fix docs - env variables, default model and init code

docs/guides/javascript/interpreter-agent.mdx

@@ -41,7 +41,7 @@ description: "This is a simple guide to demonstrate how to use CODEINTERPRETER t
     <CodeGroup>
         ```javascript Model
         const llm = new ChatOpenAI({ 
-            model: "gpt-4",
+            model: "gpt-4o",
             apiKey: process.env.OPEN_AI_API_KEY
         });
         ```
@@ -131,7 +131,7 @@ Here's the complete JavaScript code for the Code Execution Agent:
         });
 
         const llm = new ChatOpenAI({ 
-            model: "gpt-4",
+            model: "gpt-4o",
             apiKey: process.env.OPEN_AI_API_KEY
         });
 

docs/guides/python/rag_agent.mdx

@@ -173,7 +173,7 @@ This project involves setting up and running a system of agents to add content t
     tools = toolset.get_tools(apps=[App.RAGTOOL])
 
     # Initialize the ChatOpenAI model with GPT-4 and API key from environment variables
-    llm = ChatOpenAI(model="gpt-4o", openai_api_key=os.environ["OPENAI_API_KEY"])
+    llm = ChatOpenAI(model="gpt-4o")
 
     # User-provided description of the data to be added and the query
     additional_content_list = [

docs/guides/python/research-assistant.mdx

@@ -123,7 +123,6 @@ Below is the complete code snippet combining all the steps:
 
     # Initialize the language model with OpenAI API key and model name
     llm = ChatOpenAI(
-        openai_api_key=os.environ["OPENAI_API_KEY"],
         model_name="gpt-4o"
     )
 

docs/javascript/langchain.mdx

@@ -55,7 +55,7 @@ async function executeAgent (entityName){
         // Create an agent
         const prompt = await pull("hwchase17/openai-functions-agent");
         const llm = new ChatOpenAI({
-            model: "gpt-4",
+            model: "gpt-4o",
             apiKey: process.env.OPEN_AI_API_KEY
         });
 

js/examples/langchain/demo.mjs

@@ -15,7 +15,7 @@ app.get('/webhook', async (req, res) => {
         const body = "TITLE: HELLO WORLD, DESCRIPTION: HELLO WORLD for the repo - utkarsh-dixit/speedy"
 
         const llm = new ChatOpenAI({
-            model: "gpt-4",
+            model: "gpt-4o",
         });
 
         const toolset = new LangchainToolSet({

js/examples/langchain/demo.ts

@@ -16,7 +16,7 @@ app.get('/webhook', async (req, res) => {
         const body = "TITLE: HELLO WORLD, DESCRIPTION: HELLO WORLD for the repo - utkarsh-dixit/speedy"
 
         const llm = new ChatOpenAI({
-            model: "gpt-4",
+            model: "gpt-4o",
         });
 
         const toolset = new LangchainToolSet({

js/examples/langchain/sample.mjs

@@ -24,7 +24,7 @@ async function executeAgent(entityName) {
 
     const prompt = await pull("hwchase17/openai-functions-agent");
     const llm = new ChatOpenAI({
-        model: "gpt-4",
+        model: "gpt-4o",
         apiKey: process.env.OPEN_AI_API_KEY
     });
 

python/examples/image_search/image_search_crewai/main.py

@@ -17,11 +17,6 @@
 # Load environment variables from a .env file
 dotenv.load_dotenv()
 
-api_key = os.getenv("OPENAI_API_KEY", "")
-if api_key == "":
-    api_key = input("Enter OpenAI API Key:")
-    os.environ["OPENAI_API_KEY"] = api_key
-
 # Initialize a ChatOpenAI instance with GPT-4o model
 llm = ChatOpenAI(model="gpt-4o")
 
@@ -70,8 +65,9 @@
     # human_input=True  # Indicates that human input is allowed/required
 )
 
+crew = Crew(agents=[image_search_agent], tasks=[image_search_task])
 # Execute the task and retrieve the result
-result = image_search_task.execute()
+result = crew.kickoff()
 
 # Print the result
 print(result)

python/examples/image_search/image_search_langchain/image_search_frontend.py

@@ -37,7 +37,7 @@ def main():
 
 def search_images(images_path, search_prompt, top_no_of_images):
     # Initialize LLM
-    llm = ChatOpenAI(model="gpt-4")
+    llm = ChatOpenAI(model="gpt-4o")
 
     # Get prompt from LangChain hub
     prompt = hub.pull("hwchase17/openai-functions-agent")

python/examples/image_search/image_search_langchain/main.py

@@ -19,11 +19,6 @@
 # Load environment variables from a .env file (if applicable)
 dotenv.load_dotenv()  # Uncomment if you are using a .env file
 
-api_key = os.getenv("OPENAI_API_KEY", "")
-if api_key == "":
-    api_key = input("Enter OpenAI API Key:")
-    os.environ["OPENAI_API_KEY"] = api_key
-
 
 # Initialize a ChatOpenAI instance with GPT-4o model
 llm = ChatOpenAI(model="gpt-4o")

python/examples/image_search/image_search_langgraph/main.py

@@ -14,19 +14,14 @@
 
 dotenv.load_dotenv()
 
-api_key = os.getenv("OPENAI_API_KEY", "")
-if api_key == "":
-    api_key = input("Enter OpenAI API Key:")
-    os.environ["OPENAI_API_KEY"] = api_key
-
 
 composio_toolset = ComposioToolSet()
 # Retrieve tools from Composio, specifically the EMBEDTOOL app
 tools = composio_toolset.get_tools(apps=[App.EMBEDTOOL])
 tool_executor = ToolExecutor(tools)
 functions = [convert_to_openai_function(t) for t in tools]
 
-model = ChatOpenAI(model="gpt-4", temperature=0, streaming=True)
+model = ChatOpenAI(model="gpt-4o", temperature=0, streaming=True)
 model = model.bind_functions(functions)
 
 

python/examples/image_search/image_search_llamaindex/main.py

@@ -16,12 +16,6 @@
 # Load environment variables from a .env file
 dotenv.load_dotenv()
 
-api_key = os.getenv("OPENAI_API_KEY", "")
-if api_key == "":
-    api_key = input("Enter OpenAI API Key:")
-    os.environ["OPENAI_API_KEY"] = api_key
-
-
 # Initialize a ComposioToolSet with the API key from environment variables
 toolset = ComposioToolSet()
 

python/examples/local_tools/autogen_math.py

@@ -15,7 +15,7 @@
     system_message="Reply TERMINATE when the task is done or when user's content is empty",
     llm_config={
         "config_list": [
-            {"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY"]},
+            {"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]},
         ]
     },
 )

python/examples/miscellaneous/gmail_send_attachment_crew.py

@@ -6,15 +6,15 @@
 
 import dotenv
 from composio_crewai import Action, ComposioToolSet
-from crewai import Agent, Task
+from crewai import Agent, Task, Crew
 from langchain_openai import ChatOpenAI
 
 
 # Load environment variables from .env
 dotenv.load_dotenv()
 
 # Initialize tools.
-openai_client = ChatOpenAI(api_key=os.environ["OPENAI_API_KEY"])
+openai_client = ChatOpenAI(model="gpt-4o")
 composio_toolset = ComposioToolSet()
 
 # Get All the tools
@@ -42,4 +42,6 @@
 )
 
 # Execute task
-task.execute()
+my_crew = Crew(agents=[crewai_agent], tasks=[task])
+result = my_crew.kickoff()
+print(result)

python/examples/pr_agent/pr_agent_crewai/main.py

@@ -44,13 +44,10 @@
 """
 )
 
-api_key = os.getenv("OPENAI_API_KEY", "")
-if api_key == "":
-    api_key = input("Enter OPENAI API KEY:")
-    os.environ["OPENAI_API_KEY"] = api_key
+
 
 # Initialize the language model
-llm = ChatOpenAI(model="gpt-4")
+llm = ChatOpenAI(model="gpt-4o")
 
 # Create CrewAI agent
 code_reviewer = Agent(

python/examples/pr_agent/pr_agent_langchain/main.py

@@ -45,7 +45,7 @@
 
 
 # Initialize the language model
-llm = ChatOpenAI(model="gpt-4")
+llm = ChatOpenAI(model="gpt-4o")
 
 
 prompt = hub.pull("hwchase17/openai-functions-agent")

python/examples/pr_agent/pr_agent_llama_index/main.py

@@ -27,10 +27,7 @@
         Action.SLACKBOT_CHAT_POST_MESSAGE,
     ]
 )
-api_key = os.getenv("OPENAI_API_KEY", "")
-if api_key == "":
-    api_key = input("Enter OpenAI key:")
-    os.environ["OPENAI_API_KEY"] = api_key
+
 # Initialize an OpenAI instance with the GPT-4o model
 llm = OpenAI(model="gpt-4o")
 

python/plugins/autogen/README.md

@@ -29,7 +29,7 @@ from composio_autogen import ComposioToolset, App, Action
 import os
 
 # Configuration for the language model
-llm_config = {"config_list": [{"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY"]}]}
+llm_config = {"config_list": [{"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]}]}
 
 # Initialize the AssistantAgent
 chatbot = AssistantAgent(

python/plugins/autogen/autogen_demo.py

@@ -16,7 +16,7 @@
     system_message="Reply TERMINATE when the task is done or when user's content is empty",
     llm_config={
         "config_list": [
-            {"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY"]},
+            {"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]},
         ]
     },
 )

python/plugins/julep/README.md

@@ -71,7 +71,7 @@ agent = client.agents.create(
     name=name,
     about=about,
     default_settings=default_settings,
-    model="gpt-4",
+    model="gpt-4o",
     tools=composio_tools,
 )
 ```

python/plugins/julep/julep_demo.py

@@ -50,7 +50,7 @@
         name=name,
         about=about,
         default_settings=default_settings,
-        model="gpt-4",
+        model="gpt-4o",
         tools=composio_tools,
     ),
 )

python/plugins/langchain/langchain_demo.py

@@ -20,7 +20,7 @@
 prompt = hub.pull("hwchase17/openai-functions-agent")
 
 # Initialize tools.
-openai_client = ChatOpenAI(api_key=os.environ["OPENAI_API_KEY"])
+openai_client = ChatOpenAI(model="gpt-4o")
 
 
 def main():

python/swe/examples/crewai_agent/agent.py

@@ -10,13 +10,12 @@
 from langchain_openai import ChatOpenAI
 from prompts import BACKSTORY, DESCRIPTION, EXPECTED_OUTPUT, GOAL, ROLE
 
-
 # Load environment variables from .env
 dotenv.load_dotenv()
 
 # Initialize tool.
 openai_client = ChatOpenAI(
-    api_key=os.environ["OPENAI_API_KEY"], model="gpt-4-turbo"  # type: ignore
+    model="gpt-4o"  # type: ignore
 )
 composio_toolset = ComposioToolSet(workspace_config=WorkspaceType.Docker())