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Model: katanemo/Plano-Orchestrator-4B Source: Original Platform
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76
LICENSE
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LICENSE
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# KATANEMO COMMUNITY LICENSE AGREEMENT
|
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**Version Release Date:** April 2, 2026
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This KATANEMO COMMUNITY LICENSE AGREEMENT is based on the Llama 3.2 Community License Agreement (https://www.llama.com/llama3_2/license/), which has been adapted for terms specific to the distribution and use of proprietary Katanemo Materials (defined below) provided by DigitalOcean, LLC.
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---
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1.Definitions
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a. "Agreement": The terms and conditions for use, reproduction, distribution, and modification of the Katanemo Materials set forth herein.
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b. "Documentation": The specifications, manuals, and documentation accompanying Katanemo Models.
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c. "Licensee" or "you”: The individual or entity entering into this Agreement, including your employer if you are acting on their behalf.
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d. "Katanemo Model(s)": The foundational large language models and model software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by DigitalOcean at https://huggingface.co/katanemolabs.
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e. "Katanemo Materials": Collectively, Katanemo's proprietary models (including Katanemo Models) and Documentation.
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f. “DigitalOcean” or "we": DigitalOcean, LLC, a Delaware, USA Corporation.
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|
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---
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2.
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By clicking "I Accept" below or by using or distributing any portion or element of the Katanemo Materials, you agree to be bound by this Agreement.
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---
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3. LICENSE RIGHTS AND REDISTRIBUTION
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a. Grant of Rights
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Subject to Section 4, you are granted a non-exclusive, worldwide, non-transferable, and royalty-free license under DigitalOcean’s intellectual property or other rights owned by DigitalOcean embodied in the Katanemo Materials to:
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- Use, reproduce, distribute, copy, creative derivative works of, and make modifications to the Katanemo Materials, and
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ii. If you receive Katanemo Materials, or any derivative works thereof, from a Licensee as part of an integrated end user product, then Section 4 of this Agreement will not apply to you.
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iii. You must retain in all copies of the Katanemo Materials that you distribute the following attribution notice within a “Notice” text file distributed as a part of such copies: “Katanemo Models are licensed under the DigitalOcean Community License, Copyright 2026 DigitalOcean, LLC. All Rights Reserved.”
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iv. Your use of the Katanemo Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Katanemo Materials (available at https://www.digitalocean.com/legal/acceptable-use-policy), which is hereby incorporated by reference into this Agreement.
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---
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4. ADDITIONAL COMMERCIAL TERMS
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If you use, reproduce, modify, distribute, and create derivative works from the Katanemo Materials for commercial purposes, you must obtain a separate commercial license from DigitalOcean, which DigitalOcean may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until DigitalOcean otherwise expressly grants you such rights.
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5. Disclaimer of Warranty
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UNLESS REQUIRED BY APPLICABLE LAW, THE KATANEMO MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, AND DIGITALOCEAN DISCLAIMS ALL WARRANTIES OF ANY KIND, BOTH EXPRESS AND IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE KATANEMO MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE KATANEMO MATERIALS AND ANY OUTPUT AND RESULTS.
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a. Trademarks
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No trademark licenses are granted under this Agreement, and in connection with the Katanemo Materials, neither DigitalOcean nor you may use any name or mark owned by or associated with the other or any of its affiliates, except as required for reasonable and customary use in describing and redistributing the Katanemo Materials or as set forth in this Section 7(a). DigitalOcean hereby grants you a limited license to use “Katanemo” (the “Mark”) solely as required to comply with the last sentence of Section 3.b.i. You will comply with DigitalOcean’s brand guidelines as may be provided by DigitalOcean. All goodwill arising out of your use of the Mark will inure to the benefit of DigitalOcean.
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b. Ownership
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Subject to DigitalOcean’s ownership of Katanemo Materials and derivatives made by or for DigitalOcean, with respect to any derivative works and modifications of the Katanemo Materials that are made by you, as between you and DigitalOcean, you are and will be the owner of such derivative works and modifications.
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c. Litigation
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If you institute litigation or other proceedings against DigitalOcean or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Katanemo Materials or Katanemo Model outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless DigitalOcean from and against any claim by any third party arising out of or related to your use or distribution of the Katanemo Materials.
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---
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8. Term and Termination
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The term of this Agreement will commence upon your acceptance of this Agreement or access to the Katanemo Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. DigitalOcean may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Katanemo Materials. Sections 5, 6, 7.b and 9 shall survive the termination of this Agreement.
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---
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9. Governing Law and Jurisdiction
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This Agreement is governed by the laws of the State of Colorado, USA without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of Denver County, Colorado, shall have exclusive jurisdiction of any dispute arising out of this Agreement.
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125
README.md
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README.md
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---
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license: other
|
||||
license_name: katanemo-research
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license_link: >-
|
||||
https://huggingface.co/katanemo/Plano-Orchestrator-4B/blob/main/LICENSE
|
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base_model:
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- Qwen/Qwen3-4B-Instruct-2507
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language:
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- en
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pipeline_tag: text-generation
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---
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# katanemo/Plano-Orchestrator-4B
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## Overview
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**Plano-Orchestrator** is a family of state-of-the-art routing and orchestration models that decide which agent(s) or LLM(s) should handle each request, and in what sequence. Built for multi-agent orchestration systems, Plano-Orchestrator excels at analyzing user intent and conversation context to make precise routing and orchestration decisions. Designed for real-world deployments, it delivers strong performance across general conversations, coding tasks, and long-context multi-turn conversations, while remaining efficient enough for low-latency production environments.
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#### Key capabilities
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- **Multi-turn Context Understanding**: Makes routing decisions based on full conversation history, maintaining contextual awareness across extended dialogues with evolving user needs.
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- **Multi-intent Detection**: Identifies when a single user message requires multiple agents simultaneously, enabling parallel/sequential routing to fulfill complex requests.
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- **Context-dependent Routing**: Correctly interprets ambiguous or referential messages by leveraging prior conversation context for accurate routing decisions.
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- **Conversational Flow Handling**: Understands diverse interaction patterns including follow-ups, clarifications, confirmations, and corrections within ongoing conversations.
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- **Negative Case Detection**: Recognizes when no specialized routing is needed, avoiding unnecessary LLM or agent calls for casual conversation.
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## Benchmark
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We evaluate on **1,958 user messages** across **605 multi-turn conversations** with more than **130 different agents**, covering three scenarios:
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- **General** (1,438 messages): Everyday conversational queries spanning diverse topics and agent types
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- **Coding** (285 messages): Development-focused conversations including debugging, code generation, and technical assistance
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- **Long-context** (235 messages): Extended conversations requiring understanding of extensive prior context
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Each message is annotated with routing-relevant attributes, including not limited to intent multiplicity, context dependency, and continuation type. Below is the evaluation
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result.
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<div align="center">
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<img width="100%" height="auto" src="./assets/Plano-Orchestrator.png"></a>
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</div>
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> [!NOTE]
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> For evaluation, please note that all models were evaluated with minimal reasoning to ensure routing remains efficient.
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## Example
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||||
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||||
```python
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import json
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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ORCHESTRATION_PROMPT = (
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"You are a helpful assistant that selects the most suitable routes based on user intent.\n"
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"You are provided with a list of available routes enclosed within <routes></routes> XML tags:\n"
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||||
"<routes>\n{routes}\n</routes>\n\n"
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"You are also given the conversation context enclosed within <conversation></conversation> XML tags:\n"
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"<conversation>\n{conversation}\n</conversation>\n\n"
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"## Instructions\n"
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"1. Analyze the latest user intent from the conversation.\n"
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"2. Compare it against the available routes to find which routes can help fulfill the request.\n"
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"3. Respond only with the exact route names from <routes>.\n"
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"4. If no routes can help or the intent is already fulfilled, return an empty list.\n\n"
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||||
"## Response Format\n"
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||||
"Return your answer strictly in JSON as follows:\n"
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||||
'{{"route": ["route_name_1", "route_name_2", "..."]}}\n'
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"If no routes are needed, return an empty list for `route`."
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)
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def convert_agents_to_routes(agents):
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tools = [
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||||
{
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||||
"name": agent["name"],
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"description": agent["description"],
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||||
}
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for agent in agents
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]
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return "\n".join([json.dumps(tool, ensure_ascii=False) for tool in tools])
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def build_messages(available_agents, conversation):
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routes = convert_agents_to_routes(available_agents)
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conversation_str = json.dumps(conversation, indent=4, ensure_ascii=False)
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prompt = ORCHESTRATION_PROMPT.format(routes=routes, conversation=conversation_str)
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return [{"role": "user", "content": prompt}]
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||||
|
||||
# Load model
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||||
model_name = "katanemo/Plano-Orchestrator-4B"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
|
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model_name,
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torch_dtype=torch.float16,
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device_map="auto"
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)
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# Define available agents
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available_agents = [
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{"name": "WeatherAgent", "description": "Provides weather forecasts and current conditions for any location"},
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{"name": "CodeAgent", "description": "Generates, debugs, explains, and reviews code in multiple programming languages"}
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||||
]
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# Conversation history
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conversation = [
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{"role": "user", "content": "What's the weather like today?"},
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{"role": "assistant", "content": "I can help you with that. Could you tell me your location?"},
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||||
{"role": "user", "content": "San Francisco"},
|
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]
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# Build messages and generate
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model_inputs = tokenizer.apply_chat_template(
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messages, add_generation_prompt=True, return_tensors="pt", return_dict=True
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).to(model.device)
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generated_ids = model.generate(**model_inputs, max_new_tokens=32768)
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generated_ids = [
|
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output_ids[len(input_ids) :]
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for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
|
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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print(response)
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# Output: {"route": ["WeatherAgent"]}
|
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```
|
||||
|
||||
## License
|
||||
|
||||
The Plano-Orchestrator collection is distributed under the [Katanemo license](https://huggingface.co/katanemo/Plano-Orchestrator-4B/blob/main/LICENSE).
|
||||
3
assets/Plano-Orchestrator.png
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assets/Plano-Orchestrator.png
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version https://git-lfs.github.com/spec/v1
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oid sha256:92325f361f49696440c5e919424565b10d1db59bcc23ab18c471ceef1d3857b4
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size 208998
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61
chat_template.jinja
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{%- if tools %}
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||||
{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
|
||||
{{- messages[0].content + '\n\n' }}
|
||||
{%- endif %}
|
||||
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||
{%- for tool in tools %}
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||||
{{- "\n" }}
|
||||
{{- tool | tojson }}
|
||||
{%- endfor %}
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||||
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||
{%- else %}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- for message in messages %}
|
||||
{%- if message.content is string %}
|
||||
{%- set content = message.content %}
|
||||
{%- else %}
|
||||
{%- set content = '' %}
|
||||
{%- endif %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- if message.tool_calls %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- endif %}
|
||||
30
config.json
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config.json
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||||
{
|
||||
"architectures": [
|
||||
"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2560,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 9728,
|
||||
"max_position_embeddings": 262144,
|
||||
"max_window_layers": 36,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 8,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 5000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.52.4",
|
||||
"use_cache": false,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
13
generation_config.json
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generation_config.json
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||||
{
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
||||
"temperature": 0.7,
|
||||
"top_k": 20,
|
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||||
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
240
tokenizer_config.json
Normal file
240
tokenizer_config.json
Normal file
@@ -0,0 +1,240 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 1010000,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "right",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user