convo-lang 0.6.3

A conversational prompting and programming language

Convo-Lang Python Wrapper (v0.6.3)

A Python wrapper around the Convo-Lang CLI that lets you build conversations in Python and execute them via the official Convo-Lang engine.

Status: 0.6.3 – basic conversation building, runtime variables support, and single-shot completion via the CLI.

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Features

• Minimal, Pythonic API to build conversations (system, user, assistant)
• Execute full .convo files directly from Python via add_convo_file()
• One-line complete() to run via Convo-Lang CLI, with optional runtime variables via complete(variables={...})
• Automatic JSON handling when passing data between agents (no manual serialization)
• Clean multi-agent pipelines by chaining structured outputs between .convo agents
• Simple config with env passthrough (e.g., OPENAI_API_KEY) and defaultModel
• Zero server code required — uses the official Convo-Lang CLI under the hood

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Installation

1. Install Node.js and npm

The wrapper depends on the Convo-Lang CLI, which requires Node.js.
Download and install the latest LTS version of Node.js (includes npm):

• Node.js downloads

Verify installation:

node -v
npm -v

2. Install the Convo-Lang CLI

npm i -g @convo-lang/convo-lang-cli

This makes the convo binary available in your PATH.

3. Install the Python wrapper

pip install convo-lang

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Quick Start

from convo_lang import Conversation

OPENAI_API_KEY = "sk-proj-EMA"
defaultModel = "gpt-5"
convo = Conversation(
    config={
        "env": {"OPENAI_API_KEY": OPENAI_API_KEY},
        "defaultModel": defaultModel,
    }
)
convo.add_system_message("You are a home automation assistant.")
convo.add_user_message("It's time for bed, can you turn off the lights")
answer = convo.complete()
print(answer)

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Passing Variables to .convo

You can pass variables to the Convo-Lang runtime using the variables argument of complete(). These variables can be referenced inside your .convo script.

from convo_lang import Conversation

convo = Conversation(
    config={
        "env": {"OPENAI_API_KEY": OPENAI_API_KEY},
        "defaultModel": defaultModel,
    }
)

convo.add_convo_text(convo_text)

answer = convo.complete(variables={"isNewVisitor": True})
print(answer)

Variables are forwarded to the Convo-Lang CLI via --vars and support booleans, numbers, and strings.

If a variable value is a JSON string or a Python dict/list serialized to JSON, Convo-Lang will automatically treat it as structured JSON inside .convo and allow passing it between agents without manual parsing.

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Passing Data Between Agents

You can pass structured data (JSON) between agents directly.

• If you pass a Python dict/list (or a JSON string) as a variable, it will be available as JSON inside .convo.
• When an agent returns structured output, it can be forwarded to the next agent as-is.
• No manual serialization/deserialization is required.

convo_candidate_profile_analyzer = Conversation(agent_configs)
convo_candidate_profile_analyzer.add_convo_file(
    "agents/candidateProfileAnalyzer.convo"
)
profile_data = convo_candidate_profile_analyzer.complete(
    variables={"candidate_profile": candidate_profile}
)

convo_profile_job_matcher = Conversation(agent_configs)
convo_profile_job_matcher.add_convo_file("agents/profileJobMatcher.convo")
match_data = convo_profile_job_matcher.complete(
    variables={"profile_data": profile_data}
)

This enables clean multi-agent pipelines where each agent consumes the structured output of the previous one.

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Loading Entire .convo Files

You can load an entire .convo file as-is, without extracting or embedding parts of it into Python strings:

convo = Conversation(config)
convo.add_convo_file("path/to/agent.convo")
result = convo.complete()

This is the recommended approach for real projects:

• The full .convo file is executed by the CLI unchanged
• Prompt logic, control flow, and conditions live entirely in .convo
• Python is used only for orchestration and data passing
• .convo files can be versioned, reviewed, and tested independently

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Requirements

• Python 3.8+
• Node.js 18+ and npm
• Convo-Lang CLI: npm i -g @convo-lang/convo-lang-cli
• At least one LLM provider API key in the environment (e.g., OPENAI_API_KEY)

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Authors

• Scott Vance

Maintainers

• Sergey Inozemtsev