some data.
+app.add("https://www.forbes.com/profile/elon-musk")
+
+#Query the app
+response = app.query("what college degrees does elon musk have?")
+```
+Head to [Clarifai Platform](https://clarifai.com/explore/models?page=1&perPage=24&filterData=%5B%7B%22field%22%3A%22output_fields%22%2C%22value%22%3A%5B%22embeddings%22%5D%7D%5D) to explore all the State of the Art embedding models available to use.
+For passing LLM model inference parameters use `model_kwargs` argument in the config file. Also you can use `api_key` argument to pass `CLARIFAI_PAT` in the config.
+
+```yaml config.yaml
+llm:
+ provider: clarifai
+ config:
+ model: "https://clarifai.com/mistralai/completion/models/mistral-7B-Instruct"
+ model_kwargs:
+ temperature: 0.5
+ max_tokens: 1000
+embedder:
+ provider: clarifai
+ config:
+ model: "https://clarifai.com/clarifai/main/models/BAAI-bge-base-en-v15"
+```
\ No newline at end of file
diff --git a/docs/components/llms.mdx b/docs/components/llms.mdx
index 14f4ada2..194ebfda 100644
--- a/docs/components/llms.mdx
+++ b/docs/components/llms.mdx
@@ -15,6 +15,7 @@ Embedchain comes with built-in support for various popular large language models
+
@@ -385,6 +386,54 @@ llm:
+## Clarifai
+
+Install related dependencies using the following command:
+
+```bash
+pip install --upgrade 'embedchain[clarifai]'
+```
+
+set the `CLARIFAI_PAT` as environment variable which you can find in the [security page](https://clarifai.com/settings/security). Optionally you can also pass the PAT key as parameters in LLM/Embedder class.
+
+Now you are all set with exploring Embedchain.
+
+
+
+```python main.py
+import os
+from embedchain import App
+
+os.environ["CLARIFAI_PAT"] = "XXX"
+
+# load llm configuration from config.yaml file
+app = App.from_config(config_path="config.yaml")
+
+#Now let's add some data.
+app.add("https://www.forbes.com/profile/elon-musk")
+
+#Query the app
+response = app.query("what college degrees does elon musk have?")
+```
+Head to [Clarifai Platform](https://clarifai.com/explore/models?page=1&perPage=24&filterData=%5B%7B%22field%22%3A%22use_cases%22%2C%22value%22%3A%5B%22llm%22%5D%7D%5D) to browse various State-of-the-Art LLM models for your use case.
+For passing model inference parameters use `model_kwargs` argument in the config file. Also you can use `api_key` argument to pass `CLARIFAI_PAT` in the config.
+
+```yaml config.yaml
+llm:
+ provider: clarifai
+ config:
+ model: "https://clarifai.com/mistralai/completion/models/mistral-7B-Instruct"
+ model_kwargs:
+ temperature: 0.5
+ max_tokens: 1000
+embedder:
+ provider: clarifai
+ config:
+ model: "https://clarifai.com/clarifai/main/models/BAAI-bge-base-en-v15"
+```
+
+
+
## GPT4ALL
Install related dependencies using the following command:
diff --git a/embedchain/embedder/clarifai.py b/embedchain/embedder/clarifai.py
new file mode 100644
index 00000000..6f0b7c22
--- /dev/null
+++ b/embedchain/embedder/clarifai.py
@@ -0,0 +1,52 @@
+import os
+from typing import Optional, Union
+
+from embedchain.config import BaseEmbedderConfig
+from embedchain.embedder.base import BaseEmbedder
+
+from chromadb import EmbeddingFunction, Embeddings
+
+
+class ClarifaiEmbeddingFunction(EmbeddingFunction):
+ def __init__(self, config: BaseEmbedderConfig) -> None:
+ super().__init__()
+ try:
+ from clarifai.client.model import Model
+ from clarifai.client.input import Inputs
+ except ModuleNotFoundError:
+ raise ModuleNotFoundError(
+ "The required dependencies for ClarifaiEmbeddingFunction are not installed."
+ 'Please install with `pip install --upgrade "embedchain[clarifai]"`'
+ ) from None
+ self.config = config
+ self.api_key = config.api_key or os.getenv("CLARIFAI_PAT")
+ self.model = config.model
+ self.model_obj = Model(url=self.model, pat=self.api_key)
+ self.input_obj = Inputs(pat=self.api_key)
+
+ def __call__(self, input: Union[str, list[str]]) -> Embeddings:
+ if isinstance(input, str):
+ input = [input]
+
+ batch_size = 32
+ embeddings = []
+ try:
+ for i in range(0, len(input), batch_size):
+ batch = input[i : i + batch_size]
+ input_batch = [
+ self.input_obj.get_text_input(input_id=str(id), raw_text=inp) for id, inp in enumerate(batch)
+ ]
+ response = self.model_obj.predict(input_batch)
+ embeddings.extend([list(output.data.embeddings[0].vector) for output in response.outputs])
+ except Exception as e:
+ print(f"Predict failed, exception: {e}")
+
+ return embeddings
+
+
+class ClarifaiEmbedder(BaseEmbedder):
+ def __init__(self, config: Optional[BaseEmbedderConfig] = None):
+ super().__init__(config)
+
+ embedding_func = ClarifaiEmbeddingFunction(config=self.config)
+ self.set_embedding_fn(embedding_fn=embedding_func)
diff --git a/embedchain/factory.py b/embedchain/factory.py
index 81300ecc..567bdb55 100644
--- a/embedchain/factory.py
+++ b/embedchain/factory.py
@@ -23,6 +23,7 @@ class LlmFactory:
"google": "embedchain.llm.google.GoogleLlm",
"aws_bedrock": "embedchain.llm.aws_bedrock.AWSBedrockLlm",
"mistralai": "embedchain.llm.mistralai.MistralAILlm",
+ "clarifai": "embedchain.llm.clarifai.ClarifaiLlm",
"groq": "embedchain.llm.groq.GroqLlm",
"nvidia": "embedchain.llm.nvidia.NvidiaLlm",
"vllm": "embedchain.llm.vllm.VLLM",
@@ -56,6 +57,7 @@ class EmbedderFactory:
"vertexai": "embedchain.embedder.vertexai.VertexAIEmbedder",
"google": "embedchain.embedder.google.GoogleAIEmbedder",
"mistralai": "embedchain.embedder.mistralai.MistralAIEmbedder",
+ "clarifai": "embedchain.embedder.clarifai.ClarifaiEmbedder",
"nvidia": "embedchain.embedder.nvidia.NvidiaEmbedder",
"cohere": "embedchain.embedder.cohere.CohereEmbedder",
"ollama": "embedchain.embedder.ollama.OllamaEmbedder",
@@ -65,6 +67,7 @@ class EmbedderFactory:
"google": "embedchain.config.embedder.google.GoogleAIEmbedderConfig",
"gpt4all": "embedchain.config.embedder.base.BaseEmbedderConfig",
"huggingface": "embedchain.config.embedder.base.BaseEmbedderConfig",
+ "clarifai": "embedchain.config.embedder.base.BaseEmbedderConfig",
"openai": "embedchain.config.embedder.base.BaseEmbedderConfig",
"ollama": "embedchain.config.embedder.ollama.OllamaEmbedderConfig",
}
diff --git a/embedchain/llm/clarifai.py b/embedchain/llm/clarifai.py
new file mode 100644
index 00000000..c20c3d98
--- /dev/null
+++ b/embedchain/llm/clarifai.py
@@ -0,0 +1,47 @@
+import logging
+import os
+from typing import Optional
+
+from embedchain.config import BaseLlmConfig
+from embedchain.helpers.json_serializable import register_deserializable
+from embedchain.llm.base import BaseLlm
+
+
+@register_deserializable
+class ClarifaiLlm(BaseLlm):
+ def __init__(self, config: Optional[BaseLlmConfig] = None):
+ super().__init__(config=config)
+ if not self.config.api_key and "CLARIFAI_PAT" not in os.environ:
+ raise ValueError("Please set the CLARIFAI_PAT environment variable.")
+
+ def get_llm_model_answer(self, prompt):
+ return self._get_answer(prompt=prompt, config=self.config)
+
+ @staticmethod
+ def _get_answer(prompt: str, config: BaseLlmConfig) -> str:
+ try:
+ from clarifai.client.model import Model
+ except ModuleNotFoundError:
+ raise ModuleNotFoundError(
+ "The required dependencies for Clarifai are not installed."
+ 'Please install with `pip install --upgrade "embedchain[clarifai]"`'
+ ) from None
+
+ model_name = config.model
+ logging.info(f"Using clarifai LLM model: {model_name}")
+ api_key = config.api_key or os.getenv("CLARIFAI_PAT")
+ model = Model(url=model_name, pat=api_key)
+ params = config.model_kwargs
+
+ try:
+ (params := {}) if config.model_kwargs is None else config.model_kwargs
+ predict_response = model.predict_by_bytes(
+ bytes(prompt, "utf-8"),
+ input_type="text",
+ inference_params=params,
+ )
+ text = predict_response.outputs[0].data.text.raw
+ return text
+
+ except Exception as e:
+ logging.error(f"Predict failed, exception: {e}")
diff --git a/embedchain/utils/misc.py b/embedchain/utils/misc.py
index 03db506a..ba1494bc 100644
--- a/embedchain/utils/misc.py
+++ b/embedchain/utils/misc.py
@@ -414,6 +414,7 @@ def validate_config(config_data):
"google",
"aws_bedrock",
"mistralai",
+ "clarifai",
"vllm",
"groq",
"nvidia",
@@ -458,6 +459,7 @@ def validate_config(config_data):
"azure_openai",
"google",
"mistralai",
+ "clarifai",
"nvidia",
"ollama",
"cohere",
@@ -482,6 +484,7 @@ def validate_config(config_data):
"azure_openai",
"google",
"mistralai",
+ "clarifai",
"nvidia",
"ollama",
),
diff --git a/embedchain/vectordb/qdrant.py b/embedchain/vectordb/qdrant.py
index 1295b91c..c356332c 100644
--- a/embedchain/vectordb/qdrant.py
+++ b/embedchain/vectordb/qdrant.py
@@ -251,4 +251,4 @@ class QdrantDB(BaseVectorDB):
def delete(self, where: dict):
db_filter = self._generate_query(where)
- self.client.delete(collection_name=self.collection_name, points_selector=db_filter)
+ self.client.delete(collection_name=self.collection_name, points_selector=db_filter)
\ No newline at end of file
diff --git a/notebooks/clarifai.ipynb b/notebooks/clarifai.ipynb
new file mode 100644
index 00000000..e0140060
--- /dev/null
+++ b/notebooks/clarifai.ipynb
@@ -0,0 +1,135 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Cookbook for using Clarifai LLM and Embedders with Embedchain"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Step-1: Install embedchain-clarifai package"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!pip install embedchain[clarifai]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Step-2: Set Clarifai PAT as env variable.\n",
+ "Sign-up to [Clarifai](https://clarifai.com/signup?utm_source=clarifai_home&utm_medium=direct&) platform and you can obtain `CLARIFAI_PAT` by following this [link](https://docs.clarifai.com/clarifai-basics/authentication/personal-access-tokens/).\n",
+ "\n",
+ "optionally you can also pass `api_key` in config of llm/embedder class."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "from embedchain import App\n",
+ "\n",
+ "os.environ[\"CLARIFAI_PAT\"]=\"xxx\""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Step-3 Create embedchain app using clarifai LLM and embedder and define your config.\n",
+ "\n",
+ "Browse through Clarifai community page to get the URL of different [LLM](https://clarifai.com/explore/models?page=1&perPage=24&filterData=%5B%7B%22field%22%3A%22use_cases%22%2C%22value%22%3A%5B%22llm%22%5D%7D%5D) and [embedding](https://clarifai.com/explore/models?page=1&perPage=24&filterData=%5B%7B%22field%22%3A%22input_fields%22%2C%22value%22%3A%5B%22text%22%5D%7D%2C%7B%22field%22%3A%22output_fields%22%2C%22value%22%3A%5B%22embeddings%22%5D%7D%5D) models available."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Use model_kwargs to pass all model specific parameters for inference.\n",
+ "app = App.from_config(config={\n",
+ " \"llm\": {\n",
+ " \"provider\": \"clarifai\",\n",
+ " \"config\": {\n",
+ " \"model\": \"https://clarifai.com/mistralai/completion/models/mistral-7B-Instruct\",\n",
+ " \"model_kwargs\": {\n",
+ " \"temperature\": 0.5,\n",
+ " \"max_tokens\": 1000\n",
+ " }\n",
+ " }\n",
+ " },\n",
+ " \"embedder\": {\n",
+ " \"provider\": \"clarifai\",\n",
+ " \"config\": {\n",
+ " \"model\": \"https://clarifai.com/openai/embed/models/text-embedding-ada\",\n",
+ " }\n",
+ "}\n",
+ "})"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Step-4: Add data sources to your app"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "app.add(\"https://www.forbes.com/profile/elon-musk\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Step-5: All set. Now start asking questions related to your data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "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)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "v1",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "name": "python",
+ "version": "3.9.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/poetry.lock b/poetry.lock
index b3c0dd65..a3804156 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -854,6 +854,49 @@ typer = ">=0.9.0"
typing-extensions = ">=4.5.0"
uvicorn = {version = ">=0.18.3", extras = ["standard"]}
+[[package]]
+name = "clarifai"
+version = "10.3.2"
+description = "Clarifai Python SDK"
+optional = true
+python-versions = ">=3.8"
+files = [
+ {file = "clarifai-10.3.2-py3-none-any.whl", hash = "sha256:53a788af293875138a249af3334286799fa1e8dd0290e34c1da46fb522b5003e"},
+ {file = "clarifai-10.3.2.tar.gz", hash = "sha256:3ac864f67d8d294535ecaa79cbb3236ac1d8d2ff8c6319865f83c260cefa7f50"},
+]
+
+[package.dependencies]
+clarifai-grpc = ">=10.2.3,<10.3.0"
+inquirerpy = "0.3.4"
+numpy = ">=1.22.0"
+Pillow = ">=9.5.0"
+PyYAML = ">=6.0.1"
+rich = ">=13.4.2"
+schema = ">=0.7.5"
+tabulate = ">=0.9.0"
+tqdm = ">=4.65.0"
+tritonclient = ">=2.34.0"
+
+[package.extras]
+all = ["pycocotools (==2.0.6)"]
+
+[[package]]
+name = "clarifai-grpc"
+version = "10.2.3"
+description = "Clarifai gRPC API Client"
+optional = true
+python-versions = ">=3.8"
+files = [
+ {file = "clarifai-grpc-10.2.3.tar.gz", hash = "sha256:b03f87997a5ab2f810b046ad2a19c2d14260fa7bd4ce410d81c817f03e899202"},
+ {file = "clarifai_grpc-10.2.3-py3-none-any.whl", hash = "sha256:da24eb816ac93fa10cd5ec8114683ea7215ef31197e2601f92e88dc3a0566f43"},
+]
+
+[package.dependencies]
+googleapis-common-protos = ">=1.53.0"
+grpcio = ">=1.44.0"
+protobuf = ">=3.20.3"
+requests = ">=2.25.1"
+
[[package]]
name = "click"
version = "8.1.7"
@@ -2574,6 +2617,24 @@ files = [
{file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
]
+[[package]]
+name = "inquirerpy"
+version = "0.3.4"
+description = "Python port of Inquirer.js (A collection of common interactive command-line user interfaces)"
+optional = true
+python-versions = ">=3.7,<4.0"
+files = [
+ {file = "InquirerPy-0.3.4-py3-none-any.whl", hash = "sha256:c65fdfbac1fa00e3ee4fb10679f4d3ed7a012abf4833910e63c295827fe2a7d4"},
+ {file = "InquirerPy-0.3.4.tar.gz", hash = "sha256:89d2ada0111f337483cb41ae31073108b2ec1e618a49d7110b0d7ade89fc197e"},
+]
+
+[package.dependencies]
+pfzy = ">=0.3.1,<0.4.0"
+prompt-toolkit = ">=3.0.1,<4.0.0"
+
+[package.extras]
+docs = ["Sphinx (>=4.1.2,<5.0.0)", "furo (>=2021.8.17-beta.43,<2022.0.0)", "myst-parser (>=0.15.1,<0.16.0)", "sphinx-autobuild (>=2021.3.14,<2022.0.0)", "sphinx-copybutton (>=0.4.0,<0.5.0)"]
+
[[package]]
name = "intel-openmp"
version = "2021.4.0"
@@ -4300,6 +4361,20 @@ files = [
{file = "pathspec-0.12.1.tar.gz", hash = "sha256:a482d51503a1ab33b1c67a6c3813a26953dbdc71c31dacaef9a838c4e29f5712"},
]
+[[package]]
+name = "pfzy"
+version = "0.3.4"
+description = "Python port of the fzy fuzzy string matching algorithm"
+optional = true
+python-versions = ">=3.7,<4.0"
+files = [
+ {file = "pfzy-0.3.4-py3-none-any.whl", hash = "sha256:5f50d5b2b3207fa72e7ec0ef08372ef652685470974a107d0d4999fc5a903a96"},
+ {file = "pfzy-0.3.4.tar.gz", hash = "sha256:717ea765dd10b63618e7298b2d98efd819e0b30cd5905c9707223dceeb94b3f1"},
+]
+
+[package.extras]
+docs = ["Sphinx (>=4.1.2,<5.0.0)", "furo (>=2021.8.17-beta.43,<2022.0.0)", "myst-parser (>=0.15.1,<0.16.0)", "sphinx-autobuild (>=2021.3.14,<2022.0.0)", "sphinx-copybutton (>=0.4.0,<0.5.0)"]
+
[[package]]
name = "pillow"
version = "10.3.0"
@@ -4488,6 +4563,20 @@ nodeenv = ">=0.11.1"
pyyaml = ">=5.1"
virtualenv = ">=20.10.0"
+[[package]]
+name = "prompt-toolkit"
+version = "3.0.47"
+description = "Library for building powerful interactive command lines in Python"
+optional = true
+python-versions = ">=3.7.0"
+files = [
+ {file = "prompt_toolkit-3.0.47-py3-none-any.whl", hash = "sha256:0d7bfa67001d5e39d02c224b663abc33687405033a8c422d0d675a5a13361d10"},
+ {file = "prompt_toolkit-3.0.47.tar.gz", hash = "sha256:1e1b29cb58080b1e69f207c893a1a7bf16d127a5c30c9d17a25a5d77792e5360"},
+]
+
+[package.dependencies]
+wcwidth = "*"
+
[[package]]
name = "proto-plus"
version = "1.23.0"
@@ -5227,6 +5316,88 @@ files = [
[package.extras]
cli = ["click (>=5.0)"]
+[[package]]
+name = "python-rapidjson"
+version = "1.17"
+description = "Python wrapper around rapidjson"
+optional = true
+python-versions = ">=3.6"
+files = [
+ {file = "python-rapidjson-1.17.tar.gz", hash = "sha256:95a111da29d996af8549f8b32ec701dab3af2ab7c6cd9c79540391ecb05f20c8"},
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+]
+
[[package]]
name = "pytube"
version = "15.0.0"
@@ -6675,6 +6846,28 @@ build = ["cmake (>=3.20)", "lit"]
tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)", "torch"]
tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
+[[package]]
+name = "tritonclient"
+version = "2.41.1"
+description = "Python client library and utilities for communicating with Triton Inference Server"
+optional = true
+python-versions = "*"
+files = [
+ {file = "tritonclient-2.41.1-py3-none-any.whl", hash = "sha256:91cb234331a7145c407cea605caf9eecbd4276ddc5f085ddd5a6dcab64e5e70b"},
+ {file = "tritonclient-2.41.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:22ad56ae5ab25518862dec85af0a8246a32a1e14e2ee1d86f1444ce432c254e1"},
+ {file = "tritonclient-2.41.1-py3-none-manylinux2014_aarch64.whl", hash = "sha256:6545055add115e9bd07ca540af95db5ceda0c783009ad41df6a7f35a79d57474"},
+]
+
+[package.dependencies]
+numpy = ">=1.19.1"
+python-rapidjson = ">=0.9.1"
+
+[package.extras]
+all = ["aiohttp (>=3.8.1,<4.0.0)", "cuda-python", "geventhttpclient (>=1.4.4,<=2.0.2)", "grpcio (>=1.41.0)", "numpy (>=1.19.1)", "packaging (>=14.1)", "protobuf (>=3.5.0,<5)", "python-rapidjson (>=0.9.1)"]
+cuda = ["cuda-python"]
+grpc = ["grpcio (>=1.41.0)", "numpy (>=1.19.1)", "packaging (>=14.1)", "protobuf (>=3.5.0,<5)", "python-rapidjson (>=0.9.1)"]
+http = ["aiohttp (>=3.8.1,<4.0.0)", "geventhttpclient (>=1.4.4,<=2.0.2)", "numpy (>=1.19.1)", "python-rapidjson (>=0.9.1)"]
+
[[package]]
name = "twilio"
version = "8.13.0"
@@ -7121,6 +7314,17 @@ files = [
[package.dependencies]
anyio = ">=3.0.0"
+[[package]]
+name = "wcwidth"
+version = "0.2.13"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = true
+python-versions = "*"
+files = [
+ {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
+ {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
+]
+
[[package]]
name = "weaviate-client"
version = "3.26.2"
@@ -7520,4 +7724,4 @@ youtube = ["youtube-transcript-api", "yt_dlp"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.9,<=3.13"
-content-hash = "c63e9ce659b1148ca8685bbd81ac65adc07d8cc75abe28856525f6a247ce7856"
+content-hash = "757481b96e9620d643c4ef77131c295ad22541784d5c6395d2c6da366d7ae7d3"
diff --git a/pyproject.toml b/pyproject.toml
index f4889c43..27966c40 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -119,6 +119,7 @@ twilio = { version = "^8.5.0", optional = true }
fastapi-poe = { version = "0.0.16", optional = true }
discord = { version = "^2.3.2", optional = true }
slack-sdk = { version = "3.21.3", optional = true }
+clarifai = { version = "^10.0.1", optional = true }
cohere = { version = "^5.3", optional = true }
together = { version = "^0.2.8", optional = true }
weaviate-client = { version = "^3.24.1", optional = true }
diff --git a/tests/llm/test_clarifai.py b/tests/llm/test_clarifai.py
new file mode 100644
index 00000000..884fe63d
--- /dev/null
+++ b/tests/llm/test_clarifai.py
@@ -0,0 +1,23 @@
+
+import pytest
+
+from embedchain.config import BaseLlmConfig
+from embedchain.llm.clarifai import ClarifaiLlm
+
+
+@pytest.fixture
+def clarifai_llm_config(monkeypatch):
+ monkeypatch.setenv("CLARIFAI_PAT","test_api_key")
+ config = BaseLlmConfig(
+ model="https://clarifai.com/openai/chat-completion/models/GPT-4",
+ model_kwargs={"temperature": 0.7, "max_tokens": 100},
+ )
+ yield config
+ monkeypatch.delenv("CLARIFAI_PAT")
+
+def test_clarifai__llm_get_llm_model_answer(clarifai_llm_config, mocker):
+ mocker.patch("embedchain.llm.clarifai.ClarifaiLlm._get_answer", return_value="Test answer")
+ llm = ClarifaiLlm(clarifai_llm_config)
+ answer = llm.get_llm_model_answer("Test query")
+
+ assert answer == "Test answer"