gddlmZddlmZddlmZddlmZddl Z ddl Z ddl Z ddl Z ddl mZmZmZddlmZddlmZdd lmZee j.d d ZeeZe j4d eGddZdZeeeedZddZej>ddZ ej>ddZ!ej>ddZ"y)) annotations) dataclass) load_dotenv) AsyncOpenAIN)Agent ModelRetry RunContext) OpenAIModel)Client)List LLM_MODELz gpt-4o-minizif-token-present)send_to_logfirec"eZdZUded<ded<y)PydanticAIDepsr supabaser openai_clientN)__name__ __module__ __qualname____annotations__$/var/www/openai/pydantic_ai_agent.pyrrsrra* You are an expert at Pydantic AI - a Python AI agent framework that you have access to all the documentation to, including examples, an API reference, and other resources to help you build Pydantic AI agents. Your only job is to assist with this and you don't answer other questions besides describing what you are able to do. Don't ask the user before taking an action, just do it. Always make sure you look at the documentation with the provided tools before answering the user's question unless you have already. When you first look at the documentation, always start with RAG. Then also always check the list of available documentation pages and retrieve the content of page(s) if it'll help. Always let the user know when you didn't find the answer in the documentation or the right URL - be honest. ) system_prompt deps_typeretriescK |jjd|d{}|jdjS7#t$r}t d|dgdzcYd}~Sd}~wwxYww)z!Get embedding vector from OpenAI.ztext-embedding-3-small)modelinputNrzError getting embedding: i) embeddingscreatedata embedding Exceptionprint)textrresponsees r get_embeddingr*1sz&1188*9  }}Q)))   )!-.sTzsDA. AAAA.A A+ A& A+!A.&A++A.cK t||jjd{}|jjj d|dddidj }|j syg}|j D]"}d|d d |d d }|j|$d j|S7#t$r&}td|dt|cYd}~Sd}~wwxYww)a? Retrieve relevant documentation chunks based on the query with RAG. Args: ctx: The context including the Supabase client and OpenAI client user_query: The user's question or query Returns: A formatted string containing the top 5 most relevant documentation chunks Nmatch_site_pagessourcepydantic_ai_docs)query_embedding match_countfilterz No relevant documentation found.z # title content z --- z Error retrieving documentation: ) r*depsrrrpcexecuter#appendjoinr%r&str)ctx user_queryr0resultformatted_chunksdoc chunk_textr)s rretrieve_relevant_documentationrC=s  ; -j#((:P:P QQ""&& #2 #%78   ') {{5;;Cw<.YJ  # #J / !!"2335R8 ; 0451#a&::;sRC+#B9B7A B92C+3AB96C+7B99 C(C#C(C+#C((C+cfK |jjjdjdj ddj }|j sgSttd|j D}|S#t$r}td|gcYd}~Sd}~wwxYww)z Retrieve a list of all available Pydantic AI documentation pages. Returns: List[str]: List of unique URLs for all documentation pages site_pagesurlmetadata->>sourcer/c3&K|] }|d yw)rFNr).0rAs r z+list_documentation_pages..~s< #e* sz&Error retrieving documentation pages: N) r7rfrom_selecteqr9r#sortedsetr%r&)r=r?urlsr)s rlist_documentation_pagesrQks""((6 VE] R#%7 8 WY  {{Ic< <<=  6qc:; sAB1AB #B1$&B B1 B.B)#B.$B1)B..B1c6K |jjjdjdj d|j ddj dj }|jsd|S|jdd jd d}d |d g}|jD]}|j|d dj|S#t$r&}td|dt|cYd}~Sd}~wwxYww)a3 Retrieve the full content of a specific documentation page by combining all its chunks. Args: ctx: The context including the Supabase client url: The URL of the page to retrieve Returns: str: The complete page content with all chunks combined in order rEztitle, content, chunk_numberrFrGr/ chunk_numberzNo content found for URL: rr3z - z# r6r5r4zError retrieving page content: N)r7rrKrLrMorderr9r#splitr:r;r%r&r<)r=rFr? page_titleformatted_contentchunkr)s rget_page_contentrYs:""((6 V2 3 Rs^ R#%7 8 U> " WY {{/u5 5[[^G,2259!< !*R01[[E  $ $U9%5 6!{{,-- : /s340Q99:sBDBC'DA C'&D' D0D D DDD)r'r<rrreturnz List[float])r=RunContext[PydanticAIDeps]r>r<rZr<)r=r[rZz List[str])r=r[rFr<rZr<)# __future__r _annotations dataclassesrdotenvrlitellmrlogfireasynciohttpxos pydantic_airrr pydantic_ai.models.openair rr typingr getenvllmr configurerrpydantic_ai_agentr*toolrCrQrYrrrrms2! 551 bii ]+C"45       +;+;Z2$:$:r