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refactor: update model name from gpt-4o-mini to gpt-5-nano across all files

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Mervin Praison committed 2025-08-08 07:52:37 +01:00
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commit 561c32ddd5
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.github/workflows/coverage.yml
+1 -1
View File
@@ -41,7 +41,7 @@ jobs:
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
.github/workflows/python-package.yml
+1 -1
View File
@@ -29,7 +29,7 @@ jobs:
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
- name: Install dependencies
.github/workflows/test-comprehensive.yml
+1 -1
View File
@@ -59,7 +59,7 @@ jobs:
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
- name: Run Comprehensive Test Suite
run: |
.github/workflows/test-core.yml
+5 -5
View File
@@ -42,13 +42,13 @@ jobs:
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
# Also export to current shell session for immediate availability
export OPENAI_API_KEY="${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}"
export OPENAI_API_BASE="${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}"
export OPENAI_MODEL_NAME="${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}"
export OPENAI_MODEL_NAME="${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}"
export LOGLEVEL=DEBUG
# Verify immediate availability
echo "🔧 Immediate verification in same step:"
@@ -126,7 +126,7 @@ jobs:
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}
OPENAI_API_BASE: ${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}
LOGLEVEL: DEBUG
run: |
echo "🔍 Testing PraisonAI API key usage directly..."
@@ -166,7 +166,7 @@ jobs:
print('\\n🧪 Testing PraisonAIModel with explicit API key (CrewAI method):')
model_with_explicit_key = PraisonAIModel(
model='openai/gpt-4o-mini',
model='openai/gpt-5-nano',
base_url=praisonai.config_list[0].get('base_url'),
api_key=api_key_from_config # This will be a string from praisonai.config_list
)
@@ -251,7 +251,7 @@ jobs:
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}
OPENAI_API_BASE: ${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}
LOGLEVEL: DEBUG
run: |
echo "🧪 Running legacy tests with real API key..."
.github/workflows/test-extended.yml
+1 -1
View File
@@ -42,7 +42,7 @@ jobs:
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
echo "PRAISONAI_TELEMETRY_DISABLED=true" >> $GITHUB_ENV
echo "PRAISONAI_DISABLE_TELEMETRY=true" >> $GITHUB_ENV
.github/workflows/test-frameworks.yml
+1 -1
View File
@@ -56,7 +56,7 @@ jobs:
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
- name: Test ${{ matrix.framework }} Framework
run: |
.github/workflows/unittest.yml
+3 -3
View File
@@ -35,7 +35,7 @@ jobs:
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
@@ -316,8 +316,8 @@ jobs:
try:
from praisonai.inc.models import PraisonAIModel
# Test PraisonAIModel with openai/gpt-4o-mini (from YAML)
model = PraisonAIModel(model='openai/gpt-4o-mini')
# Test PraisonAIModel with openai/gpt-5-nano (from YAML)
model = PraisonAIModel(model='openai/gpt-5-nano')
print('🤖 PraisonAIModel Configuration:')
print(f' model: {model.model}')
examples/cookbooks/Conversational_Chat_Agents/Multi_Agent_Production_System.ipynb
+6 -6
View File
@@ -26,14 +26,14 @@
"\n",
"### ✨ Key Benefits:\n",
"- 🚀 **Scalable & Customizable** – Industry-agnostic design \n",
"- 💰 **Cost-Effective** – Runs on GPT-4o-mini \n",
"- 💰 **Cost-Effective** – Runs on gpt-5-nano \n",
"- 🛠️ **Production-Ready** – Realistic automation framework \n",
"- 🔄 **Complete Pipeline** – End-to-end flow\n",
"\n",
"---\n",
"\n",
"### 🔧 Technologies:\n",
"**PraisonAI** • **OpenAI GPT-4o-mini** • **Python** • **SQLite** \n",
"**PraisonAI** • **OpenAI gpt-5-nano** • **Python** • **SQLite** \n",
"**Multi-Agent Architecture**\n",
"\n",
"---\n",
@@ -100,7 +100,7 @@
"text": [
"📦 Dependencies installed!\n",
"🔄 Using PraisonAI Multi-Agent Framework\n",
"🤖 Powered by OpenAI GPT-4o-mini\n"
"🤖 Powered by OpenAI gpt-5-nano\n"
]
}
],
@@ -116,7 +116,7 @@
"\n",
"print(\"📦 Dependencies installed!\")\n",
"print(\"🔄 Using PraisonAI Multi-Agent Framework\")\n",
"print(\"🤖 Powered by OpenAI GPT-4o-mini\")"
"print(\"🤖 Powered by OpenAI gpt-5-nano\")"
]
},
{
@@ -5102,7 +5102,7 @@
"\n",
"🎊 BLENDER PRODUCTION STUDIO COMPLETE!\n",
"🎬 17-Agent AI System Successfully Executed\n",
"🤖 Powered by PraisonAI + OpenAI GPT-4o-mini\n"
"🤖 Powered by PraisonAI + OpenAI gpt-5-nano\n"
]
}
],
@@ -5149,7 +5149,7 @@
"\n",
"print(\"\\n🎊 BLENDER PRODUCTION STUDIO COMPLETE!\")\n",
"print(\"🎬 17-Agent AI System Successfully Executed\")\n",
"print(\"🤖 Powered by PraisonAI + OpenAI GPT-4o-mini\")"
"print(\"🤖 Powered by PraisonAI + OpenAI gpt-5-nano\")"
]
}
],
examples/cookbooks/Conversational_Chat_Agents/ReAct_agent.ipynb
+1 -1
View File
@@ -182,7 +182,7 @@
" ]\n",
" for turn in range(max_turns):\n",
" response = client.chat.completions.create(\n",
" model=\"gpt-4o-mini\",\n",
" model=\"gpt-5-nano\",\n",
" messages=history,\n",
" max_tokens=500\n",
" )\n",
examples/cookbooks/Conversational_Chat_Agents/Semantic_Social_Network_Agent_System.ipynb
+2 -2
View File
@@ -2642,7 +2642,7 @@
"\n",
"\ud83c\udf8a SEMANTIC NETWORK ANALYSIS COMPLETE!\n",
"\ud83c\udf10 Cross-platform profile discovery and analysis\n",
"\ud83e\udd16 Powered by PraisonAI + OpenAI GPT-4o-mini\n"
"\ud83e\udd16 Powered by PraisonAI + OpenAI gpt-5-nano\n"
]
}
],
@@ -2687,7 +2687,7 @@
"\n",
"print(\"\\n\ud83c\udf8a SEMANTIC NETWORK ANALYSIS COMPLETE!\")\n",
"print(\"\ud83c\udf10 Cross-platform profile discovery and analysis\")\n",
"print(\"\ud83e\udd16 Powered by PraisonAI + OpenAI GPT-4o-mini\")"
"print(\"\ud83e\udd16 Powered by PraisonAI + OpenAI gpt-5-nano\")"
]
},
{
examples/cookbooks/Ecommerce_Shopping_Agents/Ai_Ecommerce_Shopping_Assistant.ipynb
+2 -2
View File
@@ -1262,7 +1262,7 @@
"\n",
"🎊 AI SHOPPING ASSISTANT ACTIVE!\n",
"🛒 Ready to help customers with natural language shopping\n",
"🤖 Powered by PraisonAI + OpenAI GPT-4o-mini\n"
"🤖 Powered by PraisonAI + OpenAI gpt-5-nano\n"
]
}
],
@@ -1305,7 +1305,7 @@
"\n",
"print(\"\\n🎊 AI SHOPPING ASSISTANT ACTIVE!\")\n",
"print(\"🛒 Ready to help customers with natural language shopping\")\n",
"print(\"🤖 Powered by PraisonAI + OpenAI GPT-4o-mini\")"
"print(\"🤖 Powered by PraisonAI + OpenAI gpt-5-nano\")"
]
},
{
examples/cookbooks/Productivity_Workflow_Agents/Hackathon_Agent_Notebook.ipynb
+1 -1
View File
@@ -193,7 +193,7 @@
" goal=\"Evaluate hackathon projects through video demonstrations\",\n",
" backstory=\"\"\"You are an expert hackathon judge. You give fair scores and detailed feedback\n",
" on technical complexity, innovation, presentation, and UX.\"\"\",\n",
" llm=\"gpt-4o-mini\",\n",
" llm=\"gpt-5-nano\",\n",
" self_reflect=False\n",
")"
],
examples/cookbooks/Programming_Code_Analysis_Agents/FunctionAgent_Workflow.ipynb
+1 -1
View File
@@ -65,7 +65,7 @@
"source": [
"from llama_index.llms.openai import OpenAI\n",
"\n",
"llm = OpenAI(model=\"gpt-4o-mini\", api_key=\"Enter your api key here\") # Replace with your OpenAI API key\n"
"llm = OpenAI(model=\"gpt-5-nano\", api_key=\"Enter your api key here\") # Replace with your OpenAI API key\n"
]
},
{
examples/cookbooks/Research_Knowledge_QA_Agents/AI_CourtSimulation.ipynb
+4 -4
View File
@@ -129,7 +129,7 @@
"judge = Agent(\n",
" name=\"Judge\",\n",
" role=\"Preside over court proceedings\",\n",
" llm=\"gpt-4o-mini\",\n",
" llm=\"gpt-5-nano\",\n",
" instructions=[\n",
" \"You are an impartial judge\",\n",
" \"Make fair decisions based on evidence\",\n",
@@ -142,7 +142,7 @@
"prosecutor = Agent(\n",
" name=\"Prosecutor\",\n",
" role=\"Present case against defendant\",\n",
" llm=\"gpt-4o-mini\",\n",
" llm=\"gpt-5-nano\",\n",
" instructions=[\n",
" \"You are a prosecutor seeking conviction\",\n",
" \"Present evidence methodically\",\n",
@@ -155,7 +155,7 @@
"defense = Agent(\n",
" name=\"Defense\",\n",
" role=\"Defend the accused\",\n",
" llm=\"gpt-4o-mini\",\n",
" llm=\"gpt-5-nano\",\n",
" instructions=[\n",
" \"You are a defense attorney\",\n",
" \"Create reasonable doubt\",\n",
@@ -168,7 +168,7 @@
"witness = Agent(\n",
" name=\"Witness\",\n",
" role=\"Provide testimony\",\n",
" llm=\"gpt-4o-mini\",\n",
" llm=\"gpt-5-nano\",\n",
" instructions=[\n",
" \"You are a witness testifying\",\n",
" \"Provide factual testimony\",\n",
examples/cookbooks/Research_Knowledge_QA_Agents/AI_Data_Analysis_Agent.ipynb
+3 -3
View File
@@ -76,7 +76,7 @@
"output_type": "stream",
"text": [
"✅ API key configured!\n",
"✅ Using model: gpt-4o-mini\n"
"✅ Using model: gpt-5-nano\n"
]
}
],
@@ -85,7 +85,7 @@
"openai_key = \"sk-..\"\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = openai_key\n",
"model_choice = \"gpt-4o-mini\"\n",
"model_choice = \"gpt-5-nano\"\n",
"\n",
"print(\"✅ API key configured!\")\n",
"print(f\"✅ Using model: {model_choice}\")"
@@ -336,7 +336,7 @@
"\n",
"temperature: 0.3\n",
"max_tokens: 4000\n",
"model: \"gpt-4o-mini\"\n",
"model: \"gpt-5-nano\"\n",
"\"\"\"\n",
"\n",
"print(\"✅ YAML Prompt configured!\")"
examples/cookbooks/Research_Knowledge_QA_Agents/Ai_Documentation_Processor.ipynb
+1 -1
View File
@@ -8,7 +8,7 @@
"source": [
"# 🤖 Add AI Documentation Processor: Multi-Agent Content Analysis & Code Generation System\n",
"\n",
"This PR adds a comprehensive AI-powered documentation processing system using PraisonAI and OpenAI GPT-4o-mini. Features 3 specialized agents for content analysis, code generation, and example creation, perfect for automated documentation processing and code generation workflows.\n",
"This PR adds a comprehensive AI-powered documentation processing system using PraisonAI and OpenAI gpt-5-nano. Features 3 specialized agents for content analysis, code generation, and example creation, perfect for automated documentation processing and code generation workflows.\n",
"\n",
"**Key Features:** Multi-agent document analysis, automated code generation, usage example creation, content validation, and scalable processing workflows for various document formats."
]
examples/cookbooks/SocialMedia_Content_Agents/Ai_Meme_Creator_Agent.ipynb
+1 -1
View File
@@ -491,7 +491,7 @@
"\n",
"temperature: 0.7\n",
"max_tokens: 3000\n",
"model: \"gpt-4o-mini\"\n",
"model: \"gpt-5-nano\"\n",
"\"\"\"\n",
"\n",
"print(\"✅ YAML Prompt configured!\")"
examples/cookbooks/SocialMedia_Content_Agents/Joke_Agent.ipynb
+1 -1
View File
@@ -120,7 +120,7 @@
"\n",
" def run(self, message: str):\n",
" response = client.chat.completions.create(\n",
" model=\"gpt-4o-mini\",\n",
" model=\"gpt-5-nano\",\n",
" messages=[\n",
" {\"role\": \"system\", \"content\": self.prompt},\n",
" {\"role\": \"user\", \"content\": message}\n",
examples/cookbooks/yaml/article_generation_agents.ipynb
+1 -1
View File
@@ -585,7 +585,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/auto_email_responder_agents.ipynb
+1 -1
View File
@@ -1090,7 +1090,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/book_writing_agents.ipynb
+1 -1
View File
@@ -2077,7 +2077,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/business_product_launch_agents.ipynb
+1 -1
View File
@@ -151,7 +151,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/cli_operation_agents.ipynb
+1 -1
View File
@@ -533,7 +533,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/comprehensive_research_report_agents.ipynb
+1 -1
View File
@@ -235,7 +235,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/email_workflow_management_agents.ipynb
+1 -1
View File
@@ -1250,7 +1250,7 @@
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"TAVILY_API_KEY\"] = userdata.get('TAVILY_API_KEY') or \"ENTER TAVILY_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/game_development_agents.ipynb
+1 -1
View File
@@ -1559,7 +1559,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/instagram_post_agents.ipynb
+1 -1
View File
@@ -2159,7 +2159,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/job_hunt_agents.ipynb
+1 -1
View File
@@ -698,7 +698,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/job_profile_matching_agents.ipynb
+1 -1
View File
@@ -592,7 +592,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/language_translator_agents.ipynb
+1 -1
View File
@@ -572,7 +572,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/markdown_validator_agents.ipynb
+1 -1
View File
@@ -580,7 +580,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/meeting_prep_and_strategy_agents.ipynb
+1 -1
View File
@@ -1075,7 +1075,7 @@
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"EXA_API_KEY\"] = userdata.get('EXA_API_KEY') or \"ENTER EXA_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/meeting_prep_using_slack_and_trello_agents.ipynb
+1 -1
View File
@@ -667,7 +667,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/memory_management_and_knowledge_retreival_agents.ipynb
+1 -1
View File
@@ -1947,7 +1947,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/model_fee_retreival_agents.ipynb
+1 -1
View File
@@ -666,7 +666,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/news_retreival_rag_agents.ipynb
+1 -1
View File
@@ -475,7 +475,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/recruitment_flow_agents.ipynb
+1 -1
View File
@@ -2130,7 +2130,7 @@
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"SERPER_API_KEY\"] = userdata.get('SERPER_API_KEY') or \"ENTER SERPER_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/reddit_search_analysis_agents.ipynb
+1 -1
View File
@@ -635,7 +635,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/research_report_generation_agents.ipynb
+1 -1
View File
@@ -564,7 +564,7 @@
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"TAVILY_API_KEY\"] = userdata.get('TAVILY_API_KEY') or \"ENTER TAVILY_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/research_through_azure_instance_agents.ipynb
+1 -1
View File
@@ -564,7 +564,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/screenplay_writer_agents.ipynb
+1 -1
View File
@@ -614,7 +614,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/secondary_market_research_agents.ipynb
+1 -1
View File
@@ -66,7 +66,7 @@
"\n",
"# Set up OpenAI API key (add to Google Colab secrets)\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\""
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\""
]
},
{
examples/cookbooks/yaml/secondary_market_research_agents.yaml
+6 -6
View File
@@ -22,7 +22,7 @@ roles:
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tools:
- "InternetSearchTool"
@@ -76,7 +76,7 @@ roles:
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tools:
- "InternetSearchTool"
@@ -130,7 +130,7 @@ roles:
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tools:
- "InternetSearchTool"
@@ -185,7 +185,7 @@ roles:
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.4
tools:
- "InternetSearchTool"
@@ -239,7 +239,7 @@ roles:
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tools:
- "InternetSearchTool"
@@ -299,7 +299,7 @@ roles:
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tasks:
report_synthesis:
examples/cookbooks/yaml/shakespearean_tweets_generation_agents.ipynb
+1 -1
View File
@@ -462,7 +462,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/stock_analysis_agents.ipynb
+1 -1
View File
@@ -380,7 +380,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/story_book_author_agents.ipynb
+1 -1
View File
@@ -540,7 +540,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/surprise_trip_planner_and_itinerary_agents.ipynb
+1 -1
View File
@@ -2639,7 +2639,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/trip_planner_agents.ipynb
+1 -1
View File
@@ -1835,7 +1835,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/wikipedia_search_analysis_agents.ipynb
+1 -1
View File
@@ -623,7 +623,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/you_search_analysis_agents.ipynb
+1 -1
View File
@@ -635,7 +635,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/cookbooks/yaml/youtube_search_analysis_agents.ipynb
+1 -1
View File
@@ -582,7 +582,7 @@
"\n",
"# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below\n",
"os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY') or \"ENTER OPENAI_API_KEY HERE\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-4o-mini\"\n",
"os.environ[\"OPENAI_MODEL_NAME\"] = \"gpt-5-nano\"\n",
"\n",
"# Run PraisonAI\n",
"result = praisonai.run()\n",
examples/python/agents/MULTI_PROVIDER_README.md
+6 -6
View File
@@ -10,7 +10,7 @@ PraisonAI now supports intelligent multi-provider and multi-model capabilities,
- Supports fallback mechanisms for reliability
### 2. **Cost Optimization**
- Routes simple tasks to cheaper models (e.g., GPT-4o-mini, Gemini Flash)
- Routes simple tasks to cheaper models (e.g., gpt-5-nano, Gemini Flash)
- Reserves expensive models for complex tasks
- Tracks usage and provides cost estimates
@@ -46,7 +46,7 @@ agent = RouterAgent(
name="Smart Assistant",
role="Adaptive AI Assistant",
goal="Complete tasks using the most appropriate model",
models=["gpt-4o-mini", "gpt-4o", "claude-3-5-sonnet-20241022"],
models=["gpt-5-nano", "gpt-4o", "claude-3-5-sonnet-20241022"],
routing_strategy="auto" # Automatic model selection
)
@@ -90,7 +90,7 @@ analyzer = RouterAgent(
goal="Analyze data efficiently",
models={
"gemini/gemini-1.5-flash": {},
"gpt-4o-mini": {},
"gpt-5-nano": {},
"claude-3-haiku-20240307": {}
},
model_router=router,
@@ -130,7 +130,7 @@ The system includes pre-configured profiles for popular models:
| Model | Provider | Best For | Cost/1k tokens |
|-------|----------|----------|----------------|
| gpt-4o-mini | OpenAI | Simple tasks, speed | $0.00075 |
| gpt-5-nano | OpenAI | Simple tasks, speed | $0.00075 |
| gemini-1.5-flash | Google | Cost-effective, multimodal | $0.000125 |
| claude-3-haiku | Anthropic | Fast responses | $0.0008 |
| gpt-4o | OpenAI | General purpose | $0.0075 |
@@ -160,7 +160,7 @@ print(report)
'agent_name': 'Smart Assistant',
'routing_strategy': 'auto',
'model_usage': {
'gpt-4o-mini': {'calls': 5, 'tokens': 1500, 'cost': 0.0011},
'gpt-5-nano': {'calls': 5, 'tokens': 1500, 'cost': 0.0011},
'gpt-4o': {'calls': 2, 'tokens': 3000, 'cost': 0.0225}
},
'total_cost_estimate': 0.0236,
@@ -207,7 +207,7 @@ for i, agent in enumerate(auto.agents):
name=agent.name,
role=agent.role,
goal=agent.goal,
models=["gpt-4o-mini", "gpt-4o", "claude-3-5-sonnet"],
models=["gpt-5-nano", "gpt-4o", "claude-3-5-sonnet"],
routing_strategy="auto"
)
examples/python/agents/context-agent.py
+3 -3
View File
@@ -31,7 +31,7 @@ def demonstrate_basic_context_generation():
# Create a ContextAgent using the factory function
context_agent = create_context_agent(
llm="gpt-4o-mini",
llm="gpt-5-nano",
name="Basic Context Engineer",
verbose=True
)
@@ -133,7 +133,7 @@ def demonstrate_context_agent_as_tool():
print("=" * 60)
# Create ContextAgent
context_agent = create_context_agent(llm="gpt-4o-mini")
context_agent = create_context_agent(llm="gpt-5-nano")
# Example scenario: Product planning workflow
project_path = str(project_root)
@@ -186,7 +186,7 @@ def show_context_engineering_benefits():
# Context Engineering approach
print("\n✅ Context Engineering Approach:")
context_agent = create_context_agent(llm="gpt-4o-mini")
context_agent = create_context_agent(llm="gpt-5-nano")
# Generate comprehensive context
analysis = context_agent.analyze_codebase_patterns(str(project_root))
examples/python/agents/image-agent.py
+1 -1
View File
@@ -13,7 +13,7 @@ image_agent = Agent(
goal="Analyze images and videos to extract meaningful information",
backstory="""You are an expert in computer vision and image analysis.
You excel at describing images, detecting objects, and understanding visual content.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
self_reflect=False
)
examples/python/agents/image-to-text-agent.py
+1 -1
View File
@@ -13,7 +13,7 @@ image_agent = Agent(
goal="Analyze images and videos to extract meaningful information",
backstory="""You are an expert in computer vision and image analysis.
You excel at describing images, detecting objects, and understanding visual content.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
self_reflect=False
)
examples/python/agents/multi-provider-agent.py
+4 -4
View File
@@ -21,7 +21,7 @@ def example_auto_routing():
role="Adaptive Research Assistant",
goal="Research topics using the most appropriate AI model",
backstory="I analyze task complexity and route to the best model",
models=["gpt-4o-mini", "gpt-4o", "claude-3-5-sonnet-20241022"],
models=["gpt-5-nano", "gpt-4o", "claude-3-5-sonnet-20241022"],
routing_strategy="auto", # Automatic model selection
verbose=True
)
@@ -81,7 +81,7 @@ def example_cost_optimized_workflow():
goal="Analyze data efficiently while minimizing costs",
models={
"gemini/gemini-1.5-flash": {},
"gpt-4o-mini": {},
"gpt-5-nano": {},
"deepseek-chat": {}
},
model_router=cost_router,
@@ -144,7 +144,7 @@ def example_auto_agents_multi_provider():
auto_agents = AutoAgents(
instructions="Create a market research report on electric vehicles. Include data analysis, competitor analysis, and future projections.",
max_agents=3,
llm="gpt-4o-mini", # Default model for agent generation
llm="gpt-5-nano", # Default model for agent generation
verbose=True
)
@@ -158,7 +158,7 @@ def example_auto_agents_multi_provider():
goal=agent.goal,
backstory=agent.backstory,
tools=agent.tools,
models=["gpt-4o-mini", "gemini/gemini-1.5-flash", "claude-3-haiku-20240307", "gpt-4o"],
models=["gpt-5-nano", "gemini/gemini-1.5-flash", "claude-3-haiku-20240307", "gpt-4o"],
routing_strategy="auto",
verbose=True
)
examples/python/agents/router-agent-cost-optimization.py
+2 -2
View File
@@ -18,7 +18,7 @@ from praisonaiagents.tools import duckduckgo
# Define model options with cost considerations
# Using different models for different complexity levels
cheap_model = "gpt-4o-mini" # For simple tasks
cheap_model = "gpt-5-nano" # For simple tasks
balanced_model = "gpt-4o" # For moderate complexity
premium_model = "claude-3-5-sonnet-20241022" # For complex tasks
@@ -76,7 +76,7 @@ print("\n" + "="*80)
print("COST OPTIMIZATION ROUTER DEMONSTRATION COMPLETED")
print("="*80)
print("The RouterAgent automatically selected appropriate models based on task complexity:")
print("- Simple factual questions → Cheaper model (gpt-4o-mini)")
print("- Simple factual questions → Cheaper model (gpt-5-nano)")
print("- Moderate analysis tasks → Balanced model (gpt-4o)")
print("- Complex strategic analysis → Premium model (claude-3-5-sonnet)")
print("- This approach optimizes costs while maintaining quality for each task type")
examples/python/agents/video-agent.py
+1 -1
View File
@@ -7,7 +7,7 @@ video_agent = Agent(
goal="Analyze images and videos to extract meaningful information",
backstory="""You are an expert in computer vision and image analysis.
You excel at describing images, detecting objects, and understanding visual content.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
self_reflect=False
)
examples/python/api/mcp-sse.py
+1 -1
View File
@@ -2,7 +2,7 @@ from praisonaiagents import Agent, MCP
qa_agent = Agent(
instructions="""You are a Question Answering Agent.""",
llm="openai/gpt-4o-mini",
llm="openai/gpt-5-nano",
tools=MCP("http://localhost:8080/agents/sse")
)
examples/python/api/multi-agent-api.py
+3 -3
View File
@@ -2,17 +2,17 @@ from praisonaiagents import Agent
weather_agent = Agent(
instructions="""You are a weather agent that can provide weather information for a given city.""",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
stock_agent = Agent(
instructions="""You are a stock market agent that can provide information about stock prices and market trends.""",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
travel_agent = Agent(
instructions="""You are a travel agent that can provide recommendations for destinations, hotels, and activities.""",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
weather_agent.launch(path="/weather", port=3030)
examples/python/api/simple-api-mcp.py
+1 -1
View File
@@ -2,7 +2,7 @@ from praisonaiagents import Agent, MCP
search_agent = Agent(
instructions="""You are a weather agent that can provide weather information for a given city.""",
llm="openai/gpt-4o-mini",
llm="openai/gpt-5-nano",
tools=MCP("http://localhost:8080/sse")
)
search_agent.launch(path="/weather", port=3030)
examples/python/api/simple-api.py
+1 -1
View File
@@ -1,4 +1,4 @@
from praisonaiagents import Agent
agent = Agent(instructions="""You are a helpful assistant.""", llm="gpt-4o-mini")
agent = Agent(instructions="""You are a helpful assistant.""", llm="gpt-5-nano")
agent.launch(path="/ask", port=3030)
examples/python/camera/camera-basic.py
+1 -1
View File
@@ -28,7 +28,7 @@ def capture_and_analyze():
role="Camera Feed Analyzer",
goal="Analyze camera captures in real-time",
backstory="Expert in real-time visual analysis with computer vision skills",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Initialize camera (0 for default camera)
examples/python/camera/camera-continuous.py
+1 -1
View File
@@ -42,7 +42,7 @@ class ContinuousCameraMonitor:
role="Security Camera Analyst",
goal="Monitor camera feeds for activities and security events",
backstory="Expert security analyst with computer vision skills specialized in real-time monitoring",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
def capture_frame(self, cap):
examples/python/camera/camera-multi-agent.py
+3 -3
View File
@@ -57,7 +57,7 @@ def analyze_with_multiple_agents():
role="Security Specialist",
goal="Identify security threats and suspicious activities",
backstory="Expert security analyst with years of experience in surveillance and threat detection",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
object_detector = Agent(
@@ -65,7 +65,7 @@ def analyze_with_multiple_agents():
role="Object Recognition Specialist",
goal="Identify and catalog all objects in the scene",
backstory="Computer vision expert specializing in object detection and classification",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
scene_analyst = Agent(
@@ -73,7 +73,7 @@ def analyze_with_multiple_agents():
role="Scene Understanding Expert",
goal="Provide comprehensive scene analysis and context",
backstory="Environmental analyst expert in understanding spatial relationships and scene context",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Create specialized tasks
examples/python/camera/camera-video-analysis.py
+1 -1
View File
@@ -39,7 +39,7 @@ class CameraVideoAnalyzer:
role="Video Content Analyzer",
goal="Analyze video content for activities, objects, and events",
backstory="Expert in video analysis and temporal event detection with computer vision expertise",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
def record_video_segment(self, duration_seconds=10):
examples/python/concepts/context-engineering-workflow.py
+3 -3
View File
@@ -34,7 +34,7 @@ class ContextEngineeringWorkflow:
to achieve higher success rates in AI-driven development tasks.
"""
def __init__(self, project_path: str, llm: str = "gpt-4o-mini"):
def __init__(self, project_path: str, llm: str = "gpt-5-nano"):
self.project_path = project_path
self.llm = llm
self.context_data = {}
@@ -382,7 +382,7 @@ def run_example_workflow():
project_path = str(project_root)
workflow = ContextEngineeringWorkflow(
project_path=project_path,
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Example feature request
@@ -446,7 +446,7 @@ if __name__ == "__main__":
print("(Note: Full execution requires complete environment setup)")
project_path = str(project_root)
workflow = ContextEngineeringWorkflow(project_path, "gpt-4o-mini")
workflow = ContextEngineeringWorkflow(project_path, "gpt-5-nano")
print(f"\n✅ Workflow Setup Complete:")
print(f" • Project path: {project_path}")
examples/python/concepts/csv-processing-agents.py
+5 -5
View File
@@ -68,7 +68,7 @@ def method_1_simple_loop():
goal="Process each task from the CSV file efficiently",
backstory="Expert at handling repetitive tasks from CSV data",
instructions="Process each task thoroughly and provide detailed output",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Create a loop task that will automatically process each CSV row
@@ -127,7 +127,7 @@ def method_2_manual_csv():
4. Create a summary of the processing results
5. Save results to a new CSV file if needed
""",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Create a task for manual CSV processing
@@ -187,7 +187,7 @@ def method_3_url_processing():
4. Create a detailed analysis report
5. Save results with analysis data
""",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Create the URL processing task
@@ -264,7 +264,7 @@ def method_4_advanced_processing():
4. Create separate files for valid and invalid data
5. Provide detailed validation reports
""",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Create a processing agent
@@ -281,7 +281,7 @@ def method_4_advanced_processing():
3. Generate comprehensive results
4. Create detailed output reports
""",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Create validation task
examples/python/concepts/knowledge-reranker-example.py
+1 -1
View File
@@ -140,7 +140,7 @@ def main():
instructions="You are an AI research assistant. Use your knowledge base to answer questions about artificial intelligence topics.",
knowledge=sample_documents, # Will use default knowledge config
knowledge_config=rerank_config, # Use reranking config
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
print("7. Agent with reranking knowledge:")
examples/python/concepts/rag-agents.py
+1 -1
View File
@@ -16,7 +16,7 @@ rag_agent = Agent(
name="RAG Agent",
role="Information Specialist",
goal="Retrieve knowledge efficiently",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Define a task for the agent
examples/python/concepts/repetitive-agents.py
+1 -1
View File
@@ -2,7 +2,7 @@ from praisonaiagents import Agent, Task, PraisonAIAgents
agent = Agent(
instructions="You are a loop agent that creating a loop of tasks.",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
task = Task(
examples/python/concepts/self-reflection-optimization-patterns.py
+1 -1
View File
@@ -20,7 +20,7 @@ reflection_agent = Agent(
self_reflect=True,
min_reflect=2,
max_reflect=4,
reflect_llm="gpt-4o-mini",
reflect_llm="gpt-5-nano",
verbose=True
)
examples/python/concepts/simple-csv-url-processor.py
+1 -1
View File
@@ -46,7 +46,7 @@ def main():
goal="Analyze each URL from the CSV list",
backstory="Expert at analyzing websites and URLs",
instructions="Analyze each URL and provide insights about the website",
llm="gpt-4o-mini" # You can change this to any supported model
llm="gpt-5-nano" # You can change this to any supported model
)
# Step 3: Create a task that will loop through the CSV
examples/python/custom_tools/example_latency_tracking.py
+5 -5
View File
@@ -27,7 +27,7 @@ def example_with_tool():
role="Information Researcher",
goal="Research and provide information",
tools=[latency_tracking_tool], # Add our custom tool
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Start tracking manually
@@ -60,7 +60,7 @@ def example_with_wrappers():
name="Analyst",
role="Data Analyst",
goal="Analyze data and provide insights",
llm="gpt-4o-mini",
llm="gpt-5-nano",
request_id="request_2" # Unique request ID
)
@@ -83,7 +83,7 @@ def example_with_context_manager():
name="Calculator",
role="Math Expert",
goal="Solve mathematical problems",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
request_id = "request_3"
@@ -126,7 +126,7 @@ def example_mcp_tracking():
name="Assistant",
role="MCP Assistant",
goal="Handle MCP requests",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
plan = agent.chat("Plan: Search for Python documentation")
@@ -166,7 +166,7 @@ def example_concurrent_tracking():
name=f"Agent_{i}",
role="Concurrent Worker",
goal="Process requests concurrently",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
with tracker.track("processing", request_id):
examples/python/custom_tools/mcp_server_latency_example.py
+1 -1
View File
@@ -56,7 +56,7 @@ def create_mcp_agent_with_tracking(request_id: str = "mcp_request"):
name="MCPAssistant",
role="MCP Request Handler",
goal="Handle MCP requests with latency tracking",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
return agent
examples/python/custom_tools/minimal_latency_example.py
+1 -1
View File
@@ -23,7 +23,7 @@ def handle_mcp_request(query: str, request_id: str = "mcp_1"):
name="Assistant",
role="MCP Handler",
goal="Process requests",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
plan = f"I will search for information about {query}"
time.sleep(0.1) # Simulate planning time
examples/python/data/cot-agents.py
+4 -4
View File
@@ -29,7 +29,7 @@ qa_generator = Agent(
role="Question Creator",
goal="Create challenging math and logic questions",
backstory="Expert in educational content creation",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=[write_csv, count_questions]
)
@@ -38,7 +38,7 @@ total_questions_evaluator = Agent(
role="Total Questions Evaluator",
goal="Evaluate the total number of questions in qa_pairs.csv file",
backstory="Expert in evaluating the total number of questions in a file",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=[count_questions],
verbose=False
)
@@ -49,7 +49,7 @@ cot_generator = Agent(
goal="Generate and manage chain of thought solutions for Q&A pairs",
backstory="Expert in breaking down problems and generating detailed solution steps",
tools=[cot_save],
llm="gpt-4o-mini",
llm="gpt-5-nano",
verbose=False
)
@@ -59,7 +59,7 @@ upload_to_huggingface = Agent(
goal="Upload the generated chain of thought solutions to a Huggingface dataset",
backstory="Expert in saving data to Huggingface",
tools=[cot_upload_to_huggingface],
llm="gpt-4o-mini",
llm="gpt-5-nano",
verbose=False
)
examples/python/general/code_agents_example.py
+2 -2
View File
@@ -23,13 +23,13 @@ def code_interpreter(code: str):
code_agent = Agent(
name="code_agent",
llm="gpt-4o-mini",
llm="gpt-5-nano",
backstory="Expert in writing Python scripts",
self_reflect=False
)
execution_agent = Agent(
name="execution_agent",
llm="gpt-4o-mini",
llm="gpt-5-nano",
backstory="Expert in executing Python scripts",
self_reflect=False,
tools=[code_interpreter]
examples/python/general/memory_example.py
+2 -2
View File
@@ -33,14 +33,14 @@ def main():
role="Research Analyst",
goal="Research and document key information about topics",
backstory="Expert at analyzing and storing information in memory",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
retriever = Agent(
role="Information Retriever",
goal="Retrieve and verify stored information from memory",
backstory="Specialist in searching and validating information from memory",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Task 1: Process the facts
examples/python/general/memory_simple.py
+3 -3
View File
@@ -9,19 +9,19 @@ fact3 = "The year the first Josinga was released is 2007"
fact_agent = Agent(
name="Fact Agent",
instructions="You are a fact agent, you store and retrieve facts in memory",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
research_agent = Agent(
name="Research Agent",
instructions="You are a research analyst, you research and document key points about topics",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
blog_agent = Agent(
name="Blog Agent",
instructions="You are a blog writer, you write a blog post about the research",
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
fact_task = Task(
examples/python/general/multimodal.py
+1 -1
View File
@@ -7,7 +7,7 @@ vision_agent = Agent(
goal="Analyze images and videos to extract meaningful information",
backstory="""You are an expert in computer vision and image analysis.
You excel at describing images, detecting objects, and understanding visual content.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
self_reflect=False
)
examples/python/general/structured_agents_example.py
+2 -2
View File
@@ -13,7 +13,7 @@ researcher = Agent(
goal="Analyze and structure information about AI developments",
backstory="Expert analyst specializing in AI technology trends",
verbose=True,
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=[Tools.internet_search],
self_reflect=False
)
@@ -25,7 +25,7 @@ analyst = Agent(
goal="Structure and analyze research findings",
backstory="Senior data analyst with expertise in pattern recognition",
verbose=True,
llm="gpt-4o-mini",
llm="gpt-5-nano",
self_reflect=False
)
examples/python/general/structured_response_example.py
+1 -1
View File
@@ -35,7 +35,7 @@ def get_structured_analysis(query: str, verbose: bool = True) -> AnalysisReport:
verbose=verbose,
self_reflect=True, # Enable self-reflection for better quality
markdown=True,
llm="gpt-4o-mini"
llm="gpt-5-nano"
)
# Create the analysis prompt
examples/python/input/advanced_dynamic_input.py
+1 -1
View File
@@ -16,7 +16,7 @@ class DynamicAgentSystem:
def __init__(self):
self.user_preferences = {}
self.llm_config = {
"model": os.getenv("LLM_MODEL", "gpt-4o-mini"),
"model": os.getenv("LLM_MODEL", "gpt-5-nano"),
"temperature": 0.7
}
examples/python/input/environment_variable_input.py
+1 -1
View File
@@ -13,7 +13,7 @@ default_topic = os.getenv("RESEARCH_TOPIC", "AI trends")
user_topic = input(f"Topic to research [{default_topic}]: ") or default_topic
# Get other configuration from environment
llm_model = os.getenv("LLM_MODEL", "gpt-4o-mini")
llm_model = os.getenv("LLM_MODEL", "gpt-5-nano")
temperature = float(os.getenv("LLM_TEMPERATURE", "0.7"))
max_retries = int(os.getenv("MAX_RETRIES", "3"))
examples/python/input/streamlit_ui_input.py
+1 -1
View File
@@ -30,7 +30,7 @@ with st.sidebar:
# Model selection
model = st.selectbox(
"Select Model",
["gpt-4o-mini", "gpt-4o", "gpt-3.5-turbo", "claude-3-opus"],
["gpt-5-nano", "gpt-4o", "gpt-3.5-turbo", "claude-3-opus"],
index=0
)
examples/python/mcp/airbnb-mcp.py
+1 -1
View File
@@ -2,7 +2,7 @@ from praisonaiagents import Agent, MCP
search_agent = Agent(
instructions="""You help book apartments on Airbnb.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt")
)
examples/python/mcp/aws-kb-retrieval-mcp.py
+1 -1
View File
@@ -10,7 +10,7 @@ aws_region = os.getenv("AWS_REGION")
aws_kb_agent = Agent(
instructions="""You are a helpful assistant that can interact with AWS Knowledge Base.
Use the available tools when relevant to retrieve and process AWS information.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("npx -y @modelcontextprotocol/server-aws-kb-retrieval",
env={
"AWS_ACCESS_KEY_ID": aws_access_key,
examples/python/mcp/bravesearch-mcp.py
+1 -1
View File
@@ -8,7 +8,7 @@ brave_api_key = os.getenv("BRAVE_API_KEY")
search_agent = Agent(
instructions="""You are a helpful assistant that can search the web for information.
Use the available tools when relevant to answer user questions.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("npx -y @modelcontextprotocol/server-brave-search", env={"BRAVE_API_KEY": brave_api_key})
)
examples/python/mcp/custom-python-client.py
+1 -1
View File
@@ -3,7 +3,7 @@ from praisonaiagents import Agent, MCP
agent = Agent(
instructions="""You are a helpful assistant that can check stock prices and perform other tasks.
Use the available tools when relevant to answer user questions.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools = MCP("/Users/praison/miniconda3/envs/mcp/bin/python /Users/praison/stockprice/app.py")
)
examples/python/mcp/databutton-mcp.py
+1 -1
View File
@@ -8,7 +8,7 @@ databutton_api_key = os.getenv("DATABUTTON_API_KEY")
databutton_agent = Agent(
instructions="""You are a helpful assistant that can interact with Databutton.
Use the available tools when relevant to answer user questions.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("uvx databutton-app-mcp@latest", env={"DATABUTTON_API_KEY": databutton_api_key})
)
examples/python/mcp/everart-mcp.py
+1 -1
View File
@@ -8,7 +8,7 @@ everart_api_key = os.getenv("EVERART_API_KEY")
everart_agent = Agent(
instructions="""You are a helpful assistant that can interact with Everart.
Use the available tools when relevant to generate and manage art.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("npx -y @modelcontextprotocol/server-everart",
env={"EVERART_API_KEY": everart_api_key})
)
examples/python/mcp/fetch-mcp.py
+1 -1
View File
@@ -6,7 +6,7 @@ import os
fetch_agent = Agent(
instructions="""You are a helpful assistant that can fetch and process web content.
Use the available tools when relevant to retrieve and convert web pages to markdown.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("python -m mcp_server_fetch")
)
examples/python/mcp/filesystem-mcp.py
+1 -1
View File
@@ -11,7 +11,7 @@ allowed_dirs = [
filesystem_agent = Agent(
instructions="""You are a helpful assistant that can interact with the filesystem.
Use the available tools when relevant to manage files and directories.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("npx -y @modelcontextprotocol/server-filesystem", args=allowed_dirs)
)
examples/python/mcp/gdrive-mcp.py
+1 -1
View File
@@ -8,7 +8,7 @@ gdrive_credentials = os.getenv("GDRIVE_CREDENTIALS_PATH", "servers/gcp-oauth.key
gdrive_agent = Agent(
instructions="""You are a helpful assistant that can interact with Google Drive.
Use the available tools when relevant to manage files and folders.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("npx -y @modelcontextprotocol/server-gdrive",
env={"GDRIVE_CREDENTIALS_PATH": gdrive_credentials})
)
examples/python/mcp/git-mcp.py
+1 -1
View File
@@ -11,7 +11,7 @@ git_token = os.getenv("GIT_TOKEN") # For private repos
git_agent = Agent(
instructions="""You are a helpful assistant that can perform Git operations.
Use the available tools when relevant to manage repositories, commits, and branches.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("python -m mcp_server_git",
env={
"GIT_USERNAME": git_username,
examples/python/mcp/github-mcp.py
+1 -1
View File
@@ -8,7 +8,7 @@ github_token = os.getenv("GITHUB_PERSONAL_ACCESS_TOKEN")
github_agent = Agent(
instructions="""You are a helpful assistant that can interact with GitHub.
Use the available tools when relevant to answer user questions.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("npx -y @modelcontextprotocol/server-github", env={"GITHUB_PERSONAL_ACCESS_TOKEN": github_token})
)
examples/python/mcp/gitlab-mcp.py
+1 -1
View File
@@ -9,7 +9,7 @@ gitlab_api_url = os.getenv("GITLAB_API_URL", "https://gitlab.com/api/v4")
gitlab_agent = Agent(
instructions="""You are a helpful assistant that can interact with GitLab.
Use the available tools when relevant to answer user questions.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("npx -y @modelcontextprotocol/server-gitlab",
env={
"GITLAB_PERSONAL_ACCESS_TOKEN": gitlab_token,
examples/python/mcp/google-maps-mcp.py
+1 -1
View File
@@ -8,7 +8,7 @@ maps_api_key = os.getenv("GOOGLE_MAPS_API_KEY")
maps_agent = Agent(
instructions="""You are a helpful assistant that can interact with Google Maps.
Use the available tools when relevant to handle location-based queries.""",
llm="gpt-4o-mini",
llm="gpt-5-nano",
tools=MCP("npx -y @modelcontextprotocol/server-google-maps",
env={"GOOGLE_MAPS_API_KEY": maps_api_key})
)
examples/python/mcp/mcp-sse-weather.py
+1 -1
View File
@@ -2,7 +2,7 @@ from praisonaiagents import Agent, MCP
search_agent = Agent(
instructions="""You are a weather agent that can provide weather information for a given city.""",
llm="openai/gpt-4o-mini",
llm="openai/gpt-5-nano",
tools=MCP("http://localhost:8080/sse")
)
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