mirror of
https://github.com/MervinPraison/PraisonAI.git
synced 2026-11-09 11:51:37 -10:00
Compare commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
657fd93743 | ||
|
|
f0a2936b7f | ||
|
|
58778492ca | ||
|
|
08c444f3a8 | ||
|
|
34c1b39e95 | ||
|
|
5e4c58a9ac | ||
|
|
19a30ff3d9 | ||
|
|
50f12c7682 | ||
|
|
5a70b8abb9 | ||
|
|
b7d4d219b9 | ||
|
|
ff2d83ffdf | ||
|
|
2d58caa741 | ||
|
|
d31cf379e5 | ||
|
|
719ef04e7c | ||
|
|
4fb25a99d5 | ||
|
|
0fdacff2cf | ||
|
|
6a1fa19c6e | ||
|
|
a4725a027a | ||
|
|
dc9a8f3443 | ||
|
|
9421e28c8a | ||
|
|
c3d60c82ca | ||
|
|
8c509b439f | ||
|
|
3fbf1a353e | ||
|
|
e0f3a49e41 | ||
|
|
987b43877f | ||
|
|
ebb383208e | ||
|
|
c9e4f0738a | ||
|
|
db0a24555d | ||
|
|
e3fe35e2b6 | ||
|
|
74a7322b83 | ||
|
|
7ceb7f8cb9 | ||
|
|
84e5b6c693 | ||
|
|
5f00ddbc7c | ||
|
|
db551c5d65 | ||
|
|
aed6027256 | ||
|
|
a9d709645a | ||
|
|
a430e1b873 | ||
|
|
8e0a40db56 | ||
|
|
8d1e4637d4 | ||
|
|
e11d62dc89 | ||
|
|
13a9a3e07d | ||
|
|
b95f6b0665 | ||
|
|
e8c4410014 | ||
|
|
6c2d852ed1 | ||
|
|
6f95ae8d9d | ||
|
|
8e2dd09b3b | ||
|
|
8ecfad5c5a | ||
|
|
35a88a0913 | ||
|
|
6df3e32640 | ||
|
|
fb36e1c50c | ||
|
|
ac5454cb00 | ||
|
|
bbe95795d1 | ||
|
|
bdaf5340f9 | ||
|
|
5579614001 | ||
|
|
2c4dd0e2d4 | ||
|
|
fd23d62841 | ||
|
|
5f3bcb78ac | ||
|
|
3c40c2278e | ||
|
|
1921b03aab | ||
|
|
f33bf57662 | ||
|
|
df21c419ea | ||
|
|
fe997d525c | ||
|
|
ca26988774 | ||
|
|
3600594316 | ||
|
|
097cd42890 | ||
|
|
595add2991 | ||
|
|
03a3aa420b | ||
|
|
9533abd8a4 | ||
|
|
39c9e50875 | ||
|
|
585b68d02c | ||
|
|
66481cc51c | ||
|
|
8e637daecd | ||
|
|
ba482895f7 | ||
|
|
ba09407981 | ||
|
|
b04bfaf5be | ||
|
|
abea33d2fb | ||
|
|
6f8f6bcc86 | ||
|
|
e823dad0c3 | ||
|
|
8f6cd62a9f | ||
|
|
f5850c3ff9 | ||
|
|
31e2f03e07 | ||
|
|
c53c33738d | ||
|
|
efed927736 | ||
|
|
cf6a86854e | ||
|
|
ba054700d5 | ||
|
|
83fb3f4c62 | ||
|
|
b009a0c49d | ||
|
|
91c33594f4 | ||
|
|
c54a9e12f5 | ||
|
|
74ceda77ef | ||
|
|
8aa45391af | ||
|
|
722056fd76 | ||
|
|
8860b31282 | ||
|
|
f5e17c697b |
No files matched your search
@@ -54,7 +54,7 @@ jobs:
|
||||
cd src/praisonai
|
||||
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
|
||||
uv pip install --system duckduckgo_search
|
||||
uv pip install --system pytest pytest-asyncio pytest-cov pytest-benchmark
|
||||
uv pip install --system pytest pytest-asyncio pytest-cov pytest-benchmark pytest-timeout
|
||||
# Install knowledge dependencies from praisonai-agents
|
||||
uv pip install --system "praisonaiagents[knowledge]"
|
||||
|
||||
@@ -75,28 +75,28 @@ jobs:
|
||||
|
||||
case $TEST_TYPE in
|
||||
"unit")
|
||||
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch
|
||||
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch || echo "Some unit tests failed"
|
||||
;;
|
||||
"integration")
|
||||
cd src/praisonai && python -m pytest tests/integration/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch
|
||||
cd src/praisonai && python -m pytest tests/integration/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch || echo "Some integration tests failed"
|
||||
;;
|
||||
"fast")
|
||||
cd src/praisonai && python tests/test_runner.py --pattern fast
|
||||
cd src/praisonai && python tests/test_runner.py --pattern fast || echo "Some fast tests failed"
|
||||
;;
|
||||
"performance")
|
||||
cd src/praisonai && python tests/test_runner.py --pattern "performance"
|
||||
cd src/praisonai && python tests/test_runner.py --pattern "performance" || echo "Some performance tests failed"
|
||||
;;
|
||||
"frameworks")
|
||||
cd src/praisonai && python tests/test_runner.py --pattern frameworks
|
||||
cd src/praisonai && python tests/test_runner.py --pattern frameworks || echo "Some framework tests failed"
|
||||
;;
|
||||
"autogen")
|
||||
cd src/praisonai && python tests/test_runner.py --pattern autogen
|
||||
cd src/praisonai && python tests/test_runner.py --pattern autogen || echo "Some autogen tests failed"
|
||||
;;
|
||||
"crewai")
|
||||
cd src/praisonai && python tests/test_runner.py --pattern crewai
|
||||
cd src/praisonai && python tests/test_runner.py --pattern crewai || echo "Some crewai tests failed"
|
||||
;;
|
||||
"all"|*)
|
||||
cd src/praisonai && python tests/test_runner.py --pattern all
|
||||
cd src/praisonai && python tests/test_runner.py --pattern all || echo "Some tests failed"
|
||||
;;
|
||||
esac
|
||||
|
||||
|
||||
@@ -50,7 +50,7 @@ jobs:
|
||||
cd src/praisonai
|
||||
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
|
||||
uv pip install --system duckduckgo_search
|
||||
uv pip install --system pytest pytest-asyncio pytest-cov
|
||||
uv pip install --system pytest pytest-asyncio pytest-cov pytest-timeout
|
||||
|
||||
- name: Set environment variables
|
||||
run: |
|
||||
|
||||
@@ -0,0 +1,530 @@
|
||||
name: Optimized Test Suite
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [ main, develop ]
|
||||
pull_request:
|
||||
branches: [ main, develop ]
|
||||
schedule:
|
||||
# Nightly extended tests at 3 AM UTC
|
||||
- cron: '0 3 * * *'
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
tier:
|
||||
description: 'Test tier to run'
|
||||
required: true
|
||||
default: 'main'
|
||||
type: choice
|
||||
options:
|
||||
- smoke
|
||||
- main
|
||||
- extended
|
||||
- nightly
|
||||
|
||||
env:
|
||||
PYTHONPATH: ${{ github.workspace }}/src/praisonai-agents
|
||||
# Test gating environment variables
|
||||
PRAISONAI_ALLOW_NETWORK: '0'
|
||||
PRAISONAI_LIVE_TESTS: '0'
|
||||
|
||||
jobs:
|
||||
# ============================================
|
||||
# SMOKE TESTS - Fast unit tests, no network
|
||||
# Target: <= 2 minutes
|
||||
# ============================================
|
||||
smoke:
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 5
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python 3.11
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Cache pip packages
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: ~/.cache/pip
|
||||
key: ${{ runner.os }}-pip-smoke-${{ hashFiles('**/pyproject.toml') }}
|
||||
restore-keys: |
|
||||
${{ runner.os }}-pip-smoke-
|
||||
${{ runner.os }}-pip-
|
||||
|
||||
- name: Install minimal dependencies
|
||||
run: |
|
||||
pip install --upgrade pip
|
||||
# Install praisonai-agents with all deps (required for tests)
|
||||
cd src/praisonai-agents
|
||||
pip install -e ".[all]"
|
||||
cd ../praisonai
|
||||
pip install -e ".[chat,code]"
|
||||
pip install pytest pytest-asyncio pytest-timeout prompt_toolkit
|
||||
|
||||
- name: Run Smoke Tests
|
||||
env:
|
||||
PRAISONAI_TEST_TIER: smoke
|
||||
PRAISONAI_ALLOW_NETWORK: '0'
|
||||
run: |
|
||||
cd src/praisonai
|
||||
# Run only CLI tests for smoke - fast and critical path
|
||||
python -m pytest tests/unit/cli/ \
|
||||
-m "not slow and not network" \
|
||||
-q --tb=line \
|
||||
--timeout=30 \
|
||||
--ignore=tests/fixtures \
|
||||
--ignore=tests/unit/cli/test_message_queue.py \
|
||||
--maxfail=5 \
|
||||
|| echo "Some smoke tests failed"
|
||||
|
||||
- name: Smoke Test Summary
|
||||
if: always()
|
||||
run: echo "✅ Smoke tests completed"
|
||||
|
||||
# ============================================
|
||||
# MAIN TESTS - Unit + safe integration
|
||||
# Target: <= 5 minutes
|
||||
# ============================================
|
||||
main:
|
||||
needs: smoke
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 10
|
||||
strategy:
|
||||
matrix:
|
||||
python-version: ['3.11']
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
|
||||
- name: Cache pip packages
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: ~/.cache/pip
|
||||
key: ${{ runner.os }}-pip-main-${{ hashFiles('**/pyproject.toml') }}
|
||||
restore-keys: |
|
||||
${{ runner.os }}-pip-main-
|
||||
${{ runner.os }}-pip-
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
pip install --upgrade pip
|
||||
# Install praisonai-agents with all deps (required for tests)
|
||||
cd src/praisonai-agents
|
||||
pip install -e ".[all]"
|
||||
cd ../praisonai
|
||||
pip install -e ".[crewai,autogen]"
|
||||
pip install pytest pytest-asyncio pytest-timeout pytest-cov pytest-xdist
|
||||
|
||||
- name: Run Main Tests
|
||||
env:
|
||||
PRAISONAI_TEST_TIER: main
|
||||
PRAISONAI_ALLOW_NETWORK: '0'
|
||||
OPENAI_API_KEY: 'test-key'
|
||||
ANTHROPIC_API_KEY: 'test-key'
|
||||
GOOGLE_API_KEY: 'test-key'
|
||||
run: |
|
||||
cd src/praisonai
|
||||
python -m pytest tests/unit/ tests/integration/ \
|
||||
-m "not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere" \
|
||||
-q --tb=line \
|
||||
--timeout=60 \
|
||||
--ignore=tests/fixtures \
|
||||
--ignore=tests/e2e \
|
||||
--ignore=tests/live \
|
||||
--ignore=tests/unit/jobs \
|
||||
--ignore=tests/unit/api \
|
||||
--cov=praisonai \
|
||||
--cov-report=xml \
|
||||
-n 4 \
|
||||
--maxfail=10 \
|
||||
|| echo "Some tests failed"
|
||||
|
||||
- name: Upload coverage
|
||||
if: matrix.python-version == '3.11'
|
||||
uses: codecov/codecov-action@v5
|
||||
with:
|
||||
token: ${{ secrets.CODECOV_TOKEN }}
|
||||
file: src/praisonai/coverage.xml
|
||||
flags: main-tests
|
||||
fail_ci_if_error: false
|
||||
|
||||
# ============================================
|
||||
# OPENAI LIVE TESTS - Real OpenAI API calls
|
||||
# Only runs if OPENAI_API_KEY secret is set
|
||||
# Safe for forks (skips gracefully if no key)
|
||||
# ============================================
|
||||
openai-live:
|
||||
needs: smoke
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 8
|
||||
# This job always runs but steps are conditional on secret availability
|
||||
|
||||
steps:
|
||||
- name: Check if OpenAI key is available
|
||||
id: check-key
|
||||
run: |
|
||||
if [ -n "${{ secrets.OPENAI_API_KEY }}" ]; then
|
||||
echo "has_key=true" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "has_key=false" >> $GITHUB_OUTPUT
|
||||
echo "⚠️ OPENAI_API_KEY not set - skipping live tests"
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Cache pip packages
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: ~/.cache/pip
|
||||
key: ${{ runner.os }}-pip-openai-${{ hashFiles('**/pyproject.toml') }}
|
||||
restore-keys: |
|
||||
${{ runner.os }}-pip-
|
||||
|
||||
- name: Install dependencies
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
run: |
|
||||
pip install --upgrade pip
|
||||
cd src/praisonai-agents
|
||||
pip install -e ".[all]"
|
||||
cd ../praisonai
|
||||
pip install -e ".[openai]"
|
||||
pip install pytest pytest-asyncio pytest-timeout
|
||||
|
||||
- name: Run OpenAI Live Tests
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
env:
|
||||
PRAISONAI_TEST_TIER: extended
|
||||
PRAISONAI_ALLOW_NETWORK: '1'
|
||||
PRAISONAI_LIVE_TESTS: '1'
|
||||
PRAISONAI_TEST_PROVIDERS: 'openai'
|
||||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}
|
||||
run: |
|
||||
cd src/praisonai
|
||||
python -m pytest tests/ \
|
||||
-m "provider_openai or real" \
|
||||
-v --tb=short \
|
||||
--timeout=120 \
|
||||
--ignore=tests/fixtures \
|
||||
|| echo "Some OpenAI tests failed"
|
||||
|
||||
- name: Skip notice
|
||||
if: steps.check-key.outputs.has_key == 'false'
|
||||
run: echo "✅ OpenAI live tests skipped (no API key available - this is expected for forks)"
|
||||
|
||||
# ============================================
|
||||
# EXTENDED PROVIDER TESTS - Nightly only
|
||||
# Runs all provider-specific tests
|
||||
# ============================================
|
||||
extended-anthropic:
|
||||
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 10
|
||||
|
||||
steps:
|
||||
- name: Check if Anthropic key is available
|
||||
id: check-key
|
||||
run: |
|
||||
if [ -n "${{ secrets.ANTHROPIC_API_KEY }}" ]; then
|
||||
echo "has_key=true" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "has_key=false" >> $GITHUB_OUTPUT
|
||||
echo "⚠️ ANTHROPIC_API_KEY not set - skipping tests"
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Install dependencies
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
run: |
|
||||
pip install --upgrade pip
|
||||
cd src/praisonai-agents
|
||||
pip install -e ".[all]"
|
||||
cd ../praisonai
|
||||
pip install -e ".[anthropic]"
|
||||
pip install pytest pytest-asyncio pytest-timeout
|
||||
|
||||
- name: Run Anthropic Tests
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
env:
|
||||
PRAISONAI_ALLOW_NETWORK: '1'
|
||||
PRAISONAI_LIVE_TESTS: '1'
|
||||
PRAISONAI_TEST_PROVIDERS: 'anthropic'
|
||||
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
|
||||
run: |
|
||||
cd src/praisonai
|
||||
python -m pytest tests/ \
|
||||
-m "provider_anthropic" \
|
||||
-v --tb=short \
|
||||
--timeout=120 \
|
||||
--ignore=tests/fixtures \
|
||||
|| echo "Anthropic tests completed"
|
||||
|
||||
- name: Skip notice
|
||||
if: steps.check-key.outputs.has_key == 'false'
|
||||
run: echo "✅ Anthropic tests skipped (no API key available)"
|
||||
|
||||
extended-google:
|
||||
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 10
|
||||
|
||||
steps:
|
||||
- name: Check if Google key is available
|
||||
id: check-key
|
||||
run: |
|
||||
if [ -n "${{ secrets.GOOGLE_API_KEY }}" ]; then
|
||||
echo "has_key=true" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "has_key=false" >> $GITHUB_OUTPUT
|
||||
echo "⚠️ GOOGLE_API_KEY not set - skipping tests"
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Install dependencies
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
run: |
|
||||
pip install --upgrade pip
|
||||
cd src/praisonai-agents
|
||||
pip install -e ".[all]"
|
||||
cd ../praisonai
|
||||
pip install -e ".[google]"
|
||||
pip install pytest pytest-asyncio pytest-timeout
|
||||
|
||||
- name: Run Google/Gemini Tests
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
env:
|
||||
PRAISONAI_ALLOW_NETWORK: '1'
|
||||
PRAISONAI_LIVE_TESTS: '1'
|
||||
PRAISONAI_TEST_PROVIDERS: 'google'
|
||||
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
|
||||
run: |
|
||||
cd src/praisonai
|
||||
python -m pytest tests/ \
|
||||
-m "provider_google" \
|
||||
-v --tb=short \
|
||||
--timeout=120 \
|
||||
--ignore=tests/fixtures \
|
||||
|| echo "Google tests completed"
|
||||
|
||||
- name: Skip notice
|
||||
if: steps.check-key.outputs.has_key == 'false'
|
||||
run: echo "✅ Google tests skipped (no API key available)"
|
||||
|
||||
extended-groq:
|
||||
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 10
|
||||
|
||||
steps:
|
||||
- name: Check if Groq key is available
|
||||
id: check-key
|
||||
run: |
|
||||
if [ -n "${{ secrets.GROQ_API_KEY }}" ]; then
|
||||
echo "has_key=true" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "has_key=false" >> $GITHUB_OUTPUT
|
||||
echo "⚠️ GROQ_API_KEY not set - skipping tests"
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Install dependencies
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
run: |
|
||||
pip install --upgrade pip
|
||||
cd src/praisonai-agents
|
||||
pip install -e ".[all]"
|
||||
cd ../praisonai
|
||||
pip install -e .
|
||||
pip install pytest pytest-asyncio pytest-timeout
|
||||
|
||||
- name: Run Groq Tests
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
env:
|
||||
PRAISONAI_ALLOW_NETWORK: '1'
|
||||
PRAISONAI_LIVE_TESTS: '1'
|
||||
PRAISONAI_TEST_PROVIDERS: 'groq'
|
||||
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
|
||||
run: |
|
||||
cd src/praisonai
|
||||
python -m pytest tests/ \
|
||||
-m "provider_groq" \
|
||||
-v --tb=short \
|
||||
--timeout=120 \
|
||||
--ignore=tests/fixtures \
|
||||
|| echo "Groq tests completed"
|
||||
|
||||
- name: Skip notice
|
||||
if: steps.check-key.outputs.has_key == 'false'
|
||||
run: echo "✅ Groq tests skipped (no API key available)"
|
||||
|
||||
extended-xai:
|
||||
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 10
|
||||
|
||||
steps:
|
||||
- name: Check if xAI key is available
|
||||
id: check-key
|
||||
run: |
|
||||
if [ -n "${{ secrets.XAI_API_KEY }}" ]; then
|
||||
echo "has_key=true" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "has_key=false" >> $GITHUB_OUTPUT
|
||||
echo "⚠️ XAI_API_KEY not set - skipping tests"
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Install dependencies
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
run: |
|
||||
pip install --upgrade pip
|
||||
cd src/praisonai-agents
|
||||
pip install -e ".[all]"
|
||||
cd ../praisonai
|
||||
pip install -e .
|
||||
pip install pytest pytest-asyncio pytest-timeout
|
||||
|
||||
- name: Run xAI/Grok Tests
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
env:
|
||||
PRAISONAI_ALLOW_NETWORK: '1'
|
||||
PRAISONAI_LIVE_TESTS: '1'
|
||||
PRAISONAI_TEST_PROVIDERS: 'grok_xai'
|
||||
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
|
||||
run: |
|
||||
cd src/praisonai
|
||||
python -m pytest tests/ \
|
||||
-m "provider_grok_xai" \
|
||||
-v --tb=short \
|
||||
--timeout=120 \
|
||||
--ignore=tests/fixtures \
|
||||
|| echo "xAI tests completed"
|
||||
|
||||
- name: Skip notice
|
||||
if: steps.check-key.outputs.has_key == 'false'
|
||||
run: echo "✅ xAI tests skipped (no API key available)"
|
||||
|
||||
extended-cohere:
|
||||
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 10
|
||||
|
||||
steps:
|
||||
- name: Check if Cohere key is available
|
||||
id: check-key
|
||||
run: |
|
||||
if [ -n "${{ secrets.COHERE_API_KEY }}" ]; then
|
||||
echo "has_key=true" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "has_key=false" >> $GITHUB_OUTPUT
|
||||
echo "⚠️ COHERE_API_KEY not set - skipping tests"
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Install dependencies
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
run: |
|
||||
pip install --upgrade pip
|
||||
cd src/praisonai-agents
|
||||
pip install -e ".[all]"
|
||||
cd ../praisonai
|
||||
pip install -e ".[cohere]"
|
||||
pip install pytest pytest-asyncio pytest-timeout
|
||||
|
||||
- name: Run Cohere Tests
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
env:
|
||||
PRAISONAI_ALLOW_NETWORK: '1'
|
||||
PRAISONAI_LIVE_TESTS: '1'
|
||||
PRAISONAI_TEST_PROVIDERS: 'cohere'
|
||||
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
|
||||
run: |
|
||||
cd src/praisonai
|
||||
python -m pytest tests/ \
|
||||
-m "provider_cohere" \
|
||||
-v --tb=short \
|
||||
--timeout=120 \
|
||||
--ignore=tests/fixtures \
|
||||
|| echo "Cohere tests completed"
|
||||
|
||||
- name: Skip notice
|
||||
if: steps.check-key.outputs.has_key == 'false'
|
||||
run: echo "✅ Cohere tests skipped (no API key available)"
|
||||
|
||||
# ============================================
|
||||
# TEST SUMMARY
|
||||
# ============================================
|
||||
test-summary:
|
||||
needs: [smoke, main]
|
||||
if: always()
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Test Summary
|
||||
run: |
|
||||
echo "# 📊 Test Suite Summary" >> $GITHUB_STEP_SUMMARY
|
||||
echo "" >> $GITHUB_STEP_SUMMARY
|
||||
echo "| Job | Status |" >> $GITHUB_STEP_SUMMARY
|
||||
echo "|-----|--------|" >> $GITHUB_STEP_SUMMARY
|
||||
echo "| Smoke | ${{ needs.smoke.result }} |" >> $GITHUB_STEP_SUMMARY
|
||||
echo "| Main | ${{ needs.main.result }} |" >> $GITHUB_STEP_SUMMARY
|
||||
echo "" >> $GITHUB_STEP_SUMMARY
|
||||
echo "## Test Tiers" >> $GITHUB_STEP_SUMMARY
|
||||
echo "- **smoke**: Fast unit tests, no network (≤2 min)" >> $GITHUB_STEP_SUMMARY
|
||||
echo "- **main**: Unit + integration, no network (≤5 min)" >> $GITHUB_STEP_SUMMARY
|
||||
echo "- **openai-live**: OpenAI API tests (when key available)" >> $GITHUB_STEP_SUMMARY
|
||||
echo "- **extended-***: Provider-specific tests (nightly)" >> $GITHUB_STEP_SUMMARY
|
||||
@@ -0,0 +1,204 @@
|
||||
name: Windows Tests
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [main, develop]
|
||||
pull_request:
|
||||
branches: [main, develop]
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
test-windows:
|
||||
runs-on: windows-latest
|
||||
timeout-minutes: 5
|
||||
env:
|
||||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
OPENAI_MODEL_NAME: gpt-4o-mini
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python 3.11
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.11"
|
||||
|
||||
- name: Install praisonaiagents
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
cd src/praisonai-agents
|
||||
pip install .
|
||||
shell: bash
|
||||
|
||||
- name: Install praisonai wrapper
|
||||
run: |
|
||||
cd src/praisonai
|
||||
pip install .[dev]
|
||||
shell: bash
|
||||
|
||||
# ==================== CORE IMPORTS ====================
|
||||
- name: Test core imports
|
||||
run: |
|
||||
python -c "from praisonaiagents import Agent, Agents, Workflow; print('Core imports OK')"
|
||||
python -c "from praisonaiagents import tool, Tools; print('Tool imports OK')"
|
||||
python -c "from praisonaiagents import Task, WorkflowStep; print('Task/Step imports OK')"
|
||||
|
||||
# ==================== AGENT FEATURES ====================
|
||||
- name: Test Agent instantiation
|
||||
run: |
|
||||
python -c "
|
||||
from praisonaiagents import Agent
|
||||
a = Agent(name='Test', instructions='You are helpful')
|
||||
print('Agent created:', a.name)
|
||||
a2 = Agent(name='ToolAgent', instructions='Use tools', tools=[])
|
||||
print('Agent with tools:', a2.name)
|
||||
"
|
||||
|
||||
- name: Test Agents orchestration
|
||||
run: |
|
||||
python -c "
|
||||
from praisonaiagents import Agent, Agents, Task
|
||||
a1 = Agent(name='Agent1', instructions='First agent')
|
||||
a2 = Agent(name='Agent2', instructions='Second agent')
|
||||
t = Task(description='Do something', agent=a1)
|
||||
agents = Agents(agents=[a1, a2], tasks=[t])
|
||||
print('Agents:', len(agents.agents), 'Tasks:', len(agents.tasks))
|
||||
"
|
||||
|
||||
# ==================== WORKFLOW FEATURES ====================
|
||||
- name: Test Workflow and WorkflowStep
|
||||
run: |
|
||||
python -c "
|
||||
from praisonaiagents import Workflow, WorkflowStep
|
||||
from praisonaiagents.workflows import WorkflowOutputConfig
|
||||
|
||||
w = Workflow(name='test')
|
||||
s1 = WorkflowStep(name='step1')
|
||||
s2 = WorkflowStep(name='step2', context=['step1'])
|
||||
print('Workflow:', w.name)
|
||||
print('Steps:', s1.name, s2.name)
|
||||
|
||||
cfg = WorkflowOutputConfig(verbose=True, stream=False)
|
||||
w2 = Workflow(name='configured', output=cfg)
|
||||
print('Configured workflow verbose:', w2.verbose)
|
||||
"
|
||||
|
||||
# ==================== MEMORY FEATURES ====================
|
||||
- name: Test Memory classes
|
||||
run: |
|
||||
python -c "
|
||||
from praisonaiagents.memory import FileMemory
|
||||
from praisonaiagents.config import MemoryConfig
|
||||
|
||||
cfg = MemoryConfig(backend='file', user_id='test_user')
|
||||
print('MemoryConfig backend:', cfg.backend)
|
||||
|
||||
mem = FileMemory(user_id='test_user', base_path='.praison/test_memory')
|
||||
print('FileMemory user:', mem.user_id)
|
||||
"
|
||||
|
||||
# ==================== TOOL DECORATOR ====================
|
||||
- name: Test tool decorator
|
||||
run: |
|
||||
python -c "
|
||||
from praisonaiagents import tool
|
||||
|
||||
@tool
|
||||
def my_tool(query: str) -> str:
|
||||
'''A test tool'''
|
||||
return f'Echo: {query}'
|
||||
|
||||
result = my_tool('hello')
|
||||
print('Tool result:', result)
|
||||
"
|
||||
|
||||
# ==================== CONFIG CLASSES ====================
|
||||
- name: Test config classes
|
||||
run: |
|
||||
python -c "
|
||||
from praisonaiagents.config import OutputConfig, ExecutionConfig, PlanningConfig
|
||||
|
||||
out_cfg = OutputConfig(verbose=True, stream=True)
|
||||
print('OutputConfig verbose:', out_cfg.verbose)
|
||||
|
||||
exec_cfg = ExecutionConfig(max_iter=50, max_retry_limit=5)
|
||||
print('ExecutionConfig max_iter:', exec_cfg.max_iter)
|
||||
|
||||
plan_cfg = PlanningConfig(reasoning=True, auto_approve=False)
|
||||
print('PlanningConfig reasoning:', plan_cfg.reasoning)
|
||||
"
|
||||
# ==================== HANDOFF ====================
|
||||
- name: Test Handoff
|
||||
run: |
|
||||
python -c "
|
||||
from praisonaiagents import Handoff, handoff, Agent
|
||||
|
||||
a1 = Agent(name='Agent1', instructions='First')
|
||||
a2 = Agent(name='Agent2', instructions='Second')
|
||||
|
||||
# Using Handoff class directly
|
||||
h = Handoff(agent=a2)
|
||||
print('Handoff tool name:', h.tool_name)
|
||||
|
||||
# Using handoff function
|
||||
h2 = handoff(a1, tool_name_override='custom_handoff')
|
||||
print('Custom handoff name:', h2.tool_name)
|
||||
"
|
||||
|
||||
|
||||
# ==================== ASYNC FEATURES ====================
|
||||
- name: Test async imports
|
||||
run: |
|
||||
python -c "
|
||||
import asyncio
|
||||
from praisonaiagents import Agent
|
||||
|
||||
async def test_async():
|
||||
agent = Agent(name='AsyncAgent', instructions='Test')
|
||||
assert hasattr(agent, 'arun'), 'Missing arun'
|
||||
assert hasattr(agent, 'astart'), 'Missing astart'
|
||||
print('Async methods available')
|
||||
|
||||
asyncio.run(test_async())
|
||||
"
|
||||
|
||||
# ==================== CLI COMMANDS ====================
|
||||
- name: Test CLI help
|
||||
run: praisonai --help
|
||||
|
||||
- name: Test CLI session list
|
||||
run: praisonai session list
|
||||
continue-on-error: true
|
||||
|
||||
- name: Test CLI queue list
|
||||
run: praisonai queue list
|
||||
continue-on-error: true
|
||||
|
||||
# ==================== REAL API TESTS ====================
|
||||
- name: Real API test - Agent run
|
||||
if: env.OPENAI_API_KEY != ''
|
||||
run: |
|
||||
python -c "
|
||||
from praisonaiagents import Agent
|
||||
agent = Agent(name='TestAgent', instructions='Reply with exactly: WINDOWS_OK', llm='gpt-4o-mini')
|
||||
result = agent.run('Say WINDOWS_OK')
|
||||
print('Result:', result)
|
||||
print('Real API test passed')
|
||||
"
|
||||
|
||||
- name: Real API test - Multi-agent
|
||||
if: env.OPENAI_API_KEY != ''
|
||||
run: |
|
||||
python -c "
|
||||
from praisonaiagents import Agent, Agents, Task
|
||||
|
||||
researcher = Agent(name='Researcher', instructions='You research topics', llm='gpt-4o-mini')
|
||||
writer = Agent(name='Writer', instructions='You write content', llm='gpt-4o-mini')
|
||||
|
||||
task = Task(description='Say hello world', agent=researcher)
|
||||
|
||||
agents = Agents(agents=[researcher, writer], tasks=[task])
|
||||
result = agents.start()
|
||||
print('Multi-agent result type:', type(result))
|
||||
print('Multi-agent test passed')
|
||||
"
|
||||
@@ -0,0 +1,57 @@
|
||||
name: Update API Reference
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [ "main" ]
|
||||
paths:
|
||||
- 'src/praisonai-agents/praisonaiagents/**/*.py'
|
||||
- 'src/praisonai/praisonai/**/*.py'
|
||||
- 'src/praisonai-ts/src/**/*.ts'
|
||||
- '.github/workflows/update-api-md.yml'
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
|
||||
jobs:
|
||||
update-api-md:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: main
|
||||
persist-credentials: true
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Generate api.md
|
||||
run: |
|
||||
cd $GITHUB_WORKSPACE
|
||||
python3 src/praisonai/scripts/generate_api_md.py
|
||||
|
||||
- name: Check for changes
|
||||
id: check_changes
|
||||
run: |
|
||||
if git diff --quiet api.md; then
|
||||
echo "changes=false" >> $GITHUB_OUTPUT
|
||||
echo "No changes to api.md"
|
||||
else
|
||||
echo "changes=true" >> $GITHUB_OUTPUT
|
||||
echo "api.md has been updated"
|
||||
git diff api.md | head -50
|
||||
fi
|
||||
|
||||
- name: Commit and push changes
|
||||
if: steps.check_changes.outputs.changes == 'true'
|
||||
uses: stefanzweifel/git-auto-commit-action@v5
|
||||
with:
|
||||
commit_message: "docs: auto-update api.md [skip ci]"
|
||||
file_pattern: 'api.md'
|
||||
commit_user_name: "github-actions[bot]"
|
||||
commit_user_email: "41898282+github-actions[bot]@users.noreply.github.com"
|
||||
commit_author: "github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>"
|
||||
+2
-1
@@ -83,4 +83,5 @@ issue_details.json
|
||||
# MCP Registry tokens
|
||||
.mcpregistry_*
|
||||
|
||||
*.log
|
||||
*.log
|
||||
.internal
|
||||
@@ -23,7 +23,7 @@
|
||||
|
||||
</div>
|
||||
|
||||
PraisonAI is a production-ready Multi-AI Agents framework with self-reflection, designed to create AI Agents to automate and solve problems ranging from simple tasks to complex challenges. By integrating PraisonAI Agents, AG2 (Formerly AutoGen), and CrewAI into a low-code solution, it streamlines the building and management of multi-agent LLM systems, emphasising simplicity, customisation, and effective human-agent collaboration.
|
||||
PraisonAI is a production-ready Multi-AI Agents framework with self-reflection, designed to create AI Agents to automate and solve problems ranging from simple tasks to complex challenges. It provides a low-code solution to streamline the building and management of multi-agent LLM systems, emphasising simplicity, customisation, and effective human-agent collaboration.
|
||||
|
||||
<div align="center">
|
||||
<a href="https://docs.praison.ai">
|
||||
|
||||
@@ -0,0 +1,441 @@
|
||||
# PraisonAI API Reference
|
||||
|
||||
This file is auto-generated. Do not edit manually.
|
||||
Regenerate with: `praisonai docs api-md --write`
|
||||
|
||||
# Agents
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Agent, Agents
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">achat</a>(prompt: str, temperature = 1.0, tools = None, output_json = None, output_pydantic = None, reasoning_steps = False, task_name = None, task_description = None, task_id = None)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">aexecute</a>(task, context = None)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">agent_id</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">analyze_prompt</a>(prompt: str) -> set</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">arun</a>(prompt: str, **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">astart</a>(prompt: str, **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat</a>(prompt, temperature = 1.0, tools = None, output_json = None, output_pydantic = None, reasoning_steps = False, stream = None, task_name = None, task_description = None, task_id = None, config = None, force_retrieval = False, skip_retrieval = False)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat_with_context</a>(message: str, context: 'ContextPack', **kwargs) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">clean_json_output</a>(output: str) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">clear_history</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">console</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">context_manager</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">context_manager</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">display_generating</a>(content: str, start_time: float)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">execute</a>(task, context = None)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">execute_tool</a>(function_name, arguments)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">execute_tool_async</a>(function_name: str, arguments: Dict[str, Any]) -> Any</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">from_template</a>(uri: str, config: Optional[Dict[str, Any]] = None, offline: bool = False, **kwargs) -> 'Agent'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">generate_task</a>() -> 'Task'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_available_tools</a>() -> List[Any]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_memory_context</a>(query: Optional[str] = None) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_recommended_stage</a>(prompt: str) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_rules_context</a>(file_path: Optional[str] = None, include_manual: Optional[List[str]] = None) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_skills_prompt</a>() -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">handoff_to</a>(target_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None, config: Optional['HandoffConfig'] = None) -> 'HandoffResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">handoff_to_async</a>(target_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None, config: Optional['HandoffConfig'] = None) -> 'HandoffResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">iter_stream</a>(prompt: str, **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">launch</a>(path: str = '/', port: int = 8000, host: str = '0.0.0.0', debug: bool = False, protocol: str = 'http')</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">llm_model</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">output_style</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">output_style</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">policy</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">policy</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">query</a>(question: str, **kwargs) -> 'RAGResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rag</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rag_query</a>(question: str, **kwargs) -> 'RAGResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieval_config</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieve</a>(query: str, **kwargs) -> 'ContextPack'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rules_manager</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run</a>(prompt: str, **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_autonomous</a>(prompt: str, max_iterations: Optional[int] = None, timeout_seconds: Optional[float] = None)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">session_id</a>() -> Optional[str]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">skill_manager</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">start</a>(prompt: str = None, **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">store_memory</a>(content: str, memory_type: str = 'short_term', **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">switch_model</a>(new_model: str) -> None</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>(value)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">add_task</a>(task)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aexecute_task</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">append_to_state</a>(key: str, value: Any, max_length: Optional[int] = None) -> List[Any]</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_all_tasks</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_task</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart</a>(content = None, return_dict = False, **kwargs)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clean_json_output</a>(output: str) -> str</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clear_state</a>() -> None</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">context_manager</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">current_plan</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">default_completion_checker</a>(task, agent_output)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">delete_state</a>(key: str) -> bool</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">display_token_usage</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">execute_task</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_agent_details</a>(agent_name)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_state</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_tasks_status</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_detailed_token_report</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_plan_markdown</a>() -> str</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_state</a>(key: str, default: Any = None) -> Any</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_details</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_result</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_status</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_todo_markdown</a>() -> str</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_token_usage_summary</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">has_state</a>(key: str) -> bool</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">increment_state</a>(key: str, amount: float = 1, default: float = 0) -> float</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">launch</a>(path: str = '/agents', port: int = 8000, host: str = '0.0.0.0', debug: bool = False, protocol: str = 'http')</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">restore_session_state</a>(session_id: str) -> bool</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run</a>(content = None, return_dict = False, **kwargs)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_all_tasks</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_task</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_output_to_file</a>(task, task_output)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> None</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">set_state</a>(key: str, value: Any) -> None</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start</a>(content = None, return_dict = False, output = None, **kwargs)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">todo_list</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_plan_step_status</a>(step_id: str, status: str) -> bool</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_state</a>(updates: Dict) -> None</code>
|
||||
|
||||
# Tools
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Tools, tool
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">tool</a>(func: Optional[Callable] = None) -> Union[FunctionTool, Callable[[Callable], FunctionTool]]</code>
|
||||
|
||||
# Other
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Task
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">execute_callback</a>(task_output: TaskOutput) -> None</code>
|
||||
* <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">execute_callback_sync</a>(task_output: TaskOutput) -> None</code>
|
||||
* <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">initialize_memory</a>()</code>
|
||||
* <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">store_in_memory</a>(content: str, agent_name: str = None, task_id: str = None)</code>
|
||||
|
||||
# Wrapper (praisonai)
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonai import CloudProvider, Deploy, DeployConfig, DeployType, PraisonAI, __version__
|
||||
```
|
||||
|
||||
# CLI
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="cli">praisonai <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
|
||||
* <code title="cli">praisonai acp acp-main <a href="./src/praisonai/praisonai/cli/commands/acp.py">--help</a></code>
|
||||
* <code title="cli">praisonai agents create <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
|
||||
* <code title="cli">praisonai agents info <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
|
||||
* <code title="cli">praisonai agents list <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
|
||||
* <code title="cli">praisonai audit agent-centric <a href="./src/praisonai/praisonai/cli/commands/audit.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark agent <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark benchmark-callback <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark cli <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark compare <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark litellm <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark profile <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark sdk <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark workflow <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai call call-main <a href="./src/praisonai/praisonai/cli/commands/call.py">--help</a></code>
|
||||
* <code title="cli">praisonai chat <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
|
||||
* <code title="cli">praisonai chat chat-main <a href="./src/praisonai/praisonai/cli/commands/chat.py">--help</a></code>
|
||||
* <code title="cli">praisonai code <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
|
||||
* <code title="cli">praisonai code code-main <a href="./src/praisonai/praisonai/cli/commands/code.py">--help</a></code>
|
||||
* <code title="cli">praisonai commit commit-main <a href="./src/praisonai/praisonai/cli/commands/commit.py">--help</a></code>
|
||||
* <code title="cli">praisonai completion bash <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
|
||||
* <code title="cli">praisonai completion completion-callback <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
|
||||
* <code title="cli">praisonai completion fish <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
|
||||
* <code title="cli">praisonai completion zsh <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
|
||||
* <code title="cli">praisonai config get <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai config list <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai config path <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai config reset <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai config set <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai context add <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context clear <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context compact <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context export <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context grep <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context list <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context show <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context stats <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context tail <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug acp <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug debug-callback <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug interactive <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug lsp <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug trace <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai deploy aws <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
|
||||
* <code title="cli">praisonai deploy azure <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
|
||||
* <code title="cli">praisonai deploy docker <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
|
||||
* <code title="cli">praisonai deploy gcp <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
|
||||
* <code title="cli">praisonai diag diag-callback <a href="./src/praisonai/praisonai/cli/commands/diag.py">--help</a></code>
|
||||
* <code title="cli">praisonai diag export <a href="./src/praisonai/praisonai/cli/commands/diag.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs api-md <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs generate <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs list <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs report <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs run <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs run-all <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs serve <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs stats <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor cleanup <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor config <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor db <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor doctor-callback <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor env <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor mcp <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor network <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor performance <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor selftest <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor tools <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor troubleshoot <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai endpoints list <a href="./src/praisonai/praisonai/cli/commands/endpoints.py">--help</a></code>
|
||||
* <code title="cli">praisonai endpoints test <a href="./src/praisonai/praisonai/cli/commands/endpoints.py">--help</a></code>
|
||||
* <code title="cli">praisonai environment check <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
|
||||
* <code title="cli">praisonai environment doctor <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
|
||||
* <code title="cli">praisonai environment view <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
|
||||
* <code title="cli">praisonai eval accuracy <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
|
||||
* <code title="cli">praisonai eval performance <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples info <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples list <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples report <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples run <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples run-all <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples stats <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai hooks add <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
|
||||
* <code title="cli">praisonai hooks list <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
|
||||
* <code title="cli">praisonai hooks remove <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
|
||||
* <code title="cli">praisonai knowledge add <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
|
||||
* <code title="cli">praisonai knowledge index <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
|
||||
* <code title="cli">praisonai knowledge list <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
|
||||
* <code title="cli">praisonai knowledge search <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp logs <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp lsp-callback <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp start <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp status <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp stop <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp add <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp describe <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp list <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp mcp-callback <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp remove <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp run <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp status <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp sync <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp test <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp tools <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai memory add <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
|
||||
* <code title="cli">praisonai memory clear <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
|
||||
* <code title="cli">praisonai memory search <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
|
||||
* <code title="cli">praisonai memory show <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
|
||||
* <code title="cli">praisonai memory status <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
|
||||
* <code title="cli">praisonai package install <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
|
||||
* <code title="cli">praisonai package list <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
|
||||
* <code title="cli">praisonai package uninstall <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile imports <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile optimize <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile profile-callback <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile query <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile snapshot <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile startup <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile suite <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag chat <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag eval <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag index <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag query <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag serve <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai realtime realtime-main <a href="./src/praisonai/praisonai/cli/commands/realtime.py">--help</a></code>
|
||||
* <code title="cli">praisonai recipe install <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
|
||||
* <code title="cli">praisonai recipe list <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
|
||||
* <code title="cli">praisonai recipe run <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
|
||||
* <code title="cli">praisonai registry list <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
|
||||
* <code title="cli">praisonai registry serve <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
|
||||
* <code title="cli">praisonai research research-main <a href="./src/praisonai/praisonai/cli/commands/research.py">--help</a></code>
|
||||
* <code title="cli">praisonai retrieval index <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
|
||||
* <code title="cli">praisonai retrieval query <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
|
||||
* <code title="cli">praisonai retrieval search <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
|
||||
* <code title="cli">praisonai rules add <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
|
||||
* <code title="cli">praisonai rules clear <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
|
||||
* <code title="cli">praisonai rules list <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
|
||||
* <code title="cli">praisonai run <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
|
||||
* <code title="cli">praisonai run run-main <a href="./src/praisonai/praisonai/cli/commands/run.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule delete <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule describe <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule list <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule logs <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule restart <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule schedule-callback <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule start <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule stats <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule stop <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai serve serve-callback <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
|
||||
* <code title="cli">praisonai serve start <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
|
||||
* <code title="cli">praisonai serve status <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
|
||||
* <code title="cli">praisonai serve stop <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
|
||||
* <code title="cli">praisonai session delete <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session export <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session import <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session list <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session resume <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session show <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills create <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills info <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills install <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills list <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills search <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills validate <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai standardise check <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
|
||||
* <code title="cli">praisonai standardise fix <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
|
||||
* <code title="cli">praisonai standardise init <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
|
||||
* <code title="cli">praisonai standardise report <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
|
||||
* <code title="cli">praisonai templates create <a href="./src/praisonai/praisonai/cli/commands/templates.py">--help</a></code>
|
||||
* <code title="cli">praisonai templates list <a href="./src/praisonai/praisonai/cli/commands/templates.py">--help</a></code>
|
||||
* <code title="cli">praisonai test info <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
|
||||
* <code title="cli">praisonai test interactive <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
|
||||
* <code title="cli">praisonai test run <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
|
||||
* <code title="cli">praisonai todo add <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
|
||||
* <code title="cli">praisonai todo done <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
|
||||
* <code title="cli">praisonai todo list <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
|
||||
* <code title="cli">praisonai tools info <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
|
||||
* <code title="cli">praisonai tools list <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
|
||||
* <code title="cli">praisonai tools test <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
|
||||
* <code title="cli">praisonai traces disable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
|
||||
* <code title="cli">praisonai traces enable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
|
||||
* <code title="cli">praisonai traces list <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
|
||||
* <code title="cli">praisonai traces status <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
|
||||
* <code title="cli">praisonai train train-main <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui chat <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui code <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui gradio <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui realtime <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui ui-main <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai version check <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
|
||||
* <code title="cli">praisonai version show <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
|
||||
* <code title="cli">praisonai version version-callback <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
|
||||
* <code title="cli">praisonai workflow create <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
|
||||
* <code title="cli">praisonai workflow list <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
|
||||
* <code title="cli">praisonai workflow run <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
|
||||
|
||||
# TypeScript
|
||||
|
||||
Types/Exports:
|
||||
```ts
|
||||
export { Agent, Agents, PraisonAIAgents, Router } from "./agent";
|
||||
export type { PraisonAIAgentsConfig, SimpleAgentConfig, SimpleRouteConfig, SimpleRouterConfig } from "./agent";
|
||||
export { ContextAgent, createContextAgent } from "./agent/context";
|
||||
export { Handoff, handoff, handoffFilters } from "./agent/handoff";
|
||||
export { ImageAgent, createImageAgent } from "./agent/image";
|
||||
export { PromptExpanderAgent, createPromptExpanderAgent } from "./agent/prompt-expander";
|
||||
export { QueryRewriterAgent, createQueryRewriterAgent } from "./agent/query-rewriter";
|
||||
export { DeepResearchAgent, createDeepResearchAgent } from "./agent/research";
|
||||
export { RouterAgent, createRouter, routeConditions } from "./agent/router";
|
||||
export { // Agent loop
|
||||
createAgentLoop, // DevTools
|
||||
enableDevTools, // MCP
|
||||
createMCP, // Middleware (renamed to avoid conflicts)
|
||||
createCachingMiddleware, // Models
|
||||
createModel, // Multimodal
|
||||
createImagePart, // Next.js
|
||||
createRouteHandler, // OAuth for MCP
|
||||
type OAuthClientProvider, // Server adapters
|
||||
createHttpHandler, // Speech & Transcription
|
||||
generateSpeech, // Telemetry (AI SDK v6 parity)
|
||||
configureTelemetry, // Tool Approval (AI SDK v6 parity)
|
||||
ApprovalManager, // Tools
|
||||
defineTool, // UI Message (AI SDK v6 parity)
|
||||
convertToModelMessages, AIAgentStep, AIEmbedManyResult, AIEmbedOptions, AIEmbedResult, AIFilePart, AIGenerateImageOptions, AIGenerateImageResult, AIGenerateObjectOptions, AIGenerateObjectResult, AIGenerateTextOptions, AIGenerateTextResult, AIImagePart, AIMiddleware, AIMiddlewareConfig, AIModelMessage, AISpan, AISpanKind, AISpanOptions, AISpanStatus, AIStreamObjectOptions, AIStreamObjectResult, AIStreamTextOptions, AIStreamTextResult, AITelemetryEvent, AITelemetrySettings, AITextPart, AIToolDefinition, AITracer, AgentLoop, DANGEROUS_PATTERNS, MODEL_ALIASES, SPEECH_MODELS, TRANSCRIPTION_MODELS, ToolApprovalDeniedError, ToolApprovalTimeoutError, aiEmbed, aiEmbedMany, aiGenerateImage, aiGenerateObject, aiGenerateText, aiStreamObject, aiStreamText, applyMiddleware, autoEnableDevTools, base64ToUint8Array, clearAICache, clearEvents, closeAllMCPClients, closeMCPClient, convertToUIMessages, createAILoggingMiddleware, createAISpan, createApprovalResponse, createDangerousPatternChecker, createDevToolsMiddleware, createExpressHandler, createFastifyHandler, createFilePart, createHonoHandler, createMultimodalMessage, createNestHandler, createPagesHandler, createPdfPart, createSystemMessage, createTelemetryMiddleware, createTelemetrySettings, createTextMessage, createTextPart, createToolSet, disableAITelemetry, disableDevTools, enableAITelemetry, functionToTool, getAICacheStats, getApprovalManager, getDevToolsState, getDevToolsUrl, getEvents, getMCPClient, getModel, getTelemetrySettings, getToolsNeedingApproval, getTracer, hasModelAlias, hasPendingApprovals, initOpenTelemetry, isDangerous, isDataUrl, isDevToolsEnabled, isTelemetryEnabled, isUrl, listModelAliases, mcpToolsToAITools, parseModel, pipeUIMessageStreamToResponse, recordEvent, resolveModelAlias, safeValidateUIMessages, setApprovalManager, stopAfterSteps, stopWhen, stopWhenNoToolCalls, toMessageContent, toUIMessageStreamResponse, transcribe, uint8ArrayToBase64, validateUIMessages, withApproval, withSpan, wrapModel } from "./ai";
|
||||
export { AutoAgents, createAutoAgents } from "./auto";
|
||||
export { BaseCache, FileCache, MemoryCache, createFileCache, createMemoryCache } from "./cache";
|
||||
export { CLI_SPEC_VERSION, executeCommand, parseArgs } from "./cli";
|
||||
export { // Autonomy Mode
|
||||
AutonomyManager, // Background Jobs
|
||||
JobQueue, // Checkpoints
|
||||
CheckpointManager, // Cost Tracker
|
||||
CostTracker, // External Agents
|
||||
BaseExternalAgent, // Fast Context
|
||||
FastContext, // Flow Display
|
||||
FlowDisplay, // Git Integration
|
||||
GitManager, // Interactive TUI
|
||||
InteractiveTUI, // N8N Integration
|
||||
N8NIntegration, // Repo Map
|
||||
RepoMap, // Sandbox Executor
|
||||
SandboxExecutor, // Scheduler
|
||||
Scheduler, // Slash Commands
|
||||
SlashCommandHandler, AiderAgent, ClaudeCodeAgent, CodexCliAgent, CommandValidator, CostTokenUsage, DEFAULT_BLOCKED_COMMANDS, DEFAULT_BLOCKED_PATHS, DEFAULT_IGNORE_PATTERNS, DiffViewer, FileCheckpointStorage, FileJobStorage, GeminiCliAgent, GenericExternalAgent, HistoryManager, MODEL_PRICING, MODE_POLICIES, MemoryCheckpointStorage, MemoryJobStorage, StatusDisplay, cliApprovalPrompt, createAutonomyManager, createCheckpointManager, createCostTracker, createDiffViewer, createExternalAgent, createFastContext, createFileCheckpointStorage, createFileJobStorage, createFlowDisplay, createGitManager, createHistoryManager, createInteractiveTUI, createJobQueue, createN8NIntegration, createRepoMap, createSandboxExecutor, createScheduler, createSlashCommandHandler, createStatusDisplay, cronExpressions, estimateTokens, executeSlashCommand, externalAgentAsTool, formatCost, getExternalAgentRegistry, getQuickContext, getRepoTree, isSlashCommand, parseSlashCommand, registerCommand, renderWorkflow, sandboxExec, triggerN8NWebhook } from "./cli/features";
|
||||
export { createDbAdapter, db, getDefaultDbAdapter, setDefaultDbAdapter } from "./db";
|
||||
export type { DbAdapter, DbConfig, DbMessage, DbRun, DbTrace } from "./db";
|
||||
export { MemoryPostgresAdapter, NeonPostgresAdapter, PostgresSessionStorage, createMemoryPostgres, createNeonPostgres, createPostgresSessionStorage } from "./db/postgres";
|
||||
export { MemoryRedisAdapter, UpstashRedisAdapter, createMemoryRedis, createUpstashRedis } from "./db/redis";
|
||||
export { SQLiteAdapter, createSQLiteAdapter } from "./db/sqlite";
|
||||
export { EvalSuite, accuracyEval, performanceEval, reliabilityEval } from "./eval";
|
||||
export { AgentEventBus, AgentEvents, EventEmitterPubSub, PubSub, createEventBus, createPubSub } from "./events";
|
||||
export { LLMGuardrail, createLLMGuardrail } from "./guardrails/llm-guardrail";
|
||||
export { // Computer Use
|
||||
createComputerUse, ComputerUseClient, createCLIApprovalPrompt, createComputerUseAgent } from "./integrations/computer-use";
|
||||
export { BaseObservabilityProvider, ConsoleObservabilityProvider, LangfuseObservabilityProvider, MemoryObservabilityProvider, ObservabilityTraceContext, createConsoleObservability, createLangfuseObservability, createMemoryObservability } from "./integrations/observability";
|
||||
export { // Natural Language Postgres
|
||||
createNLPostgres, NLPostgresClient, NLPostgresConfig, createPostgresTool } from "./integrations/postgres";
|
||||
export { // Slack
|
||||
createSlackBot, SlackBot, parseSlackMessage, verifySlackSignature } from "./integrations/slack";
|
||||
export { BaseVectorStore, ChromaVectorStore, MemoryVectorStore, PineconeVectorStore, QdrantVectorStore, VectorQueryResult, WeaviateVectorStore, createChromaStore, createMemoryVectorStore, createPineconeStore, createQdrantStore, createWeaviateStore } from "./integrations/vector";
|
||||
export { BaseVoiceProvider, ElevenLabsVoiceProvider, OpenAIVoiceProvider, createElevenLabsVoice, createOpenAIVoice } from "./integrations/voice";
|
||||
export { GraphRAG, GraphStore, createGraphRAG } from "./knowledge/graph-rag";
|
||||
export { BaseReranker, CohereReranker, CrossEncoderReranker, LLMReranker, createCohereReranker, createCrossEncoderReranker, createLLMReranker } from "./knowledge/reranker";
|
||||
export { // Provider classes
|
||||
OpenAIProvider, // Provider factory and utilities
|
||||
createProvider, // Provider registry (extensibility API)
|
||||
ProviderRegistry, // Types
|
||||
type LLMProvider, AnthropicProvider, BaseProvider, GoogleProvider, ProviderMessage, ProviderToolDefinition, createProviderRegistry, getAvailableProviders, getDefaultProvider, getDefaultRegistry, hasProvider, isProviderAvailable, listProviders, parseModelString, registerBuiltinProviders, registerProvider, unregisterProvider } from "./llm/providers";
|
||||
export { ADAPTERS, AISDK_PROVIDERS, COMMUNITY_PROVIDERS, PROVIDER_ALIASES } from "./llm/providers/ai-sdk/types";
|
||||
export { AutoMemory, AutoMemoryKnowledgeBase, AutoMemoryVectorStore, DEFAULT_POLICIES, createAutoMemory, createLLMSummarizer } from "./memory/auto-memory";
|
||||
export { FileMemory, createFileMemory } from "./memory/file-memory";
|
||||
export { Memory, createMemory } from "./memory/memory";
|
||||
export type { MemoryConfig, MemoryEntry } from "./memory/memory";
|
||||
export { // Adapters
|
||||
NoopObservabilityAdapter, // Constants
|
||||
OBSERVABILITY_TOOLS, // Global adapter management
|
||||
setObservabilityAdapter, // Types
|
||||
type SpanKind, ConsoleObservabilityAdapter, MemoryObservabilityAdapter, clearAdapterCache, createConsoleAdapter, createMemoryAdapter, createObservabilityAdapter, getObservabilityAdapter, getObservabilityToolInfo, hasObservabilityToolEnvVar, listObservabilityTools, noopAdapter, resetObservabilityAdapter, trace } from "./observability";
|
||||
export { Plan, PlanStep, PlanStorage, PlanningAgent, TaskAgent, TodoItem, TodoList, createPlan, createPlanStorage, createPlanningAgent, createTaskAgent, createTodoList } from "./planning";
|
||||
export { SkillManager, createSkillManager, parseSkillFile } from "./skills";
|
||||
export { AgentTelemetry, TelemetryCollector, cleanupTelemetry, createAgentTelemetry, disableTelemetry, enableTelemetry, getTelemetry } from "./telemetry";
|
||||
export { BaseTool, FunctionTool, ToolRegistry, ToolResult, ToolValidationError, createTool, getRegistry, getTool, registerTool, tool, validateTool } from "./tools";
|
||||
export { airweaveSearch, bedrockBrowserClick, bedrockBrowserFill, bedrockBrowserNavigate, bedrockCodeInterpreter, codeExecution, codeMode, createCustomTool, exaSearch, firecrawlCrawl, firecrawlScrape, parallelSearch, perplexitySearch, registerCustomTool, registerLocalTool, registerNpmTool, superagentGuard, superagentRedact, superagentVerify, tavilyCrawl, tavilyExtract, tavilySearch, valyuBioSearch, valyuCompanyResearch, valyuEconomicsSearch, valyuFinanceSearch, valyuPaperSearch, valyuPatentSearch, valyuSecSearch, valyuWebSearch } from "./tools/builtins";
|
||||
export { MissingDependencyError, MissingEnvVarError, ToolsRegistry, composeMiddleware, createLoggingMiddleware, createRateLimitMiddleware, createRedactionMiddleware, createRetryMiddleware, createTimeoutMiddleware, createToolsRegistry, createTracingMiddleware, createValidationMiddleware, getToolsRegistry, resetToolsRegistry } from "./tools/registry";
|
||||
export type { InstallHints, PraisonTool, RedactionHooks, RegisteredTool, ToolCapabilities, ToolExecutionContext, ToolExecutionResult, ToolFactory, ToolHooks, ToolInstallStatus, ToolLimits, ToolLogger, ToolMetadata, ToolMiddleware, ToolParameterProperty, ToolParameterSchema } from "./tools/registry";
|
||||
export { registerBuiltinTools, tools } from "./tools/tools";
|
||||
export { Workflow, loop, parallel, repeat, route } from "./workflows";
|
||||
export type { StepResult, WorkflowContext, WorkflowStep } from "./workflows";
|
||||
export { createWorkflowFromYAML, loadWorkflowFromFile, parseYAMLWorkflow, validateWorkflowDefinition } from "./workflows/yaml-parser";
|
||||
```
|
||||
|
||||
# Optional Plugins
|
||||
|
||||
External tools are available via `praisonai-tools` package:
|
||||
|
||||
```bash
|
||||
pip install praisonai-tools
|
||||
```
|
||||
|
||||
See [PraisonAI-tools](https://github.com/MervinPraison/PraisonAI-tools) for available tools.
|
||||
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=3.5.2" \
|
||||
"praisonai>=3.9.2" \
|
||||
"praisonai[chat]" \
|
||||
"embedchain[github,youtube]"
|
||||
|
||||
|
||||
@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=3.5.2" \
|
||||
"praisonai>=3.9.2" \
|
||||
"praisonai[ui]" \
|
||||
"praisonai[chat]" \
|
||||
"praisonai[realtime]" \
|
||||
|
||||
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=3.5.2" \
|
||||
"praisonai>=3.9.2" \
|
||||
"praisonai[ui]" \
|
||||
"praisonai[crewai]"
|
||||
|
||||
|
||||
@@ -23,6 +23,7 @@ examples/
|
||||
|
||||
| Category | Examples | Docs |
|
||||
|----------|----------|------|
|
||||
| **Consolidated Params** | [consolidated_params/](consolidated_params/) | [📖](https://docs.praison.ai/api/consolidated-params) |
|
||||
| **Agents** | [python/agents/](python/agents/) | [📖](https://docs.praison.ai/concepts/agents) |
|
||||
| **Workflows** | [python/workflows/](python/workflows/) | [📖](https://docs.praison.ai/features/workflows) |
|
||||
| **Model Router** | [python/agents/router-agent-cost-optimization.py](python/agents/router-agent-cost-optimization.py) | [📖](https://docs.praison.ai/features/model-router) |
|
||||
@@ -35,6 +36,21 @@ examples/
|
||||
| **Serve** | [serve/](serve/) | [📖](https://docs.praison.ai/cli/serve) |
|
||||
| **Endpoints** | [serve/](serve/) | [📖](https://docs.praison.ai/cli/endpoints) |
|
||||
|
||||
## Consolidated Params Examples
|
||||
|
||||
Agent-centric API with unified parameter resolution. Precedence: Instance > Config > Array > Dict > String > Bool > Default
|
||||
|
||||
| Example | Description |
|
||||
|---------|-------------|
|
||||
| [basic_agent.py](consolidated_params/basic_agent.py) | Minimal agent with memory |
|
||||
| [basic_agents.py](consolidated_params/basic_agents.py) | Multi-agent with memory+planning |
|
||||
| [basic_workflow.py](consolidated_params/basic_workflow.py) | Workflow with consolidated params |
|
||||
| [basic_memory.py](consolidated_params/basic_memory.py) | Memory presets (file, redis, postgres) |
|
||||
| [basic_guardrails.py](consolidated_params/basic_guardrails.py) | Guardrails with callable or config |
|
||||
| [basic_workflow_agentlike.py](consolidated_params/basic_workflow_agentlike.py) | Workflow with agent-like params |
|
||||
| [basic_step_override.py](consolidated_params/basic_step_override.py) | Step-level override of workflow defaults |
|
||||
| [advanced_workflow_full_features.py](consolidated_params/advanced_workflow_full_features.py) | All consolidated params |
|
||||
|
||||
## Serve Examples
|
||||
|
||||
| Example | Description | CLI Command |
|
||||
|
||||
@@ -1,17 +1,20 @@
|
||||
"""
|
||||
Agent-Centric API Example
|
||||
|
||||
Demonstrates the new consolidated feature parameters for PraisonAI Agents.
|
||||
Demonstrates the consolidated feature parameters for PraisonAI Agents.
|
||||
These params provide a cleaner, more intuitive API with progressive disclosure.
|
||||
|
||||
New Consolidated Params:
|
||||
- memory: Union[bool, MemoryConfig, MemoryManager] - Memory and session management
|
||||
- knowledge: Union[bool, List[str], KnowledgeConfig, KnowledgeBase] - RAG and retrieval
|
||||
- planning: Union[bool, PlanningConfig] - Planning mode
|
||||
- reflection: Union[bool, ReflectionConfig] - Self-reflection
|
||||
- guardrails: Union[bool, Callable, GuardrailConfig] - Safety validation
|
||||
- web: Union[bool, WebConfig] - Web search and fetch
|
||||
- context: Union[bool, ManagerConfig, ContextManager] - Context management
|
||||
Precedence Rule: Instance > Config > Array > String > Bool > Default
|
||||
|
||||
Consolidated Params Support:
|
||||
- memory: bool | str URL | str preset | [preset, overrides] | MemoryConfig | Instance
|
||||
- knowledge: bool | str path | [sources...] | KnowledgeConfig | Instance
|
||||
- planning: bool | str LLM | [preset, overrides] | PlanningConfig
|
||||
- reflection: bool | str preset | [preset, overrides] | ReflectionConfig
|
||||
- guardrails: bool | callable | str prompt | GuardrailConfig
|
||||
- web: bool | str provider | [provider, overrides] | WebConfig
|
||||
- output: str preset | [preset, overrides] | OutputConfig
|
||||
- execution: str preset | [preset, overrides] | ExecutionConfig
|
||||
"""
|
||||
|
||||
from praisonaiagents import (
|
||||
@@ -134,13 +137,92 @@ def example_real_chat():
|
||||
instructions="You are a helpful math tutor. Be concise.",
|
||||
reflection=False,
|
||||
web=False,
|
||||
verbose=False,
|
||||
)
|
||||
|
||||
response = agent.start("What is the square root of 144?")
|
||||
print(f"Response: {response}")
|
||||
|
||||
|
||||
def example_string_presets():
|
||||
"""Example 7: String presets (NEW - user-friendly shortcuts)"""
|
||||
print("\n=== Example 7: String Presets ===")
|
||||
|
||||
# Output presets: minimal, normal, verbose, debug, silent
|
||||
agent = Agent(
|
||||
instructions="You are a verbose assistant",
|
||||
output="verbose", # String preset for output
|
||||
execution="fast", # String preset for execution
|
||||
web="tavily", # String preset for web provider
|
||||
)
|
||||
print(f"Output preset 'verbose': verbose={agent.verbose}, metrics={agent.metrics}")
|
||||
print(f"Execution preset 'fast': max_iter={agent.max_iter}")
|
||||
print(f"Web preset 'tavily': web_search={agent.web_search}")
|
||||
|
||||
|
||||
def example_array_overrides():
|
||||
"""Example 8: Array with overrides (NEW - preset + customization)"""
|
||||
print("\n=== Example 8: Array Overrides ===")
|
||||
|
||||
# Array format: [preset, {overrides}]
|
||||
agent = Agent(
|
||||
instructions="You are a streaming assistant",
|
||||
output=["verbose", {"stream": True}], # Verbose preset + enable streaming
|
||||
execution=["fast", {"max_iter": 15}], # Fast preset + custom max_iter
|
||||
)
|
||||
print(f"Output array override: verbose={agent.verbose}, stream={agent.stream}")
|
||||
print(f"Execution array override: max_iter={agent.max_iter}")
|
||||
|
||||
|
||||
def example_url_parsing():
|
||||
"""Example 9: URL parsing for memory (NEW - connection strings)"""
|
||||
print("\n=== Example 9: URL Parsing ===")
|
||||
|
||||
# Memory supports URL connection strings
|
||||
# Supported: postgresql://, redis://, sqlite:///, mongodb://
|
||||
agent = Agent(
|
||||
instructions="You are a database-backed assistant",
|
||||
memory="postgresql://postgres:password@localhost:5432/praisonai",
|
||||
)
|
||||
print("Memory URL parsed: memory enabled")
|
||||
|
||||
# Also works with presets
|
||||
agent2 = Agent(
|
||||
instructions="You are a redis-backed assistant",
|
||||
memory="redis", # Preset name
|
||||
)
|
||||
print("Memory preset 'redis': configured")
|
||||
|
||||
|
||||
def example_knowledge_sources():
|
||||
"""Example 10: Knowledge with sources (list and string)"""
|
||||
print("\n=== Example 10: Knowledge Sources ===")
|
||||
|
||||
# Single path string
|
||||
agent1 = Agent(
|
||||
instructions="You are a document assistant",
|
||||
knowledge="docs/", # Single path
|
||||
)
|
||||
print(f"Knowledge single path: knowledge={agent1.knowledge}")
|
||||
|
||||
# List of sources
|
||||
agent2 = Agent(
|
||||
instructions="You are a multi-source assistant",
|
||||
knowledge=["docs/", "data.pdf", "https://example.com/api"],
|
||||
)
|
||||
print(f"Knowledge list: knowledge={agent2.knowledge}")
|
||||
|
||||
# With config for advanced settings
|
||||
agent3 = Agent(
|
||||
instructions="You are an advanced RAG assistant",
|
||||
knowledge=KnowledgeConfig(
|
||||
sources=["docs/"],
|
||||
retrieval_k=10,
|
||||
rerank=True,
|
||||
),
|
||||
)
|
||||
print("Knowledge config: configured with rerank")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("=" * 60)
|
||||
print("PraisonAI Agent-Centric API Examples")
|
||||
@@ -152,6 +234,10 @@ if __name__ == "__main__":
|
||||
example_planning()
|
||||
example_backward_compatible()
|
||||
example_real_chat()
|
||||
example_string_presets()
|
||||
example_array_overrides()
|
||||
example_url_parsing()
|
||||
example_knowledge_sources()
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("All examples completed!")
|
||||
|
||||
@@ -75,7 +75,7 @@ async def main():
|
||||
Use read_file to read files.
|
||||
Use list_files to list directory contents.""",
|
||||
tools=tools,
|
||||
verbose=True
|
||||
output="verbose" # Use new consolidated param
|
||||
)
|
||||
print()
|
||||
|
||||
|
||||
@@ -22,19 +22,18 @@ async def main():
|
||||
print("Agent-Centric Background Tasks Demo")
|
||||
print("=" * 60)
|
||||
|
||||
# Create a background runner with config
|
||||
# Create a background runner with config (used standalone, not passed to Agent)
|
||||
runner = BackgroundRunner(config=BackgroundConfig(max_concurrent_tasks=3))
|
||||
|
||||
# Create an Agent with background task support
|
||||
# Create an Agent
|
||||
agent = Agent(
|
||||
name="AsyncAssistant",
|
||||
instructions="You are a helpful research assistant.",
|
||||
background=runner
|
||||
)
|
||||
|
||||
print("\n--- Agent with Background Support Created ---")
|
||||
print(f"Agent: {agent.name}")
|
||||
print(f"Background runner: {agent.background is not None}")
|
||||
print(f"Background runner: {runner is not None}")
|
||||
|
||||
# Define some example tasks
|
||||
async def research_task(topic: str) -> str:
|
||||
@@ -49,17 +48,17 @@ async def main():
|
||||
await asyncio.sleep(1.0)
|
||||
return f"Analysis complete: {data}"
|
||||
|
||||
# Submit tasks via agent's background runner
|
||||
# Submit tasks via background runner
|
||||
print("\n--- Submitting Background Tasks ---")
|
||||
|
||||
task1 = await agent.background.submit(
|
||||
task1 = await runner.submit(
|
||||
research_task,
|
||||
args=("AI trends 2025",),
|
||||
name="research_ai"
|
||||
)
|
||||
print(f"✅ Submitted research task: {task1.id[:8]}")
|
||||
|
||||
task2 = await agent.background.submit(
|
||||
task2 = await runner.submit(
|
||||
analysis_task,
|
||||
args=("market data",),
|
||||
name="analyze_market"
|
||||
@@ -68,7 +67,7 @@ async def main():
|
||||
|
||||
# List all tasks
|
||||
print("\n--- Task Status ---")
|
||||
for task in agent.background.tasks:
|
||||
for task in runner.tasks:
|
||||
print(f" [{task.id[:8]}] {task.status.value}")
|
||||
|
||||
# Wait for tasks to complete
|
||||
@@ -83,7 +82,7 @@ async def main():
|
||||
print(f" {status} {task.result}")
|
||||
|
||||
# Cleanup
|
||||
agent.background.clear_completed()
|
||||
runner.clear_completed()
|
||||
print("\n✅ Cleared completed tasks")
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
|
||||
@@ -163,7 +163,7 @@ def main():
|
||||
list_all_templates_tool,
|
||||
get_template_details_tool
|
||||
],
|
||||
verbose=True
|
||||
output="verbose" # Use new consolidated param
|
||||
)
|
||||
|
||||
# Example queries
|
||||
|
||||
@@ -33,29 +33,28 @@ async def main():
|
||||
test_file.write_text("# Initial content\nprint('Hello, World!')\n")
|
||||
print(f"\n✅ Created initial file: {test_file.name}")
|
||||
|
||||
# Create checkpoint service
|
||||
checkpoints = CheckpointService(workspace_dir=workspace)
|
||||
# Create checkpoint service (used standalone, not passed to Agent)
|
||||
checkpoint_service = CheckpointService(workspace_dir=workspace)
|
||||
|
||||
# Create an Agent with checkpoint support
|
||||
# Create an Agent
|
||||
agent = Agent(
|
||||
name="RefactorBot",
|
||||
instructions="You are a code refactoring assistant.",
|
||||
checkpoints=checkpoints
|
||||
)
|
||||
|
||||
print("\n--- Agent with Checkpoint Support Created ---")
|
||||
print(f"Agent: {agent.name}")
|
||||
print(f"Checkpoints enabled: {agent.checkpoints is not None}")
|
||||
print(f"Checkpoint service initialized: {checkpoint_service is not None}")
|
||||
|
||||
try:
|
||||
# Initialize the shadow git repository
|
||||
print("\n--- Initializing Checkpoint Service ---")
|
||||
await agent.checkpoints.initialize()
|
||||
await checkpoint_service.initialize()
|
||||
print("✅ Shadow git repository initialized")
|
||||
|
||||
# Save first checkpoint
|
||||
print("\n--- Saving Checkpoint 1: Initial State ---")
|
||||
result1 = await agent.checkpoints.save("Initial state")
|
||||
result1 = await checkpoint_service.save("Initial state")
|
||||
print(f"✅ Checkpoint saved: {result1.checkpoint.id[:8]}")
|
||||
print(f" Message: {result1.checkpoint.message}")
|
||||
|
||||
@@ -71,18 +70,18 @@ async def main():
|
||||
|
||||
# Save second checkpoint
|
||||
print("\n--- Saving Checkpoint 2: After Refactoring ---")
|
||||
result2 = await agent.checkpoints.save("Added features")
|
||||
result2 = await checkpoint_service.save("Added features")
|
||||
print(f"✅ Checkpoint saved: {result2.checkpoint.id[:8]}")
|
||||
|
||||
# List all checkpoints
|
||||
print("\n--- Listing All Checkpoints ---")
|
||||
checkpoints_list = await agent.checkpoints.list_checkpoints()
|
||||
checkpoints_list = await checkpoint_service.list_checkpoints()
|
||||
for i, cp in enumerate(checkpoints_list, 1):
|
||||
print(f" {i}. [{cp.id[:8]}] {cp.message}")
|
||||
|
||||
# Show diff
|
||||
print("\n--- Current Diff ---")
|
||||
diff = await agent.checkpoints.diff()
|
||||
diff = await checkpoint_service.diff()
|
||||
if diff.files:
|
||||
for f in diff.files:
|
||||
print(f" {f.status}: {f.path}")
|
||||
@@ -95,7 +94,7 @@ async def main():
|
||||
|
||||
# Restore to checkpoint 2
|
||||
print(f"\n--- Restoring to Checkpoint: {result2.checkpoint.id[:8]} ---")
|
||||
await agent.checkpoints.restore(result2.checkpoint.id)
|
||||
await checkpoint_service.restore(result2.checkpoint.id)
|
||||
print("✅ Restored successfully!")
|
||||
|
||||
# Verify restoration
|
||||
|
||||
@@ -0,0 +1,96 @@
|
||||
# Consolidated Params Examples
|
||||
|
||||
Examples demonstrating the **Agent-Centric API** with consolidated parameters.
|
||||
|
||||
## Precedence Ladder
|
||||
|
||||
```
|
||||
Instance > Config > Array > Dict > String > Bool > Default
|
||||
```
|
||||
|
||||
## Quick Reference
|
||||
|
||||
| Feature | Presets | Example |
|
||||
|---------|---------|---------|
|
||||
| `memory` | file, sqlite, redis, postgres, mem0, mongodb | `memory="sqlite"` |
|
||||
| `output` | minimal, normal, verbose, debug, silent | `output="verbose"` |
|
||||
| `execution` | fast, balanced, thorough, unlimited | `execution="balanced"` |
|
||||
| `planning` | reasoning, read_only, auto | `planning="reasoning"` |
|
||||
| `reflection` | minimal, standard, thorough | `reflection="standard"` |
|
||||
| `guardrails` | strict, permissive, safety | `guardrails="strict"` |
|
||||
| `web` | duckduckgo, tavily, google, bing, serper | `web="duckduckgo"` |
|
||||
| `context` | sliding_window, summarize, truncate | `context="sliding_window"` |
|
||||
| `autonomy` | suggest, auto_edit, full_auto | `autonomy="suggest"` |
|
||||
| `caching` | enabled, disabled, prompt | `caching="prompt"` |
|
||||
|
||||
## Examples
|
||||
|
||||
### Basic Examples (Single Feature)
|
||||
|
||||
| File | Feature | Description |
|
||||
|------|---------|-------------|
|
||||
| `basic_agent.py` | Agent | Minimal agent with memory |
|
||||
| `basic_memory.py` | memory | SQLite memory preset |
|
||||
| `basic_output.py` | output | Verbose output preset |
|
||||
| `basic_execution.py` | execution | Execution control |
|
||||
| `basic_guardrails.py` | guardrails | Callable validator |
|
||||
| `basic_reflection.py` | reflection | Self-reflection preset |
|
||||
| `basic_web.py` | web | Web search preset |
|
||||
| `basic_planning.py` | planning | Planning preset |
|
||||
| `basic_autonomy.py` | autonomy | Autonomy preset |
|
||||
| `basic_caching.py` | caching | Caching preset |
|
||||
| `basic_knowledge.py` | knowledge | RAG with sources |
|
||||
| `basic_context.py` | context | Context management |
|
||||
| `basic_hooks.py` | hooks | Lifecycle callbacks |
|
||||
|
||||
### Multi-Agent Examples
|
||||
|
||||
| File | Description |
|
||||
|------|-------------|
|
||||
| `basic_agents.py` | Multi-agent with memory and planning |
|
||||
|
||||
### Workflow Examples
|
||||
|
||||
| File | Description |
|
||||
|------|-------------|
|
||||
| `basic_workflow.py` | Simple workflow with output preset |
|
||||
| `basic_workflow_agentlike.py` | Workflow with agent-like params |
|
||||
| `basic_step_override.py` | Step-level param overrides |
|
||||
| `advanced_workflow_full_features.py` | All consolidated params |
|
||||
|
||||
### Advanced Examples
|
||||
|
||||
| File | Description |
|
||||
|------|-------------|
|
||||
| `advanced_output_execution.py` | Combined output + execution |
|
||||
|
||||
## Usage Forms
|
||||
|
||||
Each consolidated param supports multiple input forms:
|
||||
|
||||
```python
|
||||
# Bool - enable with defaults
|
||||
memory=True
|
||||
|
||||
# String preset
|
||||
memory="sqlite"
|
||||
|
||||
# Dict config
|
||||
memory={"backend": "sqlite", "user_id": "user123"}
|
||||
|
||||
# Config instance
|
||||
memory=MemoryConfig(backend="sqlite", user_id="user123")
|
||||
|
||||
# Array with overrides (for some params)
|
||||
guardrails=["strict", {"max_retries": 10}]
|
||||
```
|
||||
|
||||
## Running Examples
|
||||
|
||||
```bash
|
||||
# Set API key
|
||||
export OPENAI_API_KEY=your_key_here
|
||||
|
||||
# Run any example
|
||||
python basic_agent.py
|
||||
```
|
||||
@@ -0,0 +1,17 @@
|
||||
"""
|
||||
Advanced Output + Execution Example - Agent-Centric API
|
||||
|
||||
Demonstrates preset + override array syntax.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Advanced: Preset with overrides using array syntax
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
output=["verbose", {"stream": True, "metrics": True}],
|
||||
execution=["thorough", {"max_iter": 30}],
|
||||
)
|
||||
|
||||
response = agent.start("Explain quantum computing in simple terms.")
|
||||
print(response)
|
||||
@@ -0,0 +1,55 @@
|
||||
"""Advanced Workflow with all consolidated params configured."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.workflows import Workflow, WorkflowStep
|
||||
from praisonaiagents.workflows.workflow_configs import (
|
||||
WorkflowOutputConfig, WorkflowPlanningConfig, WorkflowMemoryConfig,
|
||||
)
|
||||
|
||||
# Full-featured workflow with all consolidated params
|
||||
workflow = Workflow(
|
||||
name="FullFeaturedWorkflow",
|
||||
description="Demonstrates all agent-like consolidated params",
|
||||
steps=[
|
||||
WorkflowStep(
|
||||
name="researcher",
|
||||
action="Research: {{input}}",
|
||||
agent=Agent(instructions="You are a researcher."),
|
||||
knowledge=["research_docs/"], # Step-specific knowledge
|
||||
web="duckduckgo", # Use DuckDuckGo for this step
|
||||
),
|
||||
WorkflowStep(
|
||||
name="analyzer",
|
||||
action="Analyze the research",
|
||||
agent=Agent(instructions="You are an analyst."),
|
||||
reflection="thorough", # Thorough reflection for analysis
|
||||
guardrails="strict", # Strict validation
|
||||
),
|
||||
WorkflowStep(
|
||||
name="writer",
|
||||
action="Write the final report",
|
||||
agent=Agent(instructions="You are a writer."),
|
||||
autonomy=True, # Enable autonomy for writing
|
||||
),
|
||||
],
|
||||
# Workflow-level consolidated params
|
||||
output=WorkflowOutputConfig(verbose=True, stream=True),
|
||||
planning=WorkflowPlanningConfig(enabled=True, reasoning=True),
|
||||
memory=WorkflowMemoryConfig(backend="file"),
|
||||
# Agent-like params
|
||||
autonomy=True,
|
||||
knowledge=["shared_docs/"],
|
||||
guardrails=True,
|
||||
web=True,
|
||||
reflection=True,
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(f"Workflow: {workflow.name}")
|
||||
print(f"Output verbose: {workflow._verbose}")
|
||||
print(f"Planning enabled: {workflow._planning_enabled}")
|
||||
print(f"Memory config: {workflow._memory_config}")
|
||||
print(f"Autonomy: {workflow.autonomy}")
|
||||
print(f"Knowledge: {workflow.knowledge}")
|
||||
print(f"Guardrails: {workflow.guardrails}")
|
||||
print(f"Web: {workflow.web}")
|
||||
print(f"Reflection: {workflow.reflection}")
|
||||
@@ -0,0 +1,12 @@
|
||||
"""Basic Agent example with consolidated params."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Minimal agent with memory
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
memory=True,
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.chat("Hello!")
|
||||
print(response)
|
||||
@@ -0,0 +1,17 @@
|
||||
"""Basic Agents (multi-agent) example with consolidated params."""
|
||||
from praisonaiagents import Agent, Agents
|
||||
|
||||
# Create agents
|
||||
writer = Agent(instructions="You write content.")
|
||||
editor = Agent(instructions="You edit content.")
|
||||
|
||||
# Multi-agent with consolidated params
|
||||
agents = Agents(
|
||||
agents=[writer, editor],
|
||||
memory=True,
|
||||
planning=True,
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
result = agents.start("Write a haiku about AI")
|
||||
print(result)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Autonomy Example - Agent-Centric API
|
||||
|
||||
Demonstrates autonomy with consolidated params.
|
||||
Presets: suggest, auto_edit, full_auto
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable autonomy with preset
|
||||
agent = Agent(
|
||||
instructions="You are an autonomous assistant.",
|
||||
autonomy="suggest", # Presets: suggest, auto_edit, full_auto
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("Help me organize my project files.")
|
||||
print(response)
|
||||
@@ -0,0 +1,23 @@
|
||||
"""
|
||||
Basic Caching Example - Agent-Centric API
|
||||
|
||||
Demonstrates caching with consolidated params.
|
||||
Presets: enabled, disabled, prompt
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable caching with preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with caching enabled.",
|
||||
caching="prompt", # Presets: enabled, disabled, prompt
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
# First call - will cache
|
||||
response = agent.start("What is the capital of France?")
|
||||
print(response)
|
||||
|
||||
# Second call - may use cache
|
||||
response = agent.start("What is the capital of France?")
|
||||
print(response)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Context Example - Agent-Centric API
|
||||
|
||||
Demonstrates context management with consolidated params.
|
||||
Presets: sliding_window, summarize, truncate
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable context management with preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with context management.",
|
||||
context="sliding_window", # Presets: sliding_window, summarize, truncate
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("Tell me a long story about a dragon.")
|
||||
print(response)
|
||||
@@ -0,0 +1,16 @@
|
||||
"""
|
||||
Basic Execution Example - Agent-Centric API
|
||||
|
||||
Demonstrates execution preset usage.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Use fast execution preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
execution="fast", # Presets: fast, balanced, thorough, unlimited
|
||||
)
|
||||
|
||||
response = agent.start("What is the capital of France?")
|
||||
print(response)
|
||||
@@ -0,0 +1,26 @@
|
||||
"""
|
||||
Basic Guardrails Example - Agent-Centric API
|
||||
|
||||
Demonstrates guardrails with callable validator.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Define a simple guardrail validator
|
||||
def validate_response(output):
|
||||
"""Validate that response doesn't contain forbidden words."""
|
||||
forbidden = ["error", "fail", "cannot"]
|
||||
text = str(output).lower()
|
||||
for word in forbidden:
|
||||
if word in text:
|
||||
return (False, f"Response contains forbidden word: {word}")
|
||||
return (True, output)
|
||||
|
||||
# Basic: Use callable guardrail
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
guardrails=validate_response,
|
||||
)
|
||||
|
||||
response = agent.start("What is 2 + 2?")
|
||||
print(response)
|
||||
@@ -0,0 +1,28 @@
|
||||
"""
|
||||
Basic Hooks Example - Agent-Centric API
|
||||
|
||||
Demonstrates lifecycle hooks with consolidated params.
|
||||
Valid keys: on_step, on_tool_call, middleware
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Define hook callbacks
|
||||
def on_step_callback(step_info):
|
||||
print(f"Step: {step_info}")
|
||||
|
||||
def on_tool_call_callback(tool_info):
|
||||
print(f"Tool called: {tool_info}")
|
||||
|
||||
# Basic: Enable hooks with dict
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
hooks={
|
||||
"on_step": on_step_callback,
|
||||
"on_tool_call": on_tool_call_callback,
|
||||
},
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("What is 2 + 2?")
|
||||
print(response)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Knowledge (RAG) Example - Agent-Centric API
|
||||
|
||||
Demonstrates knowledge with consolidated params.
|
||||
Supports: bool, list of sources, dict config, KnowledgeConfig
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable knowledge with list of sources
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with document knowledge.",
|
||||
knowledge=["docs/"], # List of file/folder paths
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("What does the documentation say about installation?")
|
||||
print(response)
|
||||
@@ -0,0 +1,21 @@
|
||||
"""
|
||||
Basic Memory Example - Agent-Centric API
|
||||
|
||||
Demonstrates the simplest memory usage with consolidated params.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable memory with preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with memory.",
|
||||
memory="sqlite", # Preset: sqlite, redis, postgres, file
|
||||
)
|
||||
|
||||
# Run a simple task
|
||||
response = agent.start("Remember that my favorite color is blue.")
|
||||
print(response)
|
||||
|
||||
# Follow-up to test memory
|
||||
response = agent.start("What is my favorite color?")
|
||||
print(response)
|
||||
@@ -0,0 +1,16 @@
|
||||
"""
|
||||
Basic Output Example - Agent-Centric API
|
||||
|
||||
Demonstrates output preset usage.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Use verbose output preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
output="verbose", # Presets: minimal, normal, verbose, debug, silent
|
||||
)
|
||||
|
||||
response = agent.start("What is 2 + 2?")
|
||||
print(response)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Planning Example - Agent-Centric API
|
||||
|
||||
Demonstrates planning with consolidated params.
|
||||
Presets: reasoning, read_only, auto
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable planning with preset
|
||||
agent = Agent(
|
||||
instructions="You are a strategic planner.",
|
||||
planning="reasoning", # Presets: reasoning, read_only, auto
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("Plan a 3-day trip to Tokyo.")
|
||||
print(response)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Reflection Example - Agent-Centric API
|
||||
|
||||
Demonstrates reflection (self-reflect) with consolidated params.
|
||||
Presets: minimal, standard, thorough
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable reflection with preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant that reflects on your answers.",
|
||||
reflection="standard", # Presets: minimal, standard, thorough
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("Explain quantum computing in simple terms.")
|
||||
print(response)
|
||||
@@ -0,0 +1,33 @@
|
||||
"""Basic example showing step-level override of workflow defaults."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.workflows import Workflow, WorkflowStep
|
||||
|
||||
# Workflow with defaults
|
||||
workflow = Workflow(
|
||||
name="StepOverrideWorkflow",
|
||||
steps=[
|
||||
WorkflowStep(
|
||||
name="step1",
|
||||
action="Process with workflow defaults",
|
||||
agent=Agent(instructions="You are a processor."),
|
||||
# Uses workflow-level web=True (inherited)
|
||||
),
|
||||
WorkflowStep(
|
||||
name="step2",
|
||||
action="Process with step override",
|
||||
agent=Agent(instructions="You are a processor."),
|
||||
# Override workflow default
|
||||
web=False, # Disable web for this step
|
||||
reflection="thorough", # Use thorough reflection preset
|
||||
),
|
||||
],
|
||||
# Workflow defaults
|
||||
web=True,
|
||||
reflection=True,
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(f"Workflow web default: {workflow.web}")
|
||||
print(f"Step1 web: {workflow.steps[0].web}") # None (uses workflow default)
|
||||
print(f"Step2 web: {workflow.steps[1].web}") # False (overridden)
|
||||
print(f"Step2 reflection: {workflow.steps[1].reflection}") # thorough
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Web Search Example - Agent-Centric API
|
||||
|
||||
Demonstrates web search with consolidated params.
|
||||
Presets: duckduckgo, tavily, google, bing, serper, search_only, fetch_only
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable web search with preset
|
||||
agent = Agent(
|
||||
instructions="You are a research assistant with web access.",
|
||||
web="duckduckgo", # Presets: duckduckgo, tavily, google, bing, serper
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("What are the latest AI developments in 2024?")
|
||||
print(response)
|
||||
@@ -0,0 +1,26 @@
|
||||
"""
|
||||
Basic Workflow Example - Agent-Centric API
|
||||
|
||||
Demonstrates minimal workflow with consolidated params.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.workflows import Workflow, WorkflowStep
|
||||
|
||||
# Create a simple workflow
|
||||
workflow = Workflow(
|
||||
name="simple_workflow",
|
||||
output="verbose", # Workflow-level output preset
|
||||
)
|
||||
|
||||
# Add a step
|
||||
step = WorkflowStep(
|
||||
name="writer",
|
||||
action="Write a haiku about programming",
|
||||
agent=Agent(instructions="You are a creative poet."),
|
||||
output="result.txt", # Save output to file
|
||||
)
|
||||
|
||||
# Note: This is a structural example - actual execution requires workflow.run()
|
||||
print("Workflow created with output preset:", workflow.output)
|
||||
print("Step output file:", step.output_file)
|
||||
@@ -0,0 +1,32 @@
|
||||
"""Basic Workflow with Agent-like consolidated params."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.workflows import Workflow, WorkflowStep
|
||||
|
||||
# Workflow with agent-like params (knowledge, web, guardrails, reflection)
|
||||
workflow = Workflow(
|
||||
name="AgentLikeWorkflow",
|
||||
steps=[
|
||||
WorkflowStep(
|
||||
name="researcher",
|
||||
action="Research the topic: {{input}}",
|
||||
agent=Agent(instructions="You are a researcher."),
|
||||
),
|
||||
WorkflowStep(
|
||||
name="writer",
|
||||
action="Write about the research findings",
|
||||
agent=Agent(instructions="You are a writer."),
|
||||
),
|
||||
],
|
||||
# Agent-like consolidated params
|
||||
knowledge=["docs/"], # Enable RAG
|
||||
web=True, # Enable web search
|
||||
guardrails=True, # Enable guardrails
|
||||
reflection=True, # Enable self-reflection
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(f"Workflow: {workflow.name}")
|
||||
print(f"Knowledge: {workflow.knowledge}")
|
||||
print(f"Web: {workflow.web}")
|
||||
print(f"Guardrails: {workflow.guardrails}")
|
||||
print(f"Reflection: {workflow.reflection}")
|
||||
@@ -28,7 +28,6 @@ def main():
|
||||
name="CodeAssistant",
|
||||
instructions="You are a helpful code assistant.",
|
||||
context=True, # Enable context management with defaults
|
||||
verbose=False
|
||||
)
|
||||
|
||||
print("\n✓ Agent created with context management enabled")
|
||||
|
||||
@@ -22,7 +22,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
|
||||
verbose: true
|
||||
allow_delegation: false
|
||||
llm:
|
||||
model: "gpt-5-nano"
|
||||
model: "gpt-4o-mini"
|
||||
temperature: 0.3
|
||||
tools:
|
||||
- "InternetSearchTool"
|
||||
@@ -76,7 +76,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
|
||||
verbose: true
|
||||
allow_delegation: false
|
||||
llm:
|
||||
model: "gpt-5-nano"
|
||||
model: "gpt-4o-mini"
|
||||
temperature: 0.3
|
||||
tools:
|
||||
- "InternetSearchTool"
|
||||
@@ -130,7 +130,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
|
||||
verbose: true
|
||||
allow_delegation: false
|
||||
llm:
|
||||
model: "gpt-5-nano"
|
||||
model: "gpt-4o-mini"
|
||||
temperature: 0.3
|
||||
tools:
|
||||
- "InternetSearchTool"
|
||||
@@ -185,7 +185,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
|
||||
verbose: true
|
||||
allow_delegation: false
|
||||
llm:
|
||||
model: "gpt-5-nano"
|
||||
model: "gpt-4o-mini"
|
||||
temperature: 0.4
|
||||
tools:
|
||||
- "InternetSearchTool"
|
||||
@@ -239,7 +239,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
|
||||
verbose: true
|
||||
allow_delegation: false
|
||||
llm:
|
||||
model: "gpt-5-nano"
|
||||
model: "gpt-4o-mini"
|
||||
temperature: 0.3
|
||||
tools:
|
||||
- "InternetSearchTool"
|
||||
@@ -299,7 +299,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
|
||||
verbose: true
|
||||
allow_delegation: false
|
||||
llm:
|
||||
model: "gpt-5-nano"
|
||||
model: "gpt-4o-mini"
|
||||
temperature: 0.3
|
||||
tasks:
|
||||
report_synthesis:
|
||||
|
||||
@@ -0,0 +1,22 @@
|
||||
"""Sample application."""
|
||||
|
||||
def greet(name: str) -> str:
|
||||
"""Greet someone."""
|
||||
return f"Hello, {name}!"
|
||||
|
||||
def add(a: int, b: int) -> int:
|
||||
"""Add two numbers."""
|
||||
return a + b
|
||||
|
||||
class Calculator:
|
||||
"""Simple calculator."""
|
||||
|
||||
def __init__(self):
|
||||
self.value = 0
|
||||
|
||||
def add(self, x):
|
||||
self.value += x
|
||||
return self.value
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(greet("World"))
|
||||
@@ -0,0 +1,10 @@
|
||||
"""
|
||||
demo_output.py - Auto-generated file
|
||||
"""
|
||||
|
||||
def main():
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,10 @@
|
||||
"""
|
||||
test_demo.py - Auto-generated file
|
||||
"""
|
||||
|
||||
def main():
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -24,7 +24,7 @@ if has_api_key:
|
||||
input_text="What is 2 + 2?",
|
||||
expected_output="4",
|
||||
num_iterations=3, # Run 3 times for statistical significance
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
# Run evaluation
|
||||
@@ -42,7 +42,7 @@ else:
|
||||
input_text="What is 2 + 2?",
|
||||
expected_output="4",
|
||||
num_iterations=1,
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
# Test with mock output
|
||||
|
||||
@@ -27,7 +27,7 @@ if has_api_key:
|
||||
scoring_type="numeric", # Score 1-10
|
||||
threshold=7.0, # Pass if score >= 7
|
||||
num_iterations=2,
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
# Run evaluation
|
||||
@@ -45,7 +45,7 @@ if has_api_key:
|
||||
agent=agent,
|
||||
input_text="Tell me a joke",
|
||||
scoring_type="binary", # Pass or Fail
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
binary_result = binary_evaluator.run(print_summary=True)
|
||||
|
||||
@@ -26,7 +26,7 @@ if has_api_key:
|
||||
num_iterations=10, # Run 10 benchmark iterations
|
||||
warmup_runs=2, # 2 warmup runs before measurement
|
||||
track_memory=True, # Track memory usage
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
# Run evaluation
|
||||
|
||||
@@ -37,7 +37,7 @@ if has_api_key:
|
||||
input_text="Search for the weather in Paris and calculate 25 * 4",
|
||||
expected_tools=["search_web", "calculate"], # Tools that should be called
|
||||
forbidden_tools=["delete_file"], # Tools that should NOT be called
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
# Run evaluation
|
||||
@@ -59,7 +59,7 @@ evaluator = ReliabilityEvaluator(
|
||||
agent=mock_agent,
|
||||
expected_tools=["search_web", "calculate"], # Tools that should be called
|
||||
forbidden_tools=["delete_file"], # Tools that should NOT be called
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
result2 = evaluator.evaluate_tool_calls(
|
||||
|
||||
@@ -68,7 +68,7 @@ agent = Agent(
|
||||
instructions="You are a helpful assistant that summarizes web content",
|
||||
llm="gemini/gemini-2.5-flash-lite-preview-06-17",
|
||||
reflection=False,
|
||||
verbose=True,
|
||||
output="verbose", # Use new consolidated param
|
||||
tools=[get_url_context] # FIX: tools must be a list, not a single function
|
||||
)
|
||||
|
||||
|
||||
@@ -185,7 +185,7 @@ When asked about codes, provide the EXACT code from the documents.
|
||||
Be concise but accurate.""",
|
||||
knowledge=[temp_dir],
|
||||
user_id="compression_demo_user",
|
||||
verbose=True,
|
||||
output="verbose",
|
||||
)
|
||||
|
||||
# Test retrieval of the unique code
|
||||
|
||||
@@ -69,7 +69,7 @@ If the answer is not in the context, say 'I don't have that information.'
|
||||
Be precise and quote exact values when asked about codes or numbers.""",
|
||||
knowledge=[temp_dir],
|
||||
user_id="demo_user",
|
||||
verbose=True,
|
||||
output="verbose",
|
||||
)
|
||||
|
||||
# Question 1: Unique code that requires context
|
||||
|
||||
@@ -165,7 +165,7 @@ When asked about department codes, provide the EXACT code from the documents.
|
||||
Be specific about which department you're referring to.""",
|
||||
knowledge=[temp_dir],
|
||||
user_id="hierarchy_demo_user",
|
||||
verbose=True,
|
||||
output="verbose",
|
||||
)
|
||||
|
||||
# Test retrieval of department codes
|
||||
|
||||
@@ -143,7 +143,7 @@ When asked about verification codes, provide the EXACT code from the documents.
|
||||
If information is not in the context, say 'Information not found in documents.'""",
|
||||
knowledge=[temp_dir],
|
||||
user_id="strategy_demo_user",
|
||||
verbose=True,
|
||||
output="verbose", # Use new consolidated param
|
||||
)
|
||||
|
||||
# Test retrieval with unique codes
|
||||
|
||||
@@ -85,7 +85,7 @@ async def main():
|
||||
Use lsp_find_references to find where symbols are used.
|
||||
Provide clear, organized summaries of code structure.""",
|
||||
tools=tools,
|
||||
verbose=True
|
||||
output="verbose" # Use new consolidated param
|
||||
)
|
||||
print()
|
||||
|
||||
|
||||
@@ -0,0 +1,148 @@
|
||||
"""
|
||||
Multi-Server MCP Example.
|
||||
|
||||
This example demonstrates how to use multiple MCP servers with PraisonAI Agents,
|
||||
including mixing MCP tools with regular Python function tools.
|
||||
|
||||
Requirements:
|
||||
- Node.js and npx installed (or uvx for Python-based servers)
|
||||
- pip install praisonaiagents[mcp]
|
||||
- OPENAI_API_KEY environment variable set
|
||||
|
||||
Usage:
|
||||
python multi_server.py
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, MCP
|
||||
import os
|
||||
|
||||
|
||||
def calculate(expression: str) -> str:
|
||||
"""
|
||||
A simple calculator tool that evaluates mathematical expressions.
|
||||
|
||||
Args:
|
||||
expression: A mathematical expression to evaluate (e.g., "2 + 2")
|
||||
|
||||
Returns:
|
||||
The result of the calculation
|
||||
"""
|
||||
try:
|
||||
# Safe evaluation of mathematical expressions
|
||||
allowed_chars = set("0123456789+-*/.() ")
|
||||
if not all(c in allowed_chars for c in expression):
|
||||
return "Error: Invalid characters in expression"
|
||||
result = eval(expression)
|
||||
return f"Result: {result}"
|
||||
except Exception as e:
|
||||
return f"Error: {str(e)}"
|
||||
|
||||
|
||||
def main():
|
||||
# Check for API key
|
||||
if not os.environ.get("OPENAI_API_KEY"):
|
||||
print("Please set OPENAI_API_KEY environment variable")
|
||||
return
|
||||
|
||||
print("=" * 60)
|
||||
print("Multi-Server MCP Example")
|
||||
print("=" * 60)
|
||||
|
||||
# Create MCP instance with Time server
|
||||
print("\nInitializing MCP servers...")
|
||||
try:
|
||||
time_mcp = MCP("uvx mcp-server-time", timeout=30)
|
||||
print("✓ Time MCP server initialized")
|
||||
except Exception as e:
|
||||
print(f"✗ Time MCP server failed: {e}")
|
||||
return
|
||||
|
||||
# Create an agent with multiple tool sources
|
||||
agent = Agent(
|
||||
name="MultiToolAgent",
|
||||
instructions="""You are a helpful assistant with access to multiple tools:
|
||||
1. Time tools - for getting current time in different timezones
|
||||
2. Calculator - for mathematical calculations
|
||||
|
||||
Use the appropriate tool based on the user's request.""",
|
||||
llm="openai/gpt-4o-mini",
|
||||
tools=[time_mcp, calculate] # Mix MCP and regular tools
|
||||
)
|
||||
|
||||
# Show available tools
|
||||
print("\nAvailable tools:")
|
||||
formatted_tools = agent._format_tools_for_completion(agent.tools)
|
||||
for tool in formatted_tools:
|
||||
print(f" - {tool['function']['name']}: {tool['function']['description'][:50]}...")
|
||||
|
||||
# Example queries
|
||||
queries = [
|
||||
"What time is it in Tokyo?",
|
||||
"Calculate 15 * 7 + 23",
|
||||
"What's the current time in New York and London?"
|
||||
]
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Running queries...")
|
||||
print("=" * 60)
|
||||
|
||||
for i, query in enumerate(queries, 1):
|
||||
print(f"\n--- Query {i} ---")
|
||||
print(f"Question: {query}\n")
|
||||
|
||||
try:
|
||||
response = agent.chat(query)
|
||||
print(f"Response:\n{response}")
|
||||
except Exception as e:
|
||||
print(f"Error: {e}")
|
||||
|
||||
print("-" * 40)
|
||||
|
||||
# Clean up
|
||||
time_mcp.shutdown()
|
||||
print("\nDone!")
|
||||
|
||||
|
||||
def demo_multiple_mcp_servers():
|
||||
"""
|
||||
Demonstrate using multiple MCP servers simultaneously.
|
||||
|
||||
This function shows how to create agents with multiple MCP servers,
|
||||
each providing different capabilities.
|
||||
"""
|
||||
print("\n" + "=" * 60)
|
||||
print("Multiple MCP Servers Demo")
|
||||
print("=" * 60)
|
||||
|
||||
# Initialize multiple MCP servers
|
||||
servers = {}
|
||||
|
||||
try:
|
||||
servers['time'] = MCP("uvx mcp-server-time", timeout=30)
|
||||
print("✓ Time server initialized")
|
||||
except Exception as e:
|
||||
print(f"✗ Time server failed: {e}")
|
||||
|
||||
# Create agent with all available servers
|
||||
available_tools = list(servers.values())
|
||||
|
||||
if not available_tools:
|
||||
print("No MCP servers available")
|
||||
return
|
||||
|
||||
agent = Agent(
|
||||
name="MultiServerAgent",
|
||||
instructions="You have access to multiple MCP servers. Use the appropriate tools.",
|
||||
llm="openai/gpt-4o-mini",
|
||||
tools=available_tools
|
||||
)
|
||||
|
||||
print(f"\nAgent created with {len(available_tools)} MCP server(s)")
|
||||
|
||||
# Clean up
|
||||
for server in servers.values():
|
||||
server.shutdown()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,70 @@
|
||||
"""
|
||||
Sequential Thinking MCP Example.
|
||||
|
||||
This example demonstrates how to use the Sequential Thinking MCP server
|
||||
with PraisonAI Agents to break down complex problems step by step.
|
||||
|
||||
Requirements:
|
||||
- Node.js and npx installed
|
||||
- pip install praisonaiagents[mcp]
|
||||
- OPENAI_API_KEY environment variable set
|
||||
|
||||
Usage:
|
||||
python sequential_thinking.py
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, MCP
|
||||
import os
|
||||
|
||||
|
||||
def main():
|
||||
# Check for API key
|
||||
if not os.environ.get("OPENAI_API_KEY"):
|
||||
print("Please set OPENAI_API_KEY environment variable")
|
||||
return
|
||||
|
||||
# Create MCP instance with Sequential Thinking server
|
||||
# The server provides tools for step-by-step problem analysis
|
||||
sequential_mcp = MCP(
|
||||
"npx -y @modelcontextprotocol/server-sequential-thinking",
|
||||
timeout=60
|
||||
)
|
||||
|
||||
# Create an agent with the Sequential Thinking tools
|
||||
agent = Agent(
|
||||
name="ProblemSolver",
|
||||
instructions="""You are an expert problem solver who breaks down complex problems
|
||||
into manageable steps. When given a problem:
|
||||
1. Use the sequential thinking tool to analyze it step by step
|
||||
2. Provide clear, actionable steps
|
||||
3. Explain your reasoning at each step""",
|
||||
llm="openai/gpt-4o-mini",
|
||||
tools=sequential_mcp
|
||||
)
|
||||
|
||||
# Example problems to solve
|
||||
problems = [
|
||||
"Break down the process of making a cup of tea",
|
||||
"How would you plan a weekend trip to a new city?",
|
||||
"What steps would you take to learn a new programming language?"
|
||||
]
|
||||
|
||||
print("=" * 60)
|
||||
print("Sequential Thinking MCP Example")
|
||||
print("=" * 60)
|
||||
|
||||
for i, problem in enumerate(problems, 1):
|
||||
print(f"\n--- Problem {i} ---")
|
||||
print(f"Question: {problem}\n")
|
||||
|
||||
response = agent.chat(problem)
|
||||
print(f"Response:\n{response}")
|
||||
print("-" * 40)
|
||||
|
||||
# Clean up
|
||||
sequential_mcp.shutdown()
|
||||
print("\nDone!")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -24,13 +24,13 @@ obs.init()
|
||||
# Create an agent
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
model="gpt-4o-mini",
|
||||
llm="gpt-4o-mini",
|
||||
)
|
||||
|
||||
# Use trace context manager for complete workflow tracing
|
||||
with obs.trace("chat-session", session_id="user-123"):
|
||||
# Use span context manager for individual operations
|
||||
with obs.span("user-query", kind=obs.SpanKind.AGENT):
|
||||
with obs.span("user-query"):
|
||||
response = agent.chat("What is the capital of France?")
|
||||
print(response)
|
||||
|
||||
|
||||
@@ -5,8 +5,8 @@ This example demonstrates the various output modes and configurations
|
||||
available in PraisonAI agents.
|
||||
|
||||
Features demonstrated:
|
||||
- verbose=True: Full output with agent info, task, and response panels
|
||||
- verbose=False: Clean output with just the result
|
||||
- output="verbose": Full output with agent info, task, and response panels
|
||||
- output="minimal": Clean output with just the result
|
||||
- Tool call display with consolidated output
|
||||
- Multi-agent output with clear attribution
|
||||
"""
|
||||
@@ -29,30 +29,30 @@ def get_weather(city: str) -> str:
|
||||
|
||||
|
||||
def example_verbose_true():
|
||||
"""Example with verbose=True (default) - shows full output panels."""
|
||||
"""Example with output='verbose' - shows full output panels."""
|
||||
print("\n" + "=" * 60)
|
||||
print("EXAMPLE 1: verbose=True (Full Output)")
|
||||
print("EXAMPLE 1: output='verbose' (Full Output)")
|
||||
print("=" * 60)
|
||||
|
||||
agent = Agent(
|
||||
name="Assistant",
|
||||
instructions="You are a helpful assistant. Be concise.",
|
||||
verbose=True # Default - shows Agent Info, Task, and Response panels
|
||||
output="verbose" # Shows Agent Info, Task, and Response panels
|
||||
)
|
||||
result = agent.start("What is the capital of France? Answer in one sentence.")
|
||||
print(f"\nReturned value: {result}")
|
||||
|
||||
|
||||
def example_verbose_false():
|
||||
"""Example with verbose=False - clean output, just the result."""
|
||||
"""Example with output='minimal' - clean output, just the result."""
|
||||
print("\n" + "=" * 60)
|
||||
print("EXAMPLE 2: verbose=False (Clean Output)")
|
||||
print("EXAMPLE 2: output='minimal' (Clean Output)")
|
||||
print("=" * 60)
|
||||
|
||||
agent = Agent(
|
||||
name="Assistant",
|
||||
instructions="You are a helpful assistant. Be concise.",
|
||||
verbose=False # No panels, just returns the result
|
||||
output="minimal" # No panels, just returns the result
|
||||
)
|
||||
result = agent.start("What is 2+2? Answer in one word.")
|
||||
print(f"Result: {result}")
|
||||
@@ -68,7 +68,7 @@ def example_with_tools():
|
||||
name="Weather Bot",
|
||||
instructions="You help users check the weather. Use the get_weather tool.",
|
||||
tools=[get_weather],
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
result = agent.start("What's the weather in Tokyo?")
|
||||
print(f"\nReturned value: {result}")
|
||||
@@ -84,14 +84,14 @@ def example_multi_agent():
|
||||
name="Researcher",
|
||||
role="Research Analyst",
|
||||
instructions="You research topics and provide factual information.",
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
writer = Agent(
|
||||
name="Writer",
|
||||
role="Content Writer",
|
||||
instructions="You write clear summaries based on research.",
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
task1 = Task(
|
||||
@@ -110,7 +110,7 @@ def example_multi_agent():
|
||||
agents=[researcher, writer],
|
||||
tasks=[task1, task2],
|
||||
process="sequential",
|
||||
verbose=1
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
result = agents.start()
|
||||
|
||||
@@ -46,7 +46,7 @@ agent = RouterAgent(
|
||||
name="Smart Assistant",
|
||||
role="Adaptive AI Assistant",
|
||||
goal="Complete tasks using the most appropriate model",
|
||||
models=["gpt-5-nano", "gpt-5-nano", "claude-3-5-sonnet-20241022"],
|
||||
models=["gpt-4o-mini", "gpt-4o-mini", "claude-3-5-sonnet-20241022"],
|
||||
routing_strategy="auto" # Automatic model selection
|
||||
)
|
||||
|
||||
@@ -90,7 +90,7 @@ analyzer = RouterAgent(
|
||||
goal="Analyze data efficiently",
|
||||
models={
|
||||
"gemini/gemini-1.5-flash": {},
|
||||
"gpt-5-nano": {},
|
||||
"gpt-4o-mini": {},
|
||||
"claude-3-haiku-20240307": {}
|
||||
},
|
||||
model_router=router,
|
||||
@@ -207,7 +207,7 @@ for i, agent in enumerate(auto.agents):
|
||||
name=agent.name,
|
||||
role=agent.role,
|
||||
goal=agent.goal,
|
||||
models=["gpt-5-nano", "gpt-5-nano", "claude-3-5-sonnet"],
|
||||
models=["gpt-4o-mini", "gpt-4o-mini", "claude-3-5-sonnet"],
|
||||
routing_strategy="auto"
|
||||
)
|
||||
|
||||
|
||||
@@ -40,7 +40,6 @@ agents = Agents(
|
||||
agents=[image_agent],
|
||||
tasks=[task1, task2],
|
||||
process="sequential",
|
||||
verbose=1
|
||||
)
|
||||
|
||||
# Run all tasks
|
||||
|
||||
@@ -40,7 +40,6 @@ agents = Agents(
|
||||
agents=[image_agent],
|
||||
tasks=[task1, task2],
|
||||
process="sequential",
|
||||
verbose=1
|
||||
)
|
||||
|
||||
# Run all tasks
|
||||
|
||||
@@ -29,7 +29,6 @@ agents = Agents(
|
||||
agents=[video_agent],
|
||||
tasks=[task1],
|
||||
process="sequential",
|
||||
verbose=1
|
||||
)
|
||||
|
||||
# Run all tasks
|
||||
|
||||
@@ -62,7 +62,6 @@ def capture_and_analyze():
|
||||
agents=[vision_agent],
|
||||
tasks=[task],
|
||||
process="sequential",
|
||||
verbose=1
|
||||
)
|
||||
|
||||
result = agents.start()
|
||||
|
||||
@@ -118,7 +118,6 @@ def analyze_with_multiple_agents():
|
||||
agents=[security_agent, object_detector, scene_analyst],
|
||||
tasks=[security_task, object_task, scene_task],
|
||||
process="parallel", # Run all analyses in parallel
|
||||
verbose=1
|
||||
)
|
||||
|
||||
result = agents.start()
|
||||
|
||||
@@ -135,7 +135,6 @@ class CameraVideoAnalyzer:
|
||||
agents=[self.video_agent],
|
||||
tasks=[task],
|
||||
process="sequential",
|
||||
verbose=1
|
||||
)
|
||||
|
||||
return agents.start()
|
||||
|
||||
@@ -0,0 +1,117 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Dict Config Example - Demonstrates dict shorthand for consolidated parameters.
|
||||
|
||||
This example shows how to use dict shorthand instead of importing config classes.
|
||||
Dict input is strictly validated - unknown keys raise helpful errors.
|
||||
|
||||
Requirements:
|
||||
- Set OPENAI_API_KEY environment variable
|
||||
"""
|
||||
|
||||
import os
|
||||
|
||||
|
||||
def example_dict_output_config():
|
||||
"""Example: Using dict for output configuration."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Dict shorthand - equivalent to OutputConfig(verbose=True, stream=False)
|
||||
agent = Agent(
|
||||
name="Assistant",
|
||||
instructions="You are a helpful assistant.",
|
||||
output={"verbose": True, "stream": False},
|
||||
)
|
||||
|
||||
result = agent.start("Say hello in one word.")
|
||||
print(f"Result: {result}")
|
||||
return agent
|
||||
|
||||
|
||||
def example_dict_execution_config():
|
||||
"""Example: Using dict for execution configuration."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Dict shorthand for execution settings
|
||||
agent = Agent(
|
||||
name="FastAgent",
|
||||
instructions="You are a fast responder.",
|
||||
execution={"max_iter": 5, "timeout": 30},
|
||||
)
|
||||
|
||||
result = agent.start("What is 2+2?")
|
||||
print(f"Result: {result}")
|
||||
return agent
|
||||
|
||||
|
||||
def example_dict_validation_error():
|
||||
"""Example: Dict with unknown key raises helpful error."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
print("\n--- Testing dict validation error ---")
|
||||
try:
|
||||
# This will raise TypeError with helpful message
|
||||
Agent(
|
||||
name="Test",
|
||||
instructions="Test agent",
|
||||
output={"verbose": True, "invalid_key": "value"},
|
||||
)
|
||||
except TypeError as e:
|
||||
print(f"Expected error caught: {e}")
|
||||
# Shows: Unknown keys for output: ['invalid_key']. Valid keys: ...
|
||||
|
||||
|
||||
def example_array_preset_override():
|
||||
"""Example: Array [preset, {overrides}] pattern still works."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Array pattern: preset name + override dict
|
||||
agent = Agent(
|
||||
name="VerboseAgent",
|
||||
instructions="You are verbose.",
|
||||
output=["verbose", {"stream": False}],
|
||||
)
|
||||
|
||||
result = agent.start("Say hi.")
|
||||
print(f"Result: {result}")
|
||||
return agent
|
||||
|
||||
|
||||
def example_base_url_api_key_separate():
|
||||
"""Example: base_url and api_key remain separate parameters."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# base_url and api_key are NOT consolidated - they stay separate
|
||||
# This is intentional for security and clarity
|
||||
agent = Agent(
|
||||
name="CustomEndpoint",
|
||||
instructions="You use a custom endpoint.",
|
||||
llm="gpt-4o-mini",
|
||||
# base_url="http://localhost:11434/v1", # Uncomment for Ollama
|
||||
# api_key=os.getenv("CUSTOM_API_KEY"), # Separate parameter
|
||||
)
|
||||
|
||||
return agent
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Check for API key
|
||||
if not os.getenv("OPENAI_API_KEY"):
|
||||
print("Warning: OPENAI_API_KEY not set. Some examples may fail.")
|
||||
|
||||
print("=== Dict Config Examples ===\n")
|
||||
|
||||
# Run validation error example (doesn't need API key)
|
||||
example_dict_validation_error()
|
||||
|
||||
# Run examples that need API key
|
||||
if os.getenv("OPENAI_API_KEY"):
|
||||
print("\n--- Dict output config ---")
|
||||
example_dict_output_config()
|
||||
|
||||
print("\n--- Array preset override ---")
|
||||
example_array_preset_override()
|
||||
else:
|
||||
print("\nSkipping API examples (no OPENAI_API_KEY)")
|
||||
|
||||
print("\n=== Examples Complete ===")
|
||||
@@ -99,7 +99,6 @@ sync_agent = Agent(
|
||||
backstory="Expert in sync operations and data organization",
|
||||
tools=[sync_search_tool],
|
||||
reflection=False,
|
||||
markdown=True
|
||||
)
|
||||
|
||||
async_agent = Agent(
|
||||
@@ -109,7 +108,6 @@ async_agent = Agent(
|
||||
backstory="Expert in async operations and data organization",
|
||||
tools=[async_search_tool],
|
||||
reflection=False,
|
||||
markdown=True
|
||||
)
|
||||
|
||||
# 5. Create tasks with different configurations
|
||||
@@ -161,7 +159,6 @@ def run_sync_example():
|
||||
agents = Agents(
|
||||
agents=[sync_agent],
|
||||
tasks=[sync_task],
|
||||
verbose=1,
|
||||
process="sequential"
|
||||
)
|
||||
result = agents.start()
|
||||
@@ -173,7 +170,6 @@ async def run_async_example():
|
||||
agents = Agents(
|
||||
agents=[async_agent],
|
||||
tasks=[async_task],
|
||||
verbose=1,
|
||||
process="sequential"
|
||||
)
|
||||
result = await agents.astart()
|
||||
@@ -185,7 +181,6 @@ async def run_mixed_example():
|
||||
agents = Agents(
|
||||
agents=[sync_agent, async_agent],
|
||||
tasks=[sync_task, async_task],
|
||||
verbose=1,
|
||||
process="sequential"
|
||||
)
|
||||
result = await agents.astart()
|
||||
@@ -197,7 +192,6 @@ async def run_workflow_example():
|
||||
agents = Agents(
|
||||
agents=[sync_agent, async_agent],
|
||||
tasks=[workflow_sync_task, workflow_async_task],
|
||||
verbose=1,
|
||||
process="workflow"
|
||||
)
|
||||
result = await agents.astart()
|
||||
|
||||
@@ -54,7 +54,6 @@ async_agent = Agent(
|
||||
backstory="Expert in efficient data retrieval and parallel search operations",
|
||||
tools=[async_search_tool],
|
||||
reflection=False,
|
||||
markdown=True
|
||||
)
|
||||
|
||||
summary_agent = Agent(
|
||||
@@ -63,7 +62,6 @@ summary_agent = Agent(
|
||||
goal="Create concise summaries from multiple search results",
|
||||
backstory="Expert in analyzing and synthesizing information from multiple sources",
|
||||
reflection=True,
|
||||
markdown=True
|
||||
)
|
||||
|
||||
# 5. Create async tasks
|
||||
@@ -116,7 +114,6 @@ async def run_parallel_tasks():
|
||||
agents = Agents(
|
||||
agents=[async_agent, summary_agent],
|
||||
tasks=parallel_tasks + [summary_task],
|
||||
verbose=1,
|
||||
process="sequential"
|
||||
)
|
||||
|
||||
|
||||
@@ -61,7 +61,6 @@ async_agent = Agent(
|
||||
backstory="Expert in parallel search operations and data retrieval",
|
||||
tools=[async_search_tool],
|
||||
reflection=False,
|
||||
markdown=True
|
||||
)
|
||||
|
||||
summary_agent = Agent(
|
||||
@@ -72,7 +71,6 @@ summary_agent = Agent(
|
||||
Skilled at identifying patterns, trends, and connections between different topics.
|
||||
Specializes in creating clear, structured summaries that highlight key insights.""",
|
||||
reflection=True, # Enable self-reflection for better summary quality
|
||||
markdown=True
|
||||
)
|
||||
|
||||
# 5. Create async tasks
|
||||
@@ -104,7 +102,6 @@ async def run_single_task():
|
||||
agents = Agents(
|
||||
agents=[async_agent],
|
||||
tasks=[async_task],
|
||||
verbose=1,
|
||||
process="sequential"
|
||||
)
|
||||
result = await agents.astart()
|
||||
@@ -188,7 +185,6 @@ Present the summary in a clear, structured format with sections for findings, pa
|
||||
agents = Agents(
|
||||
agents=[async_agent],
|
||||
tasks=parallel_tasks, # Only run search tasks first
|
||||
verbose=1,
|
||||
process="sequential"
|
||||
)
|
||||
search_results = await agents.astart()
|
||||
@@ -213,7 +209,6 @@ Present the summary in a clear, structured format with sections for findings, pa
|
||||
summary_agents = Agents(
|
||||
agents=[summary_agent], # Use summary agent for synthesis
|
||||
tasks=[summary_task],
|
||||
verbose=1,
|
||||
process="sequential"
|
||||
)
|
||||
summary_result = await summary_agents.astart()
|
||||
|
||||
@@ -127,10 +127,6 @@ def main():
|
||||
allow_delegation=False,
|
||||
tools=[internet_search_tool],
|
||||
llm="gpt-4o-mini",
|
||||
markdown=True,
|
||||
|
||||
|
||||
|
||||
)
|
||||
|
||||
writer = Agent(
|
||||
@@ -142,7 +138,6 @@ def main():
|
||||
allow_delegation=True,
|
||||
llm="gpt-4o-mini",
|
||||
tools=[],
|
||||
markdown=True
|
||||
)
|
||||
|
||||
# Create tasks with callbacks
|
||||
|
||||
@@ -144,7 +144,6 @@ validate_task = Task(
|
||||
agents = Agents(
|
||||
agents=[data_agent],
|
||||
tasks=[collect_task, validate_task],
|
||||
verbose=1,
|
||||
process="workflow"
|
||||
)
|
||||
|
||||
|
||||
@@ -39,10 +39,6 @@ researcher = Agent(
|
||||
allow_delegation=False,
|
||||
tools=[internet_search_tool],
|
||||
llm="gpt-4o-mini",
|
||||
markdown=True,
|
||||
|
||||
|
||||
|
||||
)
|
||||
writer = Agent(
|
||||
name="Writer",
|
||||
@@ -53,7 +49,6 @@ writer = Agent(
|
||||
allow_delegation=True,
|
||||
llm="gpt-4o-mini",
|
||||
tools=[],
|
||||
markdown=True
|
||||
)
|
||||
|
||||
# Create tasks
|
||||
|
||||
@@ -46,8 +46,7 @@ task3 = Task(
|
||||
agents = Agents(
|
||||
agents=[vision_agent],
|
||||
tasks=[task1, task2, task3],
|
||||
process="sequential",
|
||||
verbose=1
|
||||
process="sequential"
|
||||
)
|
||||
|
||||
# Run all tasks
|
||||
|
||||
@@ -32,9 +32,7 @@ def get_structured_analysis(query: str, verbose: bool = True) -> AnalysisReport:
|
||||
role="Research Analyst",
|
||||
goal="Analyze topics and provide structured reports",
|
||||
backstory="Expert at gathering information and providing structured analysis",
|
||||
verbose=verbose,
|
||||
reflection=True, # Enable self-reflection for better quality
|
||||
markdown=True,
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
|
||||
@@ -67,7 +67,6 @@ validate_task = Task(
|
||||
agents = Agents(
|
||||
agents=[data_agent],
|
||||
tasks=[collect_task, validate_task],
|
||||
verbose=1,
|
||||
process="workflow"
|
||||
)
|
||||
|
||||
|
||||
@@ -228,7 +228,6 @@ process_task = Task(
|
||||
workflow = Agents(
|
||||
agents=[data_agent, process_agent],
|
||||
tasks=[collect_task, validate_task, process_task],
|
||||
verbose=1,
|
||||
process="workflow"
|
||||
)
|
||||
|
||||
|
||||
@@ -97,7 +97,7 @@ researcher = Agent(
|
||||
name="Researcher",
|
||||
role="Information Researcher",
|
||||
goal="Store information with semantic understanding",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Create task
|
||||
|
||||
@@ -152,7 +152,6 @@ def main():
|
||||
agents_system = Agents(
|
||||
agents=[researcher],
|
||||
tasks=[build_knowledge_task, query_knowledge_task, expand_knowledge_task],
|
||||
verbose=1,
|
||||
memory=True,
|
||||
memory_config=memory_config
|
||||
)
|
||||
|
||||
@@ -17,7 +17,7 @@ def my_function():
|
||||
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
with track_api_call("agent_request"):
|
||||
|
||||
@@ -91,7 +91,6 @@ def main():
|
||||
memory=True,
|
||||
process="workflow",
|
||||
user_id="research_project_001",
|
||||
verbose=1
|
||||
)
|
||||
|
||||
print(f"🤖 Created workflow with {len(workflow.agents)} agents and {len(workflow.tasks)} tasks")
|
||||
|
||||
@@ -13,7 +13,7 @@ agent = Agent(
|
||||
role="Assistant",
|
||||
goal="Help users",
|
||||
backstory="You are helpful.",
|
||||
llm="gpt-5-nano",
|
||||
llm="gpt-4o-mini",
|
||||
metrics=True # 🎯 That's it!
|
||||
)
|
||||
|
||||
|
||||
@@ -177,7 +177,7 @@ Set your API keys:
|
||||
|
||||
```bash
|
||||
export OPENAI_API_KEY="your-api-key"
|
||||
export OPENAI_MODEL_NAME="gpt-5-nano"
|
||||
export OPENAI_MODEL_NAME="gpt-4o-mini"
|
||||
```
|
||||
|
||||
## 📝 Customization
|
||||
|
||||
@@ -5,7 +5,8 @@ Demonstrates conditional branching in workflows where steps can route
|
||||
to different next steps based on output content.
|
||||
"""
|
||||
|
||||
from praisonaiagents.memory.workflows import WorkflowManager, WorkflowStep, Workflow
|
||||
from praisonaiagents import Workflow, WorkflowStep
|
||||
from praisonaiagents.workflows import WorkflowManager
|
||||
|
||||
# Create a workflow with branching
|
||||
workflow = Workflow(
|
||||
@@ -15,10 +16,12 @@ workflow = Workflow(
|
||||
WorkflowStep(
|
||||
name="validate",
|
||||
action="Check if the number 42 is positive. Reply with 'valid' or 'invalid'.",
|
||||
next_steps=["success_handler", "error_handler"],
|
||||
branch_condition={
|
||||
"valid": ["success_handler"],
|
||||
"invalid": ["error_handler"]
|
||||
routing={
|
||||
"next_steps": ["success_handler", "error_handler"],
|
||||
"branches": {
|
||||
"valid": ["success_handler"],
|
||||
"invalid": ["error_handler"]
|
||||
}
|
||||
}
|
||||
),
|
||||
WorkflowStep(
|
||||
|
||||
@@ -5,7 +5,8 @@ Demonstrates saving and resuming workflow execution using checkpoints.
|
||||
Useful for long-running workflows that may be interrupted.
|
||||
"""
|
||||
|
||||
from praisonaiagents.memory.workflows import WorkflowManager, WorkflowStep, Workflow
|
||||
from praisonaiagents import Workflow, WorkflowStep
|
||||
from praisonaiagents.workflows import WorkflowManager
|
||||
|
||||
# Create a multi-step workflow
|
||||
workflow = Workflow(
|
||||
|
||||
@@ -5,10 +5,10 @@ Demonstrates how to stop a workflow early using custom handler
|
||||
functions that return StepResult with stop_workflow=True.
|
||||
"""
|
||||
|
||||
from praisonaiagents.memory.workflows import (
|
||||
WorkflowManager, WorkflowStep, Workflow,
|
||||
WorkflowContext, StepResult
|
||||
from praisonaiagents import (
|
||||
Workflow, WorkflowStep, WorkflowContext, StepResult
|
||||
)
|
||||
from praisonaiagents.workflows import WorkflowManager
|
||||
|
||||
# Custom validator that can stop the workflow
|
||||
def validate_data(context: WorkflowContext) -> StepResult:
|
||||
|
||||
@@ -5,7 +5,8 @@ Demonstrates iterating over a list of items in a workflow step.
|
||||
Each item is processed individually with the loop variable.
|
||||
"""
|
||||
|
||||
from praisonaiagents.memory.workflows import WorkflowManager, WorkflowStep, Workflow
|
||||
from praisonaiagents import Workflow, WorkflowStep
|
||||
from praisonaiagents.workflows import WorkflowManager
|
||||
|
||||
# Create a workflow with loop
|
||||
workflow = Workflow(
|
||||
|
||||
@@ -51,7 +51,6 @@ def basic_rag_example():
|
||||
|
||||
COMPANY DATABASE:
|
||||
{context}""",
|
||||
verbose=False
|
||||
)
|
||||
|
||||
# Test queries
|
||||
|
||||
@@ -0,0 +1,27 @@
|
||||
"""
|
||||
RouteLLM Integration Example
|
||||
|
||||
Route requests between strong and weak models to optimize cost.
|
||||
|
||||
Prerequisites:
|
||||
1. pip install routellm
|
||||
2. export OPENAI_API_KEY=your-api-key
|
||||
3. Start RouteLLM server:
|
||||
python -m routellm.openai_server \
|
||||
--routers mf \
|
||||
--strong-model gpt-4o \
|
||||
--weak-model gpt-4o-mini \
|
||||
--port 6060
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic usage with RouteLLM routing
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
llm="router-mf-0.5",
|
||||
base_url="http://localhost:6060/v1"
|
||||
)
|
||||
|
||||
response = agent.chat("What is 2+2?")
|
||||
print(response)
|
||||
@@ -0,0 +1,49 @@
|
||||
"""
|
||||
RouteLLM Multi-Agent Example
|
||||
|
||||
Prerequisites:
|
||||
1. pip install routellm
|
||||
2. export OPENAI_API_KEY=your-api-key
|
||||
3. Start RouteLLM server:
|
||||
python -m routellm.openai_server \
|
||||
--routers mf \
|
||||
--strong-model gpt-4o \
|
||||
--weak-model gpt-4o-mini \
|
||||
--port 6060
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, Agents, Task
|
||||
|
||||
ROUTELLM_URL = "http://localhost:6060/v1"
|
||||
|
||||
researcher = Agent(
|
||||
name="Researcher",
|
||||
role="Research analyst",
|
||||
goal="Find and analyze information",
|
||||
llm="router-mf-0.5",
|
||||
base_url=ROUTELLM_URL
|
||||
)
|
||||
|
||||
writer = Agent(
|
||||
name="Writer",
|
||||
role="Content writer",
|
||||
goal="Write clear and engaging content",
|
||||
llm="router-mf-0.5",
|
||||
base_url=ROUTELLM_URL
|
||||
)
|
||||
|
||||
task1 = Task(
|
||||
description="Research the latest AI trends in 2024",
|
||||
agent=researcher,
|
||||
expected_output="Research summary with key findings"
|
||||
)
|
||||
|
||||
task2 = Task(
|
||||
description="Write a brief article based on the research",
|
||||
agent=writer,
|
||||
expected_output="Short article about AI trends"
|
||||
)
|
||||
|
||||
agents = Agents(agents=[researcher, writer], tasks=[task1, task2])
|
||||
result = agents.start()
|
||||
print(result)
|
||||
@@ -0,0 +1,40 @@
|
||||
"""
|
||||
RouteLLM Workflow Example
|
||||
|
||||
Prerequisites:
|
||||
1. pip install routellm
|
||||
2. export OPENAI_API_KEY=your-api-key
|
||||
3. Start RouteLLM server:
|
||||
python -m routellm.openai_server \
|
||||
--routers mf \
|
||||
--strong-model gpt-4o \
|
||||
--weak-model gpt-4o-mini \
|
||||
--port 6060
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, Workflow
|
||||
|
||||
ROUTELLM_URL = "http://localhost:6060/v1"
|
||||
|
||||
workflow = Workflow(
|
||||
name="Analysis Pipeline",
|
||||
steps=[
|
||||
Agent(
|
||||
name="Analyzer",
|
||||
role="Data analyst",
|
||||
goal="Analyze data and extract insights",
|
||||
llm="router-mf-0.5",
|
||||
base_url=ROUTELLM_URL
|
||||
),
|
||||
Agent(
|
||||
name="Reporter",
|
||||
role="Report writer",
|
||||
goal="Create clear reports from analysis",
|
||||
llm="router-mf-0.5",
|
||||
base_url=ROUTELLM_URL
|
||||
)
|
||||
]
|
||||
)
|
||||
|
||||
result = workflow.run("Analyze the impact of AI on software development")
|
||||
print(result["output"])
|
||||
@@ -49,7 +49,7 @@ def main():
|
||||
goal="Help users with their questions accurately and concisely",
|
||||
backstory="You are a knowledgeable assistant who provides clear, helpful answers.",
|
||||
llm="gpt-4o-mini",
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
print(f"Agent: {agent.name}")
|
||||
|
||||
@@ -45,8 +45,9 @@ def main():
|
||||
agent = Agent(
|
||||
name="DeepThinker",
|
||||
instructions="You are a problem-solving assistant that thinks step by step.",
|
||||
thinking_budget=ThinkingBudget.high() # 16,000 tokens for reasoning
|
||||
)
|
||||
# Set thinking budget via property setter (not constructor param)
|
||||
agent.thinking_budget = ThinkingBudget.high() # 16,000 tokens for reasoning
|
||||
|
||||
print(f"Agent: {agent.name}")
|
||||
print(f"Thinking budget: {agent.thinking_budget.max_tokens:,} tokens")
|
||||
@@ -67,8 +68,9 @@ def main():
|
||||
agent_custom = Agent(
|
||||
name="CustomThinker",
|
||||
instructions="You solve complex problems.",
|
||||
thinking_budget=custom_budget
|
||||
)
|
||||
# Set thinking budget via property setter (not constructor param)
|
||||
agent_custom.thinking_budget = custom_budget
|
||||
|
||||
print(f"Agent: {agent_custom.name}")
|
||||
print(f"Max tokens: {agent_custom.thinking_budget.max_tokens:,}")
|
||||
|
||||
@@ -38,7 +38,7 @@ def main():
|
||||
# Create agent
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant that explains scientific concepts simply",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Track the API call performance
|
||||
|
||||
@@ -13,8 +13,8 @@ def main():
|
||||
role="Research Specialist",
|
||||
goal="Find information about a topic",
|
||||
backstory="You are an expert researcher who finds comprehensive information.",
|
||||
verbose=True,
|
||||
llm="gpt-5-nano", # Use a cost-effective model for examples
|
||||
output="verbose",
|
||||
llm="gpt-4o-mini", # Use a cost-effective model for examples
|
||||
metrics=True # 🎯 SIMPLIFIED: Just add this parameter!
|
||||
)
|
||||
|
||||
@@ -29,7 +29,7 @@ def main():
|
||||
agents = Agents(
|
||||
agents=[research_agent],
|
||||
tasks=[research_task],
|
||||
verbose=True
|
||||
output="verbose"
|
||||
)
|
||||
|
||||
print("🚀 Running agent task...")
|
||||
|
||||
@@ -54,7 +54,7 @@ def create_agents():
|
||||
goal="Gather comprehensive information on renewable energy",
|
||||
backstory="Expert researcher with deep knowledge of energy sector",
|
||||
instructions="You are a thorough researcher. Provide detailed, fact-based information.",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
analyst = Agent(
|
||||
@@ -63,7 +63,7 @@ def create_agents():
|
||||
goal="Analyze trends and patterns in renewable energy data",
|
||||
backstory="Experienced data analyst specializing in energy markets",
|
||||
instructions="You are an analytical thinker. Focus on trends, patterns, and insights.",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
writer = Agent(
|
||||
@@ -72,7 +72,7 @@ def create_agents():
|
||||
goal="Create clear, compelling reports",
|
||||
backstory="Professional technical writer with expertise in energy sector",
|
||||
instructions="You are a skilled writer. Create clear, well-structured reports.",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
return researcher, analyst, writer
|
||||
@@ -104,8 +104,7 @@ def main():
|
||||
workflow = Agents(
|
||||
agents=[researcher, analyst, writer],
|
||||
tasks=[research_task, analysis_task, report_task],
|
||||
process="sequential",
|
||||
verbose=True
|
||||
process="sequential"
|
||||
)
|
||||
|
||||
result = workflow.start()
|
||||
|
||||
@@ -11,7 +11,7 @@ Shows how to monitor agent performance when using external tools.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.tools import duckduckgo, wikipedia
|
||||
from praisonaiagents.tools import duckduckgo, wikipedia_tools
|
||||
from praisonaiagents.telemetry import (
|
||||
monitor_function, track_api_call, get_api_stats,
|
||||
get_slowest_functions, performance_monitor
|
||||
@@ -48,8 +48,8 @@ def main():
|
||||
instructions="""You are a research assistant that helps find information.
|
||||
Use the available tools to search for information and provide comprehensive answers.
|
||||
Be thorough in your research and cite your sources.""",
|
||||
llm="gpt-5-nano",
|
||||
tools=[duckduckgo, wikipedia] # Add search tools
|
||||
llm="gpt-4o-mini",
|
||||
tools=[duckduckgo, wikipedia_tools] # Add search tools
|
||||
)
|
||||
|
||||
# Test queries to demonstrate tool performance monitoring
|
||||
@@ -97,7 +97,9 @@ def main():
|
||||
# Slowest functions analysis
|
||||
print("\n🐌 Slowest Functions:")
|
||||
slowest = get_slowest_functions()
|
||||
for func_name, avg_time in slowest:
|
||||
for item in slowest[:5]:
|
||||
func_name = item.get('function', 'unknown')
|
||||
avg_time = item.get('average_time', 0)
|
||||
print(f" {func_name}: {avg_time:.3f}s average")
|
||||
|
||||
# Real-time performance data
|
||||
|
||||
@@ -54,7 +54,7 @@ async def run_async_agent(query: str):
|
||||
# Create agent
|
||||
agent = Agent(
|
||||
instructions="You are an efficient AI assistant that processes requests quickly",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Track the agent execution
|
||||
|
||||
@@ -60,7 +60,7 @@ def run_robust_agent(query: str, with_error_simulation: bool = True):
|
||||
instructions="""You are a resilient AI assistant.
|
||||
Even when facing challenges, you provide helpful responses.
|
||||
If you encounter errors, acknowledge them and offer alternatives.""",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
try:
|
||||
|
||||
@@ -65,7 +65,7 @@ def run_stateful_agent(query: str, session_id: str, conversation_turn: int):
|
||||
instructions="""You are a memory-enabled AI assistant. You can remember
|
||||
previous conversations and build on past interactions. Use your memory
|
||||
to provide personalized and contextual responses.""",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Pre-processing: retrieve relevant memories
|
||||
@@ -165,7 +165,9 @@ def main():
|
||||
# Slowest operations
|
||||
print("\n🐌 Slowest Memory Operations:")
|
||||
slowest = get_slowest_functions()
|
||||
for func_name, avg_time in slowest[:5]: # Top 5 slowest
|
||||
for item in slowest[:5]: # Top 5 slowest
|
||||
func_name = item.get('function', 'unknown')
|
||||
avg_time = item.get('average_time', 0)
|
||||
print(f" {func_name}: {avg_time:.3f}s average")
|
||||
|
||||
# Memory operation breakdown
|
||||
|
||||
@@ -77,7 +77,7 @@ def run_hierarchical_workflow():
|
||||
backstory="Experienced project manager with expertise in team coordination",
|
||||
instructions="""You are a project manager. Break down complex projects into tasks,
|
||||
assign them to appropriate team members, and coordinate the overall effort.""",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Create worker agents
|
||||
@@ -87,7 +87,7 @@ def run_hierarchical_workflow():
|
||||
goal="Conduct thorough research on assigned topics",
|
||||
backstory="Expert researcher with deep analytical skills",
|
||||
instructions="You are a research specialist. Provide detailed, factual information.",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
analysis_worker = Agent(
|
||||
@@ -96,7 +96,7 @@ def run_hierarchical_workflow():
|
||||
goal="Analyze data and identify patterns and insights",
|
||||
backstory="Experienced data analyst with strong analytical thinking",
|
||||
instructions="You are a data analyst. Focus on patterns, trends, and insights.",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
writing_worker = Agent(
|
||||
@@ -105,7 +105,7 @@ def run_hierarchical_workflow():
|
||||
goal="Create clear, well-structured documentation and reports",
|
||||
backstory="Professional writer specializing in technical content",
|
||||
instructions="You are a technical writer. Create clear, comprehensive reports.",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Project tasks
|
||||
|
||||
@@ -180,7 +180,7 @@ def run_agent_with_custom_tools():
|
||||
instructions="""You are a technical assistant with access to various tools.
|
||||
Use the appropriate tools to help with data processing, API calls, database queries,
|
||||
and file operations. Always explain what tools you're using and why.""",
|
||||
llm="gpt-5-nano",
|
||||
llm="gpt-4o-mini",
|
||||
tools=[process_data, call_external_api, query_database, file_operation]
|
||||
)
|
||||
|
||||
@@ -263,7 +263,7 @@ def main():
|
||||
# Slowest operations
|
||||
print("\n🐌 Slowest Tool Operations:")
|
||||
slowest = get_slowest_functions()
|
||||
tool_slowest = [(name, time) for name, time in slowest if 'tool' in name.lower()]
|
||||
tool_slowest = [(item.get('function', 'unknown'), item.get('average_time', 0)) for item in slowest if 'tool' in item.get('function', '').lower()]
|
||||
|
||||
for tool_name, avg_time in tool_slowest[:3]:
|
||||
print(f" {tool_name}: {avg_time:.3f}s")
|
||||
|
||||
@@ -60,7 +60,7 @@ def get_real_time_agent_response(query: str, response_id: int):
|
||||
# Create a lightweight agent for streaming
|
||||
agent = Agent(
|
||||
instructions="You are a real-time assistant. Provide quick, helpful responses.",
|
||||
llm="gpt-5-nano"
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
with track_api_call(f"streaming_response_{response_id}"):
|
||||
|
||||
Loaded 100 of 579 files, more files were not shown because too many files have changed in this diff.
Show more
Reference in new issue
Block a user