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b4543ba56c
* adding support for signals * reducing false positives for signals like positive interaction * adding docs. Still need to fix the messages list, but waiting on PR #621 * Improve frustration detection: normalize contractions and refine punctuation * Further refine test cases with longer messages * minor doc changes * fixing echo statement for build * fixing the messages construction and using the trait for signals * update signals docs * fixed some minor doc changes * added more tests and fixed docuemtnation. PR 100% ready * made fixes based on PR comments * Optimize latency 1. replace sliding window approach with trigram containment check 2. add code to pre-compute ngrams for patterns * removed some debug statements to make tests easier to read * PR comments to make ObservableStreamProcessor accept optonal Vec<Messagges> * fixed PR comments --------- Co-authored-by: Salman Paracha <salmanparacha@MacBook-Pro-342.local> Co-authored-by: MeiyuZhong <mariazhong9612@gmail.com> Co-authored-by: nehcgs <54548843+nehcgs@users.noreply.github.com>
65 lines
2.1 KiB
ReStructuredText
65 lines
2.1 KiB
ReStructuredText
Welcome to Plano!
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=================
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.. image:: /_static/img/PlanoTagline.svg
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:width: 100%
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:align: center
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`Plano <https://github.com/katanemo/plano>`_ is delivery infrastructure for agentic apps. A smart proxy server and data plane designed to help you build agents faster, and deliver them reliably to production.
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Plano pulls out the rote plumbing work (aka “hidden AI middleware”) and decouples you from brittle, ever‑changing framework abstractions. It centralizes what shouldn’t be bespoke in every codebase like agent routing and orchestration, rich agentic signals and traces for continuous improvement, guardrail filters for safety and moderation, and smart LLM routing APIs for UX and DX agility. Use any language or AI framework, and ship agents to production faster with Plano.
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Built by contributors to the widely adopted `Envoy Proxy <https://www.envoyproxy.io/>`_, Plano **helps developers** focus more on the core product logic of agents, **product teams** accelerate feedback loops for reinforcement learning, and **engineering teams** standardize policies and access controls across every agent and LLM for safer, more reliable scaling.
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.. tab-set::
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.. tab-item:: Get Started
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.. toctree::
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:caption: Get Started
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:titlesonly:
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:maxdepth: 2
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get_started/overview
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get_started/intro_to_plano
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get_started/quickstart
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.. tab-item:: Concepts
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.. toctree::
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:caption: Concepts
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:titlesonly:
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:maxdepth: 2
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concepts/listeners
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concepts/agents
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concepts/filter_chain
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concepts/llm_providers/llm_providers
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concepts/prompt_target
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concepts/signals
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.. tab-item:: Guides
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.. toctree::
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:caption: Guides
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:titlesonly:
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:maxdepth: 2
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guides/orchestration
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guides/llm_router
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guides/function_calling
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guides/observability/observability
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guides/prompt_guard
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guides/state
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.. tab-item:: Resources
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.. toctree::
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:caption: Resources
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:titlesonly:
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:maxdepth: 2
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resources/tech_overview/tech_overview
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resources/deployment
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resources/configuration_reference
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resources/llms_txt
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