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feat: add Cloudflare AI Gateway for Azure OpenAI provider (#3)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -25,3 +25,11 @@ bridge: | |
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| gemini: | ||
| api_key: | ||
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| cloudflare_azure: | ||
| endpoint: | ||
| api_key: | ||
| resource: | ||
| deployment_id: | ||
| api_version: | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,154 @@ | ||
| // Package cfazure is used to provide the Azure OpenAI service | ||
| package cfazure | ||
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| import ( | ||
| "bytes" | ||
| "encoding/json" | ||
| "fmt" | ||
| "io" | ||
| "net/http" | ||
| "os" | ||
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| // automatically load .env file | ||
| _ "github.com/joho/godotenv/autoload" | ||
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| "github.com/yomorun/yomo/ai" | ||
| "github.com/yomorun/yomo/core/metadata" | ||
| "github.com/yomorun/yomo/core/ylog" | ||
| "github.com/yomorun/yomo/pkg/bridge/ai/provider/azopenai" | ||
| "github.com/yomorun/yomo/pkg/bridge/ai/register" | ||
| ) | ||
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| // CloudflareAzureProvider is the provider for Azure OpenAI | ||
| type CloudflareAzureProvider struct { | ||
| APIKey string | ||
| Resource string | ||
| DeploymentID string | ||
| APIVersion string | ||
| CfEndpoint string | ||
| } | ||
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| // NewProvider creates a new AzureOpenAIProvider | ||
| func NewProvider(cfEndpoint string, apiKey string, resource string, deploymentID string, apiVersion string) *CloudflareAzureProvider { | ||
| if cfEndpoint == "" || apiKey == "" || resource == "" || deploymentID == "" || apiVersion == "" { | ||
| ylog.Error("parameters are required", "cfEndpoint", cfEndpoint, "apiKey", apiKey, "resource", resource, "deploymentID", deploymentID, "apiVersion", apiVersion) | ||
| os.Exit(-1) | ||
| return nil | ||
| } | ||
| ylog.Debug("CloudflareAzureProvider", "cfEndpoint", cfEndpoint, "apiKey", apiKey, "resource", resource, "deploymentID", deploymentID, "apiVersion", apiVersion) | ||
| return &CloudflareAzureProvider{ | ||
| CfEndpoint: cfEndpoint, // https://gateway.ai.cloudflare.com/v1/111111111111111111/ai-cc-test | ||
| APIKey: apiKey, // azure api key | ||
| Resource: resource, // azure resource | ||
| DeploymentID: deploymentID, // azure deployment id | ||
| APIVersion: apiVersion, // azure api version | ||
| } | ||
| } | ||
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| // Name returns the name of the provider | ||
| func (p *CloudflareAzureProvider) Name() string { | ||
| return "cloudflare_azure" | ||
| } | ||
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| // GetChatCompletions get chat completions for ai service | ||
| func (p *CloudflareAzureProvider) GetChatCompletions(userInstruction string, md metadata.M) (*ai.InvokeResponse, error) { | ||
| tcs, err := register.ListToolCalls(md) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
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| if len(tcs) == 0 { | ||
| ylog.Error("tools is empty") | ||
| return &ai.InvokeResponse{Content: "no toolcalls"}, ai.ErrNoFunctionCall | ||
| } | ||
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| // messages | ||
| messages := []azopenai.ReqMessage{ | ||
| {Role: "system", Content: `You are a very helpful assistant. Your job is to choose the best possible action to solve the user question or task. Don't make assumptions about what values to plug into functions. Ask for clarification if a user request is ambiguous. If you don't know the answer, stop the conversation by saying "no func call".`}, | ||
| {Role: "user", Content: userInstruction}, | ||
| } | ||
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| // prepare tools | ||
| toolCalls := make([]ai.ToolCall, len(tcs)) | ||
| idx := 0 | ||
| for _, tc := range tcs { | ||
| toolCalls[idx] = tc | ||
| idx++ | ||
| } | ||
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| body := azopenai.ReqBody{Messages: messages, Tools: toolCalls} | ||
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| ylog.Debug("request", "tools", len(toolCalls), "messages", messages) | ||
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| jsonBody, err := json.Marshal(body) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
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| url := fmt.Sprintf("%s/azure-openai/%s/%s/chat/completions?api-version=%s", p.CfEndpoint, p.Resource, p.DeploymentID, p.APIVersion) | ||
| ylog.Debug("chat completions request", "url", url) | ||
| req, err := http.NewRequest(http.MethodPost, url, bytes.NewBuffer(jsonBody)) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| req.Header.Set("Content-Type", "application/json") | ||
| req.Header.Set("api-key", p.APIKey) | ||
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| client := &http.Client{} | ||
| resp, err := client.Do(req) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| defer resp.Body.Close() | ||
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| respBody, err := io.ReadAll(resp.Body) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| ylog.Debug("response", "body", respBody) | ||
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| if resp.StatusCode >= 400 { | ||
| return nil, fmt.Errorf("ai response status code is %d", resp.StatusCode) | ||
| } | ||
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| var respBodyStruct azopenai.RespBody | ||
| err = json.Unmarshal(respBody, &respBodyStruct) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
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| choice := respBodyStruct.Choices[0] | ||
| ylog.Debug(">>finish_reason", "reason", choice.FinishReason) | ||
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| calls := respBodyStruct.Choices[0].Message.ToolCalls | ||
| content := respBodyStruct.Choices[0].Message.Content | ||
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| ylog.Debug("--response calls", "calls", calls) | ||
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| result := &ai.InvokeResponse{} | ||
| if len(calls) == 0 { | ||
| result.Content = content | ||
| return result, ai.ErrNoFunctionCall | ||
| } | ||
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| // functions may be more than one | ||
| for _, call := range calls { | ||
| for tag, tc := range tcs { | ||
| if tc.Equal(&call) { | ||
| // Use toolCalls because tool_id is required in the following llm request | ||
| if result.ToolCalls == nil { | ||
| result.ToolCalls = make(map[uint32][]*ai.ToolCall) | ||
| } | ||
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| currentCall := call | ||
| result.ToolCalls[tag] = append(result.ToolCalls[tag], ¤tCall) | ||
| } | ||
| } | ||
| } | ||
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| // sfn maybe disconnected, so we need to check if there is any function call | ||
| if len(result.ToolCalls) == 0 { | ||
| return nil, ai.ErrNoFunctionCall | ||
| } | ||
| return result, nil | ||
| } |