ollama.rs

  1use anyhow::{Context as _, Result};
  2use futures::{AsyncBufReadExt, AsyncReadExt, StreamExt, io::BufReader, stream::BoxStream};
  3use http_client::{AsyncBody, HttpClient, Method, Request as HttpRequest, http};
  4use serde::{Deserialize, Serialize};
  5use serde_json::Value;
  6use std::time::Duration;
  7
  8pub const OLLAMA_API_URL: &str = "http://localhost:11434";
  9
 10#[cfg_attr(feature = "schemars", derive(schemars::JsonSchema))]
 11#[derive(Clone, Serialize, Deserialize, Debug, Eq, PartialEq)]
 12#[serde(untagged)]
 13pub enum KeepAlive {
 14    /// Keep model alive for N seconds
 15    Seconds(isize),
 16    /// Keep model alive for a fixed duration. Accepts durations like "5m", "10m", "1h", "1d", etc.
 17    Duration(String),
 18}
 19
 20impl KeepAlive {
 21    /// Keep model alive until a new model is loaded or until Ollama shuts down
 22    fn indefinite() -> Self {
 23        Self::Seconds(-1)
 24    }
 25}
 26
 27impl Default for KeepAlive {
 28    fn default() -> Self {
 29        Self::indefinite()
 30    }
 31}
 32
 33#[cfg_attr(feature = "schemars", derive(schemars::JsonSchema))]
 34#[derive(Clone, Debug, Default, Serialize, Deserialize, PartialEq)]
 35pub struct Model {
 36    pub name: String,
 37    pub display_name: Option<String>,
 38    pub max_tokens: u64,
 39    pub keep_alive: Option<KeepAlive>,
 40    pub supports_tools: Option<bool>,
 41    pub supports_vision: Option<bool>,
 42    pub supports_thinking: Option<bool>,
 43}
 44
 45fn get_max_tokens(name: &str) -> u64 {
 46    /// Default context length for unknown models.
 47    const DEFAULT_TOKENS: u64 = 4096;
 48    /// Magic number. Lets many Ollama models work with ~16GB of ram.
 49    const MAXIMUM_TOKENS: u64 = 16384;
 50
 51    match name.split(':').next().unwrap() {
 52        "phi" | "tinyllama" | "granite-code" => 2048,
 53        "llama2" | "yi" | "vicuna" | "stablelm2" => 4096,
 54        "llama3" | "gemma2" | "gemma" | "codegemma" | "starcoder" | "aya" => 8192,
 55        "codellama" | "starcoder2" => 16384,
 56        "mistral" | "codestral" | "mixstral" | "llava" | "qwen2" | "qwen2.5-coder"
 57        | "dolphin-mixtral" => 32768,
 58        "llama3.1" | "llama3.2" | "llama3.3" | "phi3" | "phi3.5" | "phi4" | "command-r"
 59        | "qwen3" | "gemma3" | "deepseek-coder-v2" | "deepseek-v3" | "deepseek-r1" | "yi-coder"
 60        | "devstral" => 128000,
 61        _ => DEFAULT_TOKENS,
 62    }
 63    .clamp(1, MAXIMUM_TOKENS)
 64}
 65
 66impl Model {
 67    pub fn new(
 68        name: &str,
 69        display_name: Option<&str>,
 70        max_tokens: Option<u64>,
 71        supports_tools: Option<bool>,
 72        supports_vision: Option<bool>,
 73        supports_thinking: Option<bool>,
 74    ) -> Self {
 75        Self {
 76            name: name.to_owned(),
 77            display_name: display_name
 78                .map(ToString::to_string)
 79                .or_else(|| name.strip_suffix(":latest").map(ToString::to_string)),
 80            max_tokens: max_tokens.unwrap_or_else(|| get_max_tokens(name)),
 81            keep_alive: Some(KeepAlive::indefinite()),
 82            supports_tools,
 83            supports_vision,
 84            supports_thinking,
 85        }
 86    }
 87
 88    pub fn id(&self) -> &str {
 89        &self.name
 90    }
 91
 92    pub fn display_name(&self) -> &str {
 93        self.display_name.as_ref().unwrap_or(&self.name)
 94    }
 95
 96    pub fn max_token_count(&self) -> u64 {
 97        self.max_tokens
 98    }
 99}
100
101#[derive(Serialize, Deserialize, Debug)]
102#[serde(tag = "role", rename_all = "lowercase")]
103pub enum ChatMessage {
104    Assistant {
105        content: String,
106        tool_calls: Option<Vec<OllamaToolCall>>,
107        #[serde(skip_serializing_if = "Option::is_none")]
108        images: Option<Vec<String>>,
109        thinking: Option<String>,
110    },
111    User {
112        content: String,
113        #[serde(skip_serializing_if = "Option::is_none")]
114        images: Option<Vec<String>>,
115    },
116    System {
117        content: String,
118    },
119}
120
121#[derive(Serialize, Deserialize, Debug)]
122#[serde(rename_all = "lowercase")]
123pub enum OllamaToolCall {
124    Function(OllamaFunctionCall),
125}
126
127#[derive(Serialize, Deserialize, Debug)]
128pub struct OllamaFunctionCall {
129    pub name: String,
130    pub arguments: Value,
131}
132
133#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
134pub struct OllamaFunctionTool {
135    pub name: String,
136    pub description: Option<String>,
137    pub parameters: Option<Value>,
138}
139
140#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
141#[serde(tag = "type", rename_all = "lowercase")]
142pub enum OllamaTool {
143    Function { function: OllamaFunctionTool },
144}
145
146#[derive(Serialize, Debug)]
147pub struct ChatRequest {
148    pub model: String,
149    pub messages: Vec<ChatMessage>,
150    pub stream: bool,
151    pub keep_alive: KeepAlive,
152    pub options: Option<ChatOptions>,
153    pub tools: Vec<OllamaTool>,
154    pub think: Option<bool>,
155}
156
157impl ChatRequest {
158    pub fn with_tools(mut self, tools: Vec<OllamaTool>) -> Self {
159        self.stream = false;
160        self.tools = tools;
161        self
162    }
163}
164
165// https://github.com/ollama/ollama/blob/main/docs/modelfile.md#valid-parameters-and-values
166#[derive(Serialize, Default, Debug)]
167pub struct ChatOptions {
168    pub num_ctx: Option<u64>,
169    pub num_predict: Option<isize>,
170    pub stop: Option<Vec<String>>,
171    pub temperature: Option<f32>,
172    pub top_p: Option<f32>,
173}
174
175#[derive(Deserialize, Debug)]
176pub struct ChatResponseDelta {
177    #[allow(unused)]
178    pub model: String,
179    #[allow(unused)]
180    pub created_at: String,
181    pub message: ChatMessage,
182    #[allow(unused)]
183    pub done_reason: Option<String>,
184    #[allow(unused)]
185    pub done: bool,
186    pub prompt_eval_count: Option<u64>,
187    pub eval_count: Option<u64>,
188}
189
190#[derive(Serialize, Deserialize)]
191pub struct LocalModelsResponse {
192    pub models: Vec<LocalModelListing>,
193}
194
195#[derive(Serialize, Deserialize)]
196pub struct LocalModelListing {
197    pub name: String,
198    pub modified_at: String,
199    pub size: u64,
200    pub digest: String,
201    pub details: ModelDetails,
202}
203
204#[derive(Serialize, Deserialize)]
205pub struct LocalModel {
206    pub modelfile: String,
207    pub parameters: String,
208    pub template: String,
209    pub details: ModelDetails,
210}
211
212#[derive(Serialize, Deserialize)]
213pub struct ModelDetails {
214    pub format: String,
215    pub family: String,
216    pub families: Option<Vec<String>>,
217    pub parameter_size: String,
218    pub quantization_level: String,
219}
220
221#[derive(Deserialize, Debug)]
222pub struct ModelShow {
223    #[serde(default)]
224    pub capabilities: Vec<String>,
225}
226
227impl ModelShow {
228    pub fn supports_tools(&self) -> bool {
229        // .contains expects &String, which would require an additional allocation
230        self.capabilities.iter().any(|v| v == "tools")
231    }
232
233    pub fn supports_vision(&self) -> bool {
234        self.capabilities.iter().any(|v| v == "vision")
235    }
236
237    pub fn supports_thinking(&self) -> bool {
238        self.capabilities.iter().any(|v| v == "thinking")
239    }
240}
241
242pub async fn complete(
243    client: &dyn HttpClient,
244    api_url: &str,
245    request: ChatRequest,
246) -> Result<ChatResponseDelta> {
247    let uri = format!("{api_url}/api/chat");
248    let request_builder = HttpRequest::builder()
249        .method(Method::POST)
250        .uri(uri)
251        .header("Content-Type", "application/json");
252
253    let serialized_request = serde_json::to_string(&request)?;
254    let request = request_builder.body(AsyncBody::from(serialized_request))?;
255
256    let mut response = client.send(request).await?;
257
258    let mut body = Vec::new();
259    response.body_mut().read_to_end(&mut body).await?;
260
261    if response.status().is_success() {
262        let response_message: ChatResponseDelta = serde_json::from_slice(&body)?;
263        Ok(response_message)
264    } else {
265        let body_str = std::str::from_utf8(&body)?;
266        anyhow::bail!(
267            "Failed to connect to API: {} {}",
268            response.status(),
269            body_str
270        );
271    }
272}
273
274pub async fn stream_chat_completion(
275    client: &dyn HttpClient,
276    api_url: &str,
277    request: ChatRequest,
278) -> Result<BoxStream<'static, Result<ChatResponseDelta>>> {
279    let uri = format!("{api_url}/api/chat");
280    let request_builder = http::Request::builder()
281        .method(Method::POST)
282        .uri(uri)
283        .header("Content-Type", "application/json");
284
285    let request = request_builder.body(AsyncBody::from(serde_json::to_string(&request)?))?;
286    let mut response = client.send(request).await?;
287    if response.status().is_success() {
288        let reader = BufReader::new(response.into_body());
289
290        Ok(reader
291            .lines()
292            .map(|line| match line {
293                Ok(line) => serde_json::from_str(&line).context("Unable to parse chat response"),
294                Err(e) => Err(e.into()),
295            })
296            .boxed())
297    } else {
298        let mut body = String::new();
299        response.body_mut().read_to_string(&mut body).await?;
300        anyhow::bail!(
301            "Failed to connect to Ollama API: {} {}",
302            response.status(),
303            body,
304        );
305    }
306}
307
308pub async fn get_models(
309    client: &dyn HttpClient,
310    api_url: &str,
311    _: Option<Duration>,
312) -> Result<Vec<LocalModelListing>> {
313    let uri = format!("{api_url}/api/tags");
314    let request_builder = HttpRequest::builder()
315        .method(Method::GET)
316        .uri(uri)
317        .header("Accept", "application/json");
318
319    let request = request_builder.body(AsyncBody::default())?;
320
321    let mut response = client.send(request).await?;
322
323    let mut body = String::new();
324    response.body_mut().read_to_string(&mut body).await?;
325
326    anyhow::ensure!(
327        response.status().is_success(),
328        "Failed to connect to Ollama API: {} {}",
329        response.status(),
330        body,
331    );
332    let response: LocalModelsResponse =
333        serde_json::from_str(&body).context("Unable to parse Ollama tag listing")?;
334    Ok(response.models)
335}
336
337/// Fetch details of a model, used to determine model capabilities
338pub async fn show_model(client: &dyn HttpClient, api_url: &str, model: &str) -> Result<ModelShow> {
339    let uri = format!("{api_url}/api/show");
340    let request = HttpRequest::builder()
341        .method(Method::POST)
342        .uri(uri)
343        .header("Content-Type", "application/json")
344        .body(AsyncBody::from(
345            serde_json::json!({ "model": model }).to_string(),
346        ))?;
347
348    let mut response = client.send(request).await?;
349    let mut body = String::new();
350    response.body_mut().read_to_string(&mut body).await?;
351
352    anyhow::ensure!(
353        response.status().is_success(),
354        "Failed to connect to Ollama API: {} {}",
355        response.status(),
356        body,
357    );
358    let details: ModelShow = serde_json::from_str(body.as_str())?;
359    Ok(details)
360}
361
362#[cfg(test)]
363mod tests {
364    use super::*;
365
366    #[test]
367    fn parse_completion() {
368        let response = serde_json::json!({
369        "model": "llama3.2",
370        "created_at": "2023-12-12T14:13:43.416799Z",
371        "message": {
372            "role": "assistant",
373            "content": "Hello! How are you today?"
374        },
375        "done": true,
376        "total_duration": 5191566416u64,
377        "load_duration": 2154458,
378        "prompt_eval_count": 26,
379        "prompt_eval_duration": 383809000,
380        "eval_count": 298,
381        "eval_duration": 4799921000u64
382        });
383        let _: ChatResponseDelta = serde_json::from_value(response).unwrap();
384    }
385
386    #[test]
387    fn parse_streaming_completion() {
388        let partial = serde_json::json!({
389        "model": "llama3.2",
390        "created_at": "2023-08-04T08:52:19.385406455-07:00",
391        "message": {
392            "role": "assistant",
393            "content": "The",
394            "images": null
395        },
396        "done": false
397        });
398
399        let _: ChatResponseDelta = serde_json::from_value(partial).unwrap();
400
401        let last = serde_json::json!({
402        "model": "llama3.2",
403        "created_at": "2023-08-04T19:22:45.499127Z",
404        "message": {
405            "role": "assistant",
406            "content": ""
407        },
408        "done": true,
409        "total_duration": 4883583458u64,
410        "load_duration": 1334875,
411        "prompt_eval_count": 26,
412        "prompt_eval_duration": 342546000,
413        "eval_count": 282,
414        "eval_duration": 4535599000u64
415        });
416
417        let _: ChatResponseDelta = serde_json::from_value(last).unwrap();
418    }
419
420    #[test]
421    fn parse_tool_call() {
422        let response = serde_json::json!({
423            "model": "llama3.2:3b",
424            "created_at": "2025-04-28T20:02:02.140489Z",
425            "message": {
426                "role": "assistant",
427                "content": "",
428                "tool_calls": [
429                    {
430                        "function": {
431                            "name": "weather",
432                            "arguments": {
433                                "city": "london",
434                            }
435                        }
436                    }
437                ]
438            },
439            "done_reason": "stop",
440            "done": true,
441            "total_duration": 2758629166u64,
442            "load_duration": 1770059875,
443            "prompt_eval_count": 147,
444            "prompt_eval_duration": 684637583,
445            "eval_count": 16,
446            "eval_duration": 302561917,
447        });
448
449        let result: ChatResponseDelta = serde_json::from_value(response).unwrap();
450        match result.message {
451            ChatMessage::Assistant {
452                content,
453                tool_calls,
454                images: _,
455                thinking,
456            } => {
457                assert!(content.is_empty());
458                assert!(tool_calls.is_some_and(|v| !v.is_empty()));
459                assert!(thinking.is_none());
460            }
461            _ => panic!("Deserialized wrong role"),
462        }
463    }
464
465    #[test]
466    fn parse_show_model() {
467        let response = serde_json::json!({
468            "license": "LLAMA 3.2 COMMUNITY LICENSE AGREEMENT...",
469            "details": {
470                "parent_model": "",
471                "format": "gguf",
472                "family": "llama",
473                "families": ["llama"],
474                "parameter_size": "3.2B",
475                "quantization_level": "Q4_K_M"
476            },
477            "model_info": {
478                "general.architecture": "llama",
479                "general.basename": "Llama-3.2",
480                "general.file_type": 15,
481                "general.finetune": "Instruct",
482                "general.languages": ["en", "de", "fr", "it", "pt", "hi", "es", "th"],
483                "general.parameter_count": 3212749888u64,
484                "general.quantization_version": 2,
485                "general.size_label": "3B",
486                "general.tags": ["facebook", "meta", "pytorch", "llama", "llama-3", "text-generation"],
487                "general.type": "model",
488                "llama.attention.head_count": 24,
489                "llama.attention.head_count_kv": 8,
490                "llama.attention.key_length": 128,
491                "llama.attention.layer_norm_rms_epsilon": 0.00001,
492                "llama.attention.value_length": 128,
493                "llama.block_count": 28,
494                "llama.context_length": 131072,
495                "llama.embedding_length": 3072,
496                "llama.feed_forward_length": 8192,
497                "llama.rope.dimension_count": 128,
498                "llama.rope.freq_base": 500000,
499                "llama.vocab_size": 128256,
500                "tokenizer.ggml.bos_token_id": 128000,
501                "tokenizer.ggml.eos_token_id": 128009,
502                "tokenizer.ggml.merges": null,
503                "tokenizer.ggml.model": "gpt2",
504                "tokenizer.ggml.pre": "llama-bpe",
505                "tokenizer.ggml.token_type": null,
506                "tokenizer.ggml.tokens": null
507            },
508            "tensors": [
509                { "name": "rope_freqs.weight", "type": "F32", "shape": [64] },
510                { "name": "token_embd.weight", "type": "Q4_K_S", "shape": [3072, 128256] }
511            ],
512            "capabilities": ["completion", "tools"],
513            "modified_at": "2025-04-29T21:24:41.445877632+03:00"
514        });
515
516        let result: ModelShow = serde_json::from_value(response).unwrap();
517        assert!(result.supports_tools());
518        assert!(result.capabilities.contains(&"tools".to_string()));
519        assert!(result.capabilities.contains(&"completion".to_string()));
520    }
521
522    #[test]
523    fn serialize_chat_request_with_images() {
524        let base64_image = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==";
525
526        let request = ChatRequest {
527            model: "llava".to_string(),
528            messages: vec![ChatMessage::User {
529                content: "What do you see in this image?".to_string(),
530                images: Some(vec![base64_image.to_string()]),
531            }],
532            stream: false,
533            keep_alive: KeepAlive::default(),
534            options: None,
535            think: None,
536            tools: vec![],
537        };
538
539        let serialized = serde_json::to_string(&request).unwrap();
540        assert!(serialized.contains("images"));
541        assert!(serialized.contains(base64_image));
542    }
543
544    #[test]
545    fn serialize_chat_request_without_images() {
546        let request = ChatRequest {
547            model: "llama3.2".to_string(),
548            messages: vec![ChatMessage::User {
549                content: "Hello, world!".to_string(),
550                images: None,
551            }],
552            stream: false,
553            keep_alive: KeepAlive::default(),
554            options: None,
555            think: None,
556            tools: vec![],
557        };
558
559        let serialized = serde_json::to_string(&request).unwrap();
560        assert!(!serialized.contains("images"));
561    }
562
563    #[test]
564    fn test_json_format_with_images() {
565        let base64_image = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==";
566
567        let request = ChatRequest {
568            model: "llava".to_string(),
569            messages: vec![ChatMessage::User {
570                content: "What do you see?".to_string(),
571                images: Some(vec![base64_image.to_string()]),
572            }],
573            stream: false,
574            keep_alive: KeepAlive::default(),
575            options: None,
576            think: None,
577            tools: vec![],
578        };
579
580        let serialized = serde_json::to_string(&request).unwrap();
581
582        let parsed: serde_json::Value = serde_json::from_str(&serialized).unwrap();
583        let message_images = parsed["messages"][0]["images"].as_array().unwrap();
584        assert_eq!(message_images.len(), 1);
585        assert_eq!(message_images[0].as_str().unwrap(), base64_image);
586    }
587}