0c8bef82f4
## Agents Added - Alateya: R&D, biotech, innovations - Clan (Spirit): Community spirit agent - Eonarch: Consciousness evolution agent ## Changes - docker-compose.node1.yml: Added tokens for all 3 new agents - gateway-bot/http_api.py: Added configs and webhook endpoints - gateway-bot/clan_prompt.txt: New prompt file - gateway-bot/eonarch_prompt.txt: New prompt file ## Fixes - Fixed ROUTER_URL from :9102 to :8000 (internal container port) - All 9 Telegram agents now working ## Documentation - Created PROJECT-MASTER-INDEX.md - single entry point - Added various status documents and scripts Tokens configured: - Helion, NUTRA, Agromatrix (existing) - Alateya, Clan, Eonarch (new) - Druid, GreenFood, DAARWIZZ (configured)
73 lines
2.7 KiB
Python
73 lines
2.7 KiB
Python
"""
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Pydantic models for RAG Service API
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"""
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from typing import Optional, List, Dict, Any
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from pydantic import BaseModel, Field
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class IngestRequest(BaseModel):
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"""Request for document ingestion"""
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dao_id: str = Field(..., description="DAO identifier")
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doc_id: str = Field(..., description="Document identifier")
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parsed_json: Dict[str, Any] = Field(..., description="ParsedDocument JSON from PARSER service")
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user_id: Optional[str] = Field(None, description="User identifier")
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class IngestResponse(BaseModel):
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"""Response from document ingestion"""
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status: str = Field(..., description="Status: success or error")
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doc_count: int = Field(..., description="Number of documents ingested")
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dao_id: str = Field(..., description="DAO identifier")
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doc_id: str = Field(..., description="Document identifier")
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message: Optional[str] = Field(None, description="Error message if status=error")
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class QueryRequest(BaseModel):
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"""Request for RAG query"""
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dao_id: str = Field(..., description="DAO identifier")
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question: str = Field(..., description="User question")
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top_k: Optional[int] = Field(None, description="Number of documents to retrieve")
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user_id: Optional[str] = Field(None, description="User identifier")
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class Citation(BaseModel):
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"""Citation from retrieved document"""
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doc_id: str = Field(..., description="Document identifier")
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page: int = Field(..., description="Page number")
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section: Optional[str] = Field(None, description="Section name")
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excerpt: str = Field(..., description="Document excerpt")
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class QueryResponse(BaseModel):
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"""Response from RAG query"""
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answer: str = Field(..., description="Generated answer")
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citations: List[Citation] = Field(..., description="List of citations")
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documents: List[Dict[str, Any]] = Field(..., description="Retrieved documents (for debugging)")
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class UpsertChunk(BaseModel):
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content: str = Field(..., description="Chunk content")
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meta: Dict[str, Any] = Field(default_factory=dict, description="Chunk metadata")
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class UpsertRequest(BaseModel):
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chunks: List[UpsertChunk] = Field(..., description="Chunks to index")
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class UpsertResponse(BaseModel):
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status: str = Field(..., description="Status: success or error")
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indexed_count: int = Field(..., description="Number of chunks indexed")
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message: Optional[str] = Field(None, description="Optional message")
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class DeleteByFingerprintRequest(BaseModel):
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fingerprint: str = Field(..., description="Index fingerprint to delete")
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class DeleteResponse(BaseModel):
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status: str = Field(..., description="Status: success or error")
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deleted_count: int = Field(..., description="Number of chunks deleted")
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message: Optional[str] = Field(None, description="Optional message")
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