First build

2026-03-14 15:44:48 +08:00
parent 630d57a5cb
commit fb9c0906b5
145 changed files with 25148 additions and 0 deletions
@@ -0,0 +1,96 @@
+import json
+import os
+from typing import List, Optional, Dict, Any
+from fastapi import APIRouter, HTTPException, Body
+from pydantic import BaseModel, Field
+
+router = APIRouter()
+
+DATA_FILE = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(__file__))), "data", "llm_config.json")
+
+class LLMConfig(BaseModel):
+    id: str = Field(..., description="Unique identifier for the LLM configuration")
+    provider: str = Field(..., description="Provider name (e.g., openai, azure, anthropic)")
+    model: str = Field(..., description="Model name (e.g., gpt-4, claude-3-opus)")
+    api_key: Optional[str] = Field(None, description="API Key for the provider")
+    api_base: Optional[str] = Field(None, description="Base URL for the API")
+    extra_headers: Optional[Dict[str, str]] = Field(None, description="Extra headers for the request")
+    is_active: bool = Field(True, description="Whether this configuration is active")
+
+class LLMConfigCreate(BaseModel):
+    id: str
+    provider: str
+    model: str
+    api_key: Optional[str] = None
+    api_base: Optional[str] = None
+    extra_headers: Optional[Dict[str, str]] = None
+    is_active: bool = True
+
+class LLMConfigUpdate(BaseModel):
+    provider: Optional[str] = None
+    model: Optional[str] = None
+    api_key: Optional[str] = None
+    api_base: Optional[str] = None
+    extra_headers: Optional[Dict[str, str]] = None
+    is_active: Optional[bool] = None
+
+def _load_data() -> List[Dict[str, Any]]:
+    if not os.path.exists(DATA_FILE):
+        return []
+    try:
+        with open(DATA_FILE, "r") as f:
+            return json.load(f)
+    except json.JSONDecodeError:
+        return []
+
+def _save_data(data: List[Dict[str, Any]]):
+    os.makedirs(os.path.dirname(DATA_FILE), exist_ok=True)
+    with open(DATA_FILE, "w") as f:
+        json.dump(data, f, indent=2)
+
+@router.get("/llm", response_model=List[LLMConfig])
+def list_llm_configs():
+    data = _load_data()
+    return [LLMConfig(**item) for item in data]
+
+@router.get("/llm/{config_id}", response_model=LLMConfig)
+def get_llm_config(config_id: str):
+    data = _load_data()
+    for item in data:
+        if item["id"] == config_id:
+            return LLMConfig(**item)
+    raise HTTPException(status_code=404, detail="LLM configuration not found")
+
+@router.post("/llm", response_model=LLMConfig)
+def create_llm_config(config: LLMConfigCreate):
+    data = _load_data()
+    if any(item["id"] == config.id for item in data):
+        raise HTTPException(status_code=400, detail="LLM configuration with this ID already exists")
+    
+    new_config = config.dict()
+    data.append(new_config)
+    _save_data(data)
+    return LLMConfig(**new_config)
+
+@router.put("/llm/{config_id}", response_model=LLMConfig)
+def update_llm_config(config_id: str, config: LLMConfigUpdate):
+    data = _load_data()
+    for i, item in enumerate(data):
+        if item["id"] == config_id:
+            updated_item = item.copy()
+            update_data = config.dict(exclude_unset=True)
+            updated_item.update(update_data)
+            data[i] = updated_item
+            _save_data(data)
+            return LLMConfig(**updated_item)
+    raise HTTPException(status_code=404, detail="LLM configuration not found")
+
+@router.delete("/llm/{config_id}")
+def delete_llm_config(config_id: str):
+    data = _load_data()
+    initial_len = len(data)
+    data = [item for item in data if item["id"] != config_id]
+    if len(data) == initial_len:
+        raise HTTPException(status_code=404, detail="LLM configuration not found")
+    _save_data(data)
+    return {"message": "LLM configuration deleted successfully"}
@@ -0,0 +1,93 @@
+import json
+import os
+from typing import List, Optional, Dict, Any
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel, Field
+
+router = APIRouter()
+
+DATA_FILE = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(__file__))), "data", "skills.json")
+
+class Skill(BaseModel):
+    id: str = Field(..., description="Unique identifier for the skill")
+    name: str = Field(..., description="Name of the skill")
+    description: Optional[str] = Field(None, description="Description of what the skill does")
+    content: str = Field(..., description="The content/prompt/logic of the skill")
+    type: str = Field("python", description="Type of the skill (python, sql, api)")
+
+class SkillCreate(BaseModel):
+    id: str
+    name: str
+    description: Optional[str] = None
+    content: str
+    type: str = "python"
+
+class SkillUpdate(BaseModel):
+    name: Optional[str] = None
+    description: Optional[str] = None
+    content: Optional[str] = None
+    type: Optional[str] = None
+
+def _load_data() -> List[Dict[str, Any]]:
+    if not os.path.exists(DATA_FILE):
+        return []
+    try:
+        with open(DATA_FILE, "r") as f:
+            return json.load(f)
+    except json.JSONDecodeError:
+        return []
+
+def _save_data(data: List[Dict[str, Any]]):
+    os.makedirs(os.path.dirname(DATA_FILE), exist_ok=True)
+    with open(DATA_FILE, "w") as f:
+        json.dump(data, f, indent=2)
+
+def load_skills() -> List[Dict[str, Any]]:
+    return _load_data()
+
+@router.get("/skills", response_model=List[Skill])
+def list_skills():
+    data = load_skills()
+    return [Skill(**item) for item in data]
+
+@router.get("/skills/{skill_id}", response_model=Skill)
+def get_skill(skill_id: str):
+    data = _load_data()
+    for item in data:
+        if item["id"] == skill_id:
+            return Skill(**item)
+    raise HTTPException(status_code=404, detail="Skill not found")
+
+@router.post("/skills", response_model=Skill)
+def create_skill(skill: SkillCreate):
+    data = _load_data()
+    if any(item["id"] == skill.id for item in data):
+        raise HTTPException(status_code=400, detail="Skill with this ID already exists")
+    
+    new_skill = skill.dict()
+    data.append(new_skill)
+    _save_data(data)
+    return Skill(**new_skill)
+
+@router.put("/skills/{skill_id}", response_model=Skill)
+def update_skill(skill_id: str, skill: SkillUpdate):
+    data = _load_data()
+    for i, item in enumerate(data):
+        if item["id"] == skill_id:
+            updated_item = item.copy()
+            update_data = skill.dict(exclude_unset=True)
+            updated_item.update(update_data)
+            data[i] = updated_item
+            _save_data(data)
+            return Skill(**updated_item)
+    raise HTTPException(status_code=404, detail="Skill not found")
+
+@router.delete("/skills/{skill_id}")
+def delete_skill(skill_id: str):
+    data = _load_data()
+    initial_len = len(data)
+    data = [item for item in data if item["id"] != skill_id]
+    if len(data) == initial_len:
+        raise HTTPException(status_code=404, detail="Skill not found")
+    _save_data(data)
+    return {"message": "Skill deleted successfully"}
@@ -0,0 +1,53 @@
+from fastapi import APIRouter, UploadFile, File, HTTPException, BackgroundTasks
+from app.connectors.minio import minio_connector
+import pandas as pd
+import duckdb
+import io
+import uuid
+
+router = APIRouter()
+
+@router.post("/upload/csv")
+async def upload_csv(file: UploadFile = File(...), background_tasks: BackgroundTasks = None):
+    if not file.filename.endswith('.csv'):
+        raise HTTPException(status_code=400, detail="Invalid file type. Only CSV allowed.")
+
+    try:
+        content = await file.read()
+        file_size = len(content)
+        file_obj = io.BytesIO(content)
+        
+        # Generate a unique filename
+        unique_filename = f"{uuid.uuid4()}-{file.filename}"
+        
+        # Upload to MinIO
+        minio_url = minio_connector.upload_file(unique_filename, file_obj, file_size, content_type="text/csv")
+        
+        # Reset file pointer for analysis
+        file_obj.seek(0)
+        
+        # Load into DuckDB (in-memory) for quick analysis
+        try:
+            df = pd.read_csv(file_obj)
+            duckdb_conn = duckdb.connect(database=':memory:')
+            duckdb_conn.register('uploaded_csv', df)
+            summary = duckdb_conn.execute("DESCRIBE uploaded_csv").fetchall()
+            row_count = len(df)
+            columns = list(df.columns)
+            
+            return {
+                "filename": unique_filename,
+                "url": minio_url,
+                "rows": row_count,
+                "columns": columns,
+                "summary": str(summary)
+            }
+        except Exception as e:
+             return {
+                "filename": unique_filename,
+                "url": minio_url,
+                "analysis_error": str(e)
+            }
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))