How can I enable both file search and custom function calling in OpenAI Assistant API?

Below is an explanation along with some workarounds that you might consider:

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Why This Happens

In the current beta, when you include custom functions (tools with "type": "function"), the assistant’s decision process leans toward invoking those functions instead of executing the built‐in file search tool—even when the user query matches content in your PDF. Essentially, once function calling is available, the assistant prioritizes user actions (like sending emails, generating reports, etc.) over performing file retrieval with file search.

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Workarounds and Recommendations

1. Custom Function that Wraps File Search:
   One approach is to implement a custom function that internally calls the file search API. This way, when the assistant decides to call a function, you can let that particular function handle the file retrieval. For example, you could have a function called “retrieve_pdf_content” that leverages the file search endpoint underneath.

2. Explicit Prompt Engineering:
   You can adjust the assistant’s instructions (or system messages) to bias its decision. For instance:

   • Specify that for queries related to financial statements, the assistant should attempt a file search first.
   • Include prompt cues that separate the intentions (e.g., “if the user asks about document details, use file search; otherwise, if the query is about sending an email or generating a report, call the custom function”).

3. Separate Runs or Tool Configurations:
   Consider separating the functionalities into different runs or even threads. This means that if you detect that the query is best answered by document lookup, you run that query with only file search enabled. If the query demands a custom action, then you enable function calling. While this may add orchestration overhead on your side, it avoids the conflict within a single run.

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Example of a Custom “Search” Function

Below is a simplified Python snippet that outlines how you might wrap file search inside a custom function:

PYTHONCopied
def retrieve_pdf_content(query: str) -> str:
    # Internally call the file search tool, for instance by invoking
    # the stream run or using the file search API directly.
    results = file_search_api_call(query)  # Your implementation of the file search call
    if results:
        return format_search_results(results)
    return "No relevant content found."

# In your tool configuration, include it like:
tools = [
    {"type": "function", "name": "retrieve_pdf_content", "description": "Fetches relevant PDF content based on the query."},
    # ... your other custom functions ...
]

In your assistant’s instructions, you can then instruct:

“When the user query seems to require information from our PDF content, please call the function retrieve_pdf_content.”

This bridges the gap between the two features by making file search an explicit function call.

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Final Thoughts

Having both the native file search and custom function calling active simultaneously isn’t fully seamless in the current version. Adjusting how the assistant is prompted—as well as consolidating file search within a custom function—has proven to be a practical workaround until further updates to the Assistant API offer improved integration.

If you decide to implement one of these strategies, continue to monitor any API or beta announcements from OpenAI, as improvements in tool prioritization and decision logic might be available in future releases.

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This setup should help you get closer to achieving both behaviors in your chatbot.