Clarifai : Added Clarifai as LLM and embedding model provider. (#1311)

Co-authored-by: Deshraj Yadav <deshraj@gatech.edu>

docs/components/embedding-models.mdx

@@ -16,6 +16,7 @@ Embedchain supports several embedding models from the following providers:
   <Card title="NVIDIA AI" href="#nvidia-ai"></Card>
   <Card title="Cohere" href="#cohere"></Card>
   <Card title="Ollama" href="#ollama"></Card>
+  <Card title="Clarifai" href="#clarifai"></Card>
 </CardGroup>
 
 ## OpenAI
@@ -385,4 +386,51 @@ embedder:
     model: 'all-minilm:latest'
 ```
 
+</CodeGroup>
+
+## 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.
+
+<CodeGroup>
+
+```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"
+```
 </CodeGroup>

docs/components/llms.mdx

@@ -15,6 +15,7 @@ Embedchain comes with built-in support for various popular large language models
   <Card title="Together" href="#together"></Card>
   <Card title="Ollama" href="#ollama"></Card>
   <Card title="vLLM" href="#vllm"></Card>
+  <Card title="Clarifai" href="#clarifai"></Card>
   <Card title="GPT4All" href="#gpt4all"></Card>
   <Card title="JinaChat" href="#jinachat"></Card>
   <Card title="Hugging Face" href="#hugging-face"></Card>
@@ -385,6 +386,54 @@ llm:
 
 </CodeGroup>
 
+## 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.
+
+<CodeGroup>
+
+```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"
+```
+</CodeGroup>
+
+
 ## GPT4ALL
 
 Install related dependencies using the following command: