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given this prompt how do I print the contents of context_str to the console. query_str = "

given this prompt how do I print the contents of context_str to the console. query_str = "What did the author do growing up?"
QA_PROMPT_TMPL = (
"We have provided context information below. \n"
"---------------------\n"
"{context_str}"
"\n---------------------\n"
"Given this information, please answer the question: {query_str}\n"
)
QA_PROMPT = QuestionAnswerPrompt(QA_PROMPT_TMPL)
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19 comments
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To print the contents of context_str to the console, you can use the format method of the QuestionAnswerPrompt instance. Here's how you can do it:

Plain Text
context_str = "The author grew up in a small town, playing sports and reading books."
query_str = "What did the author do growing up?"

QA_PROMPT_TMPL = (
    "We have provided context information below. \n"
    "---------------------\n"
    "{context_str}"
    "\n---------------------\n"
    "Given this information, please answer the question: {query_str}\n"
)
QA_PROMPT = QuestionAnswerPrompt(QA_PROMPT_TMPL)

formatted_prompt = QA_PROMPT.format(context_str=context_str, query_str=query_str)
print(formatted_prompt)


This will print the formatted prompt with the context_str and query_str values filled in. The context_str value will be displayed between the dashed lines in the output.
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@kapa.ai were does context_str come from
Let me check the knowledge base for you. One moment! :books:
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The context_str is a string containing the context information that you want to provide to the model. In the examples provided in the extracts, the context_str is manually set or retrieved from an index.

For example, in the Test Essay notebook (https://github.com/jerryjliu/gpt_index/tree/main/examples/paul_graham_essay/TestEssay.ipynb), the context_str is set manually:

Plain Text
context_str = "The author grew up in a small town, playing sports and reading books."


In another example from the SQL guide (https://gpt-index.readthedocs.io/en/latest/guides/tutorials/sql_guide.html), the context_str is set manually for a specific table:

Plain Text
city_stats_text = (
    "This table gives information regarding the population and country of a given city.\n"
    "The user will query with codewords, where 'foo' corresponds to population and 'bar'"
    "corresponds to city."
)
table_context_dict = {"city_stats": city_stats_text}


In the same SQL guide, the context_str can also be retrieved from an index using the query_index_for_context function:

Plain Text
query_str = "Which city has the highest population?"
context_str = query_index_for_context(table_schema_index, query_str)


In these examples, the context_str is either manually set or retrieved from an index, and then used in the prompt template.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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the prompt is used in a index.query call. were does context_str comeFrom and how do I print it to the console
@kapa.ai the prompt is used in a index.query call. were does context_str comeFrom and how do I print it to the console
Let me check the knowledge base for you. One moment! :books:
----------------------
The context_str is retrieved from an index using the query_index_for_context function. In the SQL guide (https://gpt-index.readthedocs.io/en/latest/guides/tutorials/sql_guide.html), the context_str is retrieved as follows:

Plain Text
query_str = "Which city has the highest population?"
context_str = SQLContextContainerBuilder.query_index_for_context(
    table_schema_index,
    query_str,
    store_context_str=True
)


To print the context_str to the console, you can simply use the print function:

Plain Text
print(context_str)


This will print the context information retrieved from the index to the console.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
----------------------
@kapa.ai GPTSimpleVectorIndex
Let me check the knowledge base for you. One moment! :books:
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GPTSimpleVectorIndex is a class in the GPT Index library that provides an in-memory vector store for semantic search. It allows you to create an index from a collection of documents and then query the index using natural language questions. The index uses embeddings for the input text chunks and returns relevant responses based on the query.

Here's an example of how to create and query a GPTSimpleVectorIndex:

Plain Text
from gpt_index import GPTSimpleVectorIndex, SimpleDirectoryReader

# Load documents, build the GPTSimpleVectorIndex
documents = SimpleDirectoryReader('../paul_graham_essay/data').load_data()
index = GPTSimpleVectorIndex.from_documents(documents)

# Query index
response = index.query("What did the author do growing up?")


You can also save the index to disk and load it back:

Plain Text
# Save index to disk
index.save_to_disk('index_simple.json')

# Load index from disk
index = GPTSimpleVectorIndex.load_from_disk('index_simple.json')


For more information and examples, refer to the following resources:

----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
----------------------
@kapa.ai does GPTSimpleVectorIndex have a context_str it sets
Let me check the knowledge base for you. One moment! :books:
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No, GPTSimpleVectorIndex does not have a context_str that it sets directly. The GPTSimpleVectorIndex is used for semantic search over a collection of documents. It stores document embeddings and retrieves relevant documents based on the query.

The context_str is used in the context of custom prompts, like the QuestionAnswerPrompt, where you provide context information to the model. The context_str is typically set manually or retrieved from an index, such as in the SQL guide (https://gpt-index.readthedocs.io/en/latest/guides/tutorials/sql_guide.html) example.

To use a context_str with GPTSimpleVectorIndex, you would need to manually set the context or retrieve it from another source, and then use it in your custom prompt.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
----------------------
@cK5150 everything all good in here? Noticed a lot of kappa questions lol
@Logan M Ha yea. I am trying to figure out logging so I can see exactly what is being passed to the llm. It's been a struggle.
Check out the llama logger (bottom of the notebook)
https://github.com/jerryjliu/llama_index/blob/main/examples/vector_indices/SimpleIndexDemo.ipynb

It records all inputs/outputs in a list
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