Update README

Author: YoanSallami

README.md

@@ -46,7 +46,7 @@ Developping a successful LM application in a profesional context, beyond statele
 - **Ensuring the correctness of the LMs output**: Synalinks combines constrained structured output with In-Context RL to ensure both format and content correctness.
 - **Optimizing async processes**: Synalinks automatically optimizes your pipelines by detecting parallel processes.
 - **Assessing the performance of your application**: Synalinks provides built-in metrics and rewards to evaluate your workflows.
-- **Configuring Language & Embedding Models**: Synalinks uses LiteLLM and comes ready with 100+ integrations out-of-the-box.
+- **Configuring Language & Embedding Models**: Seamlessly integrate multiple LM providers like Ollama, OpenAI, Anthropic, or Groq.
 - **Documenting your ML workflows**: Plot your workflows, training history, and evaluations; document everything.
 - **Versioning the prompts/pipelines**: Each program is serializable into JSON so you can version it with git.
 - **Deploying REST APIs**: Compatible out-of-the-box with FastAPI so your Data Scientists and Web Developers can stop tearing each other apart.

docs/Introduction.md

@@ -25,7 +25,7 @@ Developping a successful LM application in a profesional context, beyond statele
 - **Ensuring the correctness of the LMs output**: Synalinks combines constrained structured output with In-Context RL to ensure both format and content correctness.
 - **Optimizing async processes**: Synalinks automatically optimizes your pipelines by detecting parallel processes.
 - **Assessing the performance of your application**: Synalinks provides built-in metrics and rewards to evaluate your workflows.
-- **Configuring Language & Embedding Models**: Synalinks uses LiteLLM and comes ready with 100+ integrations out-of-the-box.
+- **Configuring Language & Embedding Models**: Seamlessly integrate multiple LM providers like Ollama, OpenAI, Anthropic, Mistral or Groq.
 - **Documenting your ML workflows**: Plot your workflows, training history, and evaluations; document everything.
 - **Versioning the prompts/pipelines**: Each program is serializable into JSON so you can version it with git.
 - **Deploying REST APIs**: Compatible out-of-the-box with FastAPI so your Data Scientists and Web Developers can stop tearing each other apart.