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Author SHA1 Message Date
Mervin Praison 6dbf194312 Release v2.3.78 2025-12-23 06:46:15 +00:00
10 changed files with 273 additions and 43 deletions

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@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=2.3.77" \
"praisonai>=2.3.78" \
"praisonai[chat]" \
"embedchain[github,youtube]"
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@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=2.3.77" \
"praisonai>=2.3.78" \
"praisonai[ui]" \
"praisonai[chat]" \
"praisonai[realtime]" \
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@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=2.3.77" \
"praisonai>=2.3.78" \
"praisonai[ui]" \
"praisonai[crewai]"
+2 -2
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@@ -3,8 +3,8 @@ class Praisonai < Formula
desc "AI tools for various AI applications"
homepage "https://github.com/MervinPraison/PraisonAI"
url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.77.tar.gz"
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.77.tar.gz | shasum -a 256`.split.first
url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.78.tar.gz"
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.78.tar.gz | shasum -a 256`.split.first
license "MIT"
depends_on "[email protected]"
@@ -16,7 +16,7 @@ logger = logging.getLogger(__name__)
COMPARE_MODES = {
"basic": {},
"tools": {"tools": "internet_search"},
"tools": {"tools": "calculator,internet_search"},
"research": {"research": True},
"planning": {"planning": True},
"memory": {"memory": True},
@@ -407,13 +407,7 @@ class CompareHandler:
from praisonaiagents.tools import internet_search
tools.append(internet_search)
elif name == "calculator":
def calculator(expression: str) -> str:
"""Evaluate a mathematical expression."""
try:
return str(eval(expression))
except Exception as e:
return f"Error: {e}"
tools.append(calculator)
tools.append(_calculator_tool)
except ImportError:
logger.warning(f"Could not load tool: {name}")
@@ -466,3 +460,50 @@ class CompareHandler:
print(f"[red]Failed to save results to: {output_path}[/red]")
return result
def _calculator_tool(expression: str) -> str:
"""
Evaluate a mathematical expression safely.
Args:
expression: Mathematical expression to evaluate (e.g., "2+2", "15*3", "100/4")
Returns:
The result of the calculation as a string
"""
import ast
import operator
# Safe operators
operators = {
ast.Add: operator.add,
ast.Sub: operator.sub,
ast.Mult: operator.mul,
ast.Div: operator.truediv,
ast.Pow: operator.pow,
ast.USub: operator.neg,
ast.UAdd: operator.pos,
ast.Mod: operator.mod,
ast.FloorDiv: operator.floordiv,
}
def _eval(node):
if isinstance(node, ast.Constant):
return node.value
elif isinstance(node, ast.BinOp):
left = _eval(node.left)
right = _eval(node.right)
return operators[type(node.op)](left, right)
elif isinstance(node, ast.UnaryOp):
operand = _eval(node.operand)
return operators[type(node.op)](operand)
else:
raise ValueError(f"Unsupported operation: {type(node)}")
try:
tree = ast.parse(expression, mode='eval')
result = _eval(tree.body)
return str(result)
except Exception as e:
return f"Error evaluating '{expression}': {e}"
@@ -3,12 +3,21 @@ Fast Context Handler for CLI.
Provides codebase search capability using FastContext.
Usage: praisonai "Find authentication code" --fast-context ./src
Fast Context Strategy:
1. Extract search keywords from natural language query using LLM
2. Provide folder tree context to help understand codebase structure
3. Use both file name search AND content search (ripgrep-style)
4. Return relevant code snippets for context
"""
import os
import logging
from typing import Any, Dict, Tuple, List
from .base import FlagHandler
logger = logging.getLogger(__name__)
class FastContextHandler(FlagHandler):
"""
@@ -61,17 +70,172 @@ class FastContextHandler(FlagHandler):
return True, ""
def _get_folder_tree(self, path: str, max_depth: int = 2) -> str:
"""Get folder tree structure for context."""
tree_lines = []
path = os.path.abspath(path)
ignore_dirs = {'.git', '__pycache__', 'node_modules', '.venv', 'venv', '.tox', 'dist', 'build', '.egg-info'}
ignore_exts = {'.pyc', '.pyo', '.so', '.o', '.a', '.dylib'}
def walk_tree(current_path, prefix="", depth=0):
if depth > max_depth:
return
try:
entries = sorted(os.listdir(current_path))
except PermissionError:
return
dirs = []
files = []
for entry in entries:
full_path = os.path.join(current_path, entry)
if os.path.isdir(full_path):
if entry not in ignore_dirs and not entry.startswith('.'):
dirs.append(entry)
else:
ext = os.path.splitext(entry)[1]
if ext not in ignore_exts and not entry.startswith('.'):
files.append(entry)
for i, d in enumerate(dirs):
is_last = (i == len(dirs) - 1) and not files
tree_lines.append(f"{prefix}{'└── ' if is_last else '├── '}{d}/")
walk_tree(os.path.join(current_path, d),
prefix + (' ' if is_last else '│ '), depth + 1)
for i, f in enumerate(files[:10]): # Limit files shown
is_last = i == len(files[:10]) - 1
tree_lines.append(f"{prefix}{'└── ' if is_last else '├── '}{f}")
if len(files) > 10:
tree_lines.append(f"{prefix} ... and {len(files) - 10} more files")
tree_lines.append(os.path.basename(path) + "/")
walk_tree(path)
return "\n".join(tree_lines[:50]) # Limit total lines
def _extract_keywords(self, query: str, folder_tree: str) -> List[str]:
"""Extract search keywords from natural language query using LLM."""
try:
from praisonaiagents import Agent
extractor = Agent(
name="KeywordExtractor",
role="Search Query Analyzer",
goal="Extract file search keywords from natural language",
backstory="Expert at understanding code search queries",
llm="gpt-4o-mini",
verbose=False
)
prompt = f"""Given this folder structure:
{folder_tree}
And this search query: "{query}"
Extract 1-5 specific keywords/patterns to search for in file names and content.
Return ONLY the keywords, one per line, no explanations.
Focus on: file names, function names, class names, variable names that might match.
If the query mentions a folder name that exists, include files from that folder."""
response = extractor.chat(prompt, stream=False)
keywords = [k.strip() for k in str(response).strip().split('\n') if k.strip()]
logger.debug(f"Extracted keywords: {keywords}")
return keywords[:5] # Limit to 5 keywords
except Exception as e:
logger.debug(f"Keyword extraction failed: {e}")
# Fallback: extract words from query
return [w for w in query.split() if len(w) > 2][:3]
def _search_files_by_name(self, path: str, keywords: List[str]) -> List[Dict[str, Any]]:
"""Search for files matching keywords in their names."""
matches = []
path = os.path.abspath(path)
ignore_dirs = {'.git', '__pycache__', 'node_modules', '.venv', 'venv'}
for root, dirs, files in os.walk(path):
dirs[:] = [d for d in dirs if d not in ignore_dirs]
for filename in files:
filepath = os.path.join(root, filename)
rel_path = os.path.relpath(filepath, path)
# Check if any keyword matches filename or path
for kw in keywords:
kw_lower = kw.lower()
if kw_lower in filename.lower() or kw_lower in rel_path.lower():
matches.append({
'file': rel_path,
'lines': [(1, 50)], # First 50 lines
'relevance': 1.0,
'match_type': 'filename'
})
break
return matches[:20] # Limit results
def _search_files_by_content(self, path: str, keywords: List[str]) -> List[Dict[str, Any]]:
"""Search for files containing keywords in content."""
matches = []
path = os.path.abspath(path)
ignore_dirs = {'.git', '__pycache__', 'node_modules', '.venv', 'venv'}
code_exts = {'.py', '.js', '.ts', '.jsx', '.tsx', '.java', '.go', '.rs', '.rb', '.sh', '.yaml', '.yml', '.json', '.md', '.txt'}
for root, dirs, files in os.walk(path):
dirs[:] = [d for d in dirs if d not in ignore_dirs]
for filename in files:
ext = os.path.splitext(filename)[1]
if ext not in code_exts:
continue
filepath = os.path.join(root, filename)
rel_path = os.path.relpath(filepath, path)
try:
with open(filepath, 'r', encoding='utf-8', errors='ignore') as f:
content = f.read(50000) # Read first 50KB
content_lower = content.lower()
for kw in keywords:
if kw.lower() in content_lower:
# Find line numbers with matches
lines = content.split('\n')
match_lines = []
for i, line in enumerate(lines[:200], 1): # Check first 200 lines
if kw.lower() in line.lower():
match_lines.append((max(1, i-2), min(len(lines), i+2)))
if match_lines:
matches.append({
'file': rel_path,
'lines': match_lines[:5], # Limit line ranges
'relevance': 0.8,
'match_type': 'content'
})
break
except Exception:
continue
return matches[:15] # Limit results
def search_context(self, query: str, path: str, **kwargs) -> List[Dict[str, Any]]:
"""
Search for relevant context in the codebase.
Uses a smart multi-step approach:
1. Get folder tree structure
2. Use LLM to extract search keywords from query
3. Search by filename AND content
4. Return combined results
Args:
query: Search query
query: Natural language search query
path: Path to search
**kwargs: Additional search options
- use_llm: Use LLM for intelligent search (slower, default: False)
- max_turns: Max search turns for LLM mode
- model: LLM model for intelligent search
- use_llm_keywords: Use LLM to extract keywords (default: True)
Returns:
List of matching results
@@ -87,37 +251,50 @@ class FastContextHandler(FlagHandler):
return []
try:
from praisonaiagents import FastContext
use_llm_keywords = kwargs.get('use_llm_keywords', True)
# Use fast non-LLM search by default for better performance
use_llm = kwargs.get('use_llm', False)
# Step 1: Get folder tree for context
logger.debug(f"Getting folder tree for: {path}")
folder_tree = self._get_folder_tree(path)
logger.debug(f"Folder tree:\n{folder_tree}")
fc = FastContext(
workspace_path=path,
model=kwargs.get('model', 'gpt-4o-mini'),
max_turns=kwargs.get('max_turns', 2), # Reduced from 4 for speed
max_parallel=kwargs.get('parallelism', 8),
timeout=kwargs.get('timeout', 15.0), # Reduced timeout
verbose=self.verbose
)
# Step 2: Extract keywords
if use_llm_keywords:
logger.debug(f"Extracting keywords from query: {query}")
keywords = self._extract_keywords(query, folder_tree)
else:
keywords = [w for w in query.split() if len(w) > 2][:3]
# Use non-LLM search by default (much faster)
result = fc.search(query, use_llm=use_llm)
logger.debug(f"Search keywords: {keywords}")
# Convert to list of dicts
if not keywords:
self.print_status("Could not extract search keywords", "warning")
return []
# Step 3: Search by filename
logger.debug("Searching by filename...")
filename_matches = self._search_files_by_name(path, keywords)
logger.debug(f"Found {len(filename_matches)} filename matches")
# Step 4: Search by content
logger.debug("Searching by content...")
content_matches = self._search_files_by_content(path, keywords)
logger.debug(f"Found {len(content_matches)} content matches")
# Combine and deduplicate
seen_files = set()
matches = []
if hasattr(result, 'files'):
for file_match in result.files:
matches.append({
'file': file_match.path,
'lines': [(lr.start, lr.end) for lr in file_match.line_ranges],
'relevance': getattr(file_match, 'relevance', 1.0)
})
for m in filename_matches + content_matches:
if m['file'] not in seen_files:
seen_files.add(m['file'])
matches.append(m)
self.print_status(f"🔍 Found {len(matches)} relevant files", "success")
return matches
except Exception as e:
logger.error(f"FastContext search error: {e}")
self.log(f"FastContext search error: {e}", "error")
return []
@@ -95,9 +95,9 @@ class HandoffHandler(FlagHandler):
for i, agent in enumerate(agents[:-1]):
next_agent = agents[i + 1]
handoff = Handoff(
target=next_agent,
name=f"handoff_to_{agent_names[i + 1]}",
description=f"Hand off task to {agent_names[i + 1]} for further processing"
agent=next_agent,
tool_name_override=f"handoff_to_{agent_names[i + 1]}",
tool_description_override=f"Hand off task to {agent_names[i + 1]} for further processing"
)
# Add handoff to agent
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@@ -313,6 +313,18 @@ class PraisonAI:
elif hasattr(args, 'direct_prompt') and args.direct_prompt:
# Only handle direct prompt if agent_file wasn't explicitly set in constructor
if original_agent_file == "agents.yaml": # Default value, so safe to use direct prompt
# Handle --compare flag for CLI mode comparison
if hasattr(args, 'compare') and args.compare:
from .features.compare import CompareHandler
handler = CompareHandler(verbose=getattr(args, 'verbose', False))
result = handler.execute(
args.direct_prompt,
args.compare,
model=getattr(args, 'llm', None),
output_path=getattr(args, 'compare_output', None)
)
return result
# Combine direct prompt with any available inputs (stdin and/or file)
prompt_parts = [args.direct_prompt]
if stdin_input:
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@@ -57,7 +57,7 @@ class CloudDeployer:
file.write("FROM python:3.11-slim\n")
file.write("WORKDIR /app\n")
file.write("COPY . .\n")
file.write("RUN pip install flask praisonai==2.3.77 gunicorn markdown\n")
file.write("RUN pip install flask praisonai==2.3.78 gunicorn markdown\n")
file.write("EXPOSE 8080\n")
file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
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@@ -1 +1 @@
__version__ = "2.3.77"
__version__ = "2.3.78"