andre/crewAI
1
0
Fork 0
mirror of https://github.com/crewAIInc/crewAI.git synced 2026-01-11 00:58:30 +00:00
Code Issues Actions 5 Packages Projects Releases Wiki Activity

Updating docs

Browse Source
This commit is contained in:
João Moura
2024-08-11 15:04:45 -03:00
parent 7b63b6f485
commit a17fa70b1b
20 changed files with 153 additions and 118 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
docs/how-to/LLM-Connections.md
View File

@@ -9,7 +9,7 @@ description: Comprehensive guide on integrating CrewAI with various Large Langua
By default, CrewAI uses OpenAI's GPT-4o model (specifically, the model specified by the OPENAI_MODEL_NAME environment variable, defaulting to "gpt-4o") for language processing. You can configure your agents to use a different model or API as described in this guide.
By default, CrewAI uses OpenAI's GPT-4 model (specifically, the model specified by the OPENAI_MODEL_NAME environment variable, defaulting to "gpt-4") for language processing. You can configure your agents to use a different model or API as described in this guide.
CrewAI provides extensive versatility in integrating with various Language Models (LLMs), including local options through Ollama such as Llama and Mixtral to cloud-based solutions like Azure. Its compatibility extends to all [LangChain LLM components](https://python.langchain.com/v0.2/docs/integrations/llms/), offering a wide range of integration possibilities for customized AI applications.
CrewAI provides extensive versatility in integrating with various Language Models (LLMs), including local options through Ollama such as Llama and Mixtral to cloud-based solutions like Azure. Its compatibility extends to all [LangChain LLM components](https://python.langchain.com/v0.2/docs/integrations/llms/), offering a wide range of integration possibilities for customized AI applications.
The platform supports connections to an array of Generative AI models, including:
@@ -37,6 +37,7 @@ example_agent = Agent(
verbose=True
)
```
## Ollama Local Integration
Ollama is preferred for local LLM integration, offering customization and privacy benefits. To integrate Ollama with CrewAI, you will need the `langchain-ollama` package. You can then set the following environment variables to connect to your Ollama instance running locally on port 11434.
@@ -47,8 +48,8 @@ os.environ[OPENAI_API_KEY]='' # No API Key required for Ollama
```
## Ollama Integration Step by Step (ex. for using Llama 3.1 8B locally)
1. [Download and install Ollama](https://ollama.com/download).
2. After setting up the Ollama, Pull the Llama3.1 8B model by typing following lines into your terminal ```ollama run llama3.1```.
1. [Download and install Ollama](https://ollama.com/download).
2. After setting up the Ollama, Pull the Llama3.1 8B model by typing following lines into your terminal ```ollama run llama3.1```.
3. Llama3.1 should now be served locally on `http://localhost:11434`
```
from crewai import Agent, Task, Crew
@@ -165,7 +166,7 @@ llm = ChatCohere()
For Azure OpenAI API integration, set the following environment variables:
```sh
os.environ[AZURE_OPENAI_DEPLOYMENT] = "You deployment"
os.environ[AZURE_OPENAI_DEPLOYMENT] = "Your deployment"
os.environ["OPENAI_API_VERSION"] = "2023-12-01-preview"
os.environ["AZURE_OPENAI_ENDPOINT"] = "Your Endpoint"
os.environ["AZURE_OPENAI_API_KEY"] = "<Your API Key>"
@@ -191,5 +192,6 @@ azure_agent = Agent(
llm=azure_llm
)
```
## Conclusion
Integrating CrewAI with different LLMs expands the framework's versatility, allowing for customized, efficient AI solutions across various domains and platforms.
Integrating CrewAI with different LLMs expands the framework's versatility, allowing for customized, efficient AI solutions across various domains and platforms.