I am newbie to langsmith platform . Just wrote a simple code with different api keys set up in the environment. But Iam not able to track the same when I log in into my account . I have generated and tried 3 different API keys for langsmith and open AI for the eventhough Iam able to generate output at local.Please suggest.
Below is the code

I am new to Langchain and I try to currently wrap my head around a tutorial to build a LLM Agent to interact with a SQL data base (https://python.langchain.com/v0.2/docs/tutorials/sql_qa/).
I am running into issues early on. When I run the code, the create_sql_query_chain always produces a different output than expected. In the provided link, the following code snippet is supposed to result a variable ‘response’ containing a pure SQL query which is runnable using for example db.run(response)

I am creating Python code to help fine-tune a Llama-3.1-8b-Instruct model locally. I have written code to import documents, to chunk them, and then to prompt the local model to generate the questions and answer pairs. Is anyone familiar with packages that can do all of these steps? I see that Langchain will perform the chunking and create a token dataset, but it doesn’t appear to perform unsupervised prompts. A package would be useful since there are a lot of values to tune in a slow performing environment (e.g. chunk size, chunk overlap, system propmt, etc.).

I had used this code, answers = retriever.retrieve(“What’s arctic botany”, k=2).
But I get this error.
Error: ‘ColbertRetriever’ object has no attribute ‘retrieve’.

I am having trouble importing Ragas evaluation chain in colab notebook

I am having trouble importing Ragas evaluation chain in colab notebook

I want to generate text using a model along with prompt and other parameters. How do I use context-data / supporting data present in a CSV file so that the LLM can generate text content based on the contextual inputs present in that CSV file.

I’m trying to read a git repo and parse the files from that repo. For that I’m reading files with the following code

I am trying to replicate the Self Query search example as below:

“I have a PDF file as my Langchain external database, which contains text content and corresponding URLs. For example,the text looks like this:
‘To solve the problem,
step 1 You can first click the buttom on the right corner,
step 2 then open the link: https://xxxxxx, to fill the form,
step 3 then send the form to us
‘