micro
diff --git a/‎README.md‎
Lines changed: 33 additions & 0 deletions b/‎README.md‎
Lines changed: 33 additions & 0 deletions
diff --git a/‎ai/README.md‎
Lines changed: 56 additions & 0 deletions b/‎ai/README.md‎
Lines changed: 56 additions & 0 deletions
diff --git a/‎ai/gemini/gemini.go‎
Lines changed: 226 additions & 0 deletions b/‎ai/gemini/gemini.go‎
Lines changed: 226 additions & 0 deletions
@@ -149,6 +149,34 @@ micro run
 
 Use `micro mcp serve` for local AI tools like Claude Code, or connect any MCP-compatible agent to the HTTP endpoint.
 
+### micro chat
+
+For an interactive terminal session that lets you talk to your services through an LLM:
+
+```bash
+ANTHROPIC_API_KEY=sk-ant-... micro chat --provider anthropic
+> list all users
+> create an order for product 42
+```
+
+`micro chat` discovers every service in the registry, exposes each endpoint as a tool, and lets the model orchestrate calls. The same building blocks (`ai/tools`) work from your own services:
+
+```go
+import "go-micro.dev/v5/ai/tools"
+
+set := tools.New(service.Registry())
+discovered, _ := set.Discover()
+
+m := ai.New("anthropic",
+    ai.WithAPIKey(key),
+    ai.WithToolHandler(set.Handler(service.Client())),
+)
+resp, _ := m.Generate(ctx, &ai.Request{
+    Prompt: userInput,
+    Tools:  discovered,
+})
+```
+
 See the [MCP guide](https://go-micro.dev/docs/mcp.html) for authentication, scopes, and advanced usage.
 
 ## Multi-Service Binaries
@@ -247,6 +275,7 @@ Every service gets `Client()`, `Server()`, and `Model()` — call services, hand
 
 Check out [/examples](examples/) for runnable code:
 - [hello-world](examples/hello-world/) - Basic RPC service
+- [grpc-interop](examples/grpc-interop/) - Call go-micro from any gRPC client
 - [web-service](examples/web-service/) - HTTP REST API
 - [multi-service](examples/multi-service/) - Multiple services in one binary
 - [mcp](examples/mcp/) - MCP integration with AI agents
@@ -396,7 +425,11 @@ Go Micro’s `ai` package gives every provider the same interface: `Init`, `Gene
 | Provider | Import | Default Model |
 |----------|--------|---------------|
 | **Anthropic** | `go-micro.dev/v5/ai/anthropic` | `claude-sonnet-4-20250514` |
+| **Google Gemini** | `go-micro.dev/v5/ai/gemini` | `gemini-2.5-flash` |
+| **Groq** | `go-micro.dev/v5/ai/groq` | `llama-3.3-70b-versatile` |
+| **Mistral** | `go-micro.dev/v5/ai/mistral` | `mistral-large-latest` |
 | **OpenAI** | `go-micro.dev/v5/ai/openai` | `gpt-4o` |
+| **Together AI** | `go-micro.dev/v5/ai/together` | `Llama-3.3-70B-Instruct-Turbo` |
 | **Atlas Cloud** | `go-micro.dev/v5/ai/atlascloud` | `llama-3.3-70b` |
 
 Any provider that exposes an OpenAI-compatible API can also be used directly:
 
@@ -152,6 +152,62 @@ m := ai.New("openai",
 Default model: `gpt-4o`
 Default base URL: `https://api.openai.com`
 
+### Google Gemini
+
+```go
+m := ai.New("gemini",
+    ai.WithAPIKey("your-key"),
+    ai.WithModel("gemini-2.5-flash"), // default
+)
+```
+
+Default model: `gemini-2.5-flash`
+Default base URL: `https://generativelanguage.googleapis.com`
+
+Google Gemini uses its own API format with `system_instruction`, `contents` (not `messages`), and `functionDeclarations` for tool calling. The provider handles the translation automatically.
+
+### Groq
+
+```go
+m := ai.New("groq",
+    ai.WithAPIKey("your-key"),
+    ai.WithModel("llama-3.3-70b-versatile"), // default
+)
+```
+
+Default model: `llama-3.3-70b-versatile`
+Default base URL: `https://api.groq.com/openai`
+
+Groq provides ultra-fast inference for open-weight models via an OpenAI-compatible endpoint.
+
+### Mistral
+
+```go
+m := ai.New("mistral",
+    ai.WithAPIKey("your-key"),
+    ai.WithModel("mistral-large-latest"), // default
+)
+```
+
+Default model: `mistral-large-latest`
+Default base URL: `https://api.mistral.ai`
+
+Mistral AI is a European AI company offering high-performance models via an OpenAI-compatible endpoint.
+
+### Together AI
+
+```go
+m := ai.New("together",
+    ai.WithAPIKey("your-key"),
+    ai.WithModel("meta-llama/Llama-3.3-70B-Instruct-Turbo"), // default
+)
+```
+
+Default model: `meta-llama/Llama-3.3-70B-Instruct-Turbo`
+Default base URL: `https://api.together.xyz`
+
+Together AI provides fast inference for open-weight models via an OpenAI-compatible endpoint.
+
 ### Atlas Cloud
 
 ```go
 
@@ -0,0 +1,226 @@
+// Package gemini implements the Google Gemini model provider.
+//
+// Usage:
+//
+//	import _ "go-micro.dev/v5/ai/gemini"
+//
+//	m := ai.New("gemini",
+//	    ai.WithAPIKey("your-api-key"),
+//	)
+package gemini
+
+import (
+	"bytes"
+	"context"
+	"encoding/json"
+	"fmt"
+	"io"
+	"net/http"
+	"strings"
+
+	"go-micro.dev/v5/ai"
+)
+
+func init() {
+	ai.Register("gemini", func(opts ...ai.Option) ai.Model {
+		return NewProvider(opts...)
+	})
+}
+
+// Provider implements the ai.Model interface for Google Gemini.
+type Provider struct {
+	opts ai.Options
+}
+
+// NewProvider creates a new Gemini provider.
+func NewProvider(opts ...ai.Option) *Provider {
+	options := ai.NewOptions(opts...)
+
+	if options.Model == "" {
+		options.Model = "gemini-2.5-flash"
+	}
+	if options.BaseURL == "" {
+		options.BaseURL = "https://generativelanguage.googleapis.com"
+	}
+
+	return &Provider{opts: options}
+}
+
+func (p *Provider) Init(opts ...ai.Option) error {
+	for _, o := range opts {
+		o(&p.opts)
+	}
+	return nil
+}
+
+func (p *Provider) Options() ai.Options { return p.opts }
+func (p *Provider) String() string      { return "gemini" }
+
+func (p *Provider) Generate(ctx context.Context, req *ai.Request, opts ...ai.GenerateOption) (*ai.Response, error) {
+	var tools []map[string]any
+	for _, t := range req.Tools {
+		tools = append(tools, map[string]any{
+			"name":        t.Name,
+			"description": t.Description,
+			"parameters": map[string]any{
+				"type":       "object",
+				"properties": t.Properties,
+			},
+		})
+	}
+
+	contents := []map[string]any{
+		{"role": "user", "parts": []map[string]any{{"text": req.Prompt}}},
+	}
+
+	apiReq := map[string]any{
+		"contents": contents,
+	}
+
+	if req.SystemPrompt != "" {
+		apiReq["system_instruction"] = map[string]any{
+			"parts": []map[string]any{{"text": req.SystemPrompt}},
+		}
+	}
+
+	if len(tools) > 0 {
+		apiReq["tools"] = []map[string]any{
+			{"functionDeclarations": tools},
+		}
+	}
+
+	resp, rawParts, err := p.callAPI(ctx, apiReq)
+	if err != nil {
+		return nil, err
+	}
+
+	if len(resp.ToolCalls) == 0 {
+		return resp, nil
+	}
+
+	if p.opts.ToolHandler != nil {
+		var resultParts []map[string]any
+		for _, tc := range resp.ToolCalls {
+			result, _ := p.opts.ToolHandler(tc.Name, tc.Input)
+			resultParts = append(resultParts, map[string]any{
+				"functionResponse": map[string]any{
+					"name":     tc.Name,
+					"id":       tc.ID,
+					"response": result,
+				},
+			})
+		}
+
+		followUpContents := append(contents,
+			map[string]any{"role": "model", "parts": rawParts},
+			map[string]any{"role": "user", "parts": resultParts},
+		)
+
+		followUpReq := map[string]any{
+			"contents": followUpContents,
+		}
+		if req.SystemPrompt != "" {
+			followUpReq["system_instruction"] = map[string]any{
+				"parts": []map[string]any{{"text": req.SystemPrompt}},
+			}
+		}
+
+		followUpResp, _, err := p.callAPI(ctx, followUpReq)
+		if err == nil && followUpResp.Reply != "" {
+			resp.Answer = followUpResp.Reply
+		}
+	}
+
+	return resp, nil
+}
+
+func (p *Provider) Stream(ctx context.Context, req *ai.Request, opts ...ai.GenerateOption) (ai.Stream, error) {
+	return nil, fmt.Errorf("streaming not yet implemented for gemini provider")
+}
+
+func (p *Provider) callAPI(ctx context.Context, req map[string]any) (*ai.Response, []map[string]any, error) {
+	reqBody, err := json.Marshal(req)
+	if err != nil {
+		return nil, nil, fmt.Errorf("failed to marshal request: %w", err)
+	}
+
+	apiURL := strings.TrimRight(p.opts.BaseURL, "/") +
+		"/v1beta/models/" + p.opts.Model + ":generateContent"
+
+	httpReq, err := http.NewRequestWithContext(ctx, "POST", apiURL, bytes.NewReader(reqBody))
+	if err != nil {
+		return nil, nil, fmt.Errorf("failed to create request: %w", err)
+	}
+
+	httpReq.Header.Set("Content-Type", "application/json")
+	httpReq.Header.Set("x-goog-api-key", p.opts.APIKey)
+
+	httpResp, err := http.DefaultClient.Do(httpReq)
+	if err != nil {
+		return nil, nil, fmt.Errorf("API request failed: %w", err)
+	}
+	defer httpResp.Body.Close()
+
+	respBody, _ := io.ReadAll(httpResp.Body)
+	if httpResp.StatusCode != 200 {
+		return nil, nil, fmt.Errorf("API error (%s): %s", httpResp.Status, string(respBody))
+	}
+
+	var geminiResp struct {
+		Candidates []struct {
+			Content struct {
+				Parts []struct {
+					Text         string          `json:"text"`
+					FunctionCall *functionCallPB `json:"functionCall"`
+				} `json:"parts"`
+			} `json:"content"`
+		} `json:"candidates"`
+	}
+
+	if err := json.Unmarshal(respBody, &geminiResp); err != nil {
+		return nil, nil, fmt.Errorf("failed to parse response: %w", err)
+	}
+
+	if len(geminiResp.Candidates) == 0 {
+		return nil, nil, fmt.Errorf("no response from API")
+	}
+
+	parts := geminiResp.Candidates[0].Content.Parts
+	response := &ai.Response{}
+
+	var replyParts []string
+	var rawParts []map[string]any
+
+	for _, part := range parts {
+		if part.Text != "" {
+			replyParts = append(replyParts, part.Text)
+			rawParts = append(rawParts, map[string]any{"text": part.Text})
+		}
+		if part.FunctionCall != nil {
+			response.ToolCalls = append(response.ToolCalls, ai.ToolCall{
+				ID:    part.FunctionCall.ID,
+				Name:  part.FunctionCall.Name,
+				Input: part.FunctionCall.Args,
+			})
+			rawParts = append(rawParts, map[string]any{
+				"functionCall": map[string]any{
+					"id":   part.FunctionCall.ID,
+					"name": part.FunctionCall.Name,
+					"args": part.FunctionCall.Args,
+				},
+			})
+		}
+	}
+
+	if len(replyParts) > 0 {
+		response.Reply = strings.Join(replyParts, "\n")
+	}
+
+	return response, rawParts, nil
+}
+
+type functionCallPB struct {
+	ID   string         `json:"id"`
+	Name string         `json:"name"`
+	Args map[string]any `json:"args"`
+}