Models fixes (#1126)

* Models Frontend Changes

* Models Frontend Changes

* Models Frontend Changes

* Backend Compatibility for New/Existing users on local

* DEV api key requirements

* removing print statements

* removing print statements

* removing print statements

* removing print statements

* backend compatibility

* backend compatibility

* backend compatibility

gui/pages/Content/Agents/AgentCreate.js

@@ -11,7 +11,7 @@ import {
   updateExecution,
   uploadFile,
   getAgentDetails, addAgentRun, fetchModels,
-  getAgentWorkflows
+  getAgentWorkflows, validateOrAddModels
 } from "@/pages/api/DashboardService";
 import {
   formatBytes,
@@ -56,7 +56,7 @@ export default function AgentCreate({
   const [searchValue, setSearchValue] = useState('');
   const [showButton, setShowButton] = useState(false);
   const [showPlaceholder, setShowPlaceholder] = useState(true);
-  const [modelsArray, setModelsArray] = useState([]);
+  const [modelsArray, setModelsArray] = useState(['gpt-4', 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k']);
 
   const constraintsArray = [
     "If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.",
@@ -69,7 +69,7 @@ export default function AgentCreate({
   const [goals, setGoals] = useState(['Describe the agent goals here']);
   const [instructions, setInstructions] = useState(['']);
 
-  const models = ['gpt-4', 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-4-32k', 'google-palm-bison-001', 'replicate-llama13b-v2-chat']
+  const models = ['gpt-4', 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k']
   const [model, setModel] = useState(models[1]);
   const modelRef = useRef(null);
   const [modelDropdown, setModelDropdown] = useState(false);
@@ -494,7 +494,7 @@ export default function AgentCreate({
     return true;
   }
 
-  const handleAddAgent = () => {
+  const handleAddAgent = async () => {
     if (!validateAgentData(true)) {
       return;
     }

superagi/agent/agent_iteration_step_handler.py

@@ -34,7 +34,6 @@
 class AgentIterationStepHandler:
     """ Handles iteration workflow steps in the agent workflow."""
     def __init__(self, session, llm, agent_id: int, agent_execution_id: int, memory=None):
-        print(session, llm, agent_execution_id, agent_id, memory)
         self.session = session
         self.llm = llm
         self.agent_execution_id = agent_execution_id

superagi/agent/agent_tool_step_handler.py

@@ -99,7 +99,6 @@ def _process_input_instruction(self, agent_config, agent_execution_config, step_
         prompt = self._build_tool_input_prompt(step_tool, tool_obj, agent_execution_config)
         logger.info("Prompt: ", prompt)
         agent_feeds = AgentExecutionFeed.fetch_agent_execution_feeds(self.session, self.agent_execution_id)
-        print(".........//////////////..........1")
         messages = AgentLlmMessageBuilder(self.session, self.llm, self.llm.get_model(), self.agent_id, self.agent_execution_id) \
             .build_agent_messages(prompt, agent_feeds, history_enabled=step_tool.history_enabled,
                                   completion_prompt=step_tool.completion_prompt)

superagi/jobs/agent_executor.py

@@ -56,7 +56,6 @@ def execute_next_step(self, agent_execution_id):
                 return
 
             model_config = AgentConfiguration.get_model_api_key(session, agent_execution.agent_id, agent_config["model"])
-            print(model_config)
             model_api_key = model_config['api_key']
             model_llm_source = model_config['provider']
             try:
@@ -72,8 +71,6 @@ def execute_next_step(self, agent_execution_id):
             agent_workflow_step = session.query(AgentWorkflowStep).filter(
                 AgentWorkflowStep.id == agent_execution.current_agent_step_id).first()
             try:
-                print(agent_config["model"])
-                print(model_api_key)
                 if agent_workflow_step.action_type == "TOOL":
                     tool_step_handler = AgentToolStepHandler(session,
                                                              llm=get_model(model=agent_config["model"], api_key=model_api_key, organisation_id=organisation.id)
@@ -107,9 +104,6 @@ def execute_next_step(self, agent_execution_id):
 
     @classmethod
     def get_embedding(cls, model_source, model_api_key):
-        print("&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&")
-        print(model_source)
-        print(model_api_key)
         if "OpenAI" in model_source:
             return OpenAiEmbedding(api_key=model_api_key)
         if "Google" in model_source:

superagi/models/models.py

@@ -2,6 +2,8 @@
 from sqlalchemy.sql import func
 from typing import List, Dict, Union
 from superagi.models.base_model import DBBaseModel
+from superagi.llms.openai import OpenAi
+from superagi.helper.encyption_helper import decrypt_data
 import requests, logging
 
 # marketplace_url = "https://app.superagi.com/api"
@@ -153,6 +155,31 @@ def store_model_details(cls, session, organisation_id, model_name, description,
     def fetch_models(cls, session, organisation_id) -> Union[Dict[str, str], List[Dict[str, Union[str, int]]]]:
         try:
             from superagi.models.models_config import ModelsConfig
+            from superagi.models.configuration import Configuration
+
+            model_provider = session.query(ModelsConfig).filter(ModelsConfig.provider == "OpenAI",
+                                                                ModelsConfig.org_id == organisation_id).first()
+            if model_provider is None:
+                configurations = session.query(Configuration).filter(Configuration.key == 'model_api_key',
+                                                                     Configuration.organisation_id == organisation_id).first()
+
+                if configurations is None:
+                    return {"error": "API Key is Missing"}
+                else:
+                    default_models = {"gpt-3.5-turbo": 4032, "gpt-4": 8092, "gpt-3.5-turbo-16k": 16184}
+                    model_api_key = decrypt_data(configurations.value)
+
+                    model_details = ModelsConfig.store_api_key(session, organisation_id, "OpenAI", model_api_key)
+                    model_provider_id = model_details.get('model_provider_id')
+                    models = OpenAi(api_key=model_api_key).get_models()
+
+                    installed_models = [model[0] for model in session.query(Models.model_name).filter(Models.org_id == organisation_id).all()]
+
+                    for model in models:
+                        if model not in installed_models and model in default_models:
+                            result = cls.store_model_details(session, organisation_id, model, model, '',
+                                                             model_provider_id, default_models[model], 'Custom', '')
+
             models = session.query(Models.id, Models.model_name, Models.description, ModelsConfig.provider).join(
                 ModelsConfig, Models.model_provider_id == ModelsConfig.id).filter(
                 Models.org_id == organisation_id).all()

superagi/models/models_config.py

@@ -76,14 +76,17 @@ def store_api_key(cls, session, organisation_id, model_provider, model_api_key):
                                                                  ModelsConfig.provider == model_provider)).first()
         if existing_entry:
             existing_entry.api_key = encrypt_data(model_api_key)
+            session.commit()
+            result = {'message': 'The API key was successfully updated'}
         else:
             new_entry = ModelsConfig(org_id=organisation_id, provider=model_provider,
                                      api_key=encrypt_data(model_api_key))
             session.add(new_entry)
+            session.commit()
+            session.flush()
+            result = {'message': 'The API key was successfully stored', 'model_provider_id': new_entry.id}
 
-        session.commit()
-
-        return {'message': 'The API key was successfully stored'}
+        return result
 
     @classmethod
     def fetch_api_keys(cls, session, organisation_id):

tests/unit_tests/models/test_models_config.py

@@ -111,4 +111,16 @@ def test_fetch_model_by_id(mock_session):
 
     # Call the method
     model = ModelsConfig.fetch_model_by_id(mock_session, organisation_id, model_provider_id)
+    assert model == {"provider": "some_provider"}
+
+def test_fetch_model_by_id_marketplace(mock_session):
+    # Arrange
+    model_provider_id = 1
+    # Mock model
+    mock_model = MagicMock()
+    mock_model.provider = 'some_provider'
+    mock_session.query.return_value.filter.return_value.first.return_value = mock_model
+
+    # Call the method
+    model = ModelsConfig.fetch_model_by_id_marketplace(mock_session, model_provider_id)
     assert model == {"provider": "some_provider"}