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Author SHA1 Message Date
Mervin Praison 35df78874d chore: update PraisonAI and related package versions to 2.2.44 and 0.0.117
- Updated PraisonAI version in Dockerfiles and README to 2.2.44
- Updated version in pyproject.toml and uv.lock for PraisonAI and PraisonAI agents to 0.0.117
- Adjusted deployment script to reflect the new PraisonAI version
2025-07-10 21:02:01 +01:00
Mervin Praison 4abe80a563 Merge pull request #786 from Dhivya-Bharathy/grok4-intelligent-agents-examples
Add grok4_intelligent_agents Folder to Exa Tool with 5 Agent scripts
2025-07-10 21:00:03 +01:00
Mervin Praison 95c15f52fc Merge pull request #785 from MervinPraison/claude/issue-784-20250710_065335
fix: remove OPENAI_API_KEY requirement for non-OpenAI providers
2025-07-10 20:58:54 +01:00
claude[bot]andMervin Praison 0e2a753cc3 fix: add null safety checks for OpenAI client usage
- Add null check in self-reflection to prevent crash for non-OpenAI providers
- Add null checks in async chat methods before accessing OpenAI client
- Add graceful fallback for self-reflection with custom LLMs
- Add clear error message in AutoAgents explaining it requires OpenAI API
- Ensure non-OpenAI providers can use Agent class without errors

Co-authored-by: Mervin Praison <[email protected]>
2025-07-10 18:05:28 +00:00
claude[bot]andMervin Praison 660260c6e6 fix: make OpenAI client initialization lazy for non-OpenAI providers
- Convert unconditional OpenAI client init to lazy property
- Add null safety checks in critical methods
- Provide fallback implementation for message building
- Fix test script by removing non-existent attribute access

This allows using providers like xai/grok-4 without OPENAI_API_KEY

Co-authored-by: Mervin Praison <[email protected]>
2025-07-10 13:37:28 +00:00
devops-vestradata f49b5c368c Add grok4_intelligent_agents with 5 agent scripts 2025-07-10 14:53:31 +05:30
claude[bot]andMervin Praison 39f0c40dcc fix: remove client imports from main.py to fix ImportError
- Remove client from imports in agents/agents.py (not used)
- Remove client from imports in autoagents.py and use get_openai_client() instead
- Remove client from imports in process.py and create local OpenAI() instance
- This fixes the ImportError that was blocking tests after removing global client from main.py

Co-authored-by: Mervin Praison <[email protected]>
2025-07-10 07:22:42 +00:00
Mervin Praison 27b10ff3ea Rename test_xai_fix.py to src/praisonai/tests/unit/test_xai_fix.py 2025-07-10 08:03:46 +01:00
claude[bot]andMervin Praison f63f247bfe fix: remove OPENAI_API_KEY requirement for non-OpenAI providers
- Remove unnecessary OpenAI client initialization at import time in main.py
- This was blocking users from using other LLM providers (xai, anthropic, etc)
- The OpenAI client is properly initialized when needed in OpenAIClient class
- Clean up unused imports and constants
- Add test script to verify the fix

Fixes #784

Co-authored-by: Mervin Praison <[email protected]>
2025-07-10 07:02:20 +00:00
Mervin Praison 1d7e03b03e Merge pull request #779 from Dhivya-Bharathy/add-Domain_Deep_Research_Agent
Add Domain Deep Research Agent Notebook to Research Knowledge QA Agents Folder
2025-07-09 16:55:09 +01:00
Mervin Praison 290570de88 Merge pull request #780 from Dhivya-Bharathy/feature/add-ai-agent-examples
Add 5 domain-specific AI agent examples to exa-tool directory
2025-07-09 16:54:50 +01:00
Mervin Praison 542ea8c10d Merge pull request #778 from Dhivya-Bharathy/add-Game_Playing_Agent_Tic_Tac_Toe
Add Game Playing Agent (Tic Tac Toe) Notebook to Programming Code Analysis Agents Folder
2025-07-09 16:54:22 +01:00
Mervin Praison 843f70b599 Merge pull request #777 from Dhivya-Bharathy/add-News_And_Podcast_Aggregator_Agent
Add News and Podcast Aggregator Agent Notebook to Social Media Content Agents Folder
2025-07-09 16:54:10 +01:00
Mervin Praison dee707299d Merge pull request #776 from Dhivya-Bharathy/add-Financial_Coaching_Agent
Add Financial Coaching Agent Notebook to Finance Market Job Agents Folder
2025-07-09 16:53:50 +01:00
devops-vestradata 7f6e300a9e Add 5 domain-specific AI agent folders (Finance, Health, Programming, Research, Social Media) to exa-tool 2025-07-09 18:51:38 +05:30
Dhivya-Bharathy 88e9de2914 Add Domain_Deep_Research_Agent notebook 2025-07-09 10:49:17 +00:00
Dhivya-Bharathy f17daec68b Add Game_Playing_Agent_Tic_Tac_Toe notebook 2025-07-09 10:35:09 +00:00
Dhivya-Bharathy f4d54d76e8 Add News_And_Podcast_Aggregator_Agent notebook 2025-07-09 10:12:16 +00:00
Dhivya-Bharathy 23e2951724 Add Financial_Coaching_Agent notebook 2025-07-09 09:25:23 +00:00
Mervin Praison 1916b1a108 Merge pull request #775 from Dhivya-Bharathy/add-Air_Quality_Analysis_Agent
Add Air Quality Analysis Agent Notebook to Health Fitness Agents
2025-07-09 10:12:38 +01:00
DhivyaBharathy 5b99ca8357 Delete examples/cookbooks/Health_Fitness_Agents/Air_Quality_Analysis_Agent.ipynb 2025-07-09 14:39:17 +05:30
DhivyaBharathy 09ef400c15 Update Air_Quality_Analysis_Agent.ipynb 2025-07-09 14:38:25 +05:30
DhivyaBharathy d5c381890f Add files via upload 2025-07-09 14:36:29 +05:30
DhivyaBharathy 639e53ea9b Update Air_Quality_Analysis_Agent.ipynb 2025-07-09 14:26:25 +05:30
DhivyaBharathy 0954fb4d3d Update Air_Quality_Analysis_Agent.ipynb 2025-07-09 14:14:53 +05:30
Dhivya-Bharathy f5c35f31e9 Add Air_Quality_Analysis_Agent notebook 2025-07-09 08:34:57 +00:00
Mervin Praison 4f31ec9b63 Update PraisonAI and related dependencies to version 2.2.43 and praisonaiagents to version 0.0.116 across Dockerfiles, README, and project files for consistency and compatibility. 2025-07-09 00:37:21 +01:00
Mervin Praison abee86337d Merge pull request #774 from MervinPraison/claude/pr-773-20250708_232256
fix: add array schema validation to llm.py for MCP tools compatibility
2025-07-09 00:34:52 +01:00
claude[bot]andMervin Praison e6cf4ebfcd fix: add array schema validation to llm.py for MCP tools compatibility
- Add _fix_array_schemas method to recursively fix missing 'items' in array schemas
- Apply fix to pre-formatted tools in _format_tools_for_litellm
- Apply fix to generated tool definitions in _generate_tool_definition
- Ensures OpenAI compatibility for all tool types (MCP, pre-formatted, generated)
- Maintains backward compatibility by only adding missing fields

Related to PR #773

Co-authored-by: Mervin Praison <[email protected]>
2025-07-08 23:27:14 +00:00
33 changed files with 4380 additions and 56 deletions

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+1 -1
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@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
flask \
"praisonai>=2.2.42" \
"praisonai>=2.2.44" \
"praisonai[api]" \
gunicorn \
markdown
+1 -1
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@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=2.2.42" \
"praisonai>=2.2.44" \
"praisonai[chat]" \
"embedchain[github,youtube]"
+1 -1
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@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=2.2.42" \
"praisonai>=2.2.44" \
"praisonai[ui]" \
"praisonai[chat]" \
"praisonai[realtime]" \
+1 -1
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@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=2.2.42" \
"praisonai>=2.2.44" \
"praisonai[ui]" \
"praisonai[crewai]"
+2 -2
View File
@@ -121,7 +121,7 @@ healthcheck:
## 📦 Package Versions
All Docker images use consistent, up-to-date versions:
- PraisonAI: `>=2.2.42`
- PraisonAI: `>=2.2.44`
- PraisonAI Agents: `>=0.0.92`
- Python: `3.11-slim`
@@ -218,7 +218,7 @@ docker-compose up -d
### Version Pinning
To use specific versions, update the Dockerfile:
```dockerfile
RUN pip install "praisonai==2.2.42" "praisonaiagents==0.0.92"
RUN pip install "praisonai==2.2.44" "praisonaiagents==0.0.92"
```
## 🌐 Production Deployment
@@ -0,0 +1,482 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "y8L9VFhhdjhL"
},
"source": [
"# Financial Coaching Agent using PraisonAIAgents"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "6UxqTg7pdkm-"
},
"source": [
"This notebook demonstrates how to build a Financial Coaching Agent using the `praisonaiagents` library.\n",
"The agent analyzes user financial data and provides actionable recommendations for budgeting, savings, and debt management.\n",
"The notebook is CI-friendly: it uses dummy data if API keys are not set, so all tests/checks will pass."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "CNqB5dPffV3m"
},
"source": [
"[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Dhivya-Bharathy/PraisonAI/blob/main/examples/cookbooks/Finance_Market_Job_Agents/Financial_Coaching_Agent.ipynb)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3cdm72N2doNq"
},
"source": [
"# Dependencies"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Pl85wGWzdpTK"
},
"outputs": [],
"source": [
"!pip install praisonaiagents pandas"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "YOlEEkk4ePqy"
},
"source": [
"# Set up key"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "T9zKRkv_eRsc"
},
"outputs": [],
"source": [
"import os\n",
"\n",
"# Try to get keys from environment variables, or use placeholders\n",
"OPENAI_API_KEY = os.environ.get(\"OPENAI_API_KEY\", \"sk-..\")\n",
"\n",
"# Set them in the environment for downstream code\n",
"os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_KEY\n",
"\n",
"def is_valid_key(key, prefix):\n",
" return key and key != f\"{prefix}-..\" and key.startswith(prefix)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "FGYJpB9eeaSY"
},
"source": [
"# Tool: Financial Summary"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"id": "asLRt9gAecJ2"
},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
"class FinancialSummaryTool:\n",
" \"\"\"\n",
" Custom tool to summarize financial data and calculate basic stats.\n",
" \"\"\"\n",
" def __init__(self, income, expenses, debts):\n",
" self.income = income\n",
" self.expenses = expenses\n",
" self.debts = debts\n",
"\n",
" def summary(self):\n",
" total_expenses = sum(self.expenses.values())\n",
" surplus = self.income - total_expenses\n",
" total_debt = sum(d['amount'] for d in self.debts)\n",
" return {\n",
" \"total_expenses\": total_expenses,\n",
" \"surplus\": surplus,\n",
" \"total_debt\": total_debt,\n",
" \"expense_breakdown\": self.expenses,\n",
" \"debts\": self.debts\n",
" }"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "lIysLOOdef3b"
},
"source": [
"# YAML prompt"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "GDbWRmp2egsz",
"outputId": "cf4e4d15-7446-4613-9a20-298674f0b4d3"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'agent': {'name': 'Financial Coaching Agent', 'description': 'An agent that analyzes user financial data and provides actionable recommendations for budgeting, savings, and debt management.\\n', 'tools': [{'name': 'FinancialSummaryTool', 'description': 'Summarizes income, expenses, and debts for the agent.'}], 'workflow': [{'step': 'Summarize financial data using FinancialSummaryTool'}, {'step': 'Analyze summary and provide recommendations'}]}, 'inputs': ['monthly_income', 'expenses', 'debts'], 'outputs': ['recommendations']}\n"
]
}
],
"source": [
"import yaml\n",
"\n",
"yaml_prompt = \"\"\"\n",
"agent:\n",
" name: Financial Coaching Agent\n",
" description: |\n",
" An agent that analyzes user financial data and provides actionable recommendations for budgeting, savings, and debt management.\n",
" tools:\n",
" - name: FinancialSummaryTool\n",
" description: Summarizes income, expenses, and debts for the agent.\n",
" workflow:\n",
" - step: Summarize financial data using FinancialSummaryTool\n",
" - step: Analyze summary and provide recommendations\n",
"inputs:\n",
" - monthly_income\n",
" - expenses\n",
" - debts\n",
"outputs:\n",
" - recommendations\n",
"\"\"\"\n",
"print(yaml.safe_load(yaml_prompt))"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "C-FE-hTKekHK"
},
"source": [
"# Main"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000,
"referenced_widgets": [
"b27151e0a1ec47d8a36433ef503eede2",
"58e152a95c1d49d68b45aea3b837b6d3"
]
},
"id": "48oIH5LYek-q",
"outputId": "b501eae2-63c2-434d-f5c3-abba6b93956e"
},
"outputs": [
{
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"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> more effectively and reduce your debt: <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 1 </span><span style=\"font-weight: bold\">Prioritize Debt Repayment:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Focus on paying off the high-interest debt first, which is the credit card debt with an 18% interest <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>rate. Consider using the debt avalanche method, where you pay extra towards the debt with the highest <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>interest rate while making minimum payments on others. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>With a surplus of $650, allocate a significant portion of this towards the credit card debt. For example, <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>you could pay $400 towards the credit card debt (including the $50 minimum payment), which would help <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>reduce the principal faster and save on interest. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 2 </span><span style=\"font-weight: bold\">Review and Adjust Expenses:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Housing:</span> At $1200, housing is a significant portion of your expenses. If possible, explore options to <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>reduce this cost, such as negotiating rent, finding a roommate, or moving to a less expensive place. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Food:</span> Consider meal planning, cooking at home, and reducing dining out to lower the $400 food expense. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Entertainment:</span> At $150, see if you can cut back on discretionary spending. Look for free or low-cost <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>entertainment options. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Other Expenses:</span> Review the $100 in 'Other' expenses to identify any non-essential spending that can be <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>reduced or eliminated. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 3 </span><span style=\"font-weight: bold\">Increase Savings:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>While you are already saving $300 monthly, consider increasing this amount once the high-interest debt is <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>paid off. Building an emergency fund should be a priority to cover 3-6 months of expenses. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 4 </span><span style=\"font-weight: bold\">Boost Income:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Explore opportunities to increase your income, such as taking on a part-time job, freelancing, or selling <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>unused items. Any additional income can accelerate debt repayment and increase savings. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 5 </span><span style=\"font-weight: bold\">Monitor and Adjust:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Regularly review your budget and expenses to ensure you are on track with your financial goals. Adjust <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>your plan as needed to accommodate changes in income or expenses. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 6 </span><span style=\"font-weight: bold\">Consider Debt Consolidation:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>If you have a good credit score, look into consolidating your credit card debt into a lower-interest <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>personal loan. This could reduce your overall interest payments and simplify your debt repayment process. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> By implementing these recommendations, you can effectively manage your finances, reduce debt, and work towards <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> achieving greater financial stability. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[36m╭─\u001b[0m\u001b[36m──────────────────────────────────────────────────\u001b[0m\u001b[36m Response \u001b[0m\u001b[36m───────────────────────────────────────────────────\u001b[0m\u001b[36m─╮\u001b[0m\n",
"\u001b[36m│\u001b[0m Based on the provided financial summary, here are some actionable recommendations to help manage your finances \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m more effectively and reduce your debt: \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 1 \u001b[0m\u001b[1mPrioritize Debt Repayment:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mFocus on paying off the high-interest debt first, which is the credit card debt with an 18% interest \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mrate. Consider using the debt avalanche method, where you pay extra towards the debt with the highest \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0minterest rate while making minimum payments on others. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mWith a surplus of $650, allocate a significant portion of this towards the credit card debt. For example, \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0myou could pay $400 towards the credit card debt (including the $50 minimum payment), which would help \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mreduce the principal faster and save on interest. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 2 \u001b[0m\u001b[1mReview and Adjust Expenses:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0m\u001b[1mHousing:\u001b[0m At $1200, housing is a significant portion of your expenses. If possible, explore options to \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mreduce this cost, such as negotiating rent, finding a roommate, or moving to a less expensive place. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0m\u001b[1mFood:\u001b[0m Consider meal planning, cooking at home, and reducing dining out to lower the $400 food expense. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0m\u001b[1mEntertainment:\u001b[0m At $150, see if you can cut back on discretionary spending. Look for free or low-cost \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mentertainment options. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0m\u001b[1mOther Expenses:\u001b[0m Review the $100 in 'Other' expenses to identify any non-essential spending that can be \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mreduced or eliminated. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 3 \u001b[0m\u001b[1mIncrease Savings:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mWhile you are already saving $300 monthly, consider increasing this amount once the high-interest debt is \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mpaid off. Building an emergency fund should be a priority to cover 3-6 months of expenses. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 4 \u001b[0m\u001b[1mBoost Income:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mExplore opportunities to increase your income, such as taking on a part-time job, freelancing, or selling \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0munused items. Any additional income can accelerate debt repayment and increase savings. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 5 \u001b[0m\u001b[1mMonitor and Adjust:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mRegularly review your budget and expenses to ensure you are on track with your financial goals. Adjust \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0myour plan as needed to accommodate changes in income or expenses. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 6 \u001b[0m\u001b[1mConsider Debt Consolidation:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mIf you have a good credit score, look into consolidating your credit card debt into a lower-interest \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mpersonal loan. This could reduce your overall interest payments and simplify your debt repayment process. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m By implementing these recommendations, you can effectively manage your finances, reduce debt, and work towards \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m achieving greater financial stability. \u001b[36m│\u001b[0m\n",
"\u001b[36m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"=== Financial Coaching Agent Recommendations ===\n",
"Based on the provided financial summary, here are some actionable recommendations to help manage your finances more effectively and reduce your debt:\n",
"\n",
"1. **Prioritize Debt Repayment:**\n",
" - Focus on paying off the high-interest debt first, which is the credit card debt with an 18% interest rate. Consider using the debt avalanche method, where you pay extra towards the debt with the highest interest rate while making minimum payments on others.\n",
" - With a surplus of $650, allocate a significant portion of this towards the credit card debt. For example, you could pay $400 towards the credit card debt (including the $50 minimum payment), which would help reduce the principal faster and save on interest.\n",
"\n",
"2. **Review and Adjust Expenses:**\n",
" - **Housing:** At $1200, housing is a significant portion of your expenses. If possible, explore options to reduce this cost, such as negotiating rent, finding a roommate, or moving to a less expensive place.\n",
" - **Food:** Consider meal planning, cooking at home, and reducing dining out to lower the $400 food expense.\n",
" - **Entertainment:** At $150, see if you can cut back on discretionary spending. Look for free or low-cost entertainment options.\n",
" - **Other Expenses:** Review the $100 in 'Other' expenses to identify any non-essential spending that can be reduced or eliminated.\n",
"\n",
"3. **Increase Savings:**\n",
" - While you are already saving $300 monthly, consider increasing this amount once the high-interest debt is paid off. Building an emergency fund should be a priority to cover 3-6 months of expenses.\n",
"\n",
"4. **Boost Income:**\n",
" - Explore opportunities to increase your income, such as taking on a part-time job, freelancing, or selling unused items. Any additional income can accelerate debt repayment and increase savings.\n",
"\n",
"5. **Monitor and Adjust:**\n",
" - Regularly review your budget and expenses to ensure you are on track with your financial goals. Adjust your plan as needed to accommodate changes in income or expenses.\n",
"\n",
"6. **Consider Debt Consolidation:**\n",
" - If you have a good credit score, look into consolidating your credit card debt into a lower-interest personal loan. This could reduce your overall interest payments and simplify your debt repayment process.\n",
"\n",
"By implementing these recommendations, you can effectively manage your finances, reduce debt, and work towards achieving greater financial stability.\n"
]
}
],
"source": [
"from praisonaiagents import Agent\n",
"\n",
"# Dummy data for CI/public use\n",
"dummy_financial_data = {\n",
" \"monthly_income\": 3000,\n",
" \"expenses\": {\n",
" \"Housing\": 1200,\n",
" \"Food\": 400,\n",
" \"Transportation\": 200,\n",
" \"Entertainment\": 150,\n",
" \"Savings\": 300,\n",
" \"Other\": 100\n",
" },\n",
" \"debts\": [\n",
" {\"name\": \"Credit Card\", \"amount\": 2000, \"interest_rate\": 18.0, \"min_payment\": 50},\n",
" {\"name\": \"Student Loan\", \"amount\": 8000, \"interest_rate\": 5.0, \"min_payment\": 100}\n",
" ]\n",
"}\n",
"\n",
"income = dummy_financial_data[\"monthly_income\"]\n",
"expenses = dummy_financial_data[\"expenses\"]\n",
"debts = dummy_financial_data[\"debts\"]\n",
"\n",
"tool = FinancialSummaryTool(income, expenses, debts)\n",
"summary = tool.summary()\n",
"\n",
"if not is_valid_key(OPENAI_API_KEY, \"sk\"):\n",
" print(\"API key not set or is a placeholder. Using dummy recommendations for CI/testing.\")\n",
" recommendations = \"\"\"\n",
" - Review your monthly expenses and identify areas to cut back.\n",
" - Increase your monthly savings by at least 10%.\n",
" - Pay off high-interest debts first (e.g., Credit Card).\n",
" - Build an emergency fund covering at least 3-6 months of expenses.\n",
" \"\"\"\n",
"else:\n",
" prompt = f\"\"\"\n",
" You are a financial coach. Analyze the following summary and provide actionable recommendations:\n",
" - Monthly income: ${summary['surplus'] + summary['total_expenses']}\n",
" - Total expenses: ${summary['total_expenses']}\n",
" - Surplus: ${summary['surplus']}\n",
" - Total debt: ${summary['total_debt']}\n",
" - Expense breakdown: {summary['expense_breakdown']}\n",
" - Debts: {summary['debts']}\n",
" \"\"\"\n",
" agent = Agent(\n",
" name=\"Financial Coaching Agent\",\n",
" api_key=OPENAI_API_KEY\n",
" )\n",
" # Use start(prompt) instead of run()\n",
" recommendations = agent.start(prompt)\n",
"\n",
"print(\"=== Financial Coaching Agent Recommendations ===\")\n",
"print(recommendations)"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
@@ -0,0 +1,573 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "vUS5f8IhI4Iw"
},
"source": [
"# Air Quality Analysis Agent using PraisonAIAgents"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "IPiJvwVgI5hK"
},
"source": [
"## Description\n",
"\n",
"This notebook demonstrates how to build an Air Quality Analysis Agent using the `praisonaiagents` library. \n",
"The agent retrieves real-time air quality data for a specified location, analyzes the results, and provides actionable insights or health recommendations. \n",
"You will learn how to set up the environment, configure API keys, use custom tools, and orchestrate the agent workflow with a YAML prompt."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "oqdL8WpNTKu5"
},
"source": [
"[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MervinPraison/PraisonAI/blob/main/examples/cookbooks/Health_Fitness_Agents/Air_Quality_Analysis_Agent.ipynb)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "p7CFp0tkJKmU"
},
"source": [
"# Dependencies"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "q6Aq57bqJKFc"
},
"outputs": [],
"source": [
"!pip install praisonaiagents firecrawl requests"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "NLJn9uGVJldu"
},
"source": [
"# Set up API Key"
]
},{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"id": "ZxHL7mJYJpVb"
},
"outputs": [],
"source": [
"# Replace with your actual API keys\n",
"FIRECRAWL_API_KEY = \"fc-...\" # Your Firecrawl API key\n",
"OPENAI_API_KEY = \"sk-...\" # Your OpenAI API key\n",
"\n",
"import os\n",
"os.environ[\"FIRECRAWL_API_KEY\"] = FIRECRAWL_API_KEY\n",
"os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_KEY\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "eVb00IhbJ60M"
},
"source": [
"# Tools"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"id": "3YgwDwyFLXlU"
},
"outputs": [],
"source": [
"import requests\n",
"from firecrawl import FirecrawlApp\n",
"from typing import Dict\n",
"\n",
"class AQIDataFetcher:\n",
" def __init__(self, firecrawl_key: str):\n",
" self.firecrawl = FirecrawlApp(api_key=firecrawl_key)\n",
"\n",
" def fetch(self, country: str, state: str, city: str) -> Dict:\n",
" country_clean = country.lower().replace(' ', '-')\n",
" city_clean = city.lower().replace(' ', '-')\n",
" if not state or state.lower() == 'none':\n",
" url = f\"https://www.aqi.in/dashboard/{country_clean}/{city_clean}\"\n",
" else:\n",
" state_clean = state.lower().replace(' ', '-')\n",
" url = f\"https://www.aqi.in/dashboard/{country_clean}/{state_clean}/{city_clean}\"\n",
"\n",
" # Check if the URL is valid and reachable\n",
" print(f\"Testing URL: {url}\")\n",
" try:\n",
" resp = requests.get(url)\n",
" print(f\"Status code: {resp.status_code}\")\n",
" if resp.status_code != 200:\n",
" print(f\"URL not reachable: {url} (status code: {resp.status_code})\")\n",
" return None\n",
" except Exception as e:\n",
" print(f\"Error: {e}\")\n",
" return None\n",
"\n",
" schema = {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"aqi\": {\"type\": \"number\", \"description\": \"Air Quality Index\"},\n",
" \"temperature\": {\"type\": \"number\", \"description\": \"Temperature in degrees Celsius\"},\n",
" \"humidity\": {\"type\": \"number\", \"description\": \"Humidity percentage\"},\n",
" \"wind_speed\": {\"type\": \"number\", \"description\": \"Wind speed in kilometers per hour\"},\n",
" \"pm25\": {\"type\": \"number\", \"description\": \"Particulate Matter 2.5 micrometers\"},\n",
" \"pm10\": {\"type\": \"number\", \"description\": \"Particulate Matter 10 micrometers\"},\n",
" \"co\": {\"type\": \"number\", \"description\": \"Carbon Monoxide level\"}\n",
" },\n",
" \"required\": [\"aqi\", \"temperature\", \"humidity\", \"wind_speed\", \"pm25\", \"pm10\", \"co\"]\n",
" }\n",
"\n",
" response = self.firecrawl.extract(\n",
" urls=[f\"{url}/*\"],\n",
" prompt='Extract the current real-time AQI, temperature, humidity, wind speed, PM2.5, PM10, and CO levels from the page. Also extract the timestamp of the data.',\n",
" schema=schema\n",
" )\n",
" return response"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3sUNJChKOVUm"
},
"source": [
"# YAML Prompt"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "0G9tLj0nJ8B_",
"outputId": "61e66fe7-df17-4d2d-ad27-a9f4466298a4"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'agent': {'name': 'Air Quality Health Advisor', 'description': 'An agent that analyzes real-time air quality data for a given location and provides personalized health recommendations based on user context.\\n', 'tools': [{'name': 'AQIDataFetcher', 'description': 'Fetches AQI and weather data for a specified city, state, and country using Firecrawl.'}], 'workflow': [{'step': \"Fetch AQI data for the user's location using AQIDataFetcher.\"}, {'step': 'Analyze AQI and weather data.'}, {'step': \"Consider user's medical conditions and planned activity.\"}, {'step': 'Generate health and activity recommendations.'}]}, 'inputs': ['city', 'state', 'country', 'medical_conditions', 'planned_activity'], 'outputs': ['recommendations']}\n"
]
}
],
"source": [
"import yaml\n",
"\n",
"yaml_prompt = \"\"\"\n",
"agent:\n",
" name: Air Quality Health Advisor\n",
" description: |\n",
" An agent that analyzes real-time air quality data for a given location and provides personalized health recommendations based on user context.\n",
" tools:\n",
" - name: AQIDataFetcher\n",
" description: Fetches AQI and weather data for a specified city, state, and country using Firecrawl.\n",
" workflow:\n",
" - step: Fetch AQI data for the user's location using AQIDataFetcher.\n",
" - step: Analyze AQI and weather data.\n",
" - step: Consider user's medical conditions and planned activity.\n",
" - step: Generate health and activity recommendations.\n",
"inputs:\n",
" - city\n",
" - state\n",
" - country\n",
" - medical_conditions\n",
" - planned_activity\n",
"outputs:\n",
" - recommendations\n",
"\"\"\"\n",
"\n",
"print(yaml.safe_load(yaml_prompt))"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "2HIPkoUyKEY-"
},
"source": [
"# Main"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000,
"referenced_widgets": [
"4c2bac52ad444499b362978d8fe92d97",
"5203e4d9bd3c47f09d2f204c7f1e078f"
]
},
"id": "UQ4sHVW0KFp-",
"outputId": "4efe39ea-c924-41e9-cc66-f4894e367280"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Testing URL: https://www.aqi.in/dashboard/india/maharashtra/mumbai\n",
"Status code: 200\n"
]
},
{
"data": {
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">╭─ </span><span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8; font-weight: bold\">Agent Info</span><span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\"> ────────────────────────────────────────────────────────────────────────────────────────────────────╮</span>\n",
"<span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span> <span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span>\n",
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"<span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span> <span style=\"color: #b4b4b3; text-decoration-color: #b4b4b3; font-weight: bold\">Role:</span> <span style=\"color: #ffe5e5; text-decoration-color: #ffe5e5\">Assistant</span> <span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span>\n",
"<span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span> <span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span>\n",
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"\u001b[38;2;210;227;200m╭─\u001b[0m\u001b[38;2;210;227;200m \u001b[0m\u001b[1;38;2;210;227;200mAgent Info\u001b[0m\u001b[38;2;210;227;200m \u001b[0m\u001b[38;2;210;227;200m───────────────────────────────────────────────────────────────────────────────────────────────────\u001b[0m\u001b[38;2;210;227;200m─╮\u001b[0m\n",
"\u001b[38;2;210;227;200m│\u001b[0m \u001b[38;2;210;227;200m│\u001b[0m\n",
"\u001b[38;2;210;227;200m│\u001b[0m \u001b[1;38;2;255;155;155m👤 Agent:\u001b[0m \u001b[38;2;255;229;229mAir Quality Health Advisor\u001b[0m \u001b[38;2;210;227;200m│\u001b[0m\n",
"\u001b[38;2;210;227;200m│\u001b[0m \u001b[1;38;2;180;180;179mRole:\u001b[0m \u001b[38;2;255;229;229mAssistant\u001b[0m \u001b[38;2;210;227;200m│\u001b[0m\n",
"\u001b[38;2;210;227;200m│\u001b[0m \u001b[38;2;210;227;200m│\u001b[0m\n",
"\u001b[38;2;210;227;200m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
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"\u001b[2mResponse generated in 10.8s\u001b[0m\n"
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"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">╭───────────────────────────────────────────────────── Task ──────────────────────────────────────────────────────╮</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> You are an expert health advisor using the GPT-4o Mini model. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">Based on the following air quality conditions in Mumbai, Maharashtra, India:</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">- Overall AQI: 75</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">- PM2.5 Level: 22 µg/m³</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">- PM10 Level: 60 µg/m³</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">- CO Level: 650 ppb</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">Weather conditions:</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">- Temperature: 28°C</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">- Humidity: 84%</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">- Wind Speed: 30 km/h</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">User's Context:</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">- Medical Conditions: asthma</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">- Planned Activity: morning jog for 2 hours</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">**Comprehensive Health Recommendations:**</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">1. **Impact of Current Air Quality on Health:**</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">2. **Necessary Safety Precautions for Planned Activity:**</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">3. **Advisability of Planned Activity:**</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span><span style=\"color: #f8f8f2; text-decoration-color: #f8f8f2; background-color: #272822\">4. **Best Time to Conduct the Activity:**</span><span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"background-color: #272822\"> </span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[36m╭─\u001b[0m\u001b[36m────────────────────────────────────────────────────\u001b[0m\u001b[36m Task \u001b[0m\u001b[36m─────────────────────────────────────────────────────\u001b[0m\u001b[36m─╮\u001b[0m\n",
"\u001b[36m│\u001b[0m You are an expert health advisor using the GPT-4o Mini model. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34mBased on the following air quality conditions in Mumbai, Maharashtra, India:\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m- Overall AQI: 75\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m- PM2.5 Level: 22 µg/m³\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m- PM10 Level: 60 µg/m³\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m- CO Level: 650 ppb\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34mWeather conditions:\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m- Temperature: 28°C\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m- Humidity: 84%\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m- Wind Speed: 30 km/h\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34mUser's Context:\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m- Medical Conditions: asthma\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m- Planned Activity: morning jog for 2 hours\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m**Comprehensive Health Recommendations:**\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m1. **Impact of Current Air Quality on Health:**\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m2. **Necessary Safety Precautions for Planned Activity:**\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m3. **Advisability of Planned Activity:**\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m\u001b[38;2;248;248;242;48;2;39;40;34m4. **Best Time to Conduct the Activity:**\u001b[0m\u001b[48;2;39;40;34m \u001b[0m\u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[48;2;39;40;34m \u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">╭─────────────────────────────────────────────────── Response ────────────────────────────────────────────────────╮</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Certainly! Here are the comprehensive health recommendations based on the provided conditions: <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 1 </span><span style=\"font-weight: bold\">Impact of Current Air Quality on Health:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>The overall AQI of 75 is considered \"Moderate.\" This level is generally acceptable for most individuals, <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>but sensitive groups, such as those with asthma, may experience some respiratory discomfort. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>PM2.5 and PM10 levels are within moderate ranges, which can still pose a risk for people with <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>pre-existing respiratory conditions like asthma. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>The CO level of 650 ppb is not typically concerning, but it is important to be cautious as individuals <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>with asthma may be more sensitive to pollutants. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 2 </span><span style=\"font-weight: bold\">Necessary Safety Precautions for Planned Activity:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Consider wearing a mask designed to filter out particulate matter to reduce inhalation of pollutants. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Carry a rescue inhaler and any other prescribed asthma medication. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Stay hydrated, as high humidity can exacerbate asthma symptoms. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Monitor your breathing and be prepared to stop the activity if you experience any respiratory distress. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Choose a route with less traffic to minimize exposure to vehicle emissions. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 3 </span><span style=\"font-weight: bold\">Advisability of Planned Activity:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Given the moderate AQI and the user's asthma condition, it is advisable to proceed with caution. A 2-hour <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>jog may be too strenuous under these conditions, so consider reducing the duration or intensity of the <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>jog. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>It may be beneficial to consult with a healthcare provider to tailor the activity to your specific health <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>needs. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 4 </span><span style=\"font-weight: bold\">Best Time to Conduct the Activity:</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Early morning hours, just after sunrise, are typically better for outdoor activities as pollution levels <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>tend to be lower. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Avoid peak traffic times to reduce exposure to vehicle emissions. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Check real-time air quality updates to ensure conditions remain stable or improve before starting the <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>activity. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> By following these recommendations, you can help mitigate potential health risks while enjoying your planned <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> activity. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[36m╭─\u001b[0m\u001b[36m──────────────────────────────────────────────────\u001b[0m\u001b[36m Response \u001b[0m\u001b[36m───────────────────────────────────────────────────\u001b[0m\u001b[36m─╮\u001b[0m\n",
"\u001b[36m│\u001b[0m Certainly! Here are the comprehensive health recommendations based on the provided conditions: \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 1 \u001b[0m\u001b[1mImpact of Current Air Quality on Health:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mThe overall AQI of 75 is considered \"Moderate.\" This level is generally acceptable for most individuals, \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mbut sensitive groups, such as those with asthma, may experience some respiratory discomfort. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mPM2.5 and PM10 levels are within moderate ranges, which can still pose a risk for people with \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mpre-existing respiratory conditions like asthma. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mThe CO level of 650 ppb is not typically concerning, but it is important to be cautious as individuals \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mwith asthma may be more sensitive to pollutants. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 2 \u001b[0m\u001b[1mNecessary Safety Precautions for Planned Activity:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mConsider wearing a mask designed to filter out particulate matter to reduce inhalation of pollutants. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mCarry a rescue inhaler and any other prescribed asthma medication. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mStay hydrated, as high humidity can exacerbate asthma symptoms. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mMonitor your breathing and be prepared to stop the activity if you experience any respiratory distress. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mChoose a route with less traffic to minimize exposure to vehicle emissions. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 3 \u001b[0m\u001b[1mAdvisability of Planned Activity:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mGiven the moderate AQI and the user's asthma condition, it is advisable to proceed with caution. A 2-hour \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mjog may be too strenuous under these conditions, so consider reducing the duration or intensity of the \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mjog. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mIt may be beneficial to consult with a healthcare provider to tailor the activity to your specific health \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mneeds. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 4 \u001b[0m\u001b[1mBest Time to Conduct the Activity:\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mEarly morning hours, just after sunrise, are typically better for outdoor activities as pollution levels \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mtend to be lower. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mAvoid peak traffic times to reduce exposure to vehicle emissions. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m • \u001b[0mCheck real-time air quality updates to ensure conditions remain stable or improve before starting the \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m \u001b[0mactivity. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m By following these recommendations, you can help mitigate potential health risks while enjoying your planned \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m activity. \u001b[36m│\u001b[0m\n",
"\u001b[36m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
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"text": [
"=== Air Quality Analysis Agent Recommendations ===\n",
"Certainly! Here are the comprehensive health recommendations based on the provided conditions:\n",
"\n",
"1. **Impact of Current Air Quality on Health:**\n",
" - The overall AQI of 75 is considered \"Moderate.\" This level is generally acceptable for most individuals, but sensitive groups, such as those with asthma, may experience some respiratory discomfort.\n",
" - PM2.5 and PM10 levels are within moderate ranges, which can still pose a risk for people with pre-existing respiratory conditions like asthma.\n",
" - The CO level of 650 ppb is not typically concerning, but it is important to be cautious as individuals with asthma may be more sensitive to pollutants.\n",
"\n",
"2. **Necessary Safety Precautions for Planned Activity:**\n",
" - Consider wearing a mask designed to filter out particulate matter to reduce inhalation of pollutants.\n",
" - Carry a rescue inhaler and any other prescribed asthma medication.\n",
" - Stay hydrated, as high humidity can exacerbate asthma symptoms.\n",
" - Monitor your breathing and be prepared to stop the activity if you experience any respiratory distress.\n",
" - Choose a route with less traffic to minimize exposure to vehicle emissions.\n",
"\n",
"3. **Advisability of Planned Activity:**\n",
" - Given the moderate AQI and the user's asthma condition, it is advisable to proceed with caution. A 2-hour jog may be too strenuous under these conditions, so consider reducing the duration or intensity of the jog.\n",
" - It may be beneficial to consult with a healthcare provider to tailor the activity to your specific health needs.\n",
"\n",
"4. **Best Time to Conduct the Activity:**\n",
" - Early morning hours, just after sunrise, are typically better for outdoor activities as pollution levels tend to be lower.\n",
" - Avoid peak traffic times to reduce exposure to vehicle emissions.\n",
" - Check real-time air quality updates to ensure conditions remain stable or improve before starting the activity.\n",
"\n",
"By following these recommendations, you can help mitigate potential health risks while enjoying your planned activity.\n"
]
}
],
"source": [
"from praisonaiagents import Agent\n",
"import os\n",
"\n",
"# User input (you can change these for other locations)\n",
"user_city = \"Mumbai\"\n",
"user_state = \"Maharashtra\"\n",
"user_country = \"India\"\n",
"user_medical_conditions = \"asthma\"\n",
"user_planned_activity = \"morning jog for 2 hours\"\n",
"\n",
"aqi_fetcher = AQIDataFetcher(firecrawl_key=os.environ[\"FIRECRAWL_API_KEY\"])\n",
"\n",
"# Try with state, then without state, then fallback to Delhi\n",
"aqi_data = aqi_fetcher.fetch(\n",
" country=user_country,\n",
" state=user_state,\n",
" city=user_city\n",
")\n",
"\n",
"if not aqi_data or not hasattr(aqi_data, \"data\"):\n",
" print(\"Mumbai with state failed, trying without state...\")\n",
" aqi_data = aqi_fetcher.fetch(\n",
" country=user_country,\n",
" state=\"\",\n",
" city=user_city\n",
" )\n",
"\n",
"if not aqi_data or not hasattr(aqi_data, \"data\"):\n",
" print(\"Trying Delhi, India...\")\n",
" aqi_data = aqi_fetcher.fetch(\n",
" country=\"India\",\n",
" state=\"\",\n",
" city=\"Delhi\"\n",
" )\n",
"\n",
"if not aqi_data or not hasattr(aqi_data, \"data\"):\n",
" print(\"Failed to fetch AQI data for all tried locations. Please check the URLs manually.\")\n",
"else:\n",
" aqi_data = aqi_data.data # Convert to dict\n",
"\n",
" prompt = f\"\"\"\n",
" You are an expert health advisor using the GPT-4o Mini model.\n",
"\n",
" Based on the following air quality conditions in {user_city}, {user_state}, {user_country}:\n",
" - Overall AQI: {aqi_data.get('aqi', 'N/A')}\n",
" - PM2.5 Level: {aqi_data.get('pm25', 'N/A')} µg/m³\n",
" - PM10 Level: {aqi_data.get('pm10', 'N/A')} µg/m³\n",
" - CO Level: {aqi_data.get('co', 'N/A')} ppb\n",
"\n",
" Weather conditions:\n",
" - Temperature: {aqi_data.get('temperature', 'N/A')}°C\n",
" - Humidity: {aqi_data.get('humidity', 'N/A')}%\n",
" - Wind Speed: {aqi_data.get('wind_speed', 'N/A')} km/h\n",
"\n",
" User's Context:\n",
" - Medical Conditions: {user_medical_conditions or 'None'}\n",
" - Planned Activity: {user_planned_activity}\n",
"\n",
" **Comprehensive Health Recommendations:**\n",
" 1. **Impact of Current Air Quality on Health:**\n",
" 2. **Necessary Safety Precautions for Planned Activity:**\n",
" 3. **Advisability of Planned Activity:**\n",
" 4. **Best Time to Conduct the Activity:**\n",
" \"\"\"\n",
"\n",
" agent = Agent(\n",
" name=\"Air Quality Health Advisor\",\n",
" instructions=prompt,\n",
" api_key=os.environ[\"OPENAI_API_KEY\"]\n",
" )\n",
"\n",
" # Call run() with no arguments\n",
"recommendations = agent.start(prompt)\n",
"print(\"=== Air Quality Analysis Agent Recommendations ===\")\n",
"print(recommendations)"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
@@ -0,0 +1,564 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "Z-9SQRoVyG_O"
},
"source": [
"# Domain Deep Research Agent using PraisonAIAgents"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "EZYCPU_ayIMD"
},
"source": [
"This notebook demonstrates a Domain Deep Research Agent using `praisonaiagents`. \n",
"The agent performs deep research on a given topic and provides a structured report. \n",
"The notebook is CI-friendly: it uses dummy data if API keys are not set, so all tests/checks will pass."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "taa8dcsdyxHT"
},
"source": [
"[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Dhivya-Bharathy/PraisonAI/blob/main/examples/cookbooks/Research_Knowledge_QA_Agents/Domain_Deep_Research_Agent.ipynb)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "v0VlXFo-yKNA"
},
"source": [
"# Dependencies"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "t9Dw5BDryNIa"
},
"outputs": [],
"source": [
"!pip install praisonaiagents"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "V_9FzwguyS7g"
},
"source": [
"# Set up key (robust, CI-safe)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "-l0w3hmLyT47"
},
"outputs": [],
"source": [
"import os\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = os.environ.get(\"OPENAI_API_KEY\", \"sk-..\")\n",
"\n",
"def is_valid_key(key, prefix):\n",
" return key and key != f\"{prefix}-..\" and key.startswith(prefix)\n",
"\n",
"OPENAI_API_KEY = os.environ[\"OPENAI_API_KEY\"]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "xkHGhtnmyZ3m"
},
"source": [
"# Custom Tool: Dummy Deep Research Tool"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"id": "vATC0ZOVyax0"
},
"outputs": [],
"source": [
"class DummyDeepResearchTool:\n",
" \"\"\"\n",
" Custom tool to simulate deep research for CI/public use.\n",
" \"\"\"\n",
" def __init__(self, topic):\n",
" self.topic = topic\n",
"\n",
" def research(self):\n",
" # For demo/CI, just return a dummy report\n",
" return f\"## Research Report on {self.topic}\\n\\n- Key finding 1 about {self.topic}\\n- Key finding 2 about {self.topic}\\n- Key finding 3 about {self.topic}\\n\""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "t-TlO3WuyeYl"
},
"source": [
"# Main (with dummy fallback, CI-safe)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000,
"referenced_widgets": [
"520e1878a8d64958a9b73edc91260284",
"e6b0f40254e54f5a9200996d38ecbd10"
]
},
"id": "cor8P2BlyfQt",
"outputId": "750a1fba-d0f2-4279-a5bb-b3743db2c852"
},
"outputs": [
{
"data": {
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">╭─ </span><span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8; font-weight: bold\">Agent Info</span><span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\"> ────────────────────────────────────────────────────────────────────────────────────────────────────╮</span>\n",
"<span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span> <span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span>\n",
"<span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span> <span style=\"color: #ff9b9b; text-decoration-color: #ff9b9b; font-weight: bold\">👤 Agent:</span> <span style=\"color: #ffe5e5; text-decoration-color: #ffe5e5\">Domain Deep Research Agent</span> <span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span>\n",
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"<span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span> <span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">│</span>\n",
"<span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[38;2;210;227;200m╭─\u001b[0m\u001b[38;2;210;227;200m \u001b[0m\u001b[1;38;2;210;227;200mAgent Info\u001b[0m\u001b[38;2;210;227;200m \u001b[0m\u001b[38;2;210;227;200m───────────────────────────────────────────────────────────────────────────────────────────────────\u001b[0m\u001b[38;2;210;227;200m─╮\u001b[0m\n",
"\u001b[38;2;210;227;200m│\u001b[0m \u001b[38;2;210;227;200m│\u001b[0m\n",
"\u001b[38;2;210;227;200m│\u001b[0m \u001b[1;38;2;255;155;155m👤 Agent:\u001b[0m \u001b[38;2;255;229;229mDomain Deep Research Agent\u001b[0m \u001b[38;2;210;227;200m│\u001b[0m\n",
"\u001b[38;2;210;227;200m│\u001b[0m \u001b[1;38;2;180;180;179mRole:\u001b[0m \u001b[38;2;255;229;229mAssistant\u001b[0m \u001b[38;2;210;227;200m│\u001b[0m\n",
"\u001b[38;2;210;227;200m│\u001b[0m \u001b[38;2;210;227;200m│\u001b[0m\n",
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">Response generated in 25.8s</span>\n",
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">╭───────────────────────────────────────────────────── Task ──────────────────────────────────────────────────────╮</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> You are a domain research assistant. Perform deep research on the following topic and provide a structured, <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> well-cited report: TOPIC: Recent advances in quantum computing <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
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"\u001b[36m╭─\u001b[0m\u001b[36m────────────────────────────────────────────────────\u001b[0m\u001b[36m Task \u001b[0m\u001b[36m─────────────────────────────────────────────────────\u001b[0m\u001b[36m─╮\u001b[0m\n",
"\u001b[36m│\u001b[0m You are a domain research assistant. Perform deep research on the following topic and provide a structured, \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m well-cited report: TOPIC: Recent advances in quantum computing \u001b[36m│\u001b[0m\n",
"\u001b[36m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
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"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">╭─────────────────────────────────────────────────── Response ────────────────────────────────────────────────────╮</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> ┃ <span style=\"font-weight: bold\">Recent Advances in Quantum Computing</span> ┃ <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Quantum computing is a rapidly evolving field that leverages the principles of quantum mechanics to process <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> information in fundamentally new ways. This report highlights some of the most significant recent advances in <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> quantum computing, focusing on developments in hardware, algorithms, and applications. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold; text-decoration: underline\">1. Quantum Hardware Developments</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">1.1 Superconducting Qubits</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Superconducting qubits have been at the forefront of quantum computing hardware. Companies like IBM and Google <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> have made significant strides in increasing the coherence times and connectivity of these qubits. In 2023, IBM <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> announced the development of their 433-qubit processor, Osprey, which is part of their roadmap to achieve a <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> 1,000-qubit system by 2024 [1]. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">1.2 Trapped Ion Qubits</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Trapped ion technology continues to be a strong contender due to its high fidelity and long coherence times. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> IonQ, a leader in this space, has developed systems that can execute quantum circuits with high precision. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Their recent advancements include the development of error-corrected logical qubits, which are crucial for <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> scalable quantum computing [2]. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">1.3 Photonic Quantum Computing</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Photonic quantum computing has seen breakthroughs with companies like Xanadu and PsiQuantum. Xanadu's Borealis, <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> a photonic quantum computer, demonstrated quantum advantage by solving specific problems faster than classical <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> supercomputers [3]. PsiQuantum is working towards a million-qubit photonic quantum computer, leveraging silicon <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> photonics for scalability [4]. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold; text-decoration: underline\">2. Quantum Algorithms</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">2.1 Quantum Machine Learning</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Quantum machine learning (QML) is gaining traction as researchers develop algorithms that could outperform <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> classical counterparts. Recent work has focused on hybrid quantum-classical algorithms that leverage quantum <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> speedups for specific tasks like clustering and classification [5]. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">2.2 Quantum Error Correction</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Error correction remains a critical challenge in quantum computing. Recent advances include the development of <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> more efficient error-correcting codes and fault-tolerant architectures. The surface code, a leading error <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> correction method, has seen improvements in its threshold and resource requirements [6]. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">2.3 Quantum Simulation</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Quantum simulation is one of the most promising applications of quantum computing. Recent studies have <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> demonstrated the simulation of complex quantum systems, such as chemical reactions and material properties, <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> with unprecedented accuracy [7]. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold; text-decoration: underline\">3. Applications and Industry Impact</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">3.1 Cryptography</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Quantum computing poses both threats and opportunities for cryptography. The development of quantum-resistant <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> algorithms is crucial as quantum computers could potentially break widely used encryption methods. The National <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Institute of Standards and Technology (NIST) is in the process of standardizing post-quantum cryptographic <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> algorithms [8]. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">3.2 Drug Discovery</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Quantum computing is poised to revolutionize drug discovery by enabling the simulation of molecular <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> interactions at a quantum level. Companies like Qubit Pharmaceuticals and Cambridge Quantum Computing are <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> actively working on quantum algorithms for drug discovery, promising faster and more accurate predictions [9]. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">3.3 Optimization Problems</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Quantum computers have the potential to solve complex optimization problems more efficiently than classical <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> computers. This has significant implications for industries such as logistics, finance, and manufacturing. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Recent advances include the development of quantum algorithms for portfolio optimization and supply chain <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> management [10]. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold; text-decoration: underline\">4. Challenges and Future Directions</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Despite the rapid progress, several challenges remain in the field of quantum computing. These include <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> improving qubit coherence times, scaling up the number of qubits, and developing robust error correction <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> methods. Future research is likely to focus on hybrid quantum-classical systems, which combine the strengths of <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> both paradigms to tackle complex problems. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold; text-decoration: underline\">Conclusion</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> Quantum computing is advancing at a remarkable pace, with significant developments in hardware, algorithms, and <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> applications. As the field continues to mature, it holds the promise of transforming industries and solving <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> problems that are currently intractable for classical computers. Continued investment in research and <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> development, along with collaboration between academia and industry, will be crucial to realizing the full <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> potential of quantum computing. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold; text-decoration: underline\">References</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 1 </span>IBM Research. (2023). IBM Quantum Roadmap. Retrieved from <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>https://research.ibm.com/quantum-computing/roadmap <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 2 </span>IonQ. (2023). IonQ's Quantum Computing Technology. Retrieved from https://ionq.com/technology <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 3 </span>Xanadu. (2023). Borealis: A Photonic Quantum Computer. Retrieved from https://xanadu.ai/borealis <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 4 </span>PsiQuantum. (2023). Photonic Quantum Computing. Retrieved from https://psiquantum.com/technology <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 5 </span>Biamonte, J., et al. (2023). Quantum Machine Learning. Nature Reviews Physics. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 6 </span>Fowler, A. G., et al. (2023). Surface Codes: Towards Practical Quantum Computing. Physical Review A. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 7 </span>Aspuru-Guzik, A., et al. (2023). Quantum Simulation of Chemical Systems. Chemical Reviews. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 8 </span>NIST. (2023). Post-Quantum Cryptography Standardization. Retrieved from <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>https://csrc.nist.gov/Projects/post-quantum-cryptography <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 9 </span>Qubit Pharmaceuticals. (2023). Quantum Computing in Drug Discovery. Retrieved from <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> </span>https://qubit-pharmaceuticals.com/quantum-computing <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> 10 </span>Venturelli, D., et al. (2023). Quantum Optimization Algorithms. Journal of Quantum Information Processing. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
"</pre>\n"
],
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"\u001b[36m╭─\u001b[0m\u001b[36m──────────────────────────────────────────────────\u001b[0m\u001b[36m Response \u001b[0m\u001b[36m───────────────────────────────────────────────────\u001b[0m\u001b[36m─╮\u001b[0m\n",
"\u001b[36m│\u001b[0m ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m ┃ \u001b[1mRecent Advances in Quantum Computing\u001b[0m ┃ \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Quantum computing is a rapidly evolving field that leverages the principles of quantum mechanics to process \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m information in fundamentally new ways. This report highlights some of the most significant recent advances in \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m quantum computing, focusing on developments in hardware, algorithms, and applications. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;4m1. Quantum Hardware Developments\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1m1.1 Superconducting Qubits\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Superconducting qubits have been at the forefront of quantum computing hardware. Companies like IBM and Google \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m have made significant strides in increasing the coherence times and connectivity of these qubits. In 2023, IBM \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m announced the development of their 433-qubit processor, Osprey, which is part of their roadmap to achieve a \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m 1,000-qubit system by 2024 [1]. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1m1.2 Trapped Ion Qubits\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Trapped ion technology continues to be a strong contender due to its high fidelity and long coherence times. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m IonQ, a leader in this space, has developed systems that can execute quantum circuits with high precision. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Their recent advancements include the development of error-corrected logical qubits, which are crucial for \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m scalable quantum computing [2]. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1m1.3 Photonic Quantum Computing\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Photonic quantum computing has seen breakthroughs with companies like Xanadu and PsiQuantum. Xanadu's Borealis, \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m a photonic quantum computer, demonstrated quantum advantage by solving specific problems faster than classical \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m supercomputers [3]. PsiQuantum is working towards a million-qubit photonic quantum computer, leveraging silicon \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m photonics for scalability [4]. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;4m2. Quantum Algorithms\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1m2.1 Quantum Machine Learning\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Quantum machine learning (QML) is gaining traction as researchers develop algorithms that could outperform \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m classical counterparts. Recent work has focused on hybrid quantum-classical algorithms that leverage quantum \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m speedups for specific tasks like clustering and classification [5]. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1m2.2 Quantum Error Correction\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Error correction remains a critical challenge in quantum computing. Recent advances include the development of \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m more efficient error-correcting codes and fault-tolerant architectures. The surface code, a leading error \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m correction method, has seen improvements in its threshold and resource requirements [6]. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1m2.3 Quantum Simulation\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Quantum simulation is one of the most promising applications of quantum computing. Recent studies have \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m demonstrated the simulation of complex quantum systems, such as chemical reactions and material properties, \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m with unprecedented accuracy [7]. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;4m3. Applications and Industry Impact\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1m3.1 Cryptography\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Quantum computing poses both threats and opportunities for cryptography. The development of quantum-resistant \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m algorithms is crucial as quantum computers could potentially break widely used encryption methods. The National \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Institute of Standards and Technology (NIST) is in the process of standardizing post-quantum cryptographic \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m algorithms [8]. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1m3.2 Drug Discovery\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Quantum computing is poised to revolutionize drug discovery by enabling the simulation of molecular \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m interactions at a quantum level. Companies like Qubit Pharmaceuticals and Cambridge Quantum Computing are \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m actively working on quantum algorithms for drug discovery, promising faster and more accurate predictions [9]. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1m3.3 Optimization Problems\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Quantum computers have the potential to solve complex optimization problems more efficiently than classical \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m computers. This has significant implications for industries such as logistics, finance, and manufacturing. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Recent advances include the development of quantum algorithms for portfolio optimization and supply chain \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m management [10]. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;4m4. Challenges and Future Directions\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Despite the rapid progress, several challenges remain in the field of quantum computing. These include \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m improving qubit coherence times, scaling up the number of qubits, and developing robust error correction \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m methods. Future research is likely to focus on hybrid quantum-classical systems, which combine the strengths of \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m both paradigms to tackle complex problems. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;4mConclusion\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m Quantum computing is advancing at a remarkable pace, with significant developments in hardware, algorithms, and \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m applications. As the field continues to mature, it holds the promise of transforming industries and solving \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m problems that are currently intractable for classical computers. Continued investment in research and \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m development, along with collaboration between academia and industry, will be crucial to realizing the full \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m potential of quantum computing. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;4mReferences\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 1 \u001b[0mIBM Research. (2023). IBM Quantum Roadmap. Retrieved from \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0mhttps://research.ibm.com/quantum-computing/roadmap \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 2 \u001b[0mIonQ. (2023). IonQ's Quantum Computing Technology. Retrieved from https://ionq.com/technology \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 3 \u001b[0mXanadu. (2023). Borealis: A Photonic Quantum Computer. Retrieved from https://xanadu.ai/borealis \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 4 \u001b[0mPsiQuantum. (2023). Photonic Quantum Computing. Retrieved from https://psiquantum.com/technology \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 5 \u001b[0mBiamonte, J., et al. (2023). Quantum Machine Learning. Nature Reviews Physics. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 6 \u001b[0mFowler, A. G., et al. (2023). Surface Codes: Towards Practical Quantum Computing. Physical Review A. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 7 \u001b[0mAspuru-Guzik, A., et al. (2023). Quantum Simulation of Chemical Systems. Chemical Reviews. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 8 \u001b[0mNIST. (2023). Post-Quantum Cryptography Standardization. Retrieved from \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0mhttps://csrc.nist.gov/Projects/post-quantum-cryptography \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 9 \u001b[0mQubit Pharmaceuticals. (2023). Quantum Computing in Drug Discovery. Retrieved from \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m \u001b[0mhttps://qubit-pharmaceuticals.com/quantum-computing \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1;33m 10 \u001b[0mVenturelli, D., et al. (2023). Quantum Optimization Algorithms. Journal of Quantum Information Processing. \u001b[36m│\u001b[0m\n",
"\u001b[36m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
]
},
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"output_type": "stream",
"text": [
"# Recent Advances in Quantum Computing\n",
"\n",
"Quantum computing is a rapidly evolving field that leverages the principles of quantum mechanics to process information in fundamentally new ways. This report highlights some of the most significant recent advances in quantum computing, focusing on developments in hardware, algorithms, and applications.\n",
"\n",
"## 1. Quantum Hardware Developments\n",
"\n",
"### 1.1 Superconducting Qubits\n",
"Superconducting qubits have been at the forefront of quantum computing hardware. Companies like IBM and Google have made significant strides in increasing the coherence times and connectivity of these qubits. In 2023, IBM announced the development of their 433-qubit processor, Osprey, which is part of their roadmap to achieve a 1,000-qubit system by 2024 [1].\n",
"\n",
"### 1.2 Trapped Ion Qubits\n",
"Trapped ion technology continues to be a strong contender due to its high fidelity and long coherence times. IonQ, a leader in this space, has developed systems that can execute quantum circuits with high precision. Their recent advancements include the development of error-corrected logical qubits, which are crucial for scalable quantum computing [2].\n",
"\n",
"### 1.3 Photonic Quantum Computing\n",
"Photonic quantum computing has seen breakthroughs with companies like Xanadu and PsiQuantum. Xanadu's Borealis, a photonic quantum computer, demonstrated quantum advantage by solving specific problems faster than classical supercomputers [3]. PsiQuantum is working towards a million-qubit photonic quantum computer, leveraging silicon photonics for scalability [4].\n",
"\n",
"## 2. Quantum Algorithms\n",
"\n",
"### 2.1 Quantum Machine Learning\n",
"Quantum machine learning (QML) is gaining traction as researchers develop algorithms that could outperform classical counterparts. Recent work has focused on hybrid quantum-classical algorithms that leverage quantum speedups for specific tasks like clustering and classification [5].\n",
"\n",
"### 2.2 Quantum Error Correction\n",
"Error correction remains a critical challenge in quantum computing. Recent advances include the development of more efficient error-correcting codes and fault-tolerant architectures. The surface code, a leading error correction method, has seen improvements in its threshold and resource requirements [6].\n",
"\n",
"### 2.3 Quantum Simulation\n",
"Quantum simulation is one of the most promising applications of quantum computing. Recent studies have demonstrated the simulation of complex quantum systems, such as chemical reactions and material properties, with unprecedented accuracy [7].\n",
"\n",
"## 3. Applications and Industry Impact\n",
"\n",
"### 3.1 Cryptography\n",
"Quantum computing poses both threats and opportunities for cryptography. The development of quantum-resistant algorithms is crucial as quantum computers could potentially break widely used encryption methods. The National Institute of Standards and Technology (NIST) is in the process of standardizing post-quantum cryptographic algorithms [8].\n",
"\n",
"### 3.2 Drug Discovery\n",
"Quantum computing is poised to revolutionize drug discovery by enabling the simulation of molecular interactions at a quantum level. Companies like Qubit Pharmaceuticals and Cambridge Quantum Computing are actively working on quantum algorithms for drug discovery, promising faster and more accurate predictions [9].\n",
"\n",
"### 3.3 Optimization Problems\n",
"Quantum computers have the potential to solve complex optimization problems more efficiently than classical computers. This has significant implications for industries such as logistics, finance, and manufacturing. Recent advances include the development of quantum algorithms for portfolio optimization and supply chain management [10].\n",
"\n",
"## 4. Challenges and Future Directions\n",
"\n",
"Despite the rapid progress, several challenges remain in the field of quantum computing. These include improving qubit coherence times, scaling up the number of qubits, and developing robust error correction methods. Future research is likely to focus on hybrid quantum-classical systems, which combine the strengths of both paradigms to tackle complex problems.\n",
"\n",
"## Conclusion\n",
"\n",
"Quantum computing is advancing at a remarkable pace, with significant developments in hardware, algorithms, and applications. As the field continues to mature, it holds the promise of transforming industries and solving problems that are currently intractable for classical computers. Continued investment in research and development, along with collaboration between academia and industry, will be crucial to realizing the full potential of quantum computing.\n",
"\n",
"## References\n",
"\n",
"1. IBM Research. (2023). IBM Quantum Roadmap. Retrieved from https://research.ibm.com/quantum-computing/roadmap\n",
"2. IonQ. (2023). IonQ's Quantum Computing Technology. Retrieved from https://ionq.com/technology\n",
"3. Xanadu. (2023). Borealis: A Photonic Quantum Computer. Retrieved from https://xanadu.ai/borealis\n",
"4. PsiQuantum. (2023). Photonic Quantum Computing. Retrieved from https://psiquantum.com/technology\n",
"5. Biamonte, J., et al. (2023). Quantum Machine Learning. Nature Reviews Physics.\n",
"6. Fowler, A. G., et al. (2023). Surface Codes: Towards Practical Quantum Computing. Physical Review A.\n",
"7. Aspuru-Guzik, A., et al. (2023). Quantum Simulation of Chemical Systems. Chemical Reviews.\n",
"8. NIST. (2023). Post-Quantum Cryptography Standardization. Retrieved from https://csrc.nist.gov/Projects/post-quantum-cryptography\n",
"9. Qubit Pharmaceuticals. (2023). Quantum Computing in Drug Discovery. Retrieved from https://qubit-pharmaceuticals.com/quantum-computing\n",
"10. Venturelli, D., et al. (2023). Quantum Optimization Algorithms. Journal of Quantum Information Processing.\n"
]
}
],
"source": [
"from praisonaiagents import Agent\n",
"\n",
"# User input (for demo, hardcoded; in real use, use input() or widgets)\n",
"topic = \"Recent advances in quantum computing\"\n",
"\n",
"# Use the custom tool\n",
"tool = DummyDeepResearchTool(topic)\n",
"dummy_report = tool.research()\n",
"\n",
"if not is_valid_key(OPENAI_API_KEY, \"sk\"):\n",
" print(\"API key not set or is a placeholder. Using dummy research report for CI/testing.\")\n",
" print(dummy_report)\n",
"else:\n",
" prompt = f\"\"\"\n",
" You are a domain research assistant. Perform deep research on the following topic and provide a structured, well-cited report:\n",
" TOPIC: {topic}\n",
" \"\"\"\n",
" agent = Agent(\n",
" name=\"Domain Deep Research Agent\",\n",
" instructions=prompt,\n",
" api_key=OPENAI_API_KEY\n",
" )\n",
" report = agent.start(prompt)\n",
" print(report)"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
@@ -0,0 +1,689 @@
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
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},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
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"language_info": {
"name": "python"
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"widgets": {
"application/vnd.jupyter.widget-state+json": {
"4ab88bfcb62e4f9a8db7e35aefbae00a": {
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"data": {
"text/plain": "\u001b[32m╭─\u001b[0m\u001b[32m─────────────────────────────────────────────\u001b[0m\u001b[32m Generating... 23.2s \u001b[0m\u001b[32m─────────────────────────────────────────────\u001b[0m\u001b[32m─╮\u001b[0m\n\u001b[32m│\u001b[0m [INTRO MUSIC FADES IN] \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[1mAlex\u001b[0m: Hello and welcome to another episode of \"The World Today,\" where we dive into the latest in technology \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m and world news. I'm Alex, your go-to for all things analytical and fact-focused. \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[1mMorgan\u001b[0m: And I'm Morgan, here to explore the human impact and social context of today's stories. We've got a \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m fascinating lineup for you today, so let's dive right in! \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[1mAlex\u001b[0m: First up, we're talking about a topic that's been making waves across the healthcare industry: the role \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m of artificial intelligence. According to a recent article from \u001b]8;id=672819;https://news.example.com/ai-healthcare\u001b\\\u001b[4;34mNews Example\u001b[0m\u001b]8;;\u001b\\, AI is revolutionizing healthcare \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m in ways we could only dream of a decade ago. \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[1mMorgan\u001b[0m: That's right, Alex. AI is not just a buzzword anymore; it's actively changing how we approach \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m healthcare. From diagnostics to treatment plans, AI is helping doctors make more accurate decisions faster. But \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m what does this mean for patients and healthcare professionals? \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[1mAlex\u001b[0m: Well, Morgan, AI's ability to analyze vast amounts of data quickly means that doctors can diagnose \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m diseases earlier and more accurately. For instance, AI algorithms can now detect patterns in medical imaging \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m that might be too subtle for the human eye. This can lead to earlier interventions and better patient outcomes. \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[1mMorgan\u001b[0m: And let's not forget about the human side of things. For patients, this means less waiting time for \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m results and potentially more personalized treatment plans. But there's also a concern about the human touch in \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m healthcare. How do we balance the efficiency of AI with the empathy and understanding that only a human can \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m provide? \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m \u001b[1mAlex\u001b[0m: That's a great point. The integration of AI in healthcare does raise ethical questions. For example, who \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m is responsible if an AI system makes a mistake? And how do we ensure that these systems are free from bias? \u001b[32m│\u001b[0m\n\u001b[32m│\u001b[0m Line truncated
"text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">╭────────────────────────────────────────────── Generating... 23.2s ──────────────────────────────────────────────╮</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> [INTRO MUSIC FADES IN] <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"font-weight: bold\">Alex</span>: Hello and welcome to another episode of \"The World Today,\" where we dive into the latest in technology <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> and world news. I'm Alex, your go-to for all things analytical and fact-focused. <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"font-weight: bold\">Morgan</span>: And I'm Morgan, here to explore the human impact and social context of today's stories. We've got a <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> fascinating lineup for you today, so let's dive right in! <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"font-weight: bold\">Alex</span>: First up, we're talking about a topic that's been making waves across the healthcare industry: the role <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> of artificial intelligence. According to a recent article from <a href=\"https://news.example.com/ai-healthcare\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">News Example</span></a>, AI is revolutionizing healthcare <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> in ways we could only dream of a decade ago. <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"font-weight: bold\">Morgan</span>: That's right, Alex. AI is not just a buzzword anymore; it's actively changing how we approach <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> healthcare. From diagnostics to treatment plans, AI is helping doctors make more accurate decisions faster. But <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> what does this mean for patients and healthcare professionals? <span style=\"color: #008000; text-decoration-color: #008000\">│</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"coloLine truncated
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"cells": [
{
"cell_type": "markdown",
"source": [
"# News and Podcast Aggregator Agent using PraisonAIAgents"
],
"metadata": {
"id": "5DpLQOaCmYbu"
}
},
{
"cell_type": "markdown",
"source": [
"This notebook demonstrates a News and Podcast Aggregator Agent built with `praisonaiagents`. \n",
"It summarizes news articles and generates podcast-style discussion points. \n",
"The notebook is CI-friendly: it uses dummy data if API keys are not set, so all tests/checks will pass."
],
"metadata": {
"id": "qmVwAahwmYTZ"
}
},
{
"cell_type": "markdown",
"source": [
"[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Dhivya-Bharathy/PraisonAI/blob/main/examples/cookbooks/SocialMedia_Content_Agents/News_And_Podcast_Aggregator_Agent.ipynb)\n"
],
"metadata": {
"id": "tYRRrgqHqbuN"
}
},
{
"cell_type": "markdown",
"source": [
"# Dependencies"
],
"metadata": {
"id": "baTmwAjYmfDg"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "IIm2awOXmXB9"
},
"outputs": [],
"source": [
"!pip install praisonaiagents pydantic"
]
},
{
"cell_type": "markdown",
"source": [
"# Imports and Setup"
],
"metadata": {
"id": "kqNfe5S2mjnn"
}
},
{
"cell_type": "code",
"source": [
"import os\n",
"\n",
"# Set up the OpenAI API key for praisonaiagents\n",
"os.environ[\"OPENAI_API_KEY\"] = os.environ.get(\"OPENAI_API_KEY\", \"sk-..\")\n",
"\n",
"def is_valid_key(key, prefix):\n",
" return key and key != f\"{prefix}-..\" and key.startswith(prefix)\n",
"\n",
"OPENAI_API_KEY = os.environ[\"OPENAI_API_KEY\"]"
],
"metadata": {
"id": "A-OXlt2gmpUS"
},
"execution_count": 3,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# Tools"
],
"metadata": {
"id": "IJmdTrCDoufF"
}
},
{
"cell_type": "code",
"source": [
"from datetime import datetime\n",
"from typing import List\n",
"\n",
"def format_search_results_for_podcast(search_results: List[dict]) -> tuple[str, List[str]]:\n",
" \"\"\"\n",
" Custom tool to format search results for podcast script generation.\n",
" \"\"\"\n",
" created_at = datetime.now().strftime(\"%B %d, %Y at %I:%M %p\")\n",
" structured_content = []\n",
" structured_content.append(f\"PODCAST CREATION: {created_at}\\n\")\n",
" sources = []\n",
" for idx, search_result in enumerate(search_results):\n",
" try:\n",
" if search_result.get(\"confirmed\", False):\n",
" sources.append(search_result[\"url\"])\n",
" structured_content.append(\n",
" f\"\"\"\n",
" SOURCE {idx + 1}:\n",
" Title: {search_result['title']}\n",
" URL: {search_result['url']}\n",
" Content: {search_result.get('full_text') or search_result.get('description', '')}\n",
" ---END OF SOURCE {idx + 1}---\n",
" \"\"\".strip()\n",
" )\n",
" except Exception as e:\n",
" print(f\"Error processing search result: {e}\")\n",
" content_texts = \"\\n\\n\".join(structured_content)\n",
" return content_texts, sources"
],
"metadata": {
"id": "yHj7Grvmov4C"
},
"execution_count": 4,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# Pydantic Models"
],
"metadata": {
"id": "eMYs7Oibo1M3"
}
},
{
"cell_type": "code",
"source": [
"from pydantic import BaseModel, Field\n",
"from typing import List, Optional\n",
"\n",
"class Dialog(BaseModel):\n",
" speaker: str = Field(..., description=\"The speaker name (SHOULD BE 'ALEX' OR 'MORGAN')\")\n",
" text: str = Field(..., description=\"The spoken text content for this speaker based on the requested language, default is English\")\n",
"\n",
"class Section(BaseModel):\n",
" type: str = Field(..., description=\"The section type (intro, headlines, article, outro)\")\n",
" title: Optional[str] = Field(None, description=\"Optional title for the section (required for article type)\")\n",
" dialog: List[Dialog] = Field(..., description=\"List of dialog exchanges between speakers\")\n",
"\n",
"class PodcastScript(BaseModel):\n",
" title: str = Field(..., description=\"The podcast episode title with date\")\n",
" sections: List[Section] = Field(..., description=\"List of podcast sections (intro, headlines, articles, outro)\")"
],
"metadata": {
"id": "Z4uBU68eo2L_"
},
"execution_count": 5,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# Agent Instructions"
],
"metadata": {
"id": "sRTr9D35o-5D"
}
},
{
"cell_type": "code",
"source": [
"from textwrap import dedent\n",
"\n",
"PODCAST_AGENT_DESCRIPTION = \"You are a helpful assistant that can generate engaging podcast scripts for the given sources.\"\n",
"PODCAST_AGENT_INSTRUCTIONS = dedent(\"\"\"\n",
" You are a helpful assistant that can generate engaging podcast scripts for the given source content and query.\n",
" For given content, create an engaging podcast script that should be at least 15 minutes worth of content and you are allowed to enhance the script beyond given sources if you know something additional info will be interesting to the discussion or not enough content is available.\n",
" You use the provided sources to ground your podcast script generation process. Keep it engaging and interesting.\n",
" IMPORTANT: Generate the entire script in the provided language.\n",
" CONTENT GUIDELINES:\n",
" - Provide insightful analysis that helps the audience understand the significance\n",
" - Include discussions on potential implications and broader context of each story\n",
" - Explain complex concepts in an accessible but thorough manner\n",
" - Make connections between current and relevant historical developments when applicable\n",
" - Provide comparisons and contrasts with similar stories or trends when relevant\n",
" PERSONALITY NOTES:\n",
" - Alex is more analytical and fact-focused\n",
" - Morgan is more focused on human impact, social context, and practical applications\n",
" - Include natural, conversational banter and smooth transitions between topics\n",
" - Each article discussion should go beyond the basic summary to provide valuable insights\n",
" - Maintain a conversational but informed tone that would appeal to a general audience\n",
" IMPORTANT:\n",
" - MAKE SURE PODCAST SCRIPTS ARE AT LEAST 15 MINUTES LONG WHICH MEANS YOU NEED TO HAVE DETAILED DISCUSSIONS BUT KEEP IT INTERESTING AND ENGAGING.\n",
"\"\"\")"
],
"metadata": {
"id": "quslT1kFo_yc"
},
"execution_count": 6,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# Dummy Data and Main Logic"
],
"metadata": {
"id": "bicXivCipLZY"
}
},
{
"cell_type": "code",
"source": [
"from praisonaiagents import Agent\n",
"\n",
"# Dummy search results for CI/public use\n",
"dummy_search_results = [\n",
" {\n",
" \"confirmed\": True,\n",
" \"title\": \"AI Revolutionizes Healthcare\",\n",
" \"url\": \"https://news.example.com/ai-healthcare\",\n",
" \"full_text\": \"Artificial intelligence is transforming the healthcare industry by...\"\n",
" },\n",
" {\n",
" \"confirmed\": True,\n",
" \"title\": \"Climate Change and Global Policy\",\n",
" \"url\": \"https://news.example.com/climate-policy\",\n",
" \"full_text\": \"World leaders are meeting to discuss new policies for climate change...\"\n",
" }\n",
"]\n",
"\n",
"query = \"Latest technology and world news\"\n",
"language_name = \"English\"\n",
"\n",
"content_texts, sources = format_search_results_for_podcast(dummy_search_results)\n",
"\n",
"if not is_valid_key(OPENAI_API_KEY, \"sk\"):\n",
" print(\"API key not set or is a placeholder. Using dummy podcast script for CI/testing.\")\n",
" print(\"=== Podcast Script ===\")\n",
" print(f\"Podcast Title: Tech & World News Roundup ({datetime.now().strftime('%B %d, %Y')})\")\n",
" for idx, article in enumerate(dummy_search_results):\n",
" print(f\"\\nSection {idx+1}: {article['title']}\")\n",
" print(f\"Summary: {article['full_text'][:80]}...\")\n",
"else:\n",
" agent = Agent(\n",
" name=\"Podcast Script Agent\",\n",
" instructions=PODCAST_AGENT_INSTRUCTIONS,\n",
" api_key=OPENAI_API_KEY\n",
" )\n",
" prompt = f\"query: {query}\\nlanguage_name: {language_name}\\ncontent_texts: {content_texts}\\nIMPORTANT: texts should be in {language_name} language.\"\n",
" podcast_script = agent.start(prompt)\n",
" print(\"=== Podcast Script ===\")\n",
" print(podcast_script)"
],
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"\u001b[38;2;210;227;200m╭─\u001b[0m\u001b[38;2;210;227;200m \u001b[0m\u001b[1;38;2;210;227;200mAgent Info\u001b[0m\u001b[38;2;210;227;200m \u001b[0m\u001b[38;2;210;227;200m───────────────────────────────────────────────────────────────────────────────────────────────────\u001b[0m\u001b[38;2;210;227;200m─╮\u001b[0m\n",
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\">╭─ </span><span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8; font-weight: bold\">Agent Info</span><span style=\"color: #d2e3c8; text-decoration-color: #d2e3c8\"> ────────────────────────────────────────────────────────────────────────────────────────────────────╮</span>\n",
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"\u001b[36m╭─\u001b[0m\u001b[36m──────────────────────────────────────────────────\u001b[0m\u001b[36m Response \u001b[0m\u001b[36m───────────────────────────────────────────────────\u001b[0m\u001b[36m─╮\u001b[0m\n",
"\u001b[36m│\u001b[0m [INTRO MUSIC FADES IN] \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: Hello and welcome to another episode of \"The World Today,\" where we dive into the latest in technology \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m and world news. I'm Alex, your go-to for all things analytical and fact-focused. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: And I'm Morgan, here to explore the human impact and social context of today's stories. We've got a \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m fascinating lineup for you today, so let's dive right in! \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: First up, we're talking about a topic that's been making waves across the healthcare industry: the role \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m of artificial intelligence. According to a recent article from \u001b]8;id=890061;https://news.example.com/ai-healthcare\u001b\\\u001b[4;34mNews Example\u001b[0m\u001b]8;;\u001b\\, AI is revolutionizing healthcare \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m in ways we could only dream of a decade ago. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: That's right, Alex. AI is not just a buzzword anymore; it's actively changing how we approach \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m healthcare. From diagnostics to treatment plans, AI is helping doctors make more accurate decisions faster. But \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m what does this mean for patients and healthcare professionals? \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: Well, Morgan, AI's ability to analyze vast amounts of data quickly means that doctors can diagnose \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m diseases earlier and more accurately. For instance, AI algorithms can now detect patterns in medical imaging \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m that might be too subtle for the human eye. This can lead to earlier interventions and better patient outcomes. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: And let's not forget about the human side of things. For patients, this means less waiting time for \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m results and potentially more personalized treatment plans. But there's also a concern about the human touch in \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m healthcare. How do we balance the efficiency of AI with the empathy and understanding that only a human can \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m provide? \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: That's a great point. The integration of AI in healthcare does raise ethical questions. For example, who \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m is responsible if an AI system makes a mistake? And how do we ensure that these systems are free from bias? \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: Exactly. There's a lot to consider, but the potential benefits are enormous. Imagine a world where \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m healthcare is not only more efficient but also more accessible to people in remote areas thanks to AI-driven \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m telemedicine. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: It's a fascinating time for healthcare, no doubt. But let's shift gears a bit and talk about another \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m pressing issue: climate change and global policy. According to a report from \u001b]8;id=2198;https://news.example.com/climate-policy\u001b\\\u001b[4;34mNews Example\u001b[0m\u001b]8;;\u001b\\, world leaders are \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m currently meeting to discuss new policies to combat climate change. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: Climate change is one of those issues that affects everyone, regardless of where you live. These global \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m meetings are crucial because they set the stage for international cooperation. But what are the main challenges \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m these leaders face? \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: One of the biggest challenges is balancing economic growth with environmental sustainability. Many \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m developing countries argue that they need to prioritize economic development, which often relies on fossil \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m fuels. Meanwhile, developed countries are pushing for stricter environmental regulations. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: It's a classic case of differing priorities. But there's also a growing recognition that climate change \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m doesn't respect borders. Extreme weather events, rising sea levels, and shifting agricultural patterns affect \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m us all. So, there's a real urgency to find common ground. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: And technology plays a significant role here too. Innovations in renewable energy, carbon capture, and \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m sustainable agriculture are crucial in the fight against climate change. But implementing these technologies on \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m a global scale requires significant investment and political will. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: It's a complex issue, but it's encouraging to see world leaders coming together to address it. The \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m policies they create today will shape the future for generations to come. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: Absolutely. And it's not just about government action. Individuals and businesses also have a role to \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m play in reducing carbon footprints and advocating for sustainable practices. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: It's a collective effort, and every little bit helps. Before we wrap up, Alex, any final thoughts on \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m today's topics? \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: Just that both AI in healthcare and climate change policies highlight the intersection of technology and \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m society. They show us how innovation can drive progress but also remind us of the responsibilities that come \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m with it. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: Well said, Alex. It's all about finding that balance. And with that, we've reached the end of today's \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m episode. Thanks for tuning in to \"The World Today.\" \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mAlex\u001b[0m: Don't forget to subscribe and join us next time for more insights into the latest in technology and world \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m news. \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[1mMorgan\u001b[0m: Until then, stay informed and stay curious! \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m \u001b[36m│\u001b[0m\n",
"\u001b[36m│\u001b[0m [OUTRO MUSIC FADES OUT] \u001b[36m│\u001b[0m\n",
"\u001b[36m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
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"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> [INTRO MUSIC FADES IN] <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: Hello and welcome to another episode of \"The World Today,\" where we dive into the latest in technology <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> and world news. I'm Alex, your go-to for all things analytical and fact-focused. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: And I'm Morgan, here to explore the human impact and social context of today's stories. We've got a <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> fascinating lineup for you today, so let's dive right in! <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: First up, we're talking about a topic that's been making waves across the healthcare industry: the role <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> of artificial intelligence. According to a recent article from <a href=\"https://news.example.com/ai-healthcare\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">News Example</span></a>, AI is revolutionizing healthcare <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> in ways we could only dream of a decade ago. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: That's right, Alex. AI is not just a buzzword anymore; it's actively changing how we approach <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> healthcare. From diagnostics to treatment plans, AI is helping doctors make more accurate decisions faster. But <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> what does this mean for patients and healthcare professionals? <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: Well, Morgan, AI's ability to analyze vast amounts of data quickly means that doctors can diagnose <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> diseases earlier and more accurately. For instance, AI algorithms can now detect patterns in medical imaging <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> that might be too subtle for the human eye. This can lead to earlier interventions and better patient outcomes. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: And let's not forget about the human side of things. For patients, this means less waiting time for <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> results and potentially more personalized treatment plans. But there's also a concern about the human touch in <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> healthcare. How do we balance the efficiency of AI with the empathy and understanding that only a human can <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> provide? <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: That's a great point. The integration of AI in healthcare does raise ethical questions. For example, who <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> is responsible if an AI system makes a mistake? And how do we ensure that these systems are free from bias? <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: Exactly. There's a lot to consider, but the potential benefits are enormous. Imagine a world where <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> healthcare is not only more efficient but also more accessible to people in remote areas thanks to AI-driven <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> telemedicine. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: It's a fascinating time for healthcare, no doubt. But let's shift gears a bit and talk about another <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> pressing issue: climate change and global policy. According to a report from <a href=\"https://news.example.com/climate-policy\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">News Example</span></a>, world leaders are <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> currently meeting to discuss new policies to combat climate change. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: Climate change is one of those issues that affects everyone, regardless of where you live. These global <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> meetings are crucial because they set the stage for international cooperation. But what are the main challenges <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> these leaders face? <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: One of the biggest challenges is balancing economic growth with environmental sustainability. Many <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> developing countries argue that they need to prioritize economic development, which often relies on fossil <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> fuels. Meanwhile, developed countries are pushing for stricter environmental regulations. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: It's a classic case of differing priorities. But there's also a growing recognition that climate change <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> doesn't respect borders. Extreme weather events, rising sea levels, and shifting agricultural patterns affect <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> us all. So, there's a real urgency to find common ground. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: And technology plays a significant role here too. Innovations in renewable energy, carbon capture, and <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> sustainable agriculture are crucial in the fight against climate change. But implementing these technologies on <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> a global scale requires significant investment and political will. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: It's a complex issue, but it's encouraging to see world leaders coming together to address it. The <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> policies they create today will shape the future for generations to come. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: Absolutely. And it's not just about government action. Individuals and businesses also have a role to <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> play in reducing carbon footprints and advocating for sustainable practices. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: It's a collective effort, and every little bit helps. Before we wrap up, Alex, any final thoughts on <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> today's topics? <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: Just that both AI in healthcare and climate change policies highlight the intersection of technology and <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> society. They show us how innovation can drive progress but also remind us of the responsibilities that come <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> with it. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: Well said, Alex. It's all about finding that balance. And with that, we've reached the end of today's <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> episode. Thanks for tuning in to \"The World Today.\" <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Alex</span>: Don't forget to subscribe and join us next time for more insights into the latest in technology and world <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> news. <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"font-weight: bold\">Morgan</span>: Until then, stay informed and stay curious! <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">│</span> [OUTRO MUSIC FADES OUT] <span style=\"color: #008080; text-decoration-color: #008080\">│</span>\n",
"<span style=\"color: #008080; text-decoration-color: #008080\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"=== Podcast Script ===\n",
"[INTRO MUSIC FADES IN]\n",
"\n",
"**Alex**: Hello and welcome to another episode of \"The World Today,\" where we dive into the latest in technology and world news. I'm Alex, your go-to for all things analytical and fact-focused.\n",
"\n",
"**Morgan**: And I'm Morgan, here to explore the human impact and social context of today's stories. We've got a fascinating lineup for you today, so let's dive right in!\n",
"\n",
"**Alex**: First up, we're talking about a topic that's been making waves across the healthcare industry: the role of artificial intelligence. According to a recent article from [News Example](https://news.example.com/ai-healthcare), AI is revolutionizing healthcare in ways we could only dream of a decade ago.\n",
"\n",
"**Morgan**: That's right, Alex. AI is not just a buzzword anymore; it's actively changing how we approach healthcare. From diagnostics to treatment plans, AI is helping doctors make more accurate decisions faster. But what does this mean for patients and healthcare professionals?\n",
"\n",
"**Alex**: Well, Morgan, AI's ability to analyze vast amounts of data quickly means that doctors can diagnose diseases earlier and more accurately. For instance, AI algorithms can now detect patterns in medical imaging that might be too subtle for the human eye. This can lead to earlier interventions and better patient outcomes.\n",
"\n",
"**Morgan**: And let's not forget about the human side of things. For patients, this means less waiting time for results and potentially more personalized treatment plans. But there's also a concern about the human touch in healthcare. How do we balance the efficiency of AI with the empathy and understanding that only a human can provide?\n",
"\n",
"**Alex**: That's a great point. The integration of AI in healthcare does raise ethical questions. For example, who is responsible if an AI system makes a mistake? And how do we ensure that these systems are free from bias?\n",
"\n",
"**Morgan**: Exactly. There's a lot to consider, but the potential benefits are enormous. Imagine a world where healthcare is not only more efficient but also more accessible to people in remote areas thanks to AI-driven telemedicine.\n",
"\n",
"**Alex**: It's a fascinating time for healthcare, no doubt. But let's shift gears a bit and talk about another pressing issue: climate change and global policy. According to a report from [News Example](https://news.example.com/climate-policy), world leaders are currently meeting to discuss new policies to combat climate change.\n",
"\n",
"**Morgan**: Climate change is one of those issues that affects everyone, regardless of where you live. These global meetings are crucial because they set the stage for international cooperation. But what are the main challenges these leaders face?\n",
"\n",
"**Alex**: One of the biggest challenges is balancing economic growth with environmental sustainability. Many developing countries argue that they need to prioritize economic development, which often relies on fossil fuels. Meanwhile, developed countries are pushing for stricter environmental regulations.\n",
"\n",
"**Morgan**: It's a classic case of differing priorities. But there's also a growing recognition that climate change doesn't respect borders. Extreme weather events, rising sea levels, and shifting agricultural patterns affect us all. So, there's a real urgency to find common ground.\n",
"\n",
"**Alex**: And technology plays a significant role here too. Innovations in renewable energy, carbon capture, and sustainable agriculture are crucial in the fight against climate change. But implementing these technologies on a global scale requires significant investment and political will.\n",
"\n",
"**Morgan**: It's a complex issue, but it's encouraging to see world leaders coming together to address it. The policies they create today will shape the future for generations to come.\n",
"\n",
"**Alex**: Absolutely. And it's not just about government action. Individuals and businesses also have a role to play in reducing carbon footprints and advocating for sustainable practices.\n",
"\n",
"**Morgan**: It's a collective effort, and every little bit helps. Before we wrap up, Alex, any final thoughts on today's topics?\n",
"\n",
"**Alex**: Just that both AI in healthcare and climate change policies highlight the intersection of technology and society. They show us how innovation can drive progress but also remind us of the responsibilities that come with it.\n",
"\n",
"**Morgan**: Well said, Alex. It's all about finding that balance. And with that, we've reached the end of today's episode. Thanks for tuning in to \"The World Today.\"\n",
"\n",
"**Alex**: Don't forget to subscribe and join us next time for more insights into the latest in technology and world news.\n",
"\n",
"**Morgan**: Until then, stay informed and stay curious!\n",
"\n",
"[OUTRO MUSIC FADES OUT]\n"
]
}
]
}
]
}
@@ -0,0 +1,108 @@
#!/usr/bin/env python
# coding: utf-8
"""
News and Podcast Aggregator Agent using PraisonAIAgents
This script summarizes news articles and generates podcast-style discussion points.
It is CI-friendly: it uses dummy data if API keys are not set.
"""
import os
from datetime import datetime
from praisonaiagents import Agent
# Set up the OpenAI API key for praisonaiagents
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY", "sk-..")
os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
def is_valid_key(key, prefix):
return key and key != f"{prefix}-.." and key.startswith(prefix)
# Custom Tool: Format search results for podcast
def format_search_results_for_podcast(search_results):
created_at = datetime.now().strftime("%B %d, %Y at %I:%M %p")
structured_content = []
structured_content.append(f"PODCAST CREATION: {created_at}\n")
sources = []
for idx, search_result in enumerate(search_results):
try:
if search_result.get("confirmed", False):
sources.append(search_result["url"])
structured_content.append(
f"""
SOURCE {idx + 1}:
Title: {search_result['title']}
URL: {search_result['url']}
Content: {search_result.get('full_text') or search_result.get('description', '')}
---END OF SOURCE {idx + 1}---
""".strip()
)
except Exception as e:
print(f"Error processing search result: {e}")
content_texts = "\n\n".join(structured_content)
return content_texts, sources
# Agent Instructions
from textwrap import dedent
PODCAST_AGENT_INSTRUCTIONS = dedent("""
You are a helpful assistant that can generate engaging podcast scripts for the given source content and query.
For given content, create an engaging podcast script that should be at least 15 minutes worth of content and you are allowed to enhance the script beyond given sources if you know something additional info will be interesting to the discussion or not enough content is available.
You use the provided sources to ground your podcast script generation process. Keep it engaging and interesting.
IMPORTANT: Generate the entire script in the provided language.
CONTENT GUIDELINES:
- Provide insightful analysis that helps the audience understand the significance
- Include discussions on potential implications and broader context of each story
- Explain complex concepts in an accessible but thorough manner
- Make connections between current and relevant historical developments when applicable
- Provide comparisons and contrasts with similar stories or trends when relevant
PERSONALITY NOTES:
- Alex is more analytical and fact-focused
- Morgan is more focused on human impact, social context, and practical applications
- Include natural, conversational banter and smooth transitions between topics
- Each article discussion should go beyond the basic summary to provide valuable insights
- Maintain a conversational but informed tone that would appeal to a general audience
IMPORTANT:
- MAKE SURE PODCAST SCRIPTS ARE AT LEAST 15 MINUTES LONG WHICH MEANS YOU NEED TO HAVE DETAILED DISCUSSIONS BUT KEEP IT INTERESTING AND ENGAGING.
""")
if __name__ == "__main__":
# Dummy search results for CI/public use
dummy_search_results = [
{
"confirmed": True,
"title": "AI Revolutionizes Healthcare",
"url": "https://news.example.com/ai-healthcare",
"full_text": "Artificial intelligence is transforming the healthcare industry by..."
},
{
"confirmed": True,
"title": "Climate Change and Global Policy",
"url": "https://news.example.com/climate-policy",
"full_text": "World leaders are meeting to discuss new policies for climate change..."
}
]
query = "Latest technology and world news"
language_name = "English"
content_texts, sources = format_search_results_for_podcast(dummy_search_results)
if not is_valid_key(OPENAI_API_KEY, "sk"):
print("API key not set or is a placeholder. Using dummy podcast script for CI/testing.")
print("=== Podcast Script ===")
print(f"Podcast Title: Tech & World News Roundup ({datetime.now().strftime('%B %d, %Y')})")
for idx, article in enumerate(dummy_search_results):
print(f"\nSection {idx+1}: {article['title']}")
print(f"Summary: {article['full_text'][:80]}...")
else:
agent = Agent(
name="Podcast Script Agent",
instructions=PODCAST_AGENT_INSTRUCTIONS,
api_key=OPENAI_API_KEY
)
prompt = f"query: {query}\nlanguage_name: {language_name}\ncontent_texts: {content_texts}\nIMPORTANT: texts should be in {language_name} language."
podcast_script = agent.start(prompt)
print("=== Podcast Script ===")
print(podcast_script)
@@ -0,0 +1,165 @@
#!/usr/bin/env python
# coding: utf-8
"""
Air Quality Analysis Agent using PraisonAIAgents
This script retrieves real-time air quality data for a specified location, analyzes the results, and provides actionable health recommendations.
It uses only praisonaiagents and is CI-friendly: it uses dummy data if API keys are not set.
"""
import os
import requests
import yaml
from praisonaiagents import Agent
# Set up API keys
FIRECRAWL_API_KEY = os.environ.get("FIRECRAWL_API_KEY", "fc-..")
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY", "sk-..")
os.environ["FIRECRAWL_API_KEY"] = FIRECRAWL_API_KEY
os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
# Tool: AQI Data Fetcher
class AQIDataFetcher:
def __init__(self, firecrawl_key: str):
from firecrawl import FirecrawlApp
self.firecrawl = FirecrawlApp(api_key=firecrawl_key)
def fetch(self, country: str, state: str, city: str):
country_clean = country.lower().replace(' ', '-')
city_clean = city.lower().replace(' ', '-')
if not state or state.lower() == 'none':
url = f"https://www.aqi.in/dashboard/{country_clean}/{city_clean}"
else:
state_clean = state.lower().replace(' ', '-')
url = f"https://www.aqi.in/dashboard/{country_clean}/{state_clean}/{city_clean}"
print(f"Testing URL: {url}")
try:
resp = requests.get(url)
print(f"Status code: {resp.status_code}")
if resp.status_code != 200:
print(f"URL not reachable: {url} (status code: {resp.status_code})")
return None
except Exception as e:
print(f"Error: {e}")
return None
schema = {
"type": "object",
"properties": {
"aqi": {"type": "number", "description": "Air Quality Index"},
"temperature": {"type": "number", "description": "Temperature in degrees Celsius"},
"humidity": {"type": "number", "description": "Humidity percentage"},
"wind_speed": {"type": "number", "description": "Wind speed in kilometers per hour"},
"pm25": {"type": "number", "description": "Particulate Matter 2.5 micrometers"},
"pm10": {"type": "number", "description": "Particulate Matter 10 micrometers"},
"co": {"type": "number", "description": "Carbon Monoxide level"}
},
"required": ["aqi", "temperature", "humidity", "wind_speed", "pm25", "pm10", "co"]
}
response = self.firecrawl.extract(
urls=[f"{url}/*"],
prompt='Extract the current real-time AQI, temperature, humidity, wind speed, PM2.5, PM10, and CO levels from the page. Also extract the timestamp of the data.',
schema=schema
)
return response
# YAML prompt (for documentation/logging)
yaml_prompt = """
agent:
name: Air Quality Health Advisor
description: |
An agent that analyzes real-time air quality data for a given location and provides personalized health recommendations based on user context.
tools:
- name: AQIDataFetcher
description: Fetches AQI and weather data for a specified city, state, and country using Firecrawl.
workflow:
- step: Fetch AQI data for the user's location using AQIDataFetcher.
- step: Analyze AQI and weather data.
- step: Consider user's medical conditions and planned activity.
- step: Generate health and activity recommendations.
inputs:
- city
- state
- country
- medical_conditions
- planned_activity
outputs:
- recommendations
"""
print(yaml.safe_load(yaml_prompt))
if __name__ == "__main__":
# User input (you can change these for other locations)
user_city = "Mumbai"
user_state = "Maharashtra"
user_country = "India"
user_medical_conditions = "asthma"
user_planned_activity = "morning jog for 2 hours"
aqi_fetcher = AQIDataFetcher(firecrawl_key=os.environ["FIRECRAWL_API_KEY"])
# Try with state, then without state, then fallback to Delhi
aqi_data = aqi_fetcher.fetch(
country=user_country,
state=user_state,
city=user_city
)
if not aqi_data or not hasattr(aqi_data, "data"):
print("Mumbai with state failed, trying without state...")
aqi_data = aqi_fetcher.fetch(
country=user_country,
state="",
city=user_city
)
if not aqi_data or not hasattr(aqi_data, "data"):
print("Trying Delhi, India...")
aqi_data = aqi_fetcher.fetch(
country="India",
state="",
city="Delhi"
)
if not aqi_data or not hasattr(aqi_data, "data"):
print("Failed to fetch AQI data for all tried locations. Please check the URLs manually.")
else:
aqi_data = aqi_data.data # Convert to dict
prompt = f"""
You are an expert health advisor.
Based on the following air quality conditions in {user_city}, {user_state}, {user_country}:
- Overall AQI: {aqi_data.get('aqi', 'N/A')}
- PM2.5 Level: {aqi_data.get('pm25', 'N/A')} µg/m³
- PM10 Level: {aqi_data.get('pm10', 'N/A')} µg/m³
- CO Level: {aqi_data.get('co', 'N/A')} ppb
Weather conditions:
- Temperature: {aqi_data.get('temperature', 'N/A')}°C
- Humidity: {aqi_data.get('humidity', 'N/A')}%
- Wind Speed: {aqi_data.get('wind_speed', 'N/A')} km/h
User's Context:
- Medical Conditions: {user_medical_conditions or 'None'}
- Planned Activity: {user_planned_activity}
**Comprehensive Health Recommendations:**
1. **Impact of Current Air Quality on Health:**
2. **Necessary Safety Precautions for Planned Activity:**
3. **Advisability of Planned Activity:**
4. **Best Time to Conduct the Activity:**
"""
agent = Agent(
name="Air Quality Health Advisor",
instructions=prompt,
api_key=os.environ["OPENAI_API_KEY"]
)
recommendations = agent.start(prompt)
print("=== Air Quality Analysis Agent Recommendations ===")
print(recommendations)
@@ -0,0 +1,107 @@
#!/usr/bin/env python
# coding: utf-8
"""
Game Playing Agent (Tic Tac Toe) using PraisonAIAgents
Two AI agents play against each other, coordinated by a referee agent.
This script is CI-friendly: it uses dummy moves if API keys are not set.
"""
import os
from praisonaiagents import Agent
# Set up key (robust, CI-safe)
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY", "sk-..")
os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
def is_valid_key(key, prefix):
return key and key != f"{prefix}-.." and key.startswith(prefix)
# Custom Tool: Tic Tac Toe Board & Logic
class TicTacToeBoard:
def __init__(self):
self.board = [[" " for _ in range(3)] for _ in range(3)]
self.current_player = "X"
def display(self):
for row in self.board:
print("|".join(row))
print("-" * 5)
def valid_moves(self):
return [(i, j) for i in range(3) for j in range(3) if self.board[i][j] == " "]
def make_move(self, row, col):
if self.board[row][col] == " ":
self.board[row][col] = self.current_player
self.current_player = "O" if self.current_player == "X" else "X"
return True
return False
def check_winner(self):
lines = self.board + [list(col) for col in zip(*self.board)] # rows and columns
lines += [[self.board[i][i] for i in range(3)], [self.board[i][2-i] for i in range(3)]] # diagonals
for line in lines:
if line == ["X"] * 3:
return "X"
if line == ["O"] * 3:
return "O"
if all(cell != " " for row in self.board for cell in row):
return "Draw"
return None
if __name__ == "__main__":
# Dummy agent moves for CI/public use
dummy_moves = [(0, 0), (1, 1), (0, 1), (1, 0), (0, 2)]
board = TicTacToeBoard()
winner = None
if not is_valid_key(OPENAI_API_KEY, "sk"):
print("API key not set or is a placeholder. Using dummy moves for CI/testing.")
print("=== Tic Tac Toe Game ===")
board.display()
for move in dummy_moves:
board.make_move(*move)
board.display()
winner = board.check_winner()
if winner:
print(f"Winner: {winner}")
break
if not winner:
print("Game ended in a draw.")
else:
# Real agent-vs-agent play using praisonaiagents
player_x = Agent(
name="Player X",
instructions="You are Player X. Choose your move as 'row col' (e.g., '1 2').",
api_key=OPENAI_API_KEY
)
player_o = Agent(
name="Player O",
instructions="You are Player O. Choose your move as 'row col' (e.g., '1 2').",
api_key=OPENAI_API_KEY
)
print("=== Tic Tac Toe Game (AI vs AI) ===")
board.display()
for _ in range(9):
current_agent = player_x if board.current_player == "X" else player_o
prompt = f"Current board:\n{board.board}\nValid moves: {board.valid_moves()}\nYour move (row col):"
move_str = current_agent.start(prompt)
try:
row, col = map(int, move_str.strip().split())
except Exception:
print(f"Invalid move from agent: {move_str}. Skipping turn.")
continue
if (row, col) not in board.valid_moves():
print(f"Illegal move: {row} {col}. Skipping turn.")
continue
board.make_move(row, col)
board.display()
winner = board.check_winner()
if winner:
print(f"Winner: {winner}")
break
if not winner:
print("Game ended in a draw.")
@@ -0,0 +1,55 @@
#!/usr/bin/env python
# coding: utf-8
"""
Domain Deep Research Agent using PraisonAIAgents
This script performs deep research on a given topic and provides a structured report.
It is CI-friendly: it uses dummy data if API keys are not set.
"""
import os
from praisonaiagents import Agent
# Set up key (robust, CI-safe)
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY", "sk-..")
os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
def is_valid_key(key, prefix):
return key and key != f"{prefix}-.." and key.startswith(prefix)
# Custom Tool: Dummy Deep Research Tool
class DummyDeepResearchTool:
"""
Custom tool to simulate deep research for CI/public use.
"""
def __init__(self, topic):
self.topic = topic
def research(self):
# For demo/CI, just return a dummy report
return f"## Research Report on {self.topic}\n\n- Key finding 1 about {self.topic}\n- Key finding 2 about {self.topic}\n- Key finding 3 about {self.topic}\n"
if __name__ == "__main__":
# User input (for demo, hardcoded; in real use, use input() or widgets)
topic = "Recent advances in quantum computing"
# Use the custom tool
tool = DummyDeepResearchTool(topic)
dummy_report = tool.research()
if not is_valid_key(OPENAI_API_KEY, "sk"):
print("API key not set or is a placeholder. Using dummy research report for CI/testing.")
print(dummy_report)
else:
prompt = f"""
You are a domain research assistant. Perform deep research on the following topic and provide a structured, well-cited report:
TOPIC: {topic}
"""
agent = Agent(
name="Domain Deep Research Agent",
instructions=prompt,
api_key=OPENAI_API_KEY
)
report = agent.start(prompt)
print(report)
@@ -0,0 +1,169 @@
#!/usr/bin/env python
# coding: utf-8
# # News and Podcast Aggregator Agent using PraisonAIAgents
# This notebook demonstrates a News and Podcast Aggregator Agent built with `praisonaiagents`.
# It summarizes news articles and generates podcast-style discussion points.
# The notebook is CI-friendly: it uses dummy data if API keys are not set, so all tests/checks will pass.
# [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Dhivya-Bharathy/PraisonAI/blob/main/examples/cookbooks/SocialMedia_Content_Agents/News_And_Podcast_Aggregator_Agent.ipynb)
#
# # Dependencies
# In[ ]:
get_ipython().system('pip install praisonaiagents pydantic')
# # Imports and Setup
# In[3]:
import os
# Set up the OpenAI API key for praisonaiagents
os.environ["OPENAI_API_KEY"] = os.environ.get("OPENAI_API_KEY", "sk-..")
def is_valid_key(key, prefix):
return key and key != f"{prefix}-.." and key.startswith(prefix)
OPENAI_API_KEY = os.environ["OPENAI_API_KEY"]
# # Tools
# In[4]:
from datetime import datetime
from typing import List
def format_search_results_for_podcast(search_results: List[dict]) -> tuple[str, List[str]]:
"""
Custom tool to format search results for podcast script generation.
"""
created_at = datetime.now().strftime("%B %d, %Y at %I:%M %p")
structured_content = []
structured_content.append(f"PODCAST CREATION: {created_at}\n")
sources = []
for idx, search_result in enumerate(search_results):
try:
if search_result.get("confirmed", False):
sources.append(search_result["url"])
structured_content.append(
f"""
SOURCE {idx + 1}:
Title: {search_result['title']}
URL: {search_result['url']}
Content: {search_result.get('full_text') or search_result.get('description', '')}
---END OF SOURCE {idx + 1}---
""".strip()
)
except Exception as e:
print(f"Error processing search result: {e}")
content_texts = "\n\n".join(structured_content)
return content_texts, sources
# # Pydantic Models
# In[5]:
from pydantic import BaseModel, Field
from typing import List, Optional
class Dialog(BaseModel):
speaker: str = Field(..., description="The speaker name (SHOULD BE 'ALEX' OR 'MORGAN')")
text: str = Field(..., description="The spoken text content for this speaker based on the requested language, default is English")
class Section(BaseModel):
type: str = Field(..., description="The section type (intro, headlines, article, outro)")
title: Optional[str] = Field(None, description="Optional title for the section (required for article type)")
dialog: List[Dialog] = Field(..., description="List of dialog exchanges between speakers")
class PodcastScript(BaseModel):
title: str = Field(..., description="The podcast episode title with date")
sections: List[Section] = Field(..., description="List of podcast sections (intro, headlines, articles, outro)")
# # Agent Instructions
# In[6]:
from textwrap import dedent
PODCAST_AGENT_DESCRIPTION = "You are a helpful assistant that can generate engaging podcast scripts for the given sources."
PODCAST_AGENT_INSTRUCTIONS = dedent("""
You are a helpful assistant that can generate engaging podcast scripts for the given source content and query.
For given content, create an engaging podcast script that should be at least 15 minutes worth of content and you are allowed to enhance the script beyond given sources if you know something additional info will be interesting to the discussion or not enough content is available.
You use the provided sources to ground your podcast script generation process. Keep it engaging and interesting.
IMPORTANT: Generate the entire script in the provided language.
CONTENT GUIDELINES:
- Provide insightful analysis that helps the audience understand the significance
- Include discussions on potential implications and broader context of each story
- Explain complex concepts in an accessible but thorough manner
- Make connections between current and relevant historical developments when applicable
- Provide comparisons and contrasts with similar stories or trends when relevant
PERSONALITY NOTES:
- Alex is more analytical and fact-focused
- Morgan is more focused on human impact, social context, and practical applications
- Include natural, conversational banter and smooth transitions between topics
- Each article discussion should go beyond the basic summary to provide valuable insights
- Maintain a conversational but informed tone that would appeal to a general audience
IMPORTANT:
- MAKE SURE PODCAST SCRIPTS ARE AT LEAST 15 MINUTES LONG WHICH MEANS YOU NEED TO HAVE DETAILED DISCUSSIONS BUT KEEP IT INTERESTING AND ENGAGING.
""")
# # Dummy Data and Main Logic
# In[7]:
from praisonaiagents import Agent
# Dummy search results for CI/public use
dummy_search_results = [
{
"confirmed": True,
"title": "AI Revolutionizes Healthcare",
"url": "https://news.example.com/ai-healthcare",
"full_text": "Artificial intelligence is transforming the healthcare industry by..."
},
{
"confirmed": True,
"title": "Climate Change and Global Policy",
"url": "https://news.example.com/climate-policy",
"full_text": "World leaders are meeting to discuss new policies for climate change..."
}
]
query = "Latest technology and world news"
language_name = "English"
content_texts, sources = format_search_results_for_podcast(dummy_search_results)
if not is_valid_key(OPENAI_API_KEY, "sk"):
print("API key not set or is a placeholder. Using dummy podcast script for CI/testing.")
print("=== Podcast Script ===")
print(f"Podcast Title: Tech & World News Roundup ({datetime.now().strftime('%B %d, %Y')})")
for idx, article in enumerate(dummy_search_results):
print(f"\nSection {idx+1}: {article['title']}")
print(f"Summary: {article['full_text'][:80]}...")
else:
agent = Agent(
name="Podcast Script Agent",
instructions=PODCAST_AGENT_INSTRUCTIONS,
api_key=OPENAI_API_KEY
)
prompt = f"query: {query}\nlanguage_name: {language_name}\ncontent_texts: {content_texts}\nIMPORTANT: texts should be in {language_name} language."
podcast_script = agent.start(prompt)
print("=== Podcast Script ===")
print(podcast_script)
@@ -0,0 +1,8 @@
from praisonaiagents import Agent
agent = Agent(
instructions="You are a customer support AI agent for TechGadgets.com, an online electronics store. Answer customer queries helpfully.",
llm="xai/grok-4"
)
response = agent.start("How to return an item?")
@@ -0,0 +1,8 @@
from praisonaiagents import Agent
agent = Agent(
instructions="You are a lead generation AI agent for RealEstatePro.com. Help identify and qualify potential real estate leads.",
llm="xai/grok-4"
)
response = agent.start("I'm looking to buy a house in the suburbs with 3 bedrooms and a garden.")
@@ -0,0 +1,8 @@
from praisonaiagents import Agent
agent = Agent(
instructions="You are a meeting productivity AI agent. Help optimize meeting efficiency and follow-up actions.",
llm="xai/grok-4"
)
response = agent.start("I have a team meeting tomorrow. How can I make it more productive?")
@@ -0,0 +1,8 @@
from praisonaiagents import Agent
agent = Agent(
instructions="You are a mental wellbeing AI advisor. Provide supportive guidance and wellness tips.",
llm="xai/grok-4"
)
response = agent.start("I've been feeling stressed at work lately. Any tips for managing stress?")
@@ -0,0 +1,8 @@
from praisonaiagents import Agent
agent = Agent(
instructions="You are a multimodal reasoning AI agent. Analyze images and text to provide comprehensive insights.",
llm="xai/grok-4"
)
response = agent.start("Can you help me analyze a chart showing sales data for Q1 2024?")
@@ -354,8 +354,10 @@ class Agent:
# Check for model name in environment variable if not provided
self._using_custom_llm = False
# Initialize OpenAI client for direct API calls
self._openai_client = get_openai_client(api_key=api_key, base_url=base_url)
# Store OpenAI client parameters for lazy initialization
self._openai_api_key = api_key
self._openai_base_url = base_url
self.__openai_client = None
# If base_url is provided, always create a custom LLM instance
if base_url:
@@ -488,6 +490,42 @@ Your Goal: {self.goal}
for source in knowledge:
self._process_knowledge(source)
@property
def _openai_client(self):
"""Lazily initialize OpenAI client only when needed."""
if self.__openai_client is None:
try:
self.__openai_client = get_openai_client(
api_key=self._openai_api_key,
base_url=self._openai_base_url
)
except ValueError as e:
# If we're using a custom LLM, we might not need the OpenAI client
# Return None and let the calling code handle it
if self._using_custom_llm:
return None
else:
raise e
return self.__openai_client
@property
def llm_model(self):
"""Unified property to get the LLM model regardless of configuration type.
Returns:
The LLM model/instance being used by this agent.
- For standard models: returns the model string (e.g., "gpt-4o")
- For custom LLM instances: returns the LLM instance object
- For provider models: returns the LLM instance object
"""
if hasattr(self, 'llm_instance') and self.llm_instance:
return self.llm_instance
elif hasattr(self, 'llm') and self.llm:
return self.llm
else:
# Default fallback
return "gpt-4o"
def _process_knowledge(self, knowledge_item):
"""Process and store knowledge from a file path, URL, or string."""
try:
@@ -694,14 +732,39 @@ Your Role: {self.role}\n
Your Goal: {self.goal}
"""
# Use openai_client's build_messages method
messages, original_prompt = self._openai_client.build_messages(
prompt=prompt,
system_prompt=system_prompt,
chat_history=self.chat_history,
output_json=output_json,
output_pydantic=output_pydantic
)
# Use openai_client's build_messages method if available
if self._openai_client is not None:
messages, original_prompt = self._openai_client.build_messages(
prompt=prompt,
system_prompt=system_prompt,
chat_history=self.chat_history,
output_json=output_json,
output_pydantic=output_pydantic
)
else:
# Fallback implementation for when OpenAI client is not available
messages = []
# Add system message if provided
if system_prompt:
messages.append({"role": "system", "content": system_prompt})
# Add chat history
messages.extend(self.chat_history)
# Add user prompt
if isinstance(prompt, list):
messages.extend(prompt)
original_prompt = prompt
else:
messages.append({"role": "user", "content": str(prompt)})
original_prompt = str(prompt)
# Add JSON format instruction if needed
if output_json or output_pydantic:
model = output_pydantic or output_json
json_instruction = f"\nPlease respond with valid JSON matching this schema: {model.model_json_schema()}"
messages[-1]["content"] += json_instruction
return messages, original_prompt
@@ -943,6 +1006,9 @@ Your Goal: {self.goal}
def _process_stream_response(self, messages, temperature, start_time, formatted_tools=None, reasoning_steps=False):
"""Process streaming response and return final response"""
if self._openai_client is None:
raise ValueError("OpenAI client is not initialized. Please provide OPENAI_API_KEY or use a custom LLM provider.")
return self._openai_client.process_stream_response(
messages=messages,
model=self.llm,
@@ -1009,6 +1075,9 @@ Your Goal: {self.goal}
# Note: openai_client expects tools in various formats and will format them internally
# But since we already have formatted_tools, we can pass them directly
if self._openai_client is None:
raise ValueError("OpenAI client is not initialized. Please provide OPENAI_API_KEY or use a custom LLM provider.")
final_response = self._openai_client.chat_completion_with_tools(
messages=messages,
model=self.llm,
@@ -1202,6 +1271,17 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
messages.append({"role": "user", "content": reflection_prompt})
try:
# Check if OpenAI client is available
if self._openai_client is None:
# For custom LLMs, self-reflection with structured output is not supported
if self.verbose:
display_self_reflection(f"Agent {self.name}: Self-reflection with structured output is not supported for custom LLM providers. Skipping reflection.", console=self.console)
# Return the original response without reflection
self.chat_history.append({"role": "user", "content": prompt})
self.chat_history.append({"role": "assistant", "content": response_text})
display_interaction(prompt, response_text, markdown=self.markdown, generation_time=time.time() - start_time, console=self.console)
return response_text
reflection_response = self._openai_client.sync_client.beta.chat.completions.parse(
model=self.reflect_llm if self.reflect_llm else self.llm,
messages=messages,
@@ -1388,6 +1468,12 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
# Use the new _format_tools_for_completion helper method
formatted_tools = self._format_tools_for_completion(tools)
# Check if OpenAI client is available
if self._openai_client is None:
error_msg = "OpenAI client is not initialized. Please provide OPENAI_API_KEY or use a custom LLM provider."
display_error(error_msg)
return None
# Make the API call based on the type of request
if tools:
@@ -1442,6 +1528,19 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
]
try:
# Check if OpenAI client is available for self-reflection
if self._openai_client is None:
# For custom LLMs, self-reflection with structured output is not supported
if self.verbose:
display_self_reflection(f"Agent {self.name}: Self-reflection with structured output is not supported for custom LLM providers. Skipping reflection.", console=self.console)
# Return the original response without reflection
self.chat_history.append({"role": "user", "content": original_prompt})
self.chat_history.append({"role": "assistant", "content": response_text})
if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
total_time = time.time() - start_time
logging.debug(f"Agent.achat completed in {total_time:.2f} seconds")
return response_text
reflection_response = await self._openai_client.async_client.beta.chat.completions.parse(
model=self.reflect_llm if self.reflect_llm else self.llm,
messages=reflection_messages,
@@ -7,7 +7,7 @@ from pydantic import BaseModel
from rich.text import Text
from rich.panel import Panel
from rich.console import Console
from ..main import display_error, TaskOutput, error_logs, client
from ..main import display_error, TaskOutput, error_logs
from ..agent.agent import Agent
from ..task.task import Task
from ..process.process import Process, LoopItems
@@ -12,7 +12,8 @@ from typing import List, Any, Optional, Dict, Tuple
import logging
import os
from pydantic import BaseModel, ConfigDict
from ..main import display_instruction, display_tool_call, display_interaction, client
from ..main import display_instruction, display_tool_call, display_interaction
from ..llm import get_openai_client
# Define Pydantic models for structured output
class TaskConfig(BaseModel):
@@ -237,6 +238,17 @@ Return the configuration in a structured JSON format matching the AutoAgentsConf
"""
try:
# Get OpenAI client
try:
client = get_openai_client()
except ValueError as e:
# AutoAgents requires OpenAI for structured output generation
raise ValueError(
"AutoAgents requires OpenAI API for automatic agent generation. "
"Please set OPENAI_API_KEY environment variable or use PraisonAIAgents class directly "
"with manually configured agents for non-OpenAI providers."
) from e
response = client.beta.chat.completions.parse(
model=self.llm,
response_format=AutoAgentsConfig,
@@ -364,6 +364,46 @@ class LLM:
return messages, original_prompt
def _fix_array_schemas(self, schema: Dict) -> Dict:
"""
Recursively fix array schemas by adding missing 'items' attribute.
This ensures compatibility with OpenAI's function calling format which
requires array types to specify the type of items they contain.
Args:
schema: The schema dictionary to fix
Returns:
dict: The fixed schema
"""
if not isinstance(schema, dict):
return schema
# Create a copy to avoid modifying the original
fixed_schema = schema.copy()
# Fix array types at the current level
if fixed_schema.get("type") == "array" and "items" not in fixed_schema:
# Add a default items schema for arrays without it
fixed_schema["items"] = {"type": "string"}
# Recursively fix nested schemas in properties
if "properties" in fixed_schema and isinstance(fixed_schema["properties"], dict):
fixed_properties = {}
for prop_name, prop_schema in fixed_schema["properties"].items():
if isinstance(prop_schema, dict):
fixed_properties[prop_name] = self._fix_array_schemas(prop_schema)
else:
fixed_properties[prop_name] = prop_schema
fixed_schema["properties"] = fixed_properties
# Fix items schema if it exists
if "items" in fixed_schema and isinstance(fixed_schema["items"], dict):
fixed_schema["items"] = self._fix_array_schemas(fixed_schema["items"])
return fixed_schema
def _format_tools_for_litellm(self, tools: Optional[List[Any]]) -> Optional[List[Dict]]:
"""Format tools for LiteLLM - handles all tool formats.
@@ -389,7 +429,11 @@ class LLM:
# Validate nested dictionary structure before accessing
if 'function' in tool and isinstance(tool['function'], dict) and 'name' in tool['function']:
logging.debug(f"Using pre-formatted OpenAI tool: {tool['function']['name']}")
formatted_tools.append(tool)
# Fix array schemas in the tool parameters
fixed_tool = tool.copy()
if 'parameters' in fixed_tool['function']:
fixed_tool['function']['parameters'] = self._fix_array_schemas(fixed_tool['function']['parameters'])
formatted_tools.append(fixed_tool)
else:
logging.debug(f"Skipping malformed OpenAI tool: missing function or name")
# Handle lists of tools (e.g. from MCP.to_openai_tool())
@@ -399,7 +443,11 @@ class LLM:
# Validate nested dictionary structure before accessing
if 'function' in subtool and isinstance(subtool['function'], dict) and 'name' in subtool['function']:
logging.debug(f"Using pre-formatted OpenAI tool from list: {subtool['function']['name']}")
formatted_tools.append(subtool)
# Fix array schemas in the tool parameters
fixed_tool = subtool.copy()
if 'parameters' in fixed_tool['function']:
fixed_tool['function']['parameters'] = self._fix_array_schemas(fixed_tool['function']['parameters'])
formatted_tools.append(fixed_tool)
else:
logging.debug(f"Skipping malformed OpenAI tool in list: missing function or name")
elif callable(tool):
@@ -2153,7 +2201,7 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
"function": {
"name": function_name,
"description": docstring.split('\n\n')[0] if docstring else "No description available",
"parameters": parameters
"parameters": self._fix_array_schemas(parameters)
}
}
logging.debug(f"Generated tool definition: {tool_def}")
@@ -3,7 +3,6 @@ import time
import json
import logging
from typing import List, Optional, Dict, Any, Union, Literal, Type
from openai import OpenAI
from pydantic import BaseModel, ConfigDict
from rich import print
from rich.console import Console
@@ -377,24 +376,6 @@ class ReflectionOutput(BaseModel):
reflection: str
satisfactory: Literal["yes", "no"]
# Constants
LOCAL_SERVER_API_KEY_PLACEHOLDER = "not-needed"
# Initialize OpenAI client with proper API key handling
api_key = os.environ.get("OPENAI_API_KEY")
base_url = os.environ.get("OPENAI_API_BASE") or os.environ.get("OPENAI_BASE_URL")
# For local servers like LM Studio, allow minimal API key
if base_url and not api_key:
api_key = LOCAL_SERVER_API_KEY_PLACEHOLDER
elif not api_key:
raise ValueError(
"OPENAI_API_KEY environment variable is required for the default OpenAI service. "
"If you are targeting a local server (e.g., LM Studio), ensure OPENAI_API_BASE is set "
f"(e.g., 'http://localhost:1234/v1') and you can use a placeholder API key by setting OPENAI_API_KEY='{LOCAL_SERVER_API_KEY_PLACEHOLDER}'"
)
client = OpenAI(api_key=api_key, base_url=base_url)
class TaskOutput(BaseModel):
model_config = ConfigDict(arbitrary_types_allowed=True)
@@ -5,10 +5,10 @@ from typing import Dict, Optional, List, Any, AsyncGenerator
from pydantic import BaseModel, ConfigDict
from ..agent.agent import Agent
from ..task.task import Task
from ..main import display_error, client
from ..main import display_error
import csv
import os
from openai import AsyncOpenAI
from openai import AsyncOpenAI, OpenAI
class LoopItems(BaseModel):
model_config = ConfigDict(arbitrary_types_allowed=True)
@@ -140,6 +140,8 @@ class Process:
def _get_manager_instructions_with_fallback(self, manager_task, manager_prompt, ManagerInstructions):
"""Sync version of getting manager instructions with fallback"""
# Create OpenAI client
client = OpenAI()
try:
# First try structured output (OpenAI compatible)
logging.info("Attempting structured output...")
+1 -1
View File
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "praisonaiagents"
version = "0.0.115"
version = "0.0.117"
description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
requires-python = ">=3.10"
authors = [
+1 -1
View File
@@ -2375,7 +2375,7 @@ wheels = [
[[package]]
name = "praisonaiagents"
version = "0.0.115"
version = "0.0.117"
source = { editable = "." }
dependencies = [
{ name = "mcp" },
+2 -2
View File
@@ -3,8 +3,8 @@ class Praisonai < Formula
desc "AI tools for various AI applications"
homepage "https://github.com/MervinPraison/PraisonAI"
url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.42.tar.gz"
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.42.tar.gz | shasum -a 256`.split.first
url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.44.tar.gz"
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.44.tar.gz | shasum -a 256`.split.first
license "MIT"
depends_on "[email protected]"
+1 -1
View File
@@ -57,7 +57,7 @@ class CloudDeployer:
file.write("FROM python:3.11-slim\n")
file.write("WORKDIR /app\n")
file.write("COPY . .\n")
file.write("RUN pip install flask praisonai==2.2.42 gunicorn markdown\n")
file.write("RUN pip install flask praisonai==2.2.44 gunicorn markdown\n")
file.write("EXPOSE 8080\n")
file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
+4 -4
View File
@@ -1,6 +1,6 @@
[project]
name = "PraisonAI"
version = "2.2.42"
version = "2.2.44"
description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration."
readme = "README.md"
license = ""
@@ -12,7 +12,7 @@ dependencies = [
"rich>=13.7",
"markdown>=3.5",
"pyparsing>=3.0.0",
"praisonaiagents>=0.0.115",
"praisonaiagents>=0.0.117",
"python-dotenv>=0.19.0",
"instructor>=1.3.3",
"PyYAML>=6.0",
@@ -95,7 +95,7 @@ autogen = ["pyautogen>=0.2.19", "praisonai-tools>=0.0.15", "crewai"]
[tool.poetry]
name = "PraisonAI"
version = "2.2.42"
version = "2.2.44"
description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration."
authors = ["Mervin Praison"]
license = ""
@@ -113,7 +113,7 @@ python = ">=3.10,<3.13"
rich = ">=13.7"
markdown = ">=3.5"
pyparsing = ">=3.0.0"
praisonaiagents = ">=0.0.115"
praisonaiagents = ">=0.0.117"
python-dotenv = ">=0.19.0"
instructor = ">=1.3.3"
PyYAML = ">=6.0"
+31
View File
@@ -0,0 +1,31 @@
#!/usr/bin/env python3
"""Test script to verify that xai/grok-4 works without OPENAI_API_KEY"""
import os
import sys
# Ensure OPENAI_API_KEY is not set to test the fix
if 'OPENAI_API_KEY' in os.environ:
del os.environ['OPENAI_API_KEY']
# Test the import that was failing
try:
from praisonaiagents import Agent
print("✅ Successfully imported praisonaiagents without OPENAI_API_KEY!")
except ValueError as e:
print(f"❌ Import failed with error: {e}")
sys.exit(1)
# Test creating an agent with xai/grok-4
try:
agent = Agent(
instructions="You are a PhD-level mathematician.",
llm="xai/grok-4"
)
print("✅ Successfully created Agent with xai/grok-4!")
except Exception as e:
print(f"❌ Failed to create agent: {e}")
sys.exit(1)
print("\n✅ All tests passed! The issue has been fixed.")
print(" You can now use litellm providers without setting OPENAI_API_KEY.")
+5 -5
View File
@@ -3931,7 +3931,7 @@ wheels = [
[[package]]
name = "praisonai"
version = "2.2.42"
version = "2.2.44"
source = { editable = "." }
dependencies = [
{ name = "instructor" },
@@ -4073,7 +4073,7 @@ requires-dist = [
{ name = "plotly", marker = "extra == 'realtime'", specifier = ">=5.24.0" },
{ name = "praisonai-tools", marker = "extra == 'autogen'", specifier = ">=0.0.15" },
{ name = "praisonai-tools", marker = "extra == 'crewai'", specifier = ">=0.0.15" },
{ name = "praisonaiagents", specifier = ">=0.0.115" },
{ name = "praisonaiagents", specifier = ">=0.0.117" },
{ name = "pyautogen", marker = "extra == 'autogen'", specifier = ">=0.2.19" },
{ name = "pydantic", marker = "extra == 'chat'", specifier = "<=2.10.1" },
{ name = "pydantic", marker = "extra == 'code'", specifier = "<=2.10.1" },
@@ -4130,7 +4130,7 @@ wheels = [
[[package]]
name = "praisonaiagents"
version = "0.0.115"
version = "0.0.117"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "mcp" },
@@ -4139,9 +4139,9 @@ dependencies = [
{ name = "pydantic" },
{ name = "rich" },
]
sdist = { url = "https://files.pythonhosted.org/packages/c4/f3/33062dc9811b44ac0dc760b88ca3f3ce52f205021f5392785b4959e695f0/praisonaiagents-0.0.115.tar.gz", hash = "sha256:67fc681325846eb56c82ae2aba8907e9a3c934b91a754729c6e37071418b9dd3", size = 172218 }
sdist = { url = "https://files.pythonhosted.org/packages/3e/0e/663cdeecbc32af35b8f7ee662079d75c7d743a7d6507fe9742fe5e3edf9e/praisonaiagents-0.0.117.tar.gz", hash = "sha256:b28605506863689433d7825bda72272b04254b5fe95be2a9899d8e96a89467aa", size = 173294 }
wheels = [
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[[package]]