Vector embedding in Supabase throwing error 42702

[shildesai]

Hi Friends,
I am trying to use OpenAI embedding and Supabase as vector store in the "Adding vector RAG to the basic prompting flow" example. I am getting following error. please can someone help?

APIError: {'code': '42702', 'details': 'It could refer to either a PL/pgSQL
variable or a table column.', 'hint': None, 'message': 'column reference "id"
is ambiguous'}

I can see the data is getting added to the supabase but looks like error while returning?

here is the full error.

File "", line 71, in search_documents
File
"/Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-packa
ges/langchain_community/vectorstores/supabase.py", line 184, in
similarity_search
return self.similarity_search_by_vector(vector, k=k, filter=filter,
**kwargs)
| | | | | ->
{}
| | | | -> None
| | | -> 4
| | -> [-0.00740993395447731,
0.01829112321138382, -0.03440818190574646, -0.02291463129222393,
-0.023276975378394127, 0.029002008959...
| -> <function SupabaseVectorStore.similarity_search_by_vector
at 0x30f04bec0>
-> <langchain_community.vectorstores.supabase.SupabaseVectorStore
object at 0x32894f590>
File
"/Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-packa
ges/langchain_community/vectorstores/supabase.py", line 193, in
similarity_search_by_vector
result = self.similarity_search_by_vector_with_relevance_scores(
| -> <function
SupabaseVectorStore.similarity_search_by_vector_with_relevance_scores at
0x30f24b060>
-> <langchain_community.vectorstores.supabase.SupabaseVectorStore
object at 0x32894f590>
File
"/Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-packa
ges/langchain_community/vectorstores/supabase.py", line 239, in
similarity_search_by_vector_with_relevance_scores
res = query_builder.execute()
| -> <function SyncSingleRequestBuilder.execute at
0x30fa5bb00>
-> <postgrest._sync.request_builder.SyncRPCFilterRequestBuilder
object at 0x32c671790>
File
"/Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-packa
ges/postgrest/_sync/request_builder.py", line 127, in execute
raise APIError(r.json())
| | -> <function Response.json at 0x105ad5ee0>
| -> <Response [400 Bad Request]>
-> <class 'postgrest.exceptions.APIError'>

                         postgrest.exceptions.APIError: {'code': '42702', 'details': 'It could refer to            
                         either a PL/pgSQL variable or a table column.', 'hint': None, 'message':                  
                         'column reference "id" is ambiguous'}                                                     
                                                                                                                   
                         ╭──────────────────── Traceback (most recent call last) ─────────────────────╮            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/langflow/graph/vertex/base.py:709 in _build_results                 │            
                         │                                                                            │            
                         │   706 │   │   self, custom_component, custom_params, base_type: str, *,    │            
                         │       fallback_to_env_vars=False                                           │            
                         │   707 │   ) -> None:                                                       │            
                         │   708 │   │   try:                                                         │            
                         │ ❱ 709 │   │   │   result = await initialize.loading.get_instance_results(  │            
                         │   710 │   │   │   │   custom_component=custom_component,                   │            
                         │   711 │   │   │   │   custom_params=custom_params,                         │            
                         │   712 │   │   │   │   vertex=self,                                         │            
                         │                                                                            │            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/langflow/interface/initialize/loading.py:68 in get_instance_results │            
                         │                                                                            │            
                         │    65 │   │   if base_type == "custom_components":                         │            
                         │    66 │   │   │   return await build_custom_component(params=custom_params │            
                         │       custom_component=custom_component)                                   │            
                         │    67 │   │   if base_type == "component":                                 │            
                         │ ❱  68 │   │   │   return await build_component(params=custom_params,       │            
                         │       custom_component=custom_component)                                   │            
                         │    69 │   │   msg = f"Base type {base_type} not found."                    │            
                         │    70 │   │   raise ValueError(msg)                                        │            
                         │    71                                                                      │            
                         │                                                                            │            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/langflow/interface/initialize/loading.py:145 in build_component     │            
                         │                                                                            │            
                         │   142 ):                                                                   │            
                         │   143 │   # Now set the params as attributes of the custom_component       │            
                         │   144 │   custom_component.set_attributes(params)                          │            
                         │ ❱ 145 │   build_results, artifacts = await custom_component.build_results( │            
                         │   146 │                                                                    │            
                         │   147 │   return custom_component, build_results, artifacts                │            
                         │   148                                                                      │            
                         │                                                                            │            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/langflow/custom/custom_component/component.py:837 in build_results  │            
                         │                                                                            │            
                         │    834 │   │   │   session_id = None                                       │            
                         │    835 │   │   try:                                                        │            
                         │    836 │   │   │   if self._tracing_service:                               │            
                         │ ❱  837 │   │   │   │   return await self._build_with_tracing()             │            
                         │    838 │   │   │   return await self._build_without_tracing()              │            
                         │    839 │   │   except StreamingError as e:                                 │            
                         │    840 │   │   │   self.send_error(                                        │            
                         │                                                                            │            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/langflow/custom/custom_component/component.py:819 in                │            
                         │ _build_with_tracing                                                        │            
                         │                                                                            │            
                         │    816 │   │   inputs = self.get_trace_as_inputs()                         │            
                         │    817 │   │   metadata = self.get_trace_as_metadata()                     │            
                         │    818 │   │   async with self._tracing_service.trace_context(self, self.t │            
                         │        metadata):                                                          │            
                         │ ❱  819 │   │   │   _results, _artifacts = await self._build_results()      │            
                         │    820 │   │   │   self._tracing_service.set_outputs(self.trace_name, _res │            
                         │    821 │   │                                                               │            
                         │    822 │   │   return _results, _artifacts                                 │            
                         │                                                                            │            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/langflow/custom/custom_component/component.py:885 in _build_results │            
                         │                                                                            │            
                         │    882 │   │   │   │   │   │   if inspect.iscoroutinefunction(method):     │            
                         │    883 │   │   │   │   │   │   │   result = await method()                 │            
                         │    884 │   │   │   │   │   │   else:                                       │            
                         │ ❱  885 │   │   │   │   │   │   │   result = await asyncio.to_thread(method │            
                         │    886 │   │   │   │   │   │   if (                                        │            
                         │    887 │   │   │   │   │   │   │   self._vertex is not None                │            
                         │    888 │   │   │   │   │   │   │   and isinstance(result, Message)         │            
                         │                                                                            │            
                         │ /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/asyncio/ │            
                         │ threads.py:25 in to_thread                                                 │            
                         │                                                                            │            
                         │   22 │   loop = events.get_running_loop()                                  │            
                         │   23 │   ctx = contextvars.copy_context()                                  │            
                         │   24 │   func_call = functools.partial(ctx.run, func, *args, **kwargs)     │            
                         │ ❱ 25 │   return await loop.run_in_executor(None, func_call)                │            
                         │   26                                                                       │            
                         │                                                                            │            
                         │ /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/concurre │            
                         │ nt/futures/thread.py:58 in run                                             │            
                         │                                                                            │            
                         │    55 │   │   │   return                                                   │            
                         │    56 │   │                                                                │            
                         │    57 │   │   try:                                                         │            
                         │ ❱  58 │   │   │   result = self.fn(*self.args, **self.kwargs)              │            
                         │    59 │   │   except BaseException as exc:                                 │            
                         │    60 │   │   │   self.future.set_exception(exc)                           │            
                         │    61 │   │   │   # Break a reference cycle with the exception 'exc'       │            
                         │ in search_documents:71                                                     │            
                         │                                                                            │            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/langchain_community/vectorstores/supabase.py:184 in                 │            
                         │ similarity_search                                                          │            
                         │                                                                            │            
                         │   181 │   │   **kwargs: Any,                                               │            
                         │   182 │   ) -> List[Document]:                                             │            
                         │   183 │   │   vector = self._embedding.embed_query(query)                  │            
                         │ ❱ 184 │   │   return self.similarity_search_by_vector(vector, k=k, filter= │            
                         │   185 │                                                                    │            
                         │   186 │   def similarity_search_by_vector(                                 │            
                         │   187 │   │   self,                                                        │            
                         │                                                                            │            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/langchain_community/vectorstores/supabase.py:193 in                 │            
                         │ similarity_search_by_vector                                                │            
                         │                                                                            │            
                         │   190 │   │   filter: Optional[Dict[str, Any]] = None,                     │            
                         │   191 │   │   **kwargs: Any,                                               │            
                         │   192 │   ) -> List[Document]:                                             │            
                         │ ❱ 193 │   │   result = self.similarity_search_by_vector_with_relevance_sco │            
                         │   194 │   │   │   embedding, k=k, filter=filter, **kwargs                  │            
                         │   195 │   │   )                                                            │            
                         │   196                                                                      │            
                         │                                                                            │            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/langchain_community/vectorstores/supabase.py:239 in                 │            
                         │ similarity_search_by_vector_with_relevance_scores                          │            
                         │                                                                            │            
                         │   236 │   │                                                                │            
                         │   237 │   │   query_builder.params = query_builder.params.set("limit", k)  │            
                         │   238 │   │                                                                │            
                         │ ❱ 239 │   │   res = query_builder.execute()                                │            
                         │   240 │   │                                                                │            
                         │   241 │   │   match_result = [                                             │            
                         │   242 │   │   │   (                                                        │            
                         │                                                                            │            
                         │ /Users/shildesai/Documents/startapps/LangFlow/.venv/lib/python3.11/site-pa │            
                         │ ckages/postgrest/_sync/request_builder.py:127 in execute                   │            
                         │                                                                            │            
                         │   124 │   │   │   ):  # Response.ok from JS                                │            
                         │       (https://developer.mozilla.org/en-US/docs/Web/API/Response/ok)       │            
                         │   125 │   │   │   │   return SingleAPIResponse[_ReturnT].from_http_request │            
                         │   126 │   │   │   else:                                                    │            
                         │ ❱ 127 │   │   │   │   raise APIError(r.json())                             │            
                         │   128 │   │   except ValidationError as e:                                 │            
                         │   129 │   │   │   raise APIError(r.json()) from e                          │            
                         │   130 │   │   except JSONDecodeError:                                      │            
                         ╰────────────────────────────────────────────────────────────────────────────╯            
                         APIError: {'code': '42702', 'details': 'It could refer to either a PL/pgSQL               
                         variable or a table column.', 'hint': None, 'message': 'column reference "id"             
                         is ambiguous'}

[dosubot[bot]]

Hey @shildesai! 👋 I'm here to help you with any bugs, questions, or contributions you have. Let's squash those bugs together!

The error you're encountering, "column reference 'id' is ambiguous," typically occurs when there are multiple tables involved in a query, and the column name "id" exists in more than one of those tables. To resolve this ambiguity, you need to specify which table the "id" column belongs to by using a table alias or the full table name in your SQL query.

Here's a general approach to fix this issue:

1. Identify the Tables: Determine which tables are involved in the query and which ones have an "id" column.

2. Use Table Aliases: Assign aliases to your tables in the query and use these aliases to specify the "id" column. For example, if you have tables table1 and table2, you can write:

   SELECT table1.id, table2.id FROM table1 JOIN table2 ON table1.id = table2.foreign_id

3. Modify the Query in Code: If the query is constructed in your code, ensure that the table names or aliases are correctly specified when referencing the "id" column.

If you're using a query builder or ORM, check its documentation for how to specify table aliases or fully qualify column names to avoid such ambiguities. This should help in resolving the error you're facing with the Supabase vector store integration.

To continue talking to Dosu, mention @dosu.

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