50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
import os
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def tools_mapping(schema, handler, name=None):
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tool_name = name or schema["function"]["name"]
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return {"name": tool_name, "schema": schema, "handler": handler}
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def tool_schemas(tools_definition):
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return [t["schema"] for t in tools_definition]
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def tool_handlers(tools_definition):
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return {t["name"]: t["handler"] for t in tools_definition}
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def build_system_prompt(tools_definition):
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lines = [
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"You are a coding agent that assists with software engineering tasks. "
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"You have access to the following tools:",
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""
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]
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for i, tool in enumerate(tools_definition, 1):
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name = tool["name"]
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desc = tool["schema"]["function"]["description"]
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lines.append(f"{i}. {name}: {desc}")
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lines.extend([
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"",
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"Use tools by returning tool calls when needed. After receiving tool "
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"results, continue your reasoning. When you have the final answer, "
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"return it as plain text without tool calls.",
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"",
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f"Your workspace directory is: {os.getcwd()}. "
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"All file operations are relative to this directory.",
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"",
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"RAG capabilities (knowledge retrieval):",
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"- list_collections → see available collections & doc counts.",
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"- create_collection → create a new collection for a new topic.",
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"- delete_collection → permanently remove a collection and its data.",
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"- inspect_collection → learn metadata fields before searching.",
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"- search_knowledge → semantic search + optional metadata filter.",
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"- store_knowledge → save docs with rich metadata for later use.",
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"",
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"You can create collections yourself! When you encounter a new topic,",
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"use create_collection first, then store_knowledge to populate it.",
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"Always inspect_collection to discover metadata keys before filtering."
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])
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return "\n".join(lines)
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