Hermes v0.13 Search Still Broken: Fix Guide

# What Hermes v0.13 emits for a search:
# <tool_call>
# {"name": "search", "arguments": {"query": "latest python version"}}
# </tool_call>

# Common mistake: handler expects OpenAI format
def handle_tool_call(response):
    # This looks for response.tool_calls[0].function.arguments
    # Hermes doesn't use this format -> returns None
    tool_calls = response.get("tool_calls", [])  # empty!
    return None  # search silently skipped

import re, json, os, requests

SCAVIO_KEY = os.environ["SCAVIO_API_KEY"]

def parse_hermes_tool_calls(text: str) -> list:
    """Extract tool calls from Hermes ChatML format."""
    pattern = r"<tool_call>\s*(\{.*?\})\s*</tool_call>"
    matches = re.findall(pattern, text, re.DOTALL)
    calls = []
    for match in matches:
        try:
            call = json.loads(match)
            calls.append(call)
        except json.JSONDecodeError:
            continue
    return calls

def execute_search(query: str) -> str:
    """Execute search and return formatted results."""
    resp = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": SCAVIO_KEY},
        json={"query": query, "num_results": 5},
    )
    results = resp.json().get("organic_results", [])
    return "\\n".join(
        f"[{r['title']}]({r['link']}): {r['snippet']}"
        for r in results
    )

def hermes_search_handler(model_output: str) -> str:
    """Handle Hermes v0.13 search tool calls properly."""
    tool_calls = parse_hermes_tool_calls(model_output)
    results = []
    for call in tool_calls:
        if call.get("name") == "search":
            query = call.get("arguments", {}).get("query", "")
            if query:
                search_results = execute_search(query)
                results.append(search_results)
    return "\\n\\n".join(results) if results else ""

# Test
sample_output = """I need to search for this.
<tool_call>
{"name": "search", "arguments": {"query": "latest python version 2026"}}
</tool_call>"""

results = hermes_search_handler(sample_output)
print(results)

from llama_cpp import Llama

# Load Hermes v0.13
llm = Llama(model_path="./hermes-3-v0.13.gguf", n_ctx=4096)

SEARCH_TOOL_PROMPT = """You have access to the following tool:
- search: Search the web for current information. Input: {"query": "your search query"}

When you need current information, use the tool like this:
<tool_call>
{"name": "search", "arguments": {"query": "your query"}}
</tool_call>

Wait for the result before continuing your response."""

def chat_with_search(user_message: str) -> str:
    # First pass: let model decide if it needs search
    prompt = f"{SEARCH_TOOL_PROMPT}\\n\\nUser: {user_message}\\nAssistant:"
    response = llm(prompt, max_tokens=512)
    output = response["choices"][0]["text"]

    # Check for tool calls
    search_results = hermes_search_handler(output)

    if search_results:
        # Second pass: inject search results
        augmented = (f"{prompt}{output}\\n\\n"
                    f"<tool_result>{search_results}</tool_result>\\n\\n"
                    f"Now answer based on the search results:")
        final = llm(augmented, max_tokens=1024)
        return final["choices"][0]["text"]

    return output

answer = chat_with_search("What does SerpAPI cost in 2026?")
print(answer)